Estimating economic thresholds for site-specific weed control using manual weed counts and sensor technology: an example based on three winter wheat trials.

PubMed

Keller, Martina; Gutjahr, Christoph; Möhring, Jens; Weis, Martin; Sökefeld, Markus; Gerhards, Roland

2014-02-01

Precision experimental design uses the natural heterogeneity of agricultural fields and combines sensor technology with linear mixed models to estimate the effect of weeds, soil properties and herbicide on yield. These estimates can be used to derive economic thresholds. Three field trials are presented using the precision experimental design in winter wheat. Weed densities were determined by manual sampling and bi-spectral cameras, yield and soil properties were mapped. Galium aparine, other broad-leaved weeds and Alopecurus myosuroides reduced yield by 17.5, 1.2 and 12.4 kg ha(-1) plant(-1)  m(2) in one trial. The determined thresholds for site-specific weed control with independently applied herbicides were 4, 48 and 12 plants m(-2), respectively. Spring drought reduced yield effects of weeds considerably in one trial, since water became yield limiting. A negative herbicide effect on the crop was negligible, except in one trial, in which the herbicide mixture tended to reduce yield by 0.6 t ha(-1). Bi-spectral cameras for weed counting were of limited use and still need improvement. Nevertheless, large weed patches were correctly identified. The current paper presents a new approach to conducting field trials and deriving decision rules for weed control in farmers' fields. © 2013 Society of Chemical Industry.

The use of magnetic resonance sounding for quantifying specific yield and transmissivity in hard rock aquifers: The example of Benin

NASA Astrophysics Data System (ADS)

Vouillamoz, J. M.; Lawson, F. M. A.; Yalo, N.; Descloitres, M.

2014-08-01

Hundreds of thousands of boreholes have been drilled in hard rocks of Africa and Asia for supplying human communities with drinking water. Despite the common use of geophysics for improving the siting of boreholes, a significant number of drilled holes does not deliver enough water to be equipped (e.g. 40% on average in Benin). As compared to other non-invasive geophysical methods, magnetic resonance sounding (MRS) is selective to groundwater. However, this distinctive feature has not been fully used in previous published studies for quantifying the drainable groundwater in hard rocks (i.e. the specific yield) and the short-term productivity of aquifer (i.e. the transmissivity). We present in this paper a comparison of MRS results (i.e. the water content and pore-size parameter) with both specific yield and transmissivity calculated from long duration pumping tests. We conducted our experiments in six sites located in different hard rock groups in Benin, thus providing a unique data set to assess the usefulness of MRS in hard rock aquifers. We found that the MRS water content is about twice the specific yield. We also found that the MRS pore-size parameter is well correlated with the specific yield. Thus we proposed two linear equations for calculating the specific yield from the MRS water content (with an uncertainty of about 10%) and from the pore-size parameter (with an uncertainty of about 20%). The later has the advantage of defining a so-named MRS cutoff time value for indentifying non-drainable MRS water content and thus low groundwater reserve. We eventually propose a nonlinear equation for calculating the specific yield using jointly the MRS water content and the pore-size parameters, but this approach has to be confirmed with further investigations. This study also confirmed that aquifer transmissivity can be estimated from MRS results with an uncertainty of about 70%. We conclude that MRS can be usefully applied for estimating aquifer specific yield and transmissivity in weathered hard rock aquifers. Our result will contribute to the improvement of well siting and groundwater management in hard rocks.

The Estimation of the Water Table and the Specific Yield with time-lapse 2D Electrical Resistivity Imaging in the Minzu Basin of Central Taiwan

NASA Astrophysics Data System (ADS)

Yao, H. J.; Chang, P. Y.

2017-12-01

The Minzu Basin is located at the central part of Taiwan, which is bounded by the Changhua fault in the west and the Chelungpu thrust fault in its east. The Chuoshui river flows through the basin and brings in thick unconsolidated gravel layers deposited over the Pleistocene rocks and gravels. Thus, the area has a great potential for groundwater developments. However, there are not enough observation wells in the study area for a further investigation of groundwater characteristics. Therefore, we tried to use the electrical resistivity imaging(ERI) method for estimating the depth of the groundwater table and the specific yield of the unconfined aquifer in dry and wet seasons. We have deployed 13 survey lines with the Wenner-Schlumberger array in the study area in March and June of 2017. Based on the data from the ERI measurements and the nearby Xinming observation well, we turned the resistivity into the relative saturation with respect to the saturated background based on the Archie's Law. With the depth distribution curve of the relative saturation, we found that the curve exhibits a similar shape to the Soil-Water Characteristic Curve. Hence we attempted to use the Van-Genuchten model for characterizing the depth of the water table. And we also tried to calculated the specific yield by taking the difference between the saturated and residual water contents. According to our preliminary results, we found that the depth of groundwater is ranging from 8-m to 10.7-m and the specific yield is about 0.095 0.146 in March. In addition, the depth of groundwater in June is ranging from about 7.6m to 9.8m and the estimated specific yield is about 0.1 0.157. The average level of groundwater in the wet season of June is raised about 0.6m than that in March. We are now working on collecting more time-lapse data, as well as making the direct comparisons with the data from new observation wells completed recently, in order to verify our estimations from the resistivity surveys.

Regional crop gross primary production and yield estimation using fused Landsat-MODIS data

NASA Astrophysics Data System (ADS)

He, M.; Kimball, J. S.; Maneta, M. P.; Maxwell, B. D.; Moreno, A.

2017-12-01

Accurate crop yield assessments using satellite-based remote sensing are of interest for the design of regional policies that promote agricultural resiliency and food security. However, the application of current vegetation productivity algorithms derived from global satellite observations are generally too coarse to capture cropland heterogeneity. Merging information from sensors with reciprocal spatial and temporal resolution can improve the accuracy of these retrievals. In this study, we estimate annual crop yields for seven important crop types -alfalfa, barley, corn, durum wheat, peas, spring wheat and winter wheat over Montana, United States (U.S.) from 2008 to 2015. Yields are estimated as the product of gross primary production (GPP) and a crop-specific harvest index (HI) at 30 m spatial resolution. To calculate GPP we used a modified form of the MOD17 LUE algorithm driven by a 30 m 8-day fused NDVI dataset constructed by blending Landsat (5 or 7) and MODIS Terra reflectance data. The fused 30-m NDVI record shows good consistency with the original Landsat and MODIS data, but provides better spatiotemporal information on cropland vegetation growth. The resulting GPP estimates capture characteristic cropland patterns and seasonal variations, while the estimated annual 30 m crop yield results correspond favorably with county-level crop yield data (r=0.96, p<0.05). The estimated crop yield performance was generally lower, but still favorable in relation to field-scale crop yield surveys (r=0.42, p<0.01). Our methods and results are suitable for operational applications at regional scales.

Application of the algebraic difference approach for developing self-referencing specific gravity and biomass equations

Treesearch

Lewis Jordan; Ray Souter; Bernard Parresol; Richard F. Daniels

2006-01-01

Biomass estimation is critical for looking at ecosystem processes and as a measure of stand yield. The density-integral approach allows for coincident estimation of stem profile and biomass. The algebraic difference approach (ADA) permits the derivation of dynamic or nonstatic functions. In this study we applied the ADA to develop a self-referencing specific gravity...

Yields of Soviet underground nuclear explosions at Novaya Zemlya, 1964-1976, from seismic body and surface waves

PubMed Central

Sykes, Lynn R.; Wiggins, Graham C.

1986-01-01

Surface and body wave magnitudes are determined for 15 U.S.S.R. underground nuclear weapons tests conducted at Novaya Zemlya between 1964 and 1976 and are used to estimate yields. These events include the largest underground explosions detonated by the Soviet Union. A histogram of body wave magnitude (mb) values indicates a clustering of explosions at a few specific yields. The most pronounced cluster consists of six explosions of yield near 500 kilotons. Several of these seem to be tests of warheads for major strategic systems that became operational in the late 1970s. The largest Soviet underground explosion is estimated to have a yield of 3500 ± 600 kilotons, somewhat smaller than the yield of the largest U.S. underground test. A preliminary estimation of the significance of tectonic release is made by measuring the amplitude of Love waves. The bias in mb for Novaya Zemlya relative to the Nevada test site is about 0.35, nearly identical to that of the eastern Kazakhstan test site relative to Nevada. PMID:16593645

Aquifer-storage change in the lower Canada del Oro Subbasin, Pima County, Arizona, 1996-98

USGS Publications Warehouse

Pool, D.R.

1999-01-01

Aquifer storage was monitored using gravity methods in the Lower Canada del Oro subbasin from 1996 through 1998 to determine areas of infiltration and amounts of recharge along the Canada del Oro Wash after major surface flow and to estimate aquifer-storage change and specific-yield values for the regional aquifer.  Both purposes were addressed by periodic monitoring of changes in aquifer storage and water levels at a network of gravity stations and monitor wells.  Water levels and gravity were also monitored near an active withdrawal well for several months for the purpose of estimating specific yield of the aquifer within the cone of water-leel depression at the well.

Genetic parameters for milk fatty acids, milk yield and quality traits of a Holstein cattle population reared under tropical conditions

USDA-ARS?s Scientific Manuscript database

Information about genetic parameters is essential for selection decisions and genetic evaluation. Those estimates are population specific, but few studies are available for dairy cattle populations reared under tropical and subtropical conditions. Heritability and genetic correlations for milk yield...

Primary and Secondary Yield Losses Caused by Pests and Diseases: Assessment and Modeling in Coffee

PubMed Central

Gary, Christian; Tixier, Philippe; Lechevallier, Esther

2017-01-01

The assessment of crop yield losses is needed for the improvement of production systems that contribute to the incomes of rural families and food security worldwide. However, efforts to quantify yield losses and identify their causes are still limited, especially for perennial crops. Our objectives were to quantify primary yield losses (incurred in the current year of production) and secondary yield losses (resulting from negative impacts of the previous year) of coffee due to pests and diseases, and to identify the most important predictors of coffee yields and yield losses. We established an experimental coffee parcel with full-sun exposure that consisted of six treatments, which were defined as different sequences of pesticide applications. The trial lasted three years (2013–2015) and yield components, dead productive branches, and foliar pests and diseases were assessed as predictors of yield. First, we calculated yield losses by comparing actual yields of specific treatments with the estimated attainable yield obtained in plots which always had chemical protection. Second, we used structural equation modeling to identify the most important predictors. Results showed that pests and diseases led to high primary yield losses (26%) and even higher secondary yield losses (38%). We identified the fruiting nodes and the dead productive branches as the most important and useful predictors of yields and yield losses. These predictors could be added in existing mechanistic models of coffee, or can be used to develop new linear mixed models to estimate yield losses. Estimated yield losses can then be related to production factors to identify corrective actions that farmers can implement to reduce losses. The experimental and modeling approaches of this study could also be applied in other perennial crops to assess yield losses. PMID:28046054

Primary and Secondary Yield Losses Caused by Pests and Diseases: Assessment and Modeling in Coffee.

PubMed

Cerda, Rolando; Avelino, Jacques; Gary, Christian; Tixier, Philippe; Lechevallier, Esther; Allinne, Clémentine

2017-01-01

The assessment of crop yield losses is needed for the improvement of production systems that contribute to the incomes of rural families and food security worldwide. However, efforts to quantify yield losses and identify their causes are still limited, especially for perennial crops. Our objectives were to quantify primary yield losses (incurred in the current year of production) and secondary yield losses (resulting from negative impacts of the previous year) of coffee due to pests and diseases, and to identify the most important predictors of coffee yields and yield losses. We established an experimental coffee parcel with full-sun exposure that consisted of six treatments, which were defined as different sequences of pesticide applications. The trial lasted three years (2013-2015) and yield components, dead productive branches, and foliar pests and diseases were assessed as predictors of yield. First, we calculated yield losses by comparing actual yields of specific treatments with the estimated attainable yield obtained in plots which always had chemical protection. Second, we used structural equation modeling to identify the most important predictors. Results showed that pests and diseases led to high primary yield losses (26%) and even higher secondary yield losses (38%). We identified the fruiting nodes and the dead productive branches as the most important and useful predictors of yields and yield losses. These predictors could be added in existing mechanistic models of coffee, or can be used to develop new linear mixed models to estimate yield losses. Estimated yield losses can then be related to production factors to identify corrective actions that farmers can implement to reduce losses. The experimental and modeling approaches of this study could also be applied in other perennial crops to assess yield losses.

Comparison of specific-yield estimates for calculating evapotranspiration from diurnal groundwater-level fluctuations

NASA Astrophysics Data System (ADS)

Gribovszki, Zoltán

2018-05-01

Methods that use diurnal groundwater-level fluctuations are commonly used for shallow water-table environments to estimate evapotranspiration (ET) and recharge. The key element needed to obtain reliable estimates is the specific yield (Sy), a soil-water storage parameter that depends on unsaturated soil-moisture and water-table fluxes, among others. Soil-moisture profile measurement down to the water table, along with water-table-depth measurements, can provide a good opportunity to calculate Sy values even on a sub-daily scale. These values were compared with Sy estimates derived by traditional techniques, and it was found that slug-test-based Sy values gave the most similar results in a sandy soil environment. Therefore, slug-test methods, which are relatively cheap and require little time, were most suited to estimate Sy using diurnal fluctuations. The reason for this is that the timeframe of the slug-test measurement is very similar to the dynamic of the diurnal signal. The dynamic characteristic of Sy was also analyzed on a sub-daily scale (depending mostly on the speed of drainage from the soil profile) and a remarkable difference was found in Sy with respect to the rate of change of the water table. When comparing constant and sub-daily (dynamic) Sy values for ET estimation, the sub-daily Sy application yielded higher correlation, but only a slightly smaller deviation from the control ET method, compared with the usage of constant Sy.

Yield Mapping for Different Crops in Sudano-Sahelian Smallholder Farming Systems: Results Based on Metric Worldview and Decametric SPOT-5 Take5 Time Series

NASA Astrophysics Data System (ADS)

Blaes, X.; Lambert, M.-J.; Chome, G.; Traore, P. S.; de By, R. A.; Defourny, P.

2016-08-01

Efficient yield mapping in Sudano-Sahelian Africa, characterized by a very heterogeneous landscape, is crucial to help ensure food security and decrease smallholder farmers' vulnerability. Thanks to an unprecedented in-situ data and HR and VHR remote sensing time series collected in the Koutiala district (in south-eastern Mali), the yield and some key factors of yield estimation were estimated. A crop-specific biomass map was derived with a mean absolute error of 20% using metric WorldView and 25% using decametric SPOT-5 TAKE5 image time series. The very high intra- and inter-field heterogeneity was captured efficiently. The presence of trees in the fields led to a general overestimation of yields, while the mixed pixels at the field borders introduced noise in the biomass predictions.

Water-quality characteristics, trends, and nutrient and sediment loads of streams in the Treyburn development area, North Carolina, 1988–2009

USGS Publications Warehouse

Fine, Jason M.; Harned, Douglas A.; Oblinger, Carolyn J.

2013-01-01

Streamflow and water-quality data, including concentrations of nutrients, metals, and pesticides, were collected from October 1988 through September 2009 at six sites in the Treyburn development study area. A review of water-quality data for streams in and near a 5,400-acre planned, mixed-use development in the Falls Lake watershed in the upper Neuse River Basin of North Carolina indicated only small-scale changes in water quality since the previous assessment of data collected from 1988 to 1998. Loads and yields were estimated for sediment and nutrients, and temporal trends were assessed for specific conductance, pH, and concentrations of dissolved oxygen, suspended sediment, and nutrients. Water-quality conditions for the Little River tributary and Mountain Creek may reflect development within these basins. The nitrogen and phosphorus concentrations at the Treyburn sites are low compared to sites nationally. The herbicides atrazine, metolachlor, prometon, and simazine were detected frequently at Mountain Creek and Little River tributary but concentrations are low compared to sites nationally. Little River tributary had the lowest median suspended-sediment yield over the 1988–2009 study period, whereas Flat River tributary had the largest median yield. The yields estimated for suspended sediment and nutrients were low compared to yields estimated for other basins in the Southeastern United States. Recent increasing trends were detected in total nitrogen concentration and suspended-sediment concentrations for Mountain Creek, and an increasing trend was detected in specific conductance for Little River tributary. Decreasing trends were detected in dissolved nitrite plus nitrate nitrogen, total ammonia plus organic nitrogen, sediment, and specific conductance for Flat River tributary. Water chemical concentrations, loads, yields, and trends for the Treyburn study sites reflect some effects of upstream development. These measures of water quality are generally low, however, compared to regional and national averages.

Connectome sensitivity or specificity: which is more important?

PubMed

Zalesky, Andrew; Fornito, Alex; Cocchi, Luca; Gollo, Leonardo L; van den Heuvel, Martijn P; Breakspear, Michael

2016-11-15

Connectomes with high sensitivity and high specificity are unattainable with current axonal fiber reconstruction methods, particularly at the macro-scale afforded by magnetic resonance imaging. Tensor-guided deterministic tractography yields sparse connectomes that are incomplete and contain false negatives (FNs), whereas probabilistic methods steered by crossing-fiber models yield dense connectomes, often with low specificity due to false positives (FPs). Densely reconstructed probabilistic connectomes are typically thresholded to improve specificity at the cost of a reduction in sensitivity. What is the optimal tradeoff between connectome sensitivity and specificity? We show empirically and theoretically that specificity is paramount. Our evaluations of the impact of FPs and FNs on empirical connectomes indicate that specificity is at least twice as important as sensitivity when estimating key properties of brain networks, including topological measures of network clustering, network efficiency and network modularity. Our asymptotic analysis of small-world networks with idealized modular structure reveals that as the number of nodes grows, specificity becomes exactly twice as important as sensitivity to the estimation of the clustering coefficient. For the estimation of network efficiency, the relative importance of specificity grows linearly with the number of nodes. The greater importance of specificity is due to FPs occurring more prevalently between network modules rather than within them. These spurious inter-modular connections have a dramatic impact on network topology. We argue that efforts to maximize the sensitivity of connectome reconstruction should be realigned with the need to map brain networks with high specificity. Copyright © 2016 Elsevier Inc. All rights reserved.

Analytic model to estimate thermonuclear neutron yield in z-pinches using the magnetic Noh problem

NASA Astrophysics Data System (ADS)

Allen, Robert C.

The objective was to build a model which could be used to estimate neutron yield in pulsed z-pinch experiments, benchmark future z-pinch simulation tools and to assist scaling for breakeven systems. To accomplish this, a recent solution to the magnetic Noh problem was utilized which incorporates a self-similar solution with cylindrical symmetry and azimuthal magnetic field (Velikovich, 2012). The self-similar solution provides the conditions needed to calculate the time dependent implosion dynamics from which batch burn is assumed and used to calculate neutron yield. The solution to the model is presented. The ion densities and time scales fix the initial mass and implosion velocity, providing estimates of the experimental results given specific initial conditions. Agreement is shown with experimental data (Coverdale, 2007). A parameter sweep was done to find the neutron yield, implosion velocity and gain for a range of densities and time scales for DD reactions and a curve fit was done to predict the scaling as a function of preshock conditions.

Comparison of irrigation pumpage with change in ground-water storage in the High Plains aquifer in Chase, Dundy, and Perkins counties, Nebraska, 1975-83

USGS Publications Warehouse

Heimes, F.J.; Ferrigno, C.F.; Gutentag, E.D.; Lucky, R.R.; Stephens, D.M.; Weeks, J.B.

1987-01-01

The relation between pumpage and change in storage was evaluated for most of a three-county area in southwestern Nebraska from 1975 through 1983. Initial comparison of the 1975-83 pumpage with change in storage in the study area indicated that the 1 ,042,300 acre-ft of change in storage was only about 30% of the 3,425,000 acre-ft of pumpage. An evaluation of the data used to calculate pumpage and change in storage indicated that there was a relatively large potential for error in estimates of specific yield. As a result, minimum and maximum values of specific yield were estimated and used to recalculate change in storage. Estimates also were derived for the minimum and maximum amounts of recharge that could occur as a result of cultivation practices. The minimum and maximum estimates for specific yield and for recharge from cultivation practices were used to compute a range of values for the potential amount of additional recharge that occurred as a result of irrigation. The minimum and maximum amounts of recharge that could be caused by irrigation in the study area were 953,200 acre-ft (28% of pumpage) and 2,611,200 acre-ft (76% of pumpage), respectively. These values indicate that a substantial percentage of the water pumped from the aquifer is resupplied to storage in the aquifer as a result of a combination of irrigation return flow and enhanced recharge from precipitation that results from cultivation and irrigation practices. (Author 's abstract)

Effects of Different Cutting Patterns and Experimental Conditions on the Performance of a Conical Drag Tool

NASA Astrophysics Data System (ADS)

Copur, Hanifi; Bilgin, Nuh; Balci, Cemal; Tumac, Deniz; Avunduk, Emre

2017-06-01

This study aims at determining the effects of single-, double-, and triple-spiral cutting patterns; the effects of tool cutting speeds on the experimental scale; and the effects of the method of yield estimation on cutting performance by performing a set of full-scale linear cutting tests with a conical cutting tool. The average and maximum normal, cutting and side forces; specific energy; yield; and coarseness index are measured and compared in each cutting pattern at a 25-mm line spacing, at varying depths of cut per revolution, and using two cutting speeds on five different rock samples. The results indicate that the optimum specific energy decreases by approximately 25% with an increasing number of spirals from the single- to the double-spiral cutting pattern for the hard rocks, whereas generally little effect was observed for the soft- and medium-strength rocks. The double-spiral cutting pattern appeared to be more effective than the single- or triple-spiral cutting pattern and had an advantage of lower side forces. The tool cutting speed had no apparent effect on the cutting performance. The estimation of the specific energy by the yield based on the theoretical swept area was not significantly different from that estimated by the yield based on the muck weighing, especially for the double- and triple-spiral cutting patterns and with the optimum ratio of line spacing to depth of cut per revolution. This study also demonstrated that the cutterhead and mechanical miner designs, semi-theoretical deterministic computer simulations and empirical performance predictions and optimization models should be based on realistic experimental simulations. Studies should be continued to obtain more reliable results by creating a larger database of laboratory tests and field performance records for mechanical miners using drag tools.

A New Approach to Simulate Groundwater Table Dynamics and Its Validation in China

NASA Astrophysics Data System (ADS)

Lv, M.; Lu, H.; Dan, L.; Yang, K.

2017-12-01

The groundwater has very important role in hydrology-climate-human activity interaction. But the groundwater table dynamics currently is not well simulated in global-scale land surface models. Meanwhile, almost all groundwater schemes are adopting a specific yield method to estimate groundwater table, in which how to determine the proper specific yield value remains a big challenge. In this study, we developed a Soil Moisture Correlation (SMC) method to simulate groundwater table dynamics. We coupled SMC with a hydrological model (named as NEW) and compared it with the original model in which a specific yield method is used (named as CTL). Both NEW and CTL were tested in Tangnaihai Subbasin of Yellow River and Jialingjiang Subbasin along Yangtze River, where underground water is less impacted by human activities. The simulated discharges by NEW and CTL are compared against gauge observations. The comparison results reveal that after calibration both models are able to reproduce the discharge well. However, there is no parameter needed to be calibrated for SMC. It indicates that SMC method is more efficient and easy-to-use than the specific yield method. Since there is no direct groundwater table observation in these two basins, simulated groundwater table were compared with a global data set provided by Fan et al. (2013). Both NEW and CTL estimate lower depths than Fan does. Moreover, when comparing the variation of terrestrial water storage (TWS) derived from NEW with that observed by GRACE, good agreements were confirmed. It demonstrated that SMC method is able to reproduce groundwater level dynamics reliably.

Ground-water resources of the Caguas-Juncos Valley, Puerto Rico

USGS Publications Warehouse

Puig, J.C.; Rodriguez, J.M.

1993-01-01

?The Caguas-Juncos valley, which occupies an area of 35 square miles in east-central Puerto Rico, is underlain by the largely unconfined alluvial aquifer. Withdrawals from this aquifer for public water supply and for agricultural, industrial, and domestic water uses totalled about 3.0 million gallons per day in 1988. Some wells in the valley yield as much as 310 gallons per minute from the alluvial deposits along Rio Gurabo near Gurabo and near Juncos. Wells used at dairy farms in the area commonly yield about 30 gallons per minute. The potentiometric surface of the alluvial aquifer varies seasonally and generally is highest near the end of December and lowest in April. Transmissivity of the alluvial aquifer, estimated from specific capacity and slug test data, ranges from 65 to 4,800 feet squared per day. The estimated specific yield of the water-table is about 10 to 15 percent. The amount of water stored in the aquifer is estimated to be about 122,000 acre-feet. Analyses of ground-water samples revealed the presence of two distinct problems-- high natural concentrations of iron and manganese, and localized areas of human- related contamination scattered throughout the valley. The ground water is a calcium-bicarbonate type and typically has dissolved solids concentrations of less than 500 milligrams per liter.

New Estimates of Land Use Intensity of Potential Bioethanol Production in the U.S.A.

NASA Astrophysics Data System (ADS)

Kheshgi, H. S.; Song, Y.; Torkamani, S.; Jain, A. K.

2016-12-01

We estimate potential bioethanol land use intensity (the inverse of potential bioethanol yield per hectare) across the United States by modeling crop yields and conversion to bioethanol (via a fermentation pathway), based on crop field studies and conversion technology analyses. We apply the process-based land surface model, the Integrated Science Assessment model (ISAM), to estimate the potential yield of four crops - corn, Miscanthus, and two variants of switchgrass (Cave-in-Rock and Alamo) - across the U.S.A. landscape for the 14-year period from 1999 through 2012, for the case with fertilizer application but without irrigation. We estimate bioethanol yield based on recent experience for corn bioethanol production from corn kernel, and current cellulosic bioethanol process design specifications under the assumption of the maximum practical harvest fraction for the energy grasses (Miscanthus and switchgrasses) and a moderate (30%) harvest fraction of corn stover. We find that each of four crops included has regions where that crop is estimated to have the lowest land use intensity (highest potential bioethanol yield per hectare). We find that minimizing potential land use intensity by including both corn and the energy grasses only improves incrementally to that of corn (using both harvested kernel and stover for bioethanol). Bioethanol land use intensity is one fundamental factor influencing the desirability of biofuels, but is not the only one; others factors include economics, competition with food production and land use, water and climate, nitrogen runoff, life-cycle emissions, and the pace of crop and technology improvement into the future.

Waveform inversion of acoustic waves for explosion yield estimation

DOE PAGES

Kim, K.; Rodgers, A. J.

2016-07-08

We present a new waveform inversion technique to estimate the energy of near-surface explosions using atmospheric acoustic waves. Conventional methods often employ air blast models based on a homogeneous atmosphere, where the acoustic wave propagation effects (e.g., refraction and diffraction) are not taken into account, and therefore, their accuracy decreases with increasing source-receiver distance. In this study, three-dimensional acoustic simulations are performed with a finite difference method in realistic atmospheres and topography, and the modeled acoustic Green's functions are incorporated into the waveform inversion for the acoustic source time functions. The strength of the acoustic source is related to explosionmore » yield based on a standard air blast model. The technique was applied to local explosions (<10 km) and provided reasonable yield estimates (<~30% error) in the presence of realistic topography and atmospheric structure. In conclusion, the presented method can be extended to explosions recorded at far distance provided proper meteorological specifications.« less

Waveform inversion of acoustic waves for explosion yield estimation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, K.; Rodgers, A. J.

We present a new waveform inversion technique to estimate the energy of near-surface explosions using atmospheric acoustic waves. Conventional methods often employ air blast models based on a homogeneous atmosphere, where the acoustic wave propagation effects (e.g., refraction and diffraction) are not taken into account, and therefore, their accuracy decreases with increasing source-receiver distance. In this study, three-dimensional acoustic simulations are performed with a finite difference method in realistic atmospheres and topography, and the modeled acoustic Green's functions are incorporated into the waveform inversion for the acoustic source time functions. The strength of the acoustic source is related to explosionmore » yield based on a standard air blast model. The technique was applied to local explosions (<10 km) and provided reasonable yield estimates (<~30% error) in the presence of realistic topography and atmospheric structure. In conclusion, the presented method can be extended to explosions recorded at far distance provided proper meteorological specifications.« less

Production cost analysis of Euphorbia lathyris. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mendel, D.A.; Schooley, F.A.; Dickenson, R.L.

1979-08-01

The purpose of SRI's study was to estimate the costs of producing Euphorbia in commercial quantities in five regions of the United States, which include both irrigated and nonirrigated areas. The study assumed that a uniform crop yield could be achieved in the five regions by varying the quantities of production inputs. Therefore, the production costs estimates, which are based on fourth quarter 1978 dollars, include both fixed and variable costs for each region. Doane's Machinery Custom Rates for 1978 were used to estimate all variable costs except materials, which were estimated separately. Custom rates are determined by members ofmore » the Doane Countywide Farm Panel, a group of farmers specifically selected to represent the various sizes and types of commercial farms found throughout the country. The rates reported are the most recent rates the panel members had either paid, charged, or known for certain a second party had paid or charged. Custom rates for any particular operation include equipment operating costs (fuel, lubrication, and repairs), equipment ownership costs (depreciation, taxes, interest), as well as a labor charge for the operator. Custom rates are regionally specific and thereby assist the accuracy of this analysis. Fixed costs include land, management, and transportation of the plant material to a conversion facility. When appropriate, fixed costs were regionally specific. Changes in total production costs over future time periods were not addressed. The total estimated production costs of Euphorbia in each region were compared with production costs for corn and alfalfa in the same regions. Finally, the effects on yield and costs of changes in the production inputs were estimated.« less

Estimating regional wheat yield from the shape of decreasing curves of green area index temporal profiles retrieved from MODIS data

NASA Astrophysics Data System (ADS)

Kouadio, Louis; Duveiller, Grégory; Djaby, Bakary; El Jarroudi, Moussa; Defourny, Pierre; Tychon, Bernard

2012-08-01

Earth observation data, owing to their synoptic, timely and repetitive coverage, have been recognized as a valuable tool for crop monitoring at different levels. At the field level, the close correlation between green leaf area (GLA) during maturation and grain yield in wheat revealed that the onset and rate of senescence appeared to be important factors for determining wheat grain yield. Our study sought to explore a simple approach for wheat yield forecasting at the regional level, based on metrics derived from the senescence phase of the green area index (GAI) retrieved from remote sensing data. This study took advantage of recent methodological improvements in which imagery with high revisit frequency but coarse spatial resolution can be exploited to derive crop-specific GAI time series by selecting pixels whose ground-projected instantaneous field of view is dominated by the target crop: winter wheat. A logistic function was used to characterize the GAI senescence phase and derive the metrics of this phase. Four regression-based models involving these metrics (i.e., the maximum GAI value, the senescence rate and the thermal time taken to reach 50% of the green surface in the senescent phase) were related to official wheat yield data. The performances of such models at this regional scale showed that final yield could be estimated with an RMSE of 0.57 ton ha-1, representing about 7% as relative RMSE. Such an approach may be considered as a first yield estimate that could be performed in order to provide better integrated yield assessments in operational systems.

Evaluation of Rgb-Based Vegetation Indices from Uav Imagery to Estimate Forage Yield in Grassland

NASA Astrophysics Data System (ADS)

Lussem, U.; Bolten, A.; Gnyp, M. L.; Jasper, J.; Bareth, G.

2018-04-01

Monitoring forage yield throughout the growing season is of key importance to support management decisions on grasslands/pastures. Especially on intensely managed grasslands, where nitrogen fertilizer and/or manure are applied regularly, precision agriculture applications are beneficial to support sustainable, site-specific management decisions on fertilizer treatment, grazing management and yield forecasting to mitigate potential negative impacts. To support these management decisions, timely and accurate information is needed on plant parameters (e.g. forage yield) with a high spatial and temporal resolution. However, in highly heterogeneous plant communities such as grasslands, assessing their in-field variability non-destructively to determine e.g. adequate fertilizer application still remains challenging. Especially biomass/yield estimation, as an important parameter in assessing grassland quality and quantity, is rather laborious. Forage yield (dry or fresh matter) is mostly measured manually with rising plate meters (RPM) or ultrasonic sensors (handheld or mounted on vehicles). Thus the in-field variability cannot be assessed for the entire field or only with potential disturbances. Using unmanned aerial vehicles (UAV) equipped with consumer grade RGB cameras in-field variability can be assessed by computing RGB-based vegetation indices. In this contribution we want to test and evaluate the robustness of RGB-based vegetation indices to estimate dry matter forage yield on a recently established experimental grassland site in Germany. Furthermore, the RGB-based VIs are compared to indices computed from the Yara N-Sensor. The results show a good correlation of forage yield with RGB-based VIs such as the NGRDI with R2 values of 0.62.

Simulating effects of microtopography on wetland specific yield and hydroperiod

USGS Publications Warehouse

Summer, David M.; Wang, Xixi

2011-01-01

Specific yield and hydroperiod have proven to be useful parameters in hydrologic analysis of wetlands. Specific yield is a critical parameter to quantitatively relate hydrologic fluxes (e.g., rainfall, evapotranspiration, and runoff) and water level changes. Hydroperiod measures the temporal variability and frequency of land-surface inundation. Conventionally, hydrologic analyses used these concepts without considering the effects of land surface microtopography and assumed a smoothly-varying land surface. However, these microtopographic effects could result in small-scale variations in land surface inundation and water depth above or below the land surface, which in turn affect ecologic and hydrologic processes of wetlands. The objective of this chapter is to develop a physically-based approach for estimating specific yield and hydroperiod that enables the consideration of microtopographic features of wetlands, and to illustrate the approach at sites in the Florida Everglades. The results indicate that the physically-based approach can better capture the variations of specific yield with water level, in particular when the water level falls between the minimum and maximum land surface elevations. The suggested approach for hydroperiod computation predicted that the wetlands might be completely dry or completely wet much less frequently than suggested by the conventional approach neglecting microtopography. One reasonable generalization may be that the hydroperiod approaches presented in this chapter can be a more accurate prediction tool for water resources management to meet the specific hydroperiod threshold as required by a species of plant or animal of interest.

Acoustic Full Waveform Inversion to Characterize Near-surface Chemical Explosions

NASA Astrophysics Data System (ADS)

Kim, K.; Rodgers, A. J.

2015-12-01

Recent high-quality, atmospheric overpressure data from chemical high-explosive experiments provide a unique opportunity to characterize near-surface explosions, specifically estimating yield and source time function. Typically, yield is estimated from measured signal features, such as peak pressure, impulse, duration and/or arrival time of acoustic signals. However, the application of full waveform inversion to acoustic signals for yield estimation has not been fully explored. In this study, we apply a full waveform inversion method to local overpressure data to extract accurate pressure-time histories of acoustics sources during chemical explosions. A robust and accurate inversion technique for acoustic source is investigated using numerical Green's functions that take into account atmospheric and topographic propagation effects. The inverted pressure-time history represents the pressure fluctuation at the source region associated with the explosion, and thus, provides a valuable information about acoustic source mechanisms and characteristics in greater detail. We compare acoustic source properties (i.e., peak overpressure, duration, and non-isotropic shape) of a series of explosions having different emplacement conditions and investigate the relationship of the acoustic sources to the yields of explosions. The time histories of acoustic sources may refine our knowledge of sound-generation mechanisms of shallow explosions, and thereby allow for accurate yield estimation based on acoustic measurements. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Human impact on sediment fluxes within the Blue Nile and Atbara River basins

NASA Astrophysics Data System (ADS)

Balthazar, Vincent; Vanacker, Veerle; Girma, Atkilt; Poesen, Jean; Golla, Semunesh

2013-01-01

A regional assessment of the spatial variability in sediment yields allows filling the gap between detailed, process-based understanding of erosion at field scale and empirical sediment flux models at global scale. In this paper, we focus on the intrabasin variability in sediment yield within the Blue Nile and Atbara basins as biophysical and anthropogenic factors are presumably acting together to accelerate soil erosion. The Blue Nile and Atbara River systems are characterized by an important spatial variability in sediment fluxes, with area-specific sediment yield (SSY) values ranging between 4 and 4935 t/km2/y. Statistical analyses show that 41% of the observed variation in SSY can be explained by remote sensing proxy data of surface vegetation cover, rainfall intensity, mean annual temperature, and human impact. The comparison of a locally adapted regression model with global predictive sediment flux models indicates that global flux models such as the ART and BQART models are less suited to capture the spatial variability in area-specific sediment yields (SSY), but they are very efficient to predict absolute sediment yields (SY). We developed a modified version of the BQART model that estimates the human influence on sediment yield based on a high resolution composite measure of local human impact (human footprint index) instead of countrywide estimates of GNP/capita. Our modified version of the BQART is able to explain 80% of the observed variation in SY for the Blue Nile and Atbara basins and thereby performs only slightly less than locally adapted regression models.

Specific Yields Estimated from Gravity Change during Pumping Test

NASA Astrophysics Data System (ADS)

Chen, K. H.; Hwang, C.; Chang, L. C.

2017-12-01

Specific yield (Sy) is the most important parameter to describe available groundwater capacity in an unconfined aquifer. When estimating Sy by a field pumping test, aquifer heterogeneity and well performers will cause a large uncertainty. In this study, we use a gravity-based method to estimate Sy. At the time of pumping test, amounts of mass (groundwater) are forced to be taken out. If drawdown corn is big and close enough to high precision gravimeter, the gravity change can be detected. The gravity-based method use gravity observations that are independent from traditional flow computation. Only the drawdown corn should be modeled with observed head and hydrogeology data. The gravity method can be used in most groundwater field tests, such as locally pumping/injection tests initiated by active man-made or annual variations due to natural sources. We apply our gravity method at few sites in Taiwan situated over different unconfined aquifer. Here pumping tests for Sy determinations were also carried out. We will discuss why the gravity method produces different results from traditional pumping test, field designs and limitations of the gravity method.

Estimate of aquifer properties by numerically simulating ground-water/surface-water interactions, Fort Wainwright, Alaska

USGS Publications Warehouse

Nakanishi, Allen S.; Lilly, Michael R.

1998-01-01

MODFLOW, a finite-difference model of ground-water flow, was used to simulate the flow of water between the aquifer and the Chena River at Fort Wainwright, Alaska. The model was calibrated by comparing simulated ground-water hydrographs to those recorded in wells during periods of fluctuating river levels. The best fit between simulated and observed hydrographs occurred for the following: 20 feet per day for vertical hydraulic conductivity, 400 feet per day for horizontal hydraulic conductivity, 1:20 for anisotropy (vertical to horizontal hydraulic conductivity), and 350 per feet for riverbed conductance. These values include a 30 percent adjustment for geometry effects. The estimated values for hydraulic conductivities of the alluvium are based on assumed values of 0.25 for specific yield and 0.000001 per foot for specific storage of the alluvium; the values assumed for bedrock are 0.1 foot per day horizontal hydraulic conductivity, 0.005 foot per day vertical hydraulic conductivity, and 0.0000001 per foot for specific storage. The resulting diffusivity for the alluvial aquifer is 1,600 feet per day. The estimated values of these hydraulic properties are nearly proportional to the assumed value of specific yield. These values were not found to be sensitive to the assumed values for bedrock. The hydrologic parameters estimated using the cross-sectional model are only valid when taken in context with the other values (both estimated and assumed) used in this study. The model simulates horizontal and vertical flow directions near the river during periods of varying river stage. This information is useful for interpreting bank-storage effects, including the flow of contaminants in the aquifer near the river.

AMMI adjustment for statistical analysis of an international wheat yield trial.

PubMed

Crossa, J; Fox, P N; Pfeiffer, W H; Rajaram, S; Gauch, H G

1991-01-01

Multilocation trials are important for the CIMMYT Bread Wheat Program in producing high-yielding, adapted lines for a wide range of environments. This study investigated procedures for improving predictive success of a yield trial, grouping environments and genotypes into homogeneous subsets, and determining the yield stability of 18 CIMMYT bread wheats evaluated at 25 locations. Additive Main effects and Multiplicative Interaction (AMMI) analysis gave more precise estimates of genotypic yields within locations than means across replicates. This precision facilitated formation by cluster analysis of more cohesive groups of genotypes and locations for biological interpretation of interactions than occurred with unadjusted means. Locations were clustered into two subsets for which genotypes with positive interactions manifested in high, stable yields were identified. The analyses highlighted superior selections with both broad and specific adaptation.

Atomic Oxygen Erosion Yield Predictive Tool for Spacecraft Polymers in Low Earth Orbit

NASA Technical Reports Server (NTRS)

Bank, Bruce A.; de Groh, Kim K.; Backus, Jane A.

2008-01-01

A predictive tool was developed to estimate the low Earth orbit (LEO) atomic oxygen erosion yield of polymers based on the results of the Polymer Erosion and Contamination Experiment (PEACE) Polymers experiment flown as part of the Materials International Space Station Experiment 2 (MISSE 2). The MISSE 2 PEACE experiment accurately measured the erosion yield of a wide variety of polymers and pyrolytic graphite. The 40 different materials tested were selected specifically to represent a variety of polymers used in space as well as a wide variety of polymer chemical structures. The resulting erosion yield data was used to develop a predictive tool which utilizes chemical structure and physical properties of polymers that can be measured in ground laboratory testing to predict the in-space atomic oxygen erosion yield of a polymer. The properties include chemical structure, bonding information, density and ash content. The resulting predictive tool has a correlation coefficient of 0.914 when compared with actual MISSE 2 space data for 38 polymers and pyrolytic graphite. The intent of the predictive tool is to be able to make estimates of atomic oxygen erosion yields for new polymers without requiring expensive and time consumptive in-space testing.

Assessing Sediment Yield and the Effect of Best Management Practices on Sediment Yield Reduction for Tutuila Island, American Samoa

NASA Astrophysics Data System (ADS)

Leta, O. T.; Dulai, H.; El-Kadi, A. I.

2017-12-01

Upland soil erosion and sedimentation are the main threats for riparian and coastal reef ecosystems in Pacific islands. Here, due to small size of the watersheds and steep slope, the residence time of rainfall runoff and its suspended load is short. Fagaalu bay, located on the island of Tutuila (American Samoa) has been identified as a priority watershed, due to degraded coral reef condition and reduction of stream water quality from heavy anthropogenic activity yielding high nutrients and sediment loads to the receiving water bodies. This study aimed to estimate the sediment yield to the Fagaalu stream and assess the impact of Best Management Practices (BMP) on sediment yield reduction. For this, the Soil and Water Assessment Tool (SWAT) model was applied, calibrated, and validated for both daily streamflow and sediment load simulation. The model also estimated the sediment yield contributions from existing land use types of Fagaalu and identified soil erosion prone areas for introducing BMP scenarios in the watershed. Then, three BMP scenarios, such as stone bund, retention pond, and filter strip were treated on bare (quarry area), agricultural, and shrub land use types. It was found that the bare land with quarry activity yielded the highest annual average sediment yield of 133 ton per hectare (t ha-1) followed by agriculture (26.1 t ha-1) while the lowest sediment yield of 0.2 t ha-1 was estimated for the forested part of the watershed. Additionally, the bare land area (2 ha) contributed approximately 65% (207 ha) of the watershed's sediment yield, which is 4.0 t ha-1. The latter signifies the high impact as well as contribution of anthropogenic activity on sediment yield. The use of different BMP scenarios generally reduced the sediment yield to the coastal reef of Fagaalu watershed. However, treating the quarry activity area with stone bund showed the highest sediment yield reduction as compared to the other two BMP scenarios. This study provides an estimate of the impact that each BMP has on specific land use and Fagaalu's reef. It also offers information that may be useful for the coastal water resource management and mitigation measures to reduce sediment yield of the study site and similar areas.

Fission yield and criticality excursion code

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blanchard, A.

2000-06-30

The ANSI/ANS 8.3 standard allows a maximum yield not to exceed 2 x 10 fissions to calculate requiring the alarm system to be effective. It is common practice to use this allowance or to develop some other yield based on past criticality accident history or excursion experiments. The literature on the subject of yields discusses maximum yields larger and somewhat smaller than the ANS 8.3 permissive value. The ability to model criticality excursions and vary the various parameters to determine a credible maximum yield for operational specific cases has been available for some time but is not in common usemore » by criticality safety specialists. The topic of yields for various solution, metal, oxide powders, etc. in various geometry's and containers has been published by laboratory specialists or university staff and students for many decades but have not been available to practitioners. The need for best-estimate calculations of fission yields with a well-validated criticality excursion code has long been recognized. But no coordinated effort has been made so far to develop a generalized and well-validated excursion code for different types of systems. In this paper, the current practices to estimate fission yields are summarized along with its shortcomings for the 12-Rad zone (at SRS) and Criticality Alarm System (CAS) calculations. Finally the need for a user-friendly excursion code is reemphasized.« less

Yield estimation of corn with multispectral data and the potential of using imaging spectrometers

NASA Astrophysics Data System (ADS)

Bach, Heike

1997-05-01

In the frame of the special yield estimation, a regular procedure conducted for the European Union to more accurately estimate agricultural yield, a project was conducted for the state minister for Rural Environment, Food and Forestry of Baden-Wuerttemberg, Germany) to test remote sensing data with advanced yield formation models for accuracy and timelines of yield estimation of corn. The methodology employed uses field-based plant parameter estimation from atmospherically corrected multitemporal/multispectral LANDSAT-TM data. An agrometeorological plant-production-model is used for yield prediction. Based solely on 4 LANDSAT-derived estimates and daily meteorological data the grain yield of corn stands was determined for 1995. The modeled yield was compared with results independently gathered within the special yield estimation for 23 test fields in the Upper Rhine Valley. The agrement between LANDSAT-based estimates and Special Yield Estimation shows a relative error of 2.3 percent. The comparison of the results for single fields shows, that six weeks before harvest the grain yield of single corn fields was estimated with a mean relative accuracy of 13 percent using satellite information. The presented methodology can be transferred to other crops and geographical regions. For future applications hyperspectral sensors show great potential to further enhance the results or yield prediction with remote sensing.

How Big Was It? Getting at Yield

NASA Astrophysics Data System (ADS)

Pasyanos, M.; Walter, W. R.; Ford, S. R.

2013-12-01

One of the most coveted pieces of information in the wake of a nuclear test is the explosive yield. Determining the yield from remote observations, however, is not necessarily a trivial thing. For instance, recorded observations of seismic amplitudes, used to estimate the yield, are significantly modified by the intervening media, which varies widely, and needs to be properly accounted for. Even after correcting for propagation effects such as geometrical spreading, attenuation, and station site terms, getting from the resulting source term to a yield depends on the specifics of the explosion source model, including material properties, and depth. Some formulas are based on assumptions of the explosion having a standard depth-of-burial and observed amplitudes can vary if the actual test is either significantly overburied or underburied. We will consider the complications and challenges of making these determinations using a number of standard, more traditional methods and a more recent method that we have developed using regional waveform envelopes. We will do this comparison for recent declared nuclear tests from the DPRK. We will also compare the methods using older explosions at the Nevada Test Site with announced yields, material and depths, so that actual performance can be measured. In all cases, we also strive to quantify realistic uncertainties on the yield estimation.

Mrg: A Magnitude Scale for 1 s Rayleigh Waves at Local Distances with Focus on Yield Estimation

DTIC Science & Technology

2016-08-23

typical of “hard” rock emplacement media. The MRg estimates using Eq. 5 are shown in Figure 3c. The network average MRg, which is estimated after...MATERIEL COMMAND KIRTLAND AIR FORCE BASE, NM 87117-5776 DTIC COPY NOTICE AND SIGNATURE PAGE Using Government drawings, specifications, or other...convey any rights or permission to manufacture, use , or sell any patented invention that may relate to them. This report was cleared for public

Genetic parameters for milk fatty acids, milk yield and quality traits of a Holstein cattle population reared under tropical conditions.

PubMed

Petrini, J; Iung, L H S; Rodriguez, M A P; Salvian, M; Pértille, F; Rovadoscki, G A; Cassoli, L D; Coutinho, L L; Machado, P F; Wiggans, G R; Mourão, G B

2016-10-01

Information about genetic parameters is essential for selection decisions and genetic evaluation. These estimates are population specific; however, there are few studies with dairy cattle populations reared under tropical and sub-tropical conditions. Thus, the aim was to obtain estimates of heritability and genetic correlations for milk yield and quality traits using pedigree and genomic information from a Holstein population maintained in a tropical environment. Phenotypic records (n = 36 457) of 4203 cows as well as the genotypes for 57 368 single nucleotide polymorphisms from 755 of these cows were used. Covariance components were estimated using the restricted maximum likelihood method under a mixed animal model, considering a pedigree-based relationship matrix or a combined pedigree-genomic matrix. High heritabilities (around 0.30) were estimated for lactose and protein content in milk whereas moderate values (between 0.19 and 0.26) were obtained for percentages of fat, saturated fatty acids and palmitic acid in milk. Genetic correlations ranging from -0.38 to -0.13 were determined between milk yield and composition traits. The smaller estimates compared to other similar studies can be due to poor environmental conditions, which may reduce genetic variability. These results highlight the importance in using genetic parameters estimated in the population under evaluation for selection decisions. © 2016 Blackwell Verlag GmbH.

Yield estimation of corn based on multitemporal LANDSAT-TM data as input for an agrometeorological model

NASA Astrophysics Data System (ADS)

Bach, Heike

1998-07-01

In order to test remote sensing data with advanced yield formation models for accuracy and timeliness of yield estimation of corn, a project was conducted for the State Ministry for Rural Environment, Food, and Forestry of Baden-Württemberg (Germany). This project was carried out during the course of the `Special Yield Estimation', a regular procedure conducted for the European Union, to more accurately estimate agricultural yield. The methodology employed uses field-based plant parameter estimation from atmospherically corrected multitemporal/multispectral LANDSAT-TM data. An agrometeorological plant-production-model is used for yield prediction. Based solely on four LANDSAT-derived estimates (between May and August) and daily meteorological data, the grain yield of corn fields was determined for 1995. The modelled yields were compared with results gathered independently within the Special Yield Estimation for 23 test fields in the upper Rhine valley. The agreement between LANDSAT-based estimates (six weeks before harvest) and Special Yield Estimation (at harvest) shows a relative error of 2.3%. The comparison of the results for single fields shows that six weeks before harvest, the grain yield of corn was estimated with a mean relative accuracy of 13% using satellite information. The presented methodology can be transferred to other crops and geographical regions. For future applications hyperspectral sensors show great potential to further enhance the results for yield prediction with remote sensing.

Electric analog of three-dimensional flow to wells and its application to unconfined aquifers

USGS Publications Warehouse

Stallman, Robert W.

1963-01-01

Electric-analog design criteria are established from the differential equations of ground-water flow for analyzing pumping-test data. A convenient analog design was obtained by transforming the cylindrical equation of flow to a rectilinear form. The design criteria were applied in the construction of an electric analog, which was used for studying pumping-test data collected near Grand Island, Nebr. Data analysis indicated (1) vertical flow components near pumping wells in unconfined aquifers may be much more significant in the control of water-table decline than radial flow components for as much as a day of pumping; (2) the specific yield during the first few minutes of pumping appears to be a very small fraction of that observed after pumping for more than 1 day; and (3) estimates of specific yield made from model studies seem much more sensitive to variations in assumed flow conditions than are estimates of permeability. Analysis of pumping-test data where vertical flow components are important requires that the degree of anisotropy be known. A procedure for computing anisotropy directly from drawdowns observed at five points was developed. Results obtained in the analog study emphasize the futility of calculating unconfined aquifer properties from pumping tests of short duration by means of equations based on the assumptions that vertical flow components are negligible and specific yield is constant.

Climate change, variability and extreme events : risk assessment and management strategies in a Peach cultivated area in Italy.

NASA Astrophysics Data System (ADS)

Alfieri, Silvia Maria; De Lorenzi, Francesca; Basile, Angelo; Bonfante, Antonello; Missere, Daniele; Menenti, Massimo

2014-05-01

Climate change in Mediterranean area is likely to reduce precipitation amounts and to increase temperature thus affecting the timing of development stages and the productivity of crops. Further, extreme weather events are expected to increase in the future leading to significant increase in agricultural risk. Some strategies for effectively managing risks and adapting to climate change involve adjustments to irrigation management and use of different varieties. We quantified the risk on Peach production in an irrigated area of "Emilia Romagna" region ( Italy) taking into account the impact on crop yield due to climate change and variability and to extreme weather events as well as the ability of the agricultural system to modulate this impact (adaptive capacity) through changes in water and crop management. We have focused on climatic events causing insufficient water supply to crops, while taking into account the effect of climate on the duration and timing of phenological stages. Further, extreme maximum and minimum temperature events causing significant reduction of crop yield have been considered using phase-specific critical temperatures. In our study risk was assessed as the product of the probability of a damaging event (hazard), such as drought or extreme temperatures, and the estimated impact of such an event (vulnerability). To estimate vulnerability we took into account the possible options to reduce risk, by combining estimates of the sensitivity of the system (negative impact on crop yield) and its adaptive capacity. The latter was evaluated as the relative improvement due to alternate management options: the use of alternate varieties or the changes in irrigation management. Vulnerability was quantified using cultivar-specific thermal and hydrologic requirements of a set of cultivars determined by experimental data and from scientific literature. Critical temperatures determining a certain reduction of crop yield have been estimated and used to assess thermal hazard and vulnerability in sensitive phenological stages. Cultivar-specific yield response functions to water availability were used to assess the reduction of yield for a determinate management option. Downscaled climate scenarios have been used to calculate indicators of soil water availability and thermal times and to evaluate the variability of crop phenology in combination with critical temperatures. Two climate scenarios were considered: reference (1961-90) and future (2021-2050) climate, the former from climatic statistics on observed variables, and the latter from statistical downscaling of general circulation models (AOGCM). Management options were defined by combinations of irrigation strategies (optimal, rainfed and deficit) with use of alternate varieties. As regards hydrologic conditions, risk assessment has been done at landscape scale in all soil units within each study area. The mechanistic model SWAP (Soil-Water-Atmosphere-Plant model) of water flow in the soil-plant-atmosphere system was used to describe the hydrological conditions in response to climate and irrigation. Different farm management options were evaluated. In a moderate water shortage scenario, deficit irrigation was an effective strategy to cope with climate change risks. In a severe water shortage scenario, the study showed the potentiality of intra-specific biodiversity to reduce risk of yield losses, although costs should be evaluated against the benefits of each specific management option. The work was carried out within the Italian national project AGROSCENARI funded by the Ministry for Agricultural, Food and Forest Policies (MIPAAF, D.M. 8608/7303/2008)

Comparing cropland net primary production estimates from inventory, a satellite-based model, and a process-based model in the Midwest of the United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Zhengpeng; Liu, Shuguang; Tan, Zhengxi

2014-04-01

Accurately quantifying the spatial and temporal variability of net primary production (NPP) for croplands is essential to understand regional cropland carbon dynamics. We compared three NPP estimates for croplands in the Midwestern United States: inventory-based estimates using crop yield data from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS); estimates from the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) NPP product; and estimates from the General Ensemble biogeochemical Modeling System (GEMS) process-based model. The three methods estimated mean NPP in the range of 469–687 g C m -2 yr -1 and total NPP in the range of 318–490more » Tg C yr -1 for croplands in the Midwest in 2007 and 2008. The NPP estimates from crop yield data and the GEMS model showed the mean NPP for croplands was over 650 g C m -2 yr -1 while the MODIS NPP product estimated the mean NPP was less than 500 g C m -2 yr -1. MODIS NPP also showed very different spatial variability of the cropland NPP from the other two methods. We found these differences were mainly caused by the difference in the land cover data and the crop specific information used in the methods. Our study demonstrated that the detailed mapping of the temporal and spatial change of crop species is critical for estimating the spatial and temporal variability of cropland NPP. Finally, we suggest that high resolution land cover data with species–specific crop information should be used in satellite-based and process-based models to improve carbon estimates for croplands.« less

Comparing cropland net primary production estimates from inventory, a satellite-based model, and a process-based model in the Midwest of the United States

USGS Publications Warehouse

Li, Zhengpeng; Liu, Shuguang; Tan, Zhengxi; Bliss, Norman B.; Young, Claudia J.; West, Tristram O.; Ogle, Stephen M.

2014-01-01

Accurately quantifying the spatial and temporal variability of net primary production (NPP) for croplands is essential to understand regional cropland carbon dynamics. We compared three NPP estimates for croplands in the Midwestern United States: inventory-based estimates using crop yield data from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS); estimates from the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) NPP product; and estimates from the General Ensemble biogeochemical Modeling System (GEMS) process-based model. The three methods estimated mean NPP in the range of 469–687 g C m−2 yr−1and total NPP in the range of 318–490 Tg C yr−1 for croplands in the Midwest in 2007 and 2008. The NPP estimates from crop yield data and the GEMS model showed the mean NPP for croplands was over 650 g C m−2 yr−1 while the MODIS NPP product estimated the mean NPP was less than 500 g C m−2 yr−1. MODIS NPP also showed very different spatial variability of the cropland NPP from the other two methods. We found these differences were mainly caused by the difference in the land cover data and the crop specific information used in the methods. Our study demonstrated that the detailed mapping of the temporal and spatial change of crop species is critical for estimating the spatial and temporal variability of cropland NPP. We suggest that high resolution land cover data with species–specific crop information should be used in satellite-based and process-based models to improve carbon estimates for croplands.

MAXIMIZE THE EFFICIENCY OF PUMP AND TREAT SYSTEMS

EPA Science Inventory

This paper focuses on methodology for determing extent of hydraulic control and remediation effectiveness of site specific pump and treat systems. Maximum potential well yield is estimated on the basis of hydraulic characteristics described by the cooper and Jacob Equation. A ma...

Sensitivity and specificity of the Streptococcus pneumoniae urinary antigen test for unconcentrated urine from adult patients with pneumonia: a meta-analysis.

PubMed

Horita, Nobuyuki; Miyazawa, Naoki; Kojima, Ryota; Kimura, Naoko; Inoue, Miyo; Ishigatsubo, Yoshiaki; Kaneko, Takeshi

2013-11-01

Studies on the sensitivity and specificity of the Binax Now Streptococcus pneumonia urinary antigen test (index test) show considerable variance of results. Those written in English provided sufficient original data to evaluate the sensitivity and specificity of the index test using unconcentrated urine to identify S. pneumoniae infection in adults with pneumonia. Reference tests were conducted with at least one culture and/or smear. We estimated sensitivity and two specificities. One was the specificity evaluated using only patients with pneumonia of identified other aetiologies ('specificity (other)'). The other was the specificity evaluated based on both patients with pneumonia of unknown aetiology and those with pneumonia of other aetiologies ('specificity (unknown and other)') using a fixed model for meta-analysis. We found 10 articles involving 2315 patients. The analysis of 10 studies involving 399 patients yielded a pooled sensitivity of 0.75 (95% confidence interval: 0.71-0.79) without heterogeneity or publication bias. The analysis of six studies involving 258 patients yielded a pooled specificity (other) of 0.95 (95% confidence interval: 0.92-0.98) without no heterogeneity or publication bias. We attempted to conduct a meta-analysis with the 10 studies involving 1916 patients to estimate specificity (unknown and other), but it remained unclear due to moderate heterogeneity and possible publication bias. In our meta-analysis, sensitivity of the index test was moderate and specificity (other) was high; however, the specificity (unknown and other) remained unclear. © 2013 The Authors. Respirology © 2013 Asian Pacific Society of Respirology.

The patterns of genomic variances and covariances across genome for milk production traits between Chinese and Nordic Holstein populations.

PubMed

Li, Xiujin; Lund, Mogens Sandø; Janss, Luc; Wang, Chonglong; Ding, Xiangdong; Zhang, Qin; Su, Guosheng

2017-03-15

With the development of SNP chips, SNP information provides an efficient approach to further disentangle different patterns of genomic variances and covariances across the genome for traits of interest. Due to the interaction between genotype and environment as well as possible differences in genetic background, it is reasonable to treat the performances of a biological trait in different populations as different but genetic correlated traits. In the present study, we performed an investigation on the patterns of region-specific genomic variances, covariances and correlations between Chinese and Nordic Holstein populations for three milk production traits. Variances and covariances between Chinese and Nordic Holstein populations were estimated for genomic regions at three different levels of genome region (all SNP as one region, each chromosome as one region and every 100 SNP as one region) using a novel multi-trait random regression model which uses latent variables to model heterogeneous variance and covariance. In the scenario of the whole genome as one region, the genomic variances, covariances and correlations obtained from the new multi-trait Bayesian method were comparable to those obtained from a multi-trait GBLUP for all the three milk production traits. In the scenario of each chromosome as one region, BTA 14 and BTA 5 accounted for very large genomic variance, covariance and correlation for milk yield and fat yield, whereas no specific chromosome showed very large genomic variance, covariance and correlation for protein yield. In the scenario of every 100 SNP as one region, most regions explained <0.50% of genomic variance and covariance for milk yield and fat yield, and explained <0.30% for protein yield, while some regions could present large variance and covariance. Although overall correlations between two populations for the three traits were positive and high, a few regions still showed weakly positive or highly negative genomic correlations for milk yield and fat yield. The new multi-trait Bayesian method using latent variables to model heterogeneous variance and covariance could work well for estimating the genomic variances and covariances for all genome regions simultaneously. Those estimated genomic parameters could be useful to improve the genomic prediction accuracy for Chinese and Nordic Holstein populations using a joint reference data in the future.

Integrating remote sensing, geographic information system and modeling for estimating crop yield

NASA Astrophysics Data System (ADS)

Salazar, Luis Alonso

This thesis explores various aspects of the use of remote sensing, geographic information system and digital signal processing technologies for broad-scale estimation of crop yield in Kansas. Recent dry and drought years in the Great Plains have emphasized the need for new sources of timely, objective and quantitative information on crop conditions. Crop growth monitoring and yield estimation can provide important information for government agencies, commodity traders and producers in planning harvest, storage, transportation and marketing activities. The sooner this information is available the lower the economic risk translating into greater efficiency and increased return on investments. Weather data is normally used when crop yield is forecasted. Such information, to provide adequate detail for effective predictions, is typically feasible only on small research sites due to expensive and time-consuming collections. In order for crop assessment systems to be economical, more efficient methods for data collection and analysis are necessary. The purpose of this research is to use satellite data which provides 50 times more spatial information about the environment than the weather station network in a short amount of time at a relatively low cost. Specifically, we are going to use Advanced Very High Resolution Radiometer (AVHRR) based vegetation health (VH) indices as proxies for characterization of weather conditions.

Estimation of hydraulic parameters from an unconfined aquifer test conducted in a glacial outwash deposit, Cape Cod, Massachusetts

USGS Publications Warehouse

Moench, A.F.; Garabedian, Stephen P.; LeBlanc, Denis R.

2000-01-01

An aquifer test conducted in a sand and gravel, glacial outwash deposit on Cape Cod, Massachusetts was analyzed by means of a model for flow to a partially penetrating well in a homogeneous, anisotropic unconfined aquifer. The model is designed to account for all significant mechanisms expected to influence drawdown in observation piezometers and in the pumped well. In addition to the usual fluid-flow and storage processes, additional processes include effects of storage in the pumped well, storage in observation piezometers, effects of skin at the pumped-well screen, and effects of drainage from the zone above the water table. The aquifer was pumped at a rate of 320 gallons per minute for 72-hours and drawdown measurements were made in the pumped well and in 20 piezometers located at various distances from the pumped well and depths below the land surface. To facilitate the analysis, an automatic parameter estimation algorithm was used to obtain relevant unconfined aquifer parameters, including the saturated thickness and a set of empirical parameters that relate to gradual drainage from the unsaturated zone. Drainage from the unsaturated zone is treated in this paper as a finite series of exponential terms, each of which contains one empirical parameter that is to be determined. It was necessary to account for effects of gradual drainage from the unsaturated zone to obtain satisfactory agreement between measured and simulated drawdown, particularly in piezometers located near the water table. The commonly used assumption of instantaneous drainage from the unsaturated zone gives rise to large discrepancies between measured and predicted drawdown in the intermediate-time range and can result in inaccurate estimates of aquifer parameters when automatic parameter estimation procedures are used. The values of the estimated hydraulic parameters are consistent with estimates from prior studies and from what is known about the aquifer at the site. Effects of heterogeneity at the site were small as measured drawdowns in all piezometers and wells were very close to the simulated values for a homogeneous porous medium. The estimated values are: specific yield, 0.26; saturated thickness, 170 feet; horizontal hydraulic conductivity, 0.23 feet per minute; vertical hydraulic conductivity, 0.14 feet per minute; and specific storage, 1.3x10-5 per foot. It was found that drawdown in only a few piezometers strategically located at depth near the pumped well yielded parameter estimates close to the estimates obtained for the entire data set analyzed simultaneously. If the influence of gradual drainage from the unsaturated zone is not taken into account, specific yield is significantly underestimated even in these deep-seated piezometers. This helps to explain the low values of specific yield often reported for granular aquifers in the literature. If either the entire data set or only the drawdown in selected deep-seated piezometers was used, it was found unnecessary to conduct the test for the full 72-hours to obtain accurate estimates of the hydraulic parameters. For some piezometer groups, practically identical results would be obtained for an aquifer test conducted for only 8-hours. Drawdowns measured in the pumped well and piezometers at distant locations were diagnostic only of aquifer transmissivity.

Aquifer response to stream-stage and recharge variations. II. Convolution method and applications

NASA Astrophysics Data System (ADS)

Barlow, P. M.; DeSimone, L. A.; Moench, A. F.

2000-05-01

In this second of two papers, analytical step-response functions, developed in the companion paper for several cases of transient hydraulic interaction between a fully penetrating stream and a confined, leaky, or water-table aquifer, are used in the convolution integral to calculate aquifer heads, streambank seepage rates, and bank storage that occur in response to stream-stage fluctuations and basinwide recharge or evapotranspiration. Two computer programs developed on the basis of these step-response functions and the convolution integral are applied to the analysis of hydraulic interaction of two alluvial stream-aquifer systems in the northeastern and central United States. These applications demonstrate the utility of the analytical functions and computer programs for estimating aquifer and streambank hydraulic properties, recharge rates, streambank seepage rates, and bank storage. Analysis of the water-table aquifer adjacent to the Blackstone River in Massachusetts suggests that the very shallow depth of water table and associated thin unsaturated zone at the site cause the aquifer to behave like a confined aquifer (negligible specific yield). This finding is consistent with previous studies that have shown that the effective specific yield of an unconfined aquifer approaches zero when the capillary fringe, where sediment pores are saturated by tension, extends to land surface. Under this condition, the aquifer's response is determined by elastic storage only. Estimates of horizontal and vertical hydraulic conductivity, specific yield, specific storage, and recharge for a water-table aquifer adjacent to the Cedar River in eastern Iowa, determined by the use of analytical methods, are in close agreement with those estimated by use of a more complex, multilayer numerical model of the aquifer. Streambank leakance of the semipervious streambank materials also was estimated for the site. The streambank-leakance parameter may be considered to be a general (or lumped) parameter that accounts not only for the resistance of flow at the river-aquifer boundary, but also for the effects of partial penetration of the river and other near-stream flow phenomena not included in the theoretical development of the step-response functions.

Statistical and Economic Techniques for Site-specific Nematode Management.

PubMed

Liu, Zheng; Griffin, Terry; Kirkpatrick, Terrence L

2014-03-01

Recent advances in precision agriculture technologies and spatial statistics allow realistic, site-specific estimation of nematode damage to field crops and provide a platform for the site-specific delivery of nematicides within individual fields. This paper reviews the spatial statistical techniques that model correlations among neighboring observations and develop a spatial economic analysis to determine the potential of site-specific nematicide application. The spatial econometric methodology applied in the context of site-specific crop yield response contributes to closing the gap between data analysis and realistic site-specific nematicide recommendations and helps to provide a practical method of site-specifically controlling nematodes.

Temperature Increase Reduces Global Yields of Major Crops in Four Independent Estimates

NASA Technical Reports Server (NTRS)

Zhao, Chuang; Liu, Bing; Piao, Shilong; Wang, Xuhui; Lobell, David B.; Huang, Yao; Huang, Mengtian; Yao, Yitong; Bassu, Simona; Ciais, Philippe;

Temperature increase reduces global yields of major crops in four independent estimates

PubMed Central

Zhao, Chuang; Piao, Shilong; Wang, Xuhui; Lobell, David B.; Huang, Yao; Huang, Mengtian; Yao, Yitong; Bassu, Simona; Ciais, Philippe; Durand, Jean-Louis; Elliott, Joshua; Ewert, Frank; Janssens, Ivan A.; Li, Tao; Lin, Erda; Liu, Qiang; Martre, Pierre; Peng, Shushi; Wallach, Daniel; Wang, Tao; Wu, Donghai; Liu, Zhuo; Zhu, Yan; Zhu, Zaichun; Asseng, Senthold

2017-01-01

Wheat, rice, maize, and soybean provide two-thirds of human caloric intake. Assessing the impact of global temperature increase on production of these crops is therefore critical to maintaining global food supply, but different studies have yielded different results. Here, we investigated the impacts of temperature on yields of the four crops by compiling extensive published results from four analytical methods: global grid-based and local point-based models, statistical regressions, and field-warming experiments. Results from the different methods consistently showed negative temperature impacts on crop yield at the global scale, generally underpinned by similar impacts at country and site scales. Without CO2 fertilization, effective adaptation, and genetic improvement, each degree-Celsius increase in global mean temperature would, on average, reduce global yields of wheat by 6.0%, rice by 3.2%, maize by 7.4%, and soybean by 3.1%. Results are highly heterogeneous across crops and geographical areas, with some positive impact estimates. Multimethod analyses improved the confidence in assessments of future climate impacts on global major crops and suggest crop- and region-specific adaptation strategies to ensure food security for an increasing world population. PMID:28811375

Temperature increase reduces global yields of major crops in four independent estimates.

PubMed

Zhao, Chuang; Liu, Bing; Piao, Shilong; Wang, Xuhui; Lobell, David B; Huang, Yao; Huang, Mengtian; Yao, Yitong; Bassu, Simona; Ciais, Philippe; Durand, Jean-Louis; Elliott, Joshua; Ewert, Frank; Janssens, Ivan A; Li, Tao; Lin, Erda; Liu, Qiang; Martre, Pierre; Müller, Christoph; Peng, Shushi; Peñuelas, Josep; Ruane, Alex C; Wallach, Daniel; Wang, Tao; Wu, Donghai; Liu, Zhuo; Zhu, Yan; Zhu, Zaichun; Asseng, Senthold

2017-08-29

Wheat, rice, maize, and soybean provide two-thirds of human caloric intake. Assessing the impact of global temperature increase on production of these crops is therefore critical to maintaining global food supply, but different studies have yielded different results. Here, we investigated the impacts of temperature on yields of the four crops by compiling extensive published results from four analytical methods: global grid-based and local point-based models, statistical regressions, and field-warming experiments. Results from the different methods consistently showed negative temperature impacts on crop yield at the global scale, generally underpinned by similar impacts at country and site scales. Without CO 2 fertilization, effective adaptation, and genetic improvement, each degree-Celsius increase in global mean temperature would, on average, reduce global yields of wheat by 6.0%, rice by 3.2%, maize by 7.4%, and soybean by 3.1%. Results are highly heterogeneous across crops and geographical areas, with some positive impact estimates. Multimethod analyses improved the confidence in assessments of future climate impacts on global major crops and suggest crop- and region-specific adaptation strategies to ensure food security for an increasing world population.

Spatial and Temporal Uncertainty of Crop Yield Aggregations

NASA Technical Reports Server (NTRS)

Porwollik, Vera; Mueller, Christoph; Elliott, Joshua; Chryssanthacopoulos, James; Iizumi, Toshichika; Ray, Deepak K.; Ruane, Alex C.; Arneth, Almut; Balkovic, Juraj; Ciais, Philippe;

Analysis of pumping tests: Significance of well diameter, partial penetration, and noise

USGS Publications Warehouse

Heidari, M.; Ghiassi, K.; Mehnert, E.

1999-01-01

The nonlinear least squares (NLS) method was applied to pumping and recovery aquifer test data in confined and unconfined aquifers with finite diameter and partially penetrating pumping wells, and with partially penetrating piezometers or observation wells. It was demonstrated that noiseless and moderately noisy drawdown data from observation points located less than two saturated thicknesses of the aquifer from the pumping well produced an exact or acceptable set of parameters when the diameter of the pumping well was included in the analysis. The accuracy of the estimated parameters, particularly that of specific storage, decreased with increases in the noise level in the observed drawdown data. With consideration of the well radii, the noiseless drawdown data from the pumping well in an unconfined aquifer produced good estimates of horizontal and vertical hydraulic conductivities and specific yield, but the estimated specific storage was unacceptable. When noisy data from the pumping well were used, an acceptable set of parameters was not obtained. Further experiments with noisy drawdown data in an unconfined aquifer revealed that when the well diameter was included in the analysis, hydraulic conductivity, specific yield and vertical hydraulic conductivity may be estimated rather effectively from piezometers located over a range of distances from the pumping well. Estimation of specific storage became less reliable for piezemeters located at distances greater than the initial saturated thickness of the aquifer. Application of the NLS to field pumping and recovery data from a confined aquifer showed that the estimated parameters from the two tests were in good agreement only when the well diameter was included in the analysis. Without consideration of well radii, the estimated values of hydraulic conductivity from the pumping and recovery tests were off by a factor of four.The nonlinear least squares method was applied to pumping and recovery aquifer test data in confined and unconfined aquifers with finite diameter and partially penetrating piezometers and observation wells. Noiseless and moderately noisy drawdown data from observation points located less than two saturated thicknesses of the aquifer from the pumping well produced a set of parameters that agrees very well with piezometer test data when the diameter of the pumping well was included in the analysis. The accuracy of the estimated parameters decreased with increasing noise level.

Determinants of hospital tax-exempt debt yields: corrections for selection and simultaneous equation bias.

PubMed Central

Carpenter, C E

1992-01-01

The cost of capital for hospitals is a topic of continuing interest as Medicare's new capital payment policy is implemented. This study examines the determinants of tax-exempt revenue bond yields, the primary source of long-term capital for hospitals. Two important methodological issues are addressed. A probit analysis estimates the probability that a hospital or system will be observed in the tax-exempt market. A selection-corrected two-stage least squares analysis allows for the simultaneous determination of bond yield and bond size. The study is based on a sample of hospitals that issued tax-exempt revenue bonds in 1982-1984, the years immediately surrounding implementation of Medicare's new payment system based on diagnosis-related groups, and an equal number of hospitals not in the market during the study period. Results suggest that hospital systems and hospitals with high occupancy rates are most likely to enter the tax-exempt revenue bond market. The yield equation suggests that hospital-specific variables may not be good predictors of the cost of capital once estimates are corrected for selection. PMID:1464540

Determinants of hospital tax-exempt debt yields: corrections for selection and simultaneous equation bias.

PubMed

Carpenter, C E

1992-12-01

The cost of capital for hospitals is a topic of continuing interest as Medicare's new capital payment policy is implemented. This study examines the determinants of tax-exempt revenue bond yields, the primary source of long-term capital for hospitals. Two important methodological issues are addressed. A probit analysis estimates the probability that a hospital or system will be observed in the tax-exempt market. A selection-corrected two-stage least squares analysis allows for the simultaneous determination of bond yield and bond size. The study is based on a sample of hospitals that issued tax-exempt revenue bonds in 1982-1984, the years immediately surrounding implementation of Medicare's new payment system based on diagnosis-related groups, and an equal number of hospitals not in the market during the study period. Results suggest that hospital systems and hospitals with high occupancy rates are most likely to enter the tax-exempt revenue bond market. The yield equation suggests that hospital-specific variables may not be good predictors of the cost of capital once estimates are corrected for selection.

How does spatial and temporal resolution of vegetation index impact crop yield estimation?

USDA-ARS?s Scientific Manuscript database

Timely and accurate estimation of crop yield before harvest is critical for food market and administrative planning. Remote sensing data have long been used in crop yield estimation for decades. The process-based approach uses light use efficiency model to estimate crop yield. Vegetation index (VI) ...

The Rangeland Hydrology and Erosion Model: A Dynamic Approach for Predicting Soil Loss on Rangelands

NASA Astrophysics Data System (ADS)

Hernandez, Mariano; Nearing, Mark A.; Al-Hamdan, Osama Z.; Pierson, Frederick B.; Armendariz, Gerardo; Weltz, Mark A.; Spaeth, Kenneth E.; Williams, C. Jason; Nouwakpo, Sayjro K.; Goodrich, David C.; Unkrich, Carl L.; Nichols, Mary H.; Holifield Collins, Chandra D.

2017-11-01

In this study, we present the improved Rangeland Hydrology and Erosion Model (RHEM V2.3), a process-based erosion prediction tool specific for rangeland application. The article provides the mathematical formulation of the model and parameter estimation equations. Model performance is assessed against data collected from 23 runoff and sediment events in a shrub-dominated semiarid watershed in Arizona, USA. To evaluate the model, two sets of primary model parameters were determined using the RHEM V2.3 and RHEM V1.0 parameter estimation equations. Testing of the parameters indicated that RHEM V2.3 parameter estimation equations provided a 76% improvement over RHEM V1.0 parameter estimation equations. Second, the RHEM V2.3 model was calibrated to measurements from the watershed. The parameters estimated by the new equations were within the lowest and highest values of the calibrated parameter set. These results suggest that the new parameter estimation equations can be applied for this environment to predict sediment yield at the hillslope scale. Furthermore, we also applied the RHEM V2.3 to demonstrate the response of the model as a function of foliar cover and ground cover for 124 data points across Arizona and New Mexico. The dependence of average sediment yield on surface ground cover was moderately stronger than that on foliar cover. These results demonstrate that RHEM V2.3 predicts runoff volume, peak runoff, and sediment yield with sufficient accuracy for broad application to assess and manage rangeland systems.

Estimating sugarcane yield potential using an in-season determination of normalized difference vegetative index.

PubMed

Lofton, Josh; Tubana, Brenda S; Kanke, Yumiko; Teboh, Jasper; Viator, Howard; Dalen, Marilyn

2012-01-01

Estimating crop yield using remote sensing techniques has proven to be successful. However, sugarcane possesses unique characteristics; such as, a multi-year cropping cycle and plant height-limiting for midseason fertilizer application timing. Our study objective was to determine if sugarcane yield potential could be estimated using an in-season estimation of normalized difference vegetative index (NDVI). Sensor readings were taken using the GreenSeeker® handheld sensor from 2008 to 2011 in St. Gabriel and Jeanerette, LA, USA. In-season estimates of yield (INSEY) values were calculated by dividing NDVI by thermal variables. Optimum timing for estimating sugarcane yield was between 601-750 GDD. In-season estimated yield values improved the yield potential (YP) model compared to using NDVI. Generally, INSEY value showed a positive exponential relationship with yield (r(2) values 0.48 and 0.42 for cane tonnage and sugar yield, respectively). When models were separated based on canopy structure there was an increase the strength of the relationship for the erectophile varieties (r(2) 0.53 and 0.47 for cane tonnage and sugar yield, respectively); however, the model for planophile varieties weakened slightly. Results of this study indicate using an INSEY value for predicting sugarcane yield shows potential of being a valuable management tool for sugarcane producers in Louisiana.

Estimating the variance for heterogeneity in arm-based network meta-analysis.

PubMed

Piepho, Hans-Peter; Madden, Laurence V; Roger, James; Payne, Roger; Williams, Emlyn R

2018-04-19

Network meta-analysis can be implemented by using arm-based or contrast-based models. Here we focus on arm-based models and fit them using generalized linear mixed model procedures. Full maximum likelihood (ML) estimation leads to biased trial-by-treatment interaction variance estimates for heterogeneity. Thus, our objective is to investigate alternative approaches to variance estimation that reduce bias compared with full ML. Specifically, we use penalized quasi-likelihood/pseudo-likelihood and hierarchical (h) likelihood approaches. In addition, we consider a novel model modification that yields estimators akin to the residual maximum likelihood estimator for linear mixed models. The proposed methods are compared by simulation, and 2 real datasets are used for illustration. Simulations show that penalized quasi-likelihood/pseudo-likelihood and h-likelihood reduce bias and yield satisfactory coverage rates. Sum-to-zero restriction and baseline contrasts for random trial-by-treatment interaction effects, as well as a residual ML-like adjustment, also reduce bias compared with an unconstrained model when ML is used, but coverage rates are not quite as good. Penalized quasi-likelihood/pseudo-likelihood and h-likelihood are therefore recommended. Copyright © 2018 John Wiley & Sons, Ltd.

Infrasound Studies for Yield Estimation of HE Explosions

DTIC Science & Technology

2012-06-05

AFRL-RV-PS- AFRL-RV-PS- TR-2012-0084 TR-2012-0084 INFRASOUND STUDIES FOR YIELD ESTIMATION OF HE EXPLOSIONS Paul Golden, et al...05 Mar 2010 to 05 Mar 2012 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER FA9453-10-C-0212 Infrasound Studies for Yield Estimation of HE...report we discuss the capability of estimating the yield of an explosion from infrasound signals generated by low yield chemical explosions. We used

Measurement of ground-water storage change and specific yield using the temporal-gravity method near Rillito Creek, Tucson, Arizona

USGS Publications Warehouse

Pool, Donald R.; Schmidt, Werner

1997-01-01

The temporal-gravity method was used to estimate ground-water storage change and specific -yield values at wells near Rillito Creek, Tucson, Arizona, between early December 1992 and early January 1994. The method applies Newton's Law of Gravitation to measure changes in the local gravitational field of the Earth that are caused by changes in the mass and volume of ground water. Gravity at 50 stations in a 6-square-mile area was measured repeatedly relative to gravity at two bedrock stations. Ephemeral recharge through streamflow infiltration during the winter of 1992-93 resulted in water-level rises and gravity increases near Rillito Creek as the volume of ground water in storage increased. Water levels in wells rose as much as 30 feet, and gravity increased as much as 90 microgals. Water levels declined and gravity decreased near the stream after the last major winter flow but continued to rise and increase, respectively, in downgradient areas. Water levels and gravity relative to bedrock were measured at 10 wells. Good linear correlations between water levels and gravity values at five wells nearest the stream allowed for the estimation of specific-yield values for corresponding stratigraphic units assuming the mass change occurred in an infinite horizonal slab of uniform thickness. Specific-yield values for the stream-channel deposits at three wells ranged from 0.15 to 0.34, and correlation coefficients ranged from 0.81 to 0.99. Specific-yield values for the Fort Lowell Formation at three wells ranged from 0.07 to 0.18, and correlation coefficients ranged from 0.82 to 0.93. Specific-yield values were not calculated for the five wells farthest from the stream because of insufficient water-level and gravity change or poor correlations between water level and gravity. Poor correlations between water levels and gravity resulted from ground-water storage change in perched aquifers and in the unsaturated zone near ephemeral streams. Seasonal distributions of ground-water storage change since early December 1992 were evaluated from gravity change at all stations using Gauss's Law. Changes in the distribution of gravity are caused by the flow of water into or out of ground-water storage. Gravity along two profiles was measured frequently to evaluate spatial and temporal distributions of gravity change. Gravity variations indicated preferential ground-water flow to the south in the western part of the study area where the saturate thickness of the aquifer is greatest. Storage changes from December 1992 through early March 1993, mid-May 1993, late August 1993, and early January 1994 were calculated as increases of 7,900, 8,000, 6,300, and 3,700 acre-feet, respectively. Seasonal variations in storage were caused by ground-water withdrawlas, ground-water flow across the boundaries of the gravity-station network, and streamflow infiltration from December 1992 through late April 1993. Most of the estimated recharge of 10,900 acre-feet occurred before mid-May 1993.

Merchantable sawlog and bole-length equations for the Northeastern United States

Treesearch

Daniel A. Yaussy; Martin E. Dale; Martin E. Dale

1991-01-01

A modified Richards growth model is used to develop species-specific coefficients for equations estimating the merchantable sawlog and bole lengths of trees from 25 species groups common to the Northeastern United States. These regression coefficients have been incorporated into the growth-and-yield simulation software, NE-TWIGS.

Diagnostic performance of HbA1c for diabetes in Arab vs. European populations: a systematic review and meta-analysis.

PubMed

Bertran, E A; Berlie, H D; Taylor, A; Divine, G; Jaber, L A

2017-02-01

To examine differences in the performance of HbA 1c for diagnosing diabetes in Arabs compared with Europeans. The PubMed, Embase and Cochrane library databases were searched for records published between 1998 and 2015. Estimates of sensitivity, specificity and log diagnostic odds ratios for an HbA 1c cut-point of 48 mmol/mol (6.5%) were compared between Arabs and Europeans, using a bivariate linear mixed-model approach. For studies reporting multiple cut-points, population-specific summary receiver operating characteristic (SROC) curves were constructed. In addition, sensitivity, specificity and Youden Index were estimated for strata defined by HbA 1c cut-point and population type. Database searches yielded 1912 unique records; 618 full-text articles were reviewed. Fourteen studies met the inclusion criteria; hand-searching yielded three additional eligible studies. Three Arab (N = 2880) and 16 European populations (N = 49 127) were included in the analysis. Summary sensitivity and specificity for a HbA 1c cut-point of 48 mmol/mol (6.5%) in both populations were 42% (33-51%), and 97% (95-98%). There was no difference in area under SROC curves between Arab and European populations (0.844 vs. 0.847; P = 0.867), suggesting no difference in HbA 1c diagnostic accuracy between populations. Multiple cut-point summary estimates stratified by population suggest that Arabs have lower sensitivity and higher specificity at a HbA 1c cut-point of 44 mmol/mol (6.2%) compared with European populations. Estimates also suggest similar test performance at cut-points of 44 mmol/mol (6.2%) and 48 mmol/mol (6.5%) for Arabs. Given the low sensitivity of HbA 1c in the high-risk Arab American population, we recommend a combination of glucose-based and HbA 1c testing to ensure an accurate and timely diagnosis of diabetes. © 2016 Diabetes UK.

Optimized tuner selection for engine performance estimation

NASA Technical Reports Server (NTRS)

Simon, Donald L. (Inventor); Garg, Sanjay (Inventor)

2013-01-01

A methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. Theoretical Kalman filter estimation error bias and variance values are derived at steady-state operating conditions, and the tuner selection routine is applied to minimize these values. The new methodology yields an improvement in on-line engine performance estimation accuracy.

Analysis of pumping tests of partially penetrating wells in an unconfined aquifer using inverse numerical optimization

NASA Astrophysics Data System (ADS)

Hvilshøj, S.; Jensen, K. H.; Barlebo, H. C.; Madsen, B.

1999-08-01

Inverse numerical modeling was applied to analyze pumping tests of partially penetrating wells carried out in three wells established in an unconfined aquifer in Vejen, Denmark, where extensive field investigations had previously been carried out, including tracer tests, mini-slug tests, and other hydraulic tests. Drawdown data from multiple piezometers located at various horizontal and vertical distances from the pumping well were included in the optimization. Horizontal and vertical hydraulic conductivities, specific storage, and specific yield were estimated, assuming that the aquifer was either a homogeneous system with vertical anisotropy or composed of two or three layers of different hydraulic properties. In two out of three cases, a more accurate interpretation was obtained for a multi-layer model defined on the basis of lithostratigraphic information obtained from geological descriptions of sediment samples, gammalogs, and flow-meter tests. Analysis of the pumping tests resulted in values for horizontal hydraulic conductivities that are in good accordance with those obtained from slug tests and mini-slug tests. Besides the horizontal hydraulic conductivity, it is possible to determine the vertical hydraulic conductivity, specific yield, and specific storage based on a pumping test of a partially penetrating well. The study demonstrates that pumping tests of partially penetrating wells can be analyzed using inverse numerical models. The model used in the study was a finite-element flow model combined with a non-linear regression model. Such a model can accommodate more geological information and complex boundary conditions, and the parameter-estimation procedure can be formalized to obtain optimum estimates of hydraulic parameters and their standard deviations.

Study to establish cost projections for production of Redox chemicals

NASA Technical Reports Server (NTRS)

Walther, J. F.; Greco, C. C.; Rusinko, R. N.; Wadsworth, A. L., III

1982-01-01

A cost study of four proposed manufacturing processes for redox chemicals for the NASA REDOX Energy Storage System yielded favorable selling prices in the range $0.99 to $1.91/kg of chromic chloride, anhydrous basis, including ferrous chloride. The prices corresponded to specific energy storage costs from under $9 to $17/kWh. A refined and expanded cost analysis of the most favored process yielded a price estimate corresponding to a storage cost of $11/kWh. The findings supported the potential economic viability of the NASA REDOX system.

Closing yield gaps: perils and possibilities for biodiversity conservation.

PubMed

Phalan, Ben; Green, Rhys; Balmford, Andrew

2014-04-05

Increasing agricultural productivity to 'close yield gaps' creates both perils and possibilities for biodiversity conservation. Yield increases often have negative impacts on species within farmland, but at the same time could potentially make it more feasible to minimize further cropland expansion into natural habitats. We combine global data on yield gaps, projected future production of maize, rice and wheat, the distributions of birds and their estimated sensitivity to changes in crop yields to map where it might be most beneficial for bird conservation to close yield gaps as part of a land-sparing strategy, and where doing so might be most damaging. Closing yield gaps to attainable levels to meet projected demand in 2050 could potentially help spare an area equivalent to that of the Indian subcontinent. Increasing yields this much on existing farmland would inevitably reduce its biodiversity, and therefore we advocate efforts both to constrain further increases in global food demand, and to identify the least harmful ways of increasing yields. The land-sparing potential of closing yield gaps will not be realized without specific mechanisms to link yield increases to habitat protection (and restoration), and therefore we suggest that conservationists, farmers, crop scientists and policy-makers collaborate to explore promising mechanisms.

Yield estimation of sugarcane based on agrometeorological-spectral models

NASA Technical Reports Server (NTRS)

Rudorff, Bernardo Friedrich Theodor; Batista, Getulio Teixeira

1990-01-01

This work has the objective to assess the performance of a yield estimation model for sugarcane (Succharum officinarum). The model uses orbital gathered spectral data along with yield estimated from an agrometeorological model. The test site includes the sugarcane plantations of the Barra Grande Plant located in Lencois Paulista municipality in Sao Paulo State. Production data of four crop years were analyzed. Yield data observed in the first crop year (1983/84) were regressed against spectral and agrometeorological data of that same year. This provided the model to predict the yield for the following crop year i.e., 1984/85. The model to predict the yield of subsequent years (up to 1987/88) were developed similarly, incorporating all previous years data. The yield estimations obtained from these models explained 69, 54, and 50 percent of the yield variation in the 1984/85, 1985/86, and 1986/87 crop years, respectively. The accuracy of yield estimations based on spectral data only (vegetation index model) and on agrometeorological data only (agrometeorological model) were also investigated.

Noise exposure-response relationships established from repeated binary observations: Modeling approaches and applications.

PubMed

Schäffer, Beat; Pieren, Reto; Mendolia, Franco; Basner, Mathias; Brink, Mark

2017-05-01

Noise exposure-response relationships are used to estimate the effects of noise on individuals or a population. Such relationships may be derived from independent or repeated binary observations, and modeled by different statistical methods. Depending on the method by which they were established, their application in population risk assessment or estimation of individual responses may yield different results, i.e., predict "weaker" or "stronger" effects. As far as the present body of literature on noise effect studies is concerned, however, the underlying statistical methodology to establish exposure-response relationships has not always been paid sufficient attention. This paper gives an overview on two statistical approaches (subject-specific and population-averaged logistic regression analysis) to establish noise exposure-response relationships from repeated binary observations, and their appropriate applications. The considerations are illustrated with data from three noise effect studies, estimating also the magnitude of differences in results when applying exposure-response relationships derived from the two statistical approaches. Depending on the underlying data set and the probability range of the binary variable it covers, the two approaches yield similar to very different results. The adequate choice of a specific statistical approach and its application in subsequent studies, both depending on the research question, are therefore crucial.

Hydrogeologic terranes and potential yield of water to wells in the Valley and Ridge Physiographic Province in the eastern and southeastern United States

USGS Publications Warehouse

Hollyday, E.F.; Hileman, G.E.

1996-01-01

The Valley and Ridge Physiographic Province is underlain by deformed sedimentary rock of Paleozoic age including dolomite, limestone, shale, and sandstone. Regolith (soil, sediment, and weathered rock) covers the Paleozoic rock throughout most of the province. Local differences in lithology, structure, and weathering can result in four orders of magnitude variation in the water-yielding properties of the geologic units that underlie the area. Selected rock types, however, can account for a substantial part of this variation because of the unique way in which these dense, consolidated sedimentary rock types deform and weather to produce secondary openings.On the basis of relations among rock type, water-yielding openings, and water-yielding properties (as indicated by specific capacity), the regolith and consolidated rock were classified and mapped as five hydrogeologic terranes alluvium, dolomite, limestone, argillaceous carbonate rock, and siliciclastic rock. The hydrogeologic terranes are named after the predominant outcrop lithology within them. The western toe of the Blue Ridge Mountains is classified as a subdivision of the dolomite hydrogeologic terrane that may produce yields of water in excess of 1,000 gallons per minute (gal/min) to public and industrial supply wells. Specific-capacity data for homogeneous data sets, which consist of all wells that have the same characteristics in regard to casing diameter, primary use of the water, and topographic setting, revealed significant differences in water-yielding properties among the five hydrogeologic terranes. According to results of Tukey statistical tests at a probability (alpha level) of 0.05, 8 out of 10 pairs of hydrogeologic terranes (for example, alluvium/limestone) had significantly different median specific-capacity values. The median value for public and industrial supply wells in the western toe is three times greater than the value for comparable wells in the dolomite hydrogeologic terrane elsewhere. Estimates of potential yields to public and industrial supply wells were calculated from specific-capacity data for most-productive wells, which have casing diameter of 7 in. or more, discharge water primarily for public or industrial supply, and are in a valley. Median constant drawdowns, calculated from reported drawdowns, were assumed to be between 10 and 90 ft for wells completed in each of the five hydrogeologic terranes, and well-entrance losses were assumed to be negligible. Estimated interquartile ranges in potential yields to 412 mostproductive wells in the five hydrogeologic terranes were 170 to 580 gal/min, alluvium; 210 to 1,400 gal/min, dolomite; 80 to 720 gal/min, limestone; 65 to 850 gal/min, argillaceous carbonate rock; and 70 to 280 gal/min, siliciclastic rock.

Modeling Microalgae Productivity in Industrial-Scale Vertical Flat Panel Photobioreactors.

PubMed

Endres, Christian H; Roth, Arne; Brück, Thomas B

2018-05-01

Potentially achievable biomass yields are a decisive performance indicator for the economic viability of mass cultivation of microalgae. In this study, a computer model has been developed and applied to estimate the productivity of microalgae for large-scale outdoor cultivation in vertical flat panel photobioreactors. Algae growth is determined based on simulations of the reactor temperature and light distribution. Site-specific weather and irradiation data are used for annual yield estimations in six climate zones. Shading and reflections between opposing panels and between panels and the ground are dynamically computed based on the reactor geometry and the position of the sun. The results indicate that thin panels (≤0.05 m) are best suited for the assumed cell density of 2 g L -1 and that reactor panels should face in north-south direction. Panel spacings of 0.4-0.75 m at a panel height of 1 m appear most suitable for commercial applications. Under these preconditions, yields of around 10 kg m -2 a -1 are possible for most locations in the U.S. Only in hot climates significantly lower yields have to be expected, as extreme reactor temperatures limit overall productivity.

Evaluating direct medical expenditures estimation methods of adults using the medical expenditure panel survey: an example focusing on head and neck cancer.

PubMed

Coughlan, Diarmuid; Yeh, Susan T; O'Neill, Ciaran; Frick, Kevin D

2014-01-01

To inform policymakers of the importance of evaluating various methods for estimating the direct medical expenditures for a low-incidence condition, head and neck cancer (HNC). Four methods of estimation have been identified: 1) summing all health care expenditures, 2) estimating disease-specific expenditures consistent with an attribution approach, 3) estimating disease-specific expenditures by matching, and 4) estimating disease-specific expenditures by using a regression-based approach. A literature review of studies (2005-2012) that used the Medical Expenditure Panel Survey (MEPS) was undertaken to establish the most popular expenditure estimation methods. These methods were then applied to a sample of 120 respondents with HNC, derived from pooled data (2003-2008). The literature review shows that varying expenditure estimation methods have been used with MEPS but no study compared and contrasted all four methods. Our estimates are reflective of the national treated prevalence of HNC. The upper-bound estimate of annual direct medical expenditures of adult respondents with HNC between 2003 and 2008 was $3.18 billion (in 2008 dollars). Comparable estimates arising from methods focusing on disease-specific and incremental expenditures were all lower in magnitude. Attribution yielded annual expenditures of $1.41 billion, matching method of $1.56 billion, and regression method of $1.09 billion. This research demonstrates that variation exists across and within expenditure estimation methods applied to MEPS data. Despite concerns regarding aspects of reliability and consistency, reporting a combination of the four methods offers a degree of transparency and validity to estimating the likely range of annual direct medical expenditures of a condition. © 2013 International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Published by International Society for Pharmacoeconomics and Outcomes Research (ISPOR) All rights reserved.

Sensitivity analysis of the add-on price estimate for the edge-defined film-fed growth process

NASA Technical Reports Server (NTRS)

Mokashi, A. R.; Kachare, A. H.

1981-01-01

The analysis is in terms of cost parameters and production parameters. The cost parameters include equipment, space, direct labor, materials, and utilities. The production parameters include growth rate, process yield, and duty cycle. A computer program was developed specifically to do the sensitivity analysis.

Fatigue properties of JIS H3300 C1220 copper for strain life prediction

NASA Astrophysics Data System (ADS)

Harun, Muhammad Faiz; Mohammad, Roslina

2018-05-01

The existing methods for estimating strain life parameters are dependent on the material's monotonic tensile properties. However, a few of these methods yield quite complicated expressions for calculating fatigue parameters, and are specific to certain groups of materials only. The Universal Slopes method, Modified Universal Slopes method, Uniform Material Law, the Hardness method, and Medians method are a few existing methods for predicting strain-life fatigue based on monotonic tensile material properties and hardness of material. In the present study, nine methods for estimating fatigue life and properties are applied on JIS H3300 C1220 copper to determine the best methods for strain life estimation of this ductile material. Experimental strain-life curves are compared to estimations obtained using each method. Muralidharan-Manson's Modified Universal Slopes method and Bäumel-Seeger's method for unalloyed and low-alloy steels are found to yield batter accuracy in estimating fatigue life with a deviation of less than 25%. However, the prediction of both methods only yield much better accuracy for a cycle of less than 1000 or for strain amplitudes of more than 1% and less than 6%. Manson's Original Universal Slopes method and Ong's Modified Four-Point Correlation method are found to predict the strain-life fatigue of copper with better accuracy for a high number of cycles of strain amplitudes of less than 1%. The differences between mechanical behavior during monotonic and cyclic loading and the complexity in deciding the coefficient in an equation are probably the reason for the lack of a reliable method for estimating fatigue behavior using the monotonic properties of a group of materials. It is therefore suggested that a differential approach and new expressions be developed to estimate the strain-life fatigue parameters for ductile materials such as copper.

High-resolution model for estimating the economic and policy implications of agricultural soil salinization in California

NASA Astrophysics Data System (ADS)

Welle, Paul D.; Mauter, Meagan S.

2017-09-01

This work introduces a generalizable approach for estimating the field-scale agricultural yield losses due to soil salinization. When integrated with regional data on crop yields and prices, this model provides high-resolution estimates for revenue losses over large agricultural regions. These methods account for the uncertainty inherent in model inputs derived from satellites, experimental field data, and interpreted model results. We apply this method to estimate the effect of soil salinity on agricultural outputs in California, performing the analysis with both high-resolution (i.e. field scale) and low-resolution (i.e. county-scale) data sources to highlight the importance of spatial resolution in agricultural analysis. We estimate that soil salinity reduced agricultural revenues by 3.7 billion (1.7-7.0 billion) in 2014, amounting to 8.0 million tons of lost production relative to soil salinities below the crop-specific thresholds. When using low-resolution data sources, we find that the costs of salinization are underestimated by a factor of three. These results highlight the need for high-resolution data in agro-environmental assessment as well as the challenges associated with their integration.

Estimating total suspended sediment yield with probability sampling

Treesearch

Robert B. Thomas

1985-01-01

The ""Selection At List Time"" (SALT) scheme controls sampling of concentration for estimating total suspended sediment yield. The probability of taking a sample is proportional to its estimated contribution to total suspended sediment discharge. This procedure gives unbiased estimates of total suspended sediment yield and the variance of the...

WTAQ: A Computer Program for Calculating Drawdowns and Estimating Hydraulic Properties for Confined and Water-Table Aquifers

USGS Publications Warehouse

Barlow, Paul M.; Moench, Allen F.

1999-01-01

The computer program WTAQ calculates hydraulic-head drawdowns in a confined or water-table aquifer that result from pumping at a well of finite or infinitesimal diameter. The program is based on an analytical model of axial-symmetric ground-water flow in a homogeneous and anisotropic aquifer. The program allows for well-bore storage and well-bore skin at the pumped well and for delayed drawdown response at an observation well; by including these factors, it is possible to accurately evaluate the specific storage of a water-table aquifer from early-time drawdown data in observation wells and piezometers. For water-table aquifers, the program allows for either delayed or instantaneous drainage from the unsaturated zone. WTAQ calculates dimensionless or dimensional theoretical drawdowns that can be used with measured drawdowns at observation points to estimate the hydraulic properties of confined and water-table aquifers. Three sample problems illustrate use of WTAQ for estimating horizontal and vertical hydraulic conductivity, specific storage, and specific yield of a water-table aquifer by type-curve methods and by an automatic parameter-estimation method.

Wheat productivity estimates using LANDSAT data

NASA Technical Reports Server (NTRS)

Nalepka, R. F.; Colwell, J. E. (Principal Investigator); Rice, D. P.; Bresnahan, P. A.

1977-01-01

The author has identified the following significant results. Large area LANDSAT yield estimates were generated. These results were compared with estimates computed using a meteorological yield model (CCEA). Both of these estimates were compared with Kansas Crop and Livestock Reporting Service (KCLRS) estimates of yield, in an attempt to assess the relative and absolute accuracy of the LANDSAT and CCEA estimates. Results were inconclusive. A large area direct wheat prediction procedure was implemented. Initial results have produced a wheat production estimate comparable with the KCLRS estimate.

Is current irrigation sustainable in the United States? An integrated assessment of climate change impact on water resources and irrigated crop yields

NASA Astrophysics Data System (ADS)

Blanc, Elodie; Caron, Justin; Fant, Charles; Monier, Erwan

2017-08-01

While climate change impacts on crop yields has been extensively studied, estimating the impact of water shortages on irrigated crop yields is challenging because the water resources management system is complex. To investigate this issue, we integrate a crop yield reduction module and a water resources model into the MIT Integrated Global System Modeling framework, an integrated assessment model linking a global economic model to an Earth system model. We assess the effects of climate and socioeconomic changes on water availability for irrigation in the U.S. as well as subsequent impacts on crop yields by 2050, while accounting for climate change projection uncertainty. We find that climate and socioeconomic changes will increase water shortages and strongly reduce irrigated yields for specific crops (i.e., cotton and forage), or in specific regions (i.e., the Southwest) where irrigation is not sustainable. Crop modeling studies that do not represent changes in irrigation availability can thus be misleading. Yet, since the most water-stressed basins represent a relatively small share of U.S. irrigated areas, the overall reduction in U.S. crop yields is small. The response of crop yields to climate change and water stress also suggests that some level of adaptation will be feasible, like relocating croplands to regions with sustainable irrigation or switching to less irrigation intensive crops. Finally, additional simulations show that greenhouse gas (GHG) mitigation can alleviate the effect of water stress on irrigated crop yields, enough to offset the reduced CO2 fertilization effect compared to an unconstrained GHG emission scenario.

Is current irrigation sustainable in the United States? An integrated assessment of climate change impact on water resources and irrigated crop yields.

PubMed

Blanc, Elodie; Caron, Justin; Fant, Charles; Monier, Erwan

2017-08-01

While climate change impacts on crop yields has been extensively studied, estimating the impact of water shortages on irrigated crop yields is challenging because the water resources management system is complex. To investigate this issue, we integrate a crop yield reduction module and a water resources model into the MIT Integrated Global System Modeling framework, an integrated assessment model linking a global economic model to an Earth system model. We assess the effects of climate and socioeconomic changes on water availability for irrigation in the U.S. as well as subsequent impacts on crop yields by 2050, while accounting for climate change projection uncertainty. We find that climate and socioeconomic changes will increase water shortages and strongly reduce irrigated yields for specific crops (i.e., cotton and forage), or in specific regions (i.e., the Southwest) where irrigation is not sustainable. Crop modeling studies that do not represent changes in irrigation availability can thus be misleading. Yet, since the most water-stressed basins represent a relatively small share of U.S. irrigated areas, the overall reduction in U.S. crop yields is small. The response of crop yields to climate change and water stress also suggests that some level of adaptation will be feasible, like relocating croplands to regions with sustainable irrigation or switching to less irrigation intensive crops. Finally, additional simulations show that greenhouse gas (GHG) mitigation can alleviate the effect of water stress on irrigated crop yields, enough to offset the reduced CO 2 fertilization effect compared to an unconstrained GHG emission scenario.

An experimental case study to estimate Pre-harvest Wheat Acreage/Production in Hilly and Plain region of Uttarakhand state: Challenges and solutions of problems by using satellite data

NASA Astrophysics Data System (ADS)

Uniyal, D.; Kimothi, M. M.; Bhagya, N.; Ram, R. D.; Patel, N. K.; Dhaundiya, V. K.

2014-11-01

Wheat is an economically important Rabi crop for the state, which is grown on around 26 % of total available agriculture area in the state. There is a variation in productivity of wheat crop in hilly and tarai region. The agricultural productivity is less in hilly region in comparison of tarai region due to terrace cultivation, traditional system of agriculture, small land holdings, variation in physiography, top soil erosion, lack of proper irrigation system etc. Pre-harvest acreage/yield/production estimation of major crops is being done with the help of conventional crop cutting method, which is biased, inaccurate and time consuming. Remote Sensing data with multi-temporal and multi-spectral capabilities has shown new dimension in crop discrimination analysis and acreage/yield/production estimation in recent years. In view of this, Uttarakhand Space Applications Centre (USAC), Dehradun with the collaboration of Space Applications Centre (SAC), ISRO, Ahmedabad and Uttarakhand State Agriculture Department, have developed different techniques for the discrimination of crops and estimation of pre-harvest wheat acreage/yield/production. In the 1st phase, five districts (Dehradun, Almora, Udham Singh Nagar, Pauri Garhwal and Haridwar) with distinct physiography i.e. hilly and plain regions, have been selected for testing and verification of techniques using IRS (Indian Remote Sensing Satellites), LISS-III, LISS-IV satellite data of Rabi season for the year 2008-09 and whole 13 districts of the Uttarakhand state from 2009-14 along with ground data were used for detailed analysis. Five methods have been developed i.e. NDVI (Normalized Differential Vegetation Index), Supervised classification, Spatial modeling, Masking out method and Programming on visual basics methods using multitemporal satellite data of Rabi season along with the collateral and ground data. These methods were used for wheat discriminations and preharvest acreage estimations and subsequently results were compared with Bureau of Estimation Statistics (BES). Out of these five different methods, wheat area that was estimated by spatial modeling and programming on visual basics has been found quite near to Bureau of Estimation Statistics (BES). But for hilly region, maximum fields were going in shadow region, so it was difficult to estimate accurate result, so frequency distribution curve method has been used and frequency range has been decided to discriminate wheat pixels from other pixels in hilly region, digitized those regions and result shows good result. For yield estimation, an algorithm has been developed by using soil characteristics i.e. texture, depth, drainage, temperature, rainfall and historical yield data. To get the production estimation, estimated yield multiplied by acreage of crop per hectare. Result shows deviation for acreage estimation from BES is around 3.28 %, 2.46 %, 3.45 %, 1.56 %, 1.2 % and 1.6 % (estimation not declared till now by state Agriculture dept. For the year 2013-14) estimation and deviation for production estimation is around 4.98 %, 3.66 % 3.21 % , 3.1 % NA and 2.9 % for the consecutive above mentioned years i.e. 2008-09, 2009-10, 2010-11, 2011-12, 2012-13 and 2013-14. The estimated data has been provided to State Agriculture department for their use. To forecast production before harvest facilitate the formulation of workable marketing strategies leading to better export/import of crop in the state, which will help to lead better economic condition of the state. Yield estimation would help agriculture department in assessment of productivity of land for specific crop. Pre-harvest wheat acreage/production estimation, is useful to facilitate the reliable and timely estimates and enable the administrators and planners to take strategic decisions on import-export policy matters and trade negotiations.

Global direct radiative forcing by process-parameterized aerosol optical properties

NASA Astrophysics Data System (ADS)

KirkevâG, Alf; Iversen, Trond

2002-10-01

A parameterization of aerosol optical parameters is developed and implemented in an extended version of the community climate model version 3.2 (CCM3) of the U.S. National Center for Atmospheric Research. Direct radiative forcing (DRF) by monthly averaged calculated concentrations of non-sea-salt sulfate and black carbon (BC) is estimated. Inputs are production-specific BC and sulfate from [2002] and background aerosol size distribution and composition. The scheme interpolates between tabulated values to obtain the aerosol single scattering albedo, asymmetry factor, extinction coefficient, and specific extinction coefficient. The tables are constructed by full calculations of optical properties for an array of aerosol input values, for which size-distributed aerosol properties are estimated from theory for condensation and Brownian coagulation, assumed distribution of cloud-droplet residuals from aqueous phase oxidation, and prescribed properties of the background aerosols. Humidity swelling is estimated from the Köhler equation, and Mie calculations finally yield spectrally resolved aerosol optical parameters for 13 solar bands. The scheme is shown to give excellent agreement with nonparameterized DRF calculations for a wide range of situations. Using IPCC emission scenarios for the years 2000 and 2100, calculations with an atmospheric global cliamte model (AFCM) yield a global net anthropogenic DRF of -0.11 and 0.11 W m-2, respectively, when 90% of BC from biomass burning is assumed anthropogenic. In the 2000 scenario, the individual DRF due to sulfate and BC has separately been estimated to -0.29 and 0.19 W m-2, respectively. Our estimates of DRF by BC per BC mass burden are lower than earlier published estimates. Some sensitivity tests are included to investigate to what extent uncertain assumptions may influence these results.

Evaluation of the percentage of ganglion cells in the ganglion cell layer of the rodent retina

PubMed Central

Schlamp, Cassandra L.; Montgomery, Angela D.; Mac Nair, Caitlin E.; Schuart, Claudia; Willmer, Daniel J.

2013-01-01

Purpose Retinal ganglion cells comprise a percentage of the neurons actually residing in the ganglion cell layer (GCL) of the rodent retina. This estimate is useful to extrapolate ganglion cell loss in models of optic nerve disease, but the values reported in the literature are highly variable depending on the methods used to obtain them. Methods We tested three retrograde labeling methods and two immunostaining methods to calculate ganglion cell number in the mouse retina (C57BL/6). Additionally, a double-stain retrograde staining method was used to label rats (Long-Evans). The number of total neurons was estimated using a nuclear stain and selecting for nuclei that met specific criteria. Cholinergic amacrine cells were identified using transgenic mice expressing Tomato fluorescent protein. Total neurons and total ganglion cell numbers were measured in microscopic fields of 104 µm2 to determine the percentage of neurons comprising ganglion cells in each field. Results Historical estimates of the percentage of ganglion cells in the mouse GCL range from 36.1% to 67.5% depending on the method used. Experimentally, retrograde labeling methods yielded a combined estimate of 50.3% in mice. A retrograde method also yielded a value of 50.21% for rat retinas. Immunolabeling estimates were higher at 64.8%. Immunolabeling may introduce overestimates, however, with non-specific labeling effects, or ectopic expression of antigens in neurons other than ganglion cells. Conclusions Since immunolabeling methods may overestimate ganglion cell numbers, we conclude that 50%, which is consistently derived from retrograde labeling methods, is a reliable estimate of the ganglion cells in the neuronal population of the GCL. PMID:23825918

Growth and yield models for central hardwoods

Treesearch

Martin E. Dale; Donald E. Hilt

1989-01-01

Over the last 20 years computers have become an efficient tool to estimate growth and yield. Computerized yield estimates vary from simple approximation or interpolation of traditional normal yield tables to highly sophisticated programs that simulate the growth and yield of each individual tree.

Growth and Yield Estimation for Loblolly Pine in the West Gulf

Treesearch

Paul A. Murphy; Herbert S. Sternitzke

1979-01-01

An equation system is developed to estimate current yield, projected basal area, and projected volume for merchantable natural stands on a per-acre basis. These estimates indicate yields that can be expected from woods-run conditions.

Estimating groundwater evapotranspiration by a subtropical pine plantation using diurnal water table fluctuations: Implications from night-time water use

NASA Astrophysics Data System (ADS)

Fan, Junliang; Ostergaard, Kasper T.; Guyot, Adrien; Fujiwara, Stephen; Lockington, David A.

2016-11-01

Exotic pine plantations have replaced large areas of the native forests for timber production in the subtropical coastal Australia. To evaluate potential impacts of changes in vegetation on local groundwater discharge, we estimated groundwater evapotranspiration (ETg) by the pine plantation using diurnal water table fluctuations for the dry season of 2012 from August 1st to December 31st. The modified White method was used to estimate the ETg, considering the night-time water use by pine trees (Tn). Depth-dependent specific yields were also determined both experimentally and numerically for estimation of ETg. Night-time water use by pine trees was comprehensively investigated using a combination of groundwater level, sap flow, tree growth, specific yield, soil matric potential and climatic variables measurements. Results reveal a constant average transpiration flux of 0.02 mm h-1 at the plot scale from 23:00 to 05:00 during the study period, which verified the presence of night-time water use. The total ETg for the period investigated was 259.0 mm with an accumulated Tn of 64.5 mm, resulting in an error of 25% on accumulated evapotranspiration from the groundwater if night-time water use was neglected. The results indicate that the development of commercial pine plantations may result in groundwater losses in these areas. It is also recommended that any future application of diurnal water table fluctuation based methods investigate the validity of the zero night-time water use assumption prior to use.

Rate and yield relationships in the production of xanthan gum by batch fermentations using complex and chemically defined growth media

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pinches, A.; Pallent, L.J.

1986-10-01

Rate and yield information relating to biomass and product formation and to nitrogen, glucose and oxygen consumption are described for xanthan gum batch fermentations in which both chemically defined (glutamate nitrogen) and complex (peptone nitrogen) media are employed. Simple growth and product models are used for data interpretation. For both nitrogen sources, rate and yield parameter estimates are shown to be independent of initial nitrogen concentrations. For stationary phases, specific rates of gum production are shown to be independent of nitrogen source but dependent on initial nitrogen concentration. The latter is modeled empirically and suggests caution in applying simple productmore » models to xanthan gum fermentations. 13 references.« less

Knockdown of an inflorescence meristem-specific cytokinin oxidase - OsCKX2 in rice reduces yield penalty under salinity stress condition.

PubMed

Joshi, Rohit; Sahoo, Khirod Kumar; Tripathi, Amit Kumar; Kumar, Ritesh; Gupta, Brijesh Kumar; Pareek, Ashwani; Singla-Pareek, Sneh Lata

2018-05-01

Cytokinins play a significant role in determining grain yield in plants. Cytokinin oxidases catalyse irreversible degradation of cytokinins and hence modulate cellular cytokinin levels. Here, we studied the role of an inflorescence meristem-specific rice cytokinin oxidase - OsCKX2 - in reducing yield penalty under salinity stress conditions. We utilized an RNAi-based approach to study the function of OsCKX2 in maintaining grain yield under salinity stress condition. Ultra-performance liquid chromatography-based estimation revealed a significant increase in cytokinins in the inflorescence meristem of OsCKX2-knockdown plants. To determine if there exists a correlation between OsCKX2 levels and yield under salinity stress condition, we assessed the growth, physiology and grain yield of OsCKX2-knockdown plants vis-à-vis the wild type. OsCKX2-knockdown plants showed better vegetative growth, higher relative water content and photosynthetic efficiency and reduced electrolyte leakage as compared with the wild type under salinity stress. Importantly, we found a negative correlation between OsCKX2 expression and plant productivity as evident by assessment of agronomical parameters such as panicle branching, filled grains per plant and harvest index both under control and salinity stress conditions. These results suggest that OsCKX2, via controlling cytokinin levels, regulates floral primordial activity modulating rice grain yield under normal as well as abiotic stress conditions. © 2017 John Wiley & Sons Ltd.

Estimation of 305 Day Milk Yield from Cumulative Monthly and Bimonthly Test Day Records in Indonesian Holstein Cattle

NASA Astrophysics Data System (ADS)

Rahayu, A. P.; Hartatik, T.; Purnomoadi, A.; Kurnianto, E.

2018-02-01

The aims of this study were to estimate 305 day first lactation milk yield of Indonesian Holstein cattle from cumulative monthly and bimonthly test day records and to analyze its accuracy.The first lactation records of 258 dairy cows from 2006 to 2014 consisted of 2571 monthly (MTDY) and 1281 bimonthly test day yield (BTDY) records were used. Milk yields were estimated by regression method. Correlation coefficients between actual and estimated milk yield by cumulative MTDY were 0.70, 0.78, 0.83, 0.86, 0.89, 0.92, 0.94 and 0.96 for 2-9 months, respectively, meanwhile by cumulative BTDY were 0.69, 0.81, 0.87 and 0.92 for 2, 4, 6 and 8 months, respectively. The accuracy of fitting regression models (R2) increased with the increasing in the number of cumulative test day used. The used of 5 cumulative MTDY was considered sufficient for estimating 305 day first lactation milk yield with 80.6% accuracy and 7% error percentage of estimation. The estimated milk yield from MTDY was more accurate than BTDY by 1.1 to 2% less error percentage in the same time.

Laboratory-based maximum slip rates in earthquake rupture zones and radiated energy

USGS Publications Warehouse

McGarr, A.; Fletcher, Joe B.; Boettcher, M.; Beeler, N.; Boatwright, J.

2010-01-01

Laboratory stick-slip friction experiments indicate that peak slip rates increase with the stresses loading the fault to cause rupture. If this applies also to earthquake fault zones, then the analysis of rupture processes is simplified inasmuch as the slip rates depend only on the local yield stress and are independent of factors specific to a particular event, including the distribution of slip in space and time. We test this hypothesis by first using it to develop an expression for radiated energy that depends primarily on the seismic moment and the maximum slip rate. From laboratory results, the maximum slip rate for any crustal earthquake, as well as various stress parameters including the yield stress, can be determined based on its seismic moment and the maximum slip within its rupture zone. After finding that our new equation for radiated energy works well for laboratory stick-slip friction experiments, we used it to estimate radiated energies for five earthquakes with magnitudes near 2 that were induced in a deep gold mine, an M 2.1 repeating earthquake near the San Andreas Fault Observatory at Depth (SAFOD) site and seven major earthquakes in California and found good agreement with energies estimated independently from spectra of local and regional ground-motion data. Estimates of yield stress for the earthquakes in our study range from 12 MPa to 122 MPa with a median of 64 MPa. The lowest value was estimated for the 2004 M 6 Parkfield, California, earthquake whereas the nearby M 2.1 repeating earthquake, as recorded in the SAFOD pilot hole, showed a more typical yield stress of 64 MPa.

Genetic parameters across lactation for feed intake, fat- and protein-corrected milk, and liveweight in first-parity Holstein cattle.

PubMed

Manzanilla Pech, C I V; Veerkamp, R F; Calus, M P L; Zom, R; van Knegsel, A; Pryce, J E; De Haas, Y

2014-09-01

Breeding values for dry matter intake (DMI) are important to optimize dairy cattle breeding goals for feed efficiency. However, generally, only small data sets are available for feed intake, due to the cost and difficulty of measuring DMI, which makes understanding the genetic associations between traits across lactation difficult, let alone the possibility for selection of breeding animals. However, estimating national breeding values through cheaper and more easily measured correlated traits, such as milk yield and liveweight (LW), could be a first step to predict DMI. Combining DMI data across historical nutritional experiments might help to expand the data sets. Therefore, the objective was to estimate genetic parameters for DMI, fat- and protein-corrected milk (FPCM) yield, and LW across the entire first lactation using a relatively large data set combining experimental data across the Netherlands. A total of 30,483 weekly records for DMI, 49,977 for FPCM yield, and 31,956 for LW were available from 2,283 Dutch Holstein-Friesian first-parity cows between 1990 and 2011. Heritabilities, covariance components, and genetic correlations were estimated using a multivariate random regression model. The model included an effect for year-season of calving, and polynomials for age of cow at calving and days in milk (DIM). The random effects were experimental treatment, year-month of measurement, and the additive genetic, permanent environmental, and residual term. Additive genetic and permanent environmental effects were modeled using a third-order orthogonal polynomial. Estimated heritabilities ranged from 0.21 to 0.40 for DMI, from 0.20 to 0.43 for FPCM yield, and from 0.25 to 0.48 for LW across DIM. Genetic correlations between DMI at different DIM were relatively low during early and late lactation, compared with mid lactation. The genetic correlations between DMI and FPCM yield varied across DIM. This correlation was negative (up to -0.5) between FPCM yield in early lactation and DMI across the entire lactation, but highly positive (above 0.8) when both traits were in mid lactation. The correlation between DMI and LW was 0.6 during early lactation, but decreased to 0.4 during mid lactation. The highest correlations between FPCM yield and LW (0.3-0.5) were estimated during mid lactation. However, the genetic correlations between DMI and either FPCM yield or LW were not symmetric across DIM, and differed depending on which trait was measured first. The results of our study are useful to understand the genetic relationship of DMI, FPCM yield, and LW on specific days across lactation. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Evaluation of a Records-Review Surveillance System Used to Determine the Prevalence of Autism Spectrum Disorders

ERIC Educational Resources Information Center

Avchen, Rachel Nonkin; Wiggins, Lisa D.; Devine, Owen; Van Naarden Braun, Kim; Rice, Catherine; Hobson, Nancy C.; Schendel, Diana; Yeargin-Allsopp, Marshalyn

2011-01-01

We conducted the first study that estimates the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of a population-based autism spectrum disorders (ASD) surveillance system developed at the Centers for Disease Control and Prevention. The system employs a records-review methodology that yields ASD…

Remote sensing and modelling of vegetation dynamics for early estimation and spatial analysis of grain yields in semiarid context in central Tunisia

NASA Astrophysics Data System (ADS)

Chahbi, Aicha; Zribi, Mehrez; Lili-Chabaane, Zohra

2016-04-01

In arid and semi-arid areas, population growth, urbanization, food security and climate change have an impact on agriculture in general and particular on the cereal production. Therefore to improve food security in arid countries, crop canopy monitoring and yield forecasting cereals are needed. Many models, based on the use of remote sensing or agro-meteorological models, have been developed to estimate the biomass and grain yield of cereals. Through the use of a rich database, acquired over a period of two years for more than 80 test fields, and from optical satellite SPOT/HRV images, the aim of the present study is to evaluate the feasibility of two yield prediction approaches. The first approach is based on the application of the semi-empirical growth model SAFY, developed to simulate the dynamics of the LAI and the grain yield, at the field scale. The model is able to reproduce the time evolution of the leaf area index of all fields with acceptable error. However, an inter-comparison between ground yield measurements and SAFY model simulations reveals that the yields are under-estimated by this model. We can explain the limits of the semi-empirical model SAFY by its simplicity and also by various factors that were not considered (fertilization, irrigation,...). To improve the yield estimation, a new approach is proposed: the grain yield is estimated in function of the LAI in the growth period between 25 March and 5 April. The LAI of this period is estimated by SAFY model. A linear relationship is developed between the measured grain yield and the LAI area of the maximum growth period.This approach is robust, the measured and estimated grain yields are well correlated. Following the validation of this approach, yield estimations are proposed for the entire studied site using the SPOT/HRV images.

Progressive calibration and averaging for tandem mass spectrometry statistical confidence estimation: Why settle for a single decoy?

PubMed Central

Keich, Uri; Noble, William Stafford

2017-01-01

Estimating the false discovery rate (FDR) among a list of tandem mass spectrum identifications is mostly done through target-decoy competition (TDC). Here we offer two new methods that can use an arbitrarily small number of additional randomly drawn decoy databases to improve TDC. Specifically, “Partial Calibration” utilizes a new meta-scoring scheme that allows us to gradually benefit from the increase in the number of identifications calibration yields and “Averaged TDC” (a-TDC) reduces the liberal bias of TDC for small FDR values and its variability throughout. Combining a-TDC with “Progressive Calibration” (PC), which attempts to find the “right” number of decoys required for calibration we see substantial impact in real datasets: when analyzing the Plasmodium falciparum data it typically yields almost the entire 17% increase in discoveries that “full calibration” yields (at FDR level 0.05) using 60 times fewer decoys. Our methods are further validated using a novel realistic simulation scheme and importantly, they apply more generally to the problem of controlling the FDR among discoveries from searching an incomplete database. PMID:29326989

Evaluating the capabilities of watershed-scale models in estimating sediment yield at field-scale.

PubMed

Sommerlot, Andrew R; Nejadhashemi, A Pouyan; Woznicki, Sean A; Giri, Subhasis; Prohaska, Michael D

2013-09-30

Many watershed model interfaces have been developed in recent years for predicting field-scale sediment loads. They share the goal of providing data for decisions aimed at improving watershed health and the effectiveness of water quality conservation efforts. The objectives of this study were to: 1) compare three watershed-scale models (Soil and Water Assessment Tool (SWAT), Field_SWAT, and the High Impact Targeting (HIT) model) against calibrated field-scale model (RUSLE2) in estimating sediment yield from 41 randomly selected agricultural fields within the River Raisin watershed; 2) evaluate the statistical significance among models; 3) assess the watershed models' capabilities in identifying areas of concern at the field level; 4) evaluate the reliability of the watershed-scale models for field-scale analysis. The SWAT model produced the most similar estimates to RUSLE2 by providing the closest median and the lowest absolute error in sediment yield predictions, while the HIT model estimates were the worst. Concerning statistically significant differences between models, SWAT was the only model found to be not significantly different from the calibrated RUSLE2 at α = 0.05. Meanwhile, all models were incapable of identifying priorities areas similar to the RUSLE2 model. Overall, SWAT provided the most correct estimates (51%) within the uncertainty bounds of RUSLE2 and is the most reliable among the studied models, while HIT is the least reliable. The results of this study suggest caution should be exercised when using watershed-scale models for field level decision-making, while field specific data is of paramount importance. Copyright © 2013 Elsevier Ltd. All rights reserved.

Closing yield gaps: perils and possibilities for biodiversity conservation

PubMed Central

Phalan, Ben; Green, Rhys; Balmford, Andrew

2014-01-01

Increasing agricultural productivity to ‘close yield gaps’ creates both perils and possibilities for biodiversity conservation. Yield increases often have negative impacts on species within farmland, but at the same time could potentially make it more feasible to minimize further cropland expansion into natural habitats. We combine global data on yield gaps, projected future production of maize, rice and wheat, the distributions of birds and their estimated sensitivity to changes in crop yields to map where it might be most beneficial for bird conservation to close yield gaps as part of a land-sparing strategy, and where doing so might be most damaging. Closing yield gaps to attainable levels to meet projected demand in 2050 could potentially help spare an area equivalent to that of the Indian subcontinent. Increasing yields this much on existing farmland would inevitably reduce its biodiversity, and therefore we advocate efforts both to constrain further increases in global food demand, and to identify the least harmful ways of increasing yields. The land-sparing potential of closing yield gaps will not be realized without specific mechanisms to link yield increases to habitat protection (and restoration), and therefore we suggest that conservationists, farmers, crop scientists and policy-makers collaborate to explore promising mechanisms. PMID:24535392

Hierarchical Bayes estimation of species richness and occupancy in spatially replicated surveys

USGS Publications Warehouse

Kery, M.; Royle, J. Andrew

2008-01-01

1. Species richness is the most widely used biodiversity metric, but cannot be observed directly as, typically, some species are overlooked. Imperfect detectability must therefore be accounted for to obtain unbiased species-richness estimates. When richness is assessed at multiple sites, two approaches can be used to estimate species richness: either estimating for each site separately, or pooling all samples. The first approach produces imprecise estimates, while the second loses site-specific information. 2. In contrast, a hierarchical Bayes (HB) multispecies site-occupancy model benefits from the combination of information across sites without losing site-specific information and also yields occupancy estimates for each species. The heart of the model is an estimate of the incompletely observed presence-absence matrix, a centrepiece of biogeography and monitoring studies. We illustrate the model using Swiss breeding bird survey data, and compare its estimates with the widely used jackknife species-richness estimator and raw species counts. 3. Two independent observers each conducted three surveys in 26 1-km(2) quadrats, and detected 27-56 (total 103) species. The average estimated proportion of species detected after three surveys was 0.87 under the HB model. Jackknife estimates were less precise (less repeatable between observers) than raw counts, but HB estimates were as repeatable as raw counts. The combination of information in the HB model thus resulted in species-richness estimates presumably at least as unbiased as previous approaches that correct for detectability, but without costs in precision relative to uncorrected, biased species counts. 4. Total species richness in the entire region sampled was estimated at 113.1 (CI 106-123); species detectability ranged from 0.08 to 0.99, illustrating very heterogeneous species detectability; and species occupancy was 0.06-0.96. Even after six surveys, absolute bias in observed occupancy was estimated at up to 0.40. 5. Synthesis and applications. The HB model for species-richness estimation combines information across sites and enjoys more precise, and presumably less biased, estimates than previous approaches. It also yields estimates of several measures of community size and composition. Covariates for occupancy and detectability can be included. We believe it has considerable potential for monitoring programmes as well as in biogeography and community ecology.

WTAQ - A computer program for aquifer-test analysis of confined and unconfined aquifers

USGS Publications Warehouse

Barlow, P.M.; Moench, A.F.

2004-01-01

Computer program WTAQ was developed to implement a Laplace-transform analytical solution for axial-symmetric flow to a partially penetrating, finite-diameter well in a homogeneous and anisotropic unconfined (water-table) aquifer. The solution accounts for wellbore storage and skin effects at the pumped well, delayed response at an observation well, and delayed or instantaneous drainage from the unsaturated zone. For the particular case of zero drainage from the unsaturated zone, the solution simplifies to that of axial-symmetric flow in a confined aquifer. WTAQ calculates theoretical time-drawdown curves for the pumped well and observation wells and piezometers. The theoretical curves are used with measured time-drawdown data to estimate hydraulic parameters of confined or unconfined aquifers by graphical type-curve methods or by automatic parameter-estimation methods. Parameters that can be estimated are horizontal and vertical hydraulic conductivity, specific storage, and specific yield. A sample application illustrates use of WTAQ for estimating hydraulic parameters of a hypothetical, unconfined aquifer by type-curve methods. Copyright ASCE 2004.

An information system design for watershed-wide modeling of water loss to the atmosphere using remote sensing techniques

NASA Technical Reports Server (NTRS)

Khorram, S.

1977-01-01

Results are presented of a study intended to develop a general location-specific remote-sensing procedure for watershed-wide estimation of water loss to the atmosphere by evaporation and transpiration. The general approach involves a stepwise sequence of required information definition (input data), appropriate sample design, mathematical modeling, and evaluation of results. More specifically, the remote sensing-aided system developed to evaluate evapotranspiration employs a basic two-stage two-phase sample of three information resolution levels. Based on the discussed design, documentation, and feasibility analysis to yield timely, relatively accurate, and cost-effective evapotranspiration estimates on a watershed or subwatershed basis, work is now proceeding to implement this remote sensing-aided system.

Estimates of phytoplankton class-specific and total primary production in the Mediterranean Sea from satellite ocean color observations

NASA Astrophysics Data System (ADS)

Uitz, Julia; Stramski, Dariusz; Gentili, Bernard; D'Ortenzio, Fabrizio; Claustre, Hervé

2012-06-01

An approach that combines a recently developed procedure for improved estimation of surface chlorophyll a concentration (Chlsurf) from ocean color and a phytoplankton class-specific bio-optical model was used to examine primary production in the Mediterranean Sea. Specifically, this approach was applied to the 10 year time series of satellite Chlsurfdata from the Sea-viewing Wide Field-of-view Sensor. We estimated the primary production associated with three major phytoplankton classes (micro, nano, and picophytoplankton), which also yielded new estimates of the total primary production (Ptot). These estimates of Ptot (e.g., 68 g C m-2 yr-1for the entire Mediterranean basin) are lower by a factor of ˜2 and show a different seasonal cycle when compared with results from conventional approaches based on standard ocean color chlorophyll algorithm and a non-class-specific primary production model. Nanophytoplankton are found to be dominant contributors to Ptot (43-50%) throughout the year and entire basin. Micro and picophytoplankton exhibit variable contributions to Ptot depending on the season and ecological regime. In the most oligotrophic regime, these contributions are relatively stable all year long with picophytoplankton (˜32%) playing a larger role than microphytoplankton (˜22%). In the blooming regime, picophytoplankton dominate over microphytoplankton most of the year, except during the spring bloom when microphytoplankton (27-38%) are considerably more important than picophytoplankton (20-27%).

Effects of social organization, trap arrangement and density, sampling scale, and population density on bias in population size estimation using some common mark-recapture estimators.

PubMed

Gupta, Manan; Joshi, Amitabh; Vidya, T N C

2017-01-01

Mark-recapture estimators are commonly used for population size estimation, and typically yield unbiased estimates for most solitary species with low to moderate home range sizes. However, these methods assume independence of captures among individuals, an assumption that is clearly violated in social species that show fission-fusion dynamics, such as the Asian elephant. In the specific case of Asian elephants, doubts have been raised about the accuracy of population size estimates. More importantly, the potential problem for the use of mark-recapture methods posed by social organization in general has not been systematically addressed. We developed an individual-based simulation framework to systematically examine the potential effects of type of social organization, as well as other factors such as trap density and arrangement, spatial scale of sampling, and population density, on bias in population sizes estimated by POPAN, Robust Design, and Robust Design with detection heterogeneity. In the present study, we ran simulations with biological, demographic and ecological parameters relevant to Asian elephant populations, but the simulation framework is easily extended to address questions relevant to other social species. We collected capture history data from the simulations, and used those data to test for bias in population size estimation. Social organization significantly affected bias in most analyses, but the effect sizes were variable, depending on other factors. Social organization tended to introduce large bias when trap arrangement was uniform and sampling effort was low. POPAN clearly outperformed the two Robust Design models we tested, yielding close to zero bias if traps were arranged at random in the study area, and when population density and trap density were not too low. Social organization did not have a major effect on bias for these parameter combinations at which POPAN gave more or less unbiased population size estimates. Therefore, the effect of social organization on bias in population estimation could be removed by using POPAN with specific parameter combinations, to obtain population size estimates in a social species.

Effects of social organization, trap arrangement and density, sampling scale, and population density on bias in population size estimation using some common mark-recapture estimators

PubMed Central

Joshi, Amitabh; Vidya, T. N. C.

2017-01-01

Mark-recapture estimators are commonly used for population size estimation, and typically yield unbiased estimates for most solitary species with low to moderate home range sizes. However, these methods assume independence of captures among individuals, an assumption that is clearly violated in social species that show fission-fusion dynamics, such as the Asian elephant. In the specific case of Asian elephants, doubts have been raised about the accuracy of population size estimates. More importantly, the potential problem for the use of mark-recapture methods posed by social organization in general has not been systematically addressed. We developed an individual-based simulation framework to systematically examine the potential effects of type of social organization, as well as other factors such as trap density and arrangement, spatial scale of sampling, and population density, on bias in population sizes estimated by POPAN, Robust Design, and Robust Design with detection heterogeneity. In the present study, we ran simulations with biological, demographic and ecological parameters relevant to Asian elephant populations, but the simulation framework is easily extended to address questions relevant to other social species. We collected capture history data from the simulations, and used those data to test for bias in population size estimation. Social organization significantly affected bias in most analyses, but the effect sizes were variable, depending on other factors. Social organization tended to introduce large bias when trap arrangement was uniform and sampling effort was low. POPAN clearly outperformed the two Robust Design models we tested, yielding close to zero bias if traps were arranged at random in the study area, and when population density and trap density were not too low. Social organization did not have a major effect on bias for these parameter combinations at which POPAN gave more or less unbiased population size estimates. Therefore, the effect of social organization on bias in population estimation could be removed by using POPAN with specific parameter combinations, to obtain population size estimates in a social species. PMID:28306735

Is current irrigation sustainable in the United States? An integrated assessment of climate change impact on water resources and irrigated crop yields

DOE PAGES

Blanc, Elodie; Caron, Justin; Fant, Charles; ...

2017-06-27

While climate change impacts on crop yields has been extensively studied, estimating the impact of water shortages on irrigated crop yields is challenging because the water resources management system is complex. To investigate this issue, we integrate a crop yield reduction module and a water resources model into the MIT Integrated Global System Modeling framework, an integrated assessment model linking a global economic model to an Earth system model. We assess the effects of climate and socioeconomic changes on water availability for irrigation in the U.S. as well as subsequent impacts on crop yields by 2050, while accounting for climatemore » change projection uncertainty. We find that climate and socioeconomic changes will increase water shortages and strongly reduce irrigated yields for specific crops (i.e., cotton and forage), or in specific regions (i.e., the Southwest) where irrigation is not sustainable. Crop modeling studies that do not represent changes in irrigation availability can thus be misleading. Yet, since the most water-stressed basins represent a relatively small share of U.S. irrigated areas, the overall reduction in U.S. crop yields is small. The response of crop yields to climate change and water stress also suggests that some level of adaptation will be feasible, like relocating croplands to regions with sustainable irrigation or switching to less irrigation intensive crops. Finally, additional simulations show that greenhouse gas (GHG) mitigation can alleviate the effect of water stress on irrigated crop yields, enough to offset the reduced CO 2 fertilization effect compared to an unconstrained GHG emission scenario.« less

Is current irrigation sustainable in the United States? An integrated assessment of climate change impact on water resources and irrigated crop yields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blanc, Elodie; Caron, Justin; Fant, Charles

While climate change impacts on crop yields has been extensively studied, estimating the impact of water shortages on irrigated crop yields is challenging because the water resources management system is complex. To investigate this issue, we integrate a crop yield reduction module and a water resources model into the MIT Integrated Global System Modeling framework, an integrated assessment model linking a global economic model to an Earth system model. We assess the effects of climate and socioeconomic changes on water availability for irrigation in the U.S. as well as subsequent impacts on crop yields by 2050, while accounting for climatemore » change projection uncertainty. We find that climate and socioeconomic changes will increase water shortages and strongly reduce irrigated yields for specific crops (i.e., cotton and forage), or in specific regions (i.e., the Southwest) where irrigation is not sustainable. Crop modeling studies that do not represent changes in irrigation availability can thus be misleading. Yet, since the most water-stressed basins represent a relatively small share of U.S. irrigated areas, the overall reduction in U.S. crop yields is small. The response of crop yields to climate change and water stress also suggests that some level of adaptation will be feasible, like relocating croplands to regions with sustainable irrigation or switching to less irrigation intensive crops. Finally, additional simulations show that greenhouse gas (GHG) mitigation can alleviate the effect of water stress on irrigated crop yields, enough to offset the reduced CO 2 fertilization effect compared to an unconstrained GHG emission scenario.« less

Assessment of source-specific health effects associated with an unknown number of major sources of multiple air pollutants: a unified Bayesian approach.

PubMed

Park, Eun Sug; Hopke, Philip K; Oh, Man-Suk; Symanski, Elaine; Han, Daikwon; Spiegelman, Clifford H

2014-07-01

There has been increasing interest in assessing health effects associated with multiple air pollutants emitted by specific sources. A major difficulty with achieving this goal is that the pollution source profiles are unknown and source-specific exposures cannot be measured directly; rather, they need to be estimated by decomposing ambient measurements of multiple air pollutants. This estimation process, called multivariate receptor modeling, is challenging because of the unknown number of sources and unknown identifiability conditions (model uncertainty). The uncertainty in source-specific exposures (source contributions) as well as uncertainty in the number of major pollution sources and identifiability conditions have been largely ignored in previous studies. A multipollutant approach that can deal with model uncertainty in multivariate receptor models while simultaneously accounting for parameter uncertainty in estimated source-specific exposures in assessment of source-specific health effects is presented in this paper. The methods are applied to daily ambient air measurements of the chemical composition of fine particulate matter ([Formula: see text]), weather data, and counts of cardiovascular deaths from 1995 to 1997 for Phoenix, AZ, USA. Our approach for evaluating source-specific health effects yields not only estimates of source contributions along with their uncertainties and associated health effects estimates but also estimates of model uncertainty (posterior model probabilities) that have been ignored in previous studies. The results from our methods agreed in general with those from the previously conducted workshop/studies on the source apportionment of PM health effects in terms of number of major contributing sources, estimated source profiles, and contributions. However, some of the adverse source-specific health effects identified in the previous studies were not statistically significant in our analysis, which probably resulted because we incorporated parameter uncertainty in estimated source contributions that has been ignored in the previous studies into the estimation of health effects parameters. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Estimated loads and yields of suspended soils and water-quality constituents in Kentucky streams

USGS Publications Warehouse

Crain, Angela S.

2001-01-01

Loads and yields of suspended solids, nutrients, major ions, trace elements, organic carbon, fecal coliform, dissolved oxygen, and alkalinity were estimated for 22 streams in 11 major river basins in Kentucky. Mean daily discharge was estimated at ungaged stations or stations with incomplete discharge records using drainage-area ratio, regression analysis, or a combination of the two techniques. Streamflow was partitioned into total and base flow and used to estimate loads and yields for suspended solids and water-quality constituents by use of the ESTIMATOR and FLUX computer programs. The relative magnitude of constituent transport to streams from groundand surface-water sources was determined for the 22 stations. Nutrient and suspended solids yields for drainage basins with relatively homogenous land use were used to estimate the total-flow and base-flow yields of nutrient and suspended solids for forested, agricultural, and urban land. Yields of nutrients?nitrite plus nitrate, ammonia plus organic nitrogen, and total phosphorus?in forested drainage basins were generally less than 1 ton per square mile per year ((ton/mi2)/yr) and were generally less than 2 (ton/mi2)/yr in agricultural drainage basins. The smallest total-flow yields for nitrogen (nitrite plus nitrate) was estimated at Levisa Fork at Paintsville in which 95 percent of the land is forested. This site also had one of the smallest total-flow yields for ammonia plus organic nitrogen. In general, nutrient yields from forested lands were lower than those from urban and agricultural land. Some of the largest estimated total-flow yields of nutrients among agricultural basins were for streams in the Licking River Basin, the North Fork Licking River near Milford, and the South Fork Licking River at Cynthiana. Agricultural land constitutes greater than 75 percent of the drainage area in these two basins. Possible sources of nutrients discharging into the Licking River are farm and residential fertilizers. Estimated base-flow yields of suspended solids and nutrients at several basins in the larger Green River and Lower Cumberland River Basins were about half of their estimated total-flow yields. The karst terrain in these basins makes the ground water highly susceptible to contamination, especially if a confining unit is thin or absent.

Infrasound Studies for Yield Estimation of HE Explosions

DTIC Science & Technology

2011-03-05

AFRL-RV-HA-TR-2011-1022 Infrasound Studies for Yield Estimation of HE Explosions Paul Golden Petru Negraru Southern Methodist...DATES COVERED (From - To) 5 Mar 2010 to 5 Mar 2011 4. TITLE AND SUBTITLE Infrasound Studies for Yield Estimation of HE Explosions 5a. CONTRACT NUMBER...conducting investigations to determine the yield of HE explosions from infrasound signals. In particular SMU is investigating how the period and amplitude

Infant attachment and toddlers' sleep assessed by maternal reports and actigraphy: different measurement methods yield different relations.

PubMed

Simard, Valérie; Bernier, Annie; Bélanger, Marie-Ève; Carrier, Julie

2013-06-01

To investigate relations between children's attachment and sleep, using objective and subjective sleep measures. Secondarily, to identify the most accurate actigraphy algorithm for toddlers. 55 mother-child dyads took part in the Strange Situation Procedure (18 months) to assess attachment. At 2 years, children wore an Actiwatch for a 72-hr period, and their mothers completed a sleep diary. The high sensitivity (80) and smoothed actigraphy algorithms provided the most plausible sleep data. Maternal diaries yielded longer estimated sleep duration and shorter wake duration at night and showed poor agreement with actigraphy. More resistant attachment behavior was not associated with actigraphy-assessed sleep, but was associated with longer nocturnal wake duration as estimated by mothers, and with a reduced actigraphy-diary discrepancy. Mothers of children with resistant attachment are more aware of their child's nocturnal awakenings. Researchers and clinicians should select the best sleep measurement method for their specific needs.

Optimal threshold estimation for binary classifiers using game theory.

PubMed

Sanchez, Ignacio Enrique

2016-01-01

Many bioinformatics algorithms can be understood as binary classifiers. They are usually compared using the area under the receiver operating characteristic ( ROC ) curve. On the other hand, choosing the best threshold for practical use is a complex task, due to uncertain and context-dependent skews in the abundance of positives in nature and in the yields/costs for correct/incorrect classification. We argue that considering a classifier as a player in a zero-sum game allows us to use the minimax principle from game theory to determine the optimal operating point. The proposed classifier threshold corresponds to the intersection between the ROC curve and the descending diagonal in ROC space and yields a minimax accuracy of 1-FPR. Our proposal can be readily implemented in practice, and reveals that the empirical condition for threshold estimation of "specificity equals sensitivity" maximizes robustness against uncertainties in the abundance of positives in nature and classification costs.

Linking ecophysiological modelling with quantitative genetics to support marker-assisted crop design for improved yields of rice (Oryza sativa) under drought stress

PubMed Central

Gu, Junfei; Yin, Xinyou; Zhang, Chengwei; Wang, Huaqi; Struik, Paul C.

2014-01-01

Background and Aims Genetic markers can be used in combination with ecophysiological crop models to predict the performance of genotypes. Crop models can estimate the contribution of individual markers to crop performance in given environments. The objectives of this study were to explore the use of crop models to design markers and virtual ideotypes for improving yields of rice (Oryza sativa) under drought stress. Methods Using the model GECROS, crop yield was dissected into seven easily measured parameters. Loci for these parameters were identified for a rice population of 94 introgression lines (ILs) derived from two parents differing in drought tolerance. Marker-based values of ILs for each of these parameters were estimated from additive allele effects of the loci, and were fed to the model in order to simulate yields of the ILs grown under well-watered and drought conditions and in order to design virtual ideotypes for those conditions. Key Results To account for genotypic yield differences, it was necessary to parameterize the model for differences in an additional trait ‘total crop nitrogen uptake’ (Nmax) among the ILs. Genetic variation in Nmax had the most significant effect on yield; five other parameters also significantly influenced yield, but seed weight and leaf photosynthesis did not. Using the marker-based parameter values, GECROS also simulated yield variation among 251 recombinant inbred lines of the same parents. The model-based dissection approach detected more markers than the analysis using only yield per se. Model-based sensitivity analysis ranked all markers for their importance in determining yield differences among the ILs. Virtual ideotypes based on markers identified by modelling had 10–36 % more yield than those based on markers for yield per se. Conclusions This study outlines a genotype-to-phenotype approach that exploits the potential value of marker-based crop modelling in developing new plant types with high yields. The approach can provide more markers for selection programmes for specific environments whilst also allowing for prioritization. Crop modelling is thus a powerful tool for marker design for improved rice yields and for ideotyping under contrasting conditions. PMID:24984712

Linking Field and Satellite Observations to Reveal Differences in Single vs. Double-Cropped Soybean Yields in Central Brazil

NASA Astrophysics Data System (ADS)

Jeffries, G. R.; Cohn, A.

2016-12-01

Soy-corn double cropping (DC) has been widely adopted in Central Brazil alongside single cropped (SC) soybean production. DC involves different cropping calendars, soy varieties, and may be associated with different crop yield patterns and volatility than SC. Study of the performance of the region's agriculture in a changing climate depends on tracking differences in the productivity of SC vs. DC, but has been limited by crop yield data that conflate the two systems. We predicted SC and DC yields across Central Brazil, drawing on field observations and remotely sensed data. We first modeled field yield estimates as a function of remotely sensed DC status and vegetation index (VI) metrics, and other management and biophysical factors. We then used the statistical model estimated to predict SC and DC soybean yields at each 500 m2 grid cell of Central Brazil for harvest years 2001 - 2015. The yield estimation model was constructed using 1) a repeated cross-sectional survey of soybean yields and management factors for years 2007-2015, 2) a custom agricultural land cover classification dataset which assimilates earlier datasets for the region, and 3) 500m 8-day MODIS image composites used to calculate the wide dynamic range vegetation index (WDRVI) and derivative metrics such as area under the curve for WDRVI values in critical crop development periods. A statistical yield estimation model which primarily entails WDRVI metrics, DC status, and spatial fixed effects was developed on a subset of the yield dataset. Model validation was conducted by predicting previously withheld yield records, and then assessing error and goodness-of-fit for predicted values with metrics including root mean squared error (RMSE), mean squared error (MSE), and R2. We found a statistical yield estimation model which incorporates WDRVI and DC status to be way to estimate crop yields over the region. Statistical properties of the resulting gridded yield dataset may be valuable for understanding linkages between crop yields, farm management factors, and climate.

Using Geostatistical Data Fusion Techniques and MODIS Data to Upscale Simulated Wheat Yield

NASA Astrophysics Data System (ADS)

Castrignano, A.; Buttafuoco, G.; Matese, A.; Toscano, P.

2014-12-01

Population growth increases food request. Assessing food demand and predicting the actual supply for a given location are critical components of strategic food security planning at regional scale. Crop yield can be simulated using crop models because is site-specific and determined by weather, management, length of growing season and soil properties. Crop models require reliable location-specific data that are not generally available. Obtaining these data at a large number of locations is time-consuming, costly and sometimes simply not feasible. An upscaling method to extend coverage of sparse estimates of crop yield to an appropriate extrapolation domain is required. This work is aimed to investigate the applicability of a geostatistical data fusion approach for merging remote sensing data with the predictions of a simulation model of wheat growth and production using ground-based data. The study area is Capitanata plain (4000 km2) located in Apulia Region, mostly cropped with durum wheat. The MODIS EVI/NDVI data products for Capitanata plain were downloaded from the Land Processes Distributed Active Archive Center (LPDAAC) remote for the whole crop cycle of durum wheat. Phenological development, biomass growth and grain quantity of durum wheat were simulated by the Delphi system, based on a crop simulation model linked to a database including soil properties, agronomical and meteorological data. Multicollocated cokriging was used to integrate secondary exhaustive information (multi-spectral MODIS data) with primary variable (sparsely distributed biomass/yield model predictions of durum wheat). The model estimates looked strongly spatially correlated with the radiance data (red and NIR bands) and the fusion data approach proved to be quite suitable and flexible to integrate data of different type and support.

Study on paddy rice yield estimation based on multisource data and the Grey system theory

NASA Astrophysics Data System (ADS)

Deng, Wensheng; Wang, Wei; Liu, Hai; Li, Chen; Ge, Yimin; Zheng, Xianghua

2009-10-01

The paddy rice is our important crops. In study of the paddy rice yield estimation, compared with the scholars who usually only take the remote sensing data or meteorology as the influence factors, we combine the remote sensing and the meteorological data to make the monitoring result closer reality. Although the gray system theory has used in many aspects, it is applied very little in paddy rice yield estimation. This study introduces it to the paddy rice yield estimation, and makes the yield estimation model. This can resolve small data sets problem that can not be solved by deterministic model. It selects some regions in Jianghan plain for the study area. The data includes multi-temporal remote sensing image, meteorological and statistic data. The remote sensing data is the 16-day composite images (250-m spatial resolution) of MODIS. The meteorological data includes monthly average temperature, sunshine duration and rain fall amount. The statistical data is the long-term paddy rice yield of the study area. Firstly, it extracts the paddy rice planting area from the multi-temporal MODIS images with the help of GIS and RS. Then taking the paddy rice yield as the reference sequence, MODIS data and meteorological data as the comparative sequence, computing the gray correlative coefficient, it selects the yield estimation factor based on the grey system theory. Finally, using the factors, it establishes the yield estimation model and does the result test. The result indicated that the method is feasible and the conclusion is credible. It can provide the scientific method and reference value to carry on the region paddy rice remote sensing estimation.

Specification of ISS Plasma Environment Variability

NASA Technical Reports Server (NTRS)

Minow, Joseph I.; Neergaard, Linda F.; Bui, Them H.; Mikatarian, Ronald R.; Barsamian, H.; Koontz, Steven L.

2004-01-01

Quantifying spacecraft charging risks and associated hazards for the International Space Station (ISS) requires a plasma environment specification for the natural variability of ionospheric temperature (Te) and density (Ne). Empirical ionospheric specification and forecast models such as the International Reference Ionosphere (IRI) model typically only provide long term (seasonal) mean Te and Ne values for the low Earth orbit environment. This paper describes a statistical analysis of historical ionospheric low Earth orbit plasma measurements from the AE-C, AE-D, and DE-2 satellites used to derive a model of deviations of observed data values from IRI-2001 estimates of Ne, Te parameters for each data point to provide a statistical basis for modeling the deviations of the plasma environment from the IRI model output. Application of the deviation model with the IRI-2001 output yields a method for estimating extreme environments for the ISS spacecraft charging analysis.

Anaerobic Degradation of Phthalate Isomers by Methanogenic Consortia

PubMed Central

Kleerebezem, Robbert; Pol, Look W. Hulshoff; Lettinga, Gatze

1999-01-01

Three methanogenic enrichment cultures, grown on ortho-phthalate, iso-phthalate, or terephthalate were obtained from digested sewage sludge or methanogenic granular sludge. Cultures grown on one of the phthalate isomers were not capable of degrading the other phthalate isomers. All three cultures had the ability to degrade benzoate. Maximum specific growth rates (μSmax) and biomass yields (YXtotS) of the mixed cultures were determined by using both the phthalate isomers and benzoate as substrates. Comparable values for these parameters were found for all three cultures. Values for μSmax and YXtotS were higher for growth on benzoate compared to the phthalate isomers. Based on measured and estimated values for the microbial yield of the methanogens in the mixed culture, specific yields for the phthalate and benzoate fermenting organisms were calculated. A kinetic model, involving three microbial species, was developed to predict intermediate acetate and hydrogen accumulation and the final production of methane. Values for the ratio of the concentrations of methanogenic organisms, versus the phthalate isomer and benzoate fermenting organisms, and apparent half-saturation constants (KS) for the methanogens were calculated. By using this combination of measured and estimated parameter values, a reasonable description of intermediate accumulation and methane formation was obtained, with the initial concentration of phthalate fermenting organisms being the only variable. The energetic efficiency for growth of the fermenting organisms on the phthalate isomers was calculated to be significantly smaller than for growth on benzoate. PMID:10049876

Phenotypic effects of calving ease on the subsequent fertility and milk production of dam and calf in UK Holstein-Friesian heifers.

PubMed

Eaglen, S A E; Coffey, M P; Woolliams, J A; Mrode, R; Wall, E

2011-11-01

The effect of calving ease on the fertility and production performance of both dam and calf was studied in approximately 50,000 and 10,000 UK Holstein-Friesian heifers and heifer calves, respectively. The first objective of this study was to estimate the effect of a difficult calving on the subsequent first-lactation milk production by estimating lactation curves using cubic splines. This methodology allows the estimation of daily milk, protein, and fat yields following calvings of differing degrees of difficulty. Losses in milk yield after a difficult calving have been quantified previously; however, estimates are generally restricted to the accumulated yields at specific days in lactation. By fitting cubic splines, gaps (in which the shape of the lactation curve can be merely guessed) between estimations were avoided. The second objective of this study was to estimate the effect of a difficult birth on the subsequent performance of the calf as an adult animal. Even though the calving process is known to involve cooperation between dam and calf, the effect of a difficult calving has, until now, only been estimated for the subsequent performance of the dam. Addressing the effects of a difficult birth on the adult calf strengthens the importance of calving ease as a selection trait because it suggests that the benefit of genetic improvement may currently be underestimated. The effect of calving ease on the subsequent reproductive performance of dam and calf was analyzed using linear regression and with calving ease score fitted as a fixed effect. Dams with veterinary-assisted calvings required 0.7 more services to conception and 8 more days to first service and experienced a 28-d longer calving interval in first lactation compared with dams that were not assisted at calving. Effects of calving ease on the reproductive performance of the adult calf in first lactation were not detected. Losses in milk yield of the dam were significant between d 9 to 90 in milk subsequent to a veterinary-assisted calving, creating a loss of approximately 2 kg of milk per day, compared with a nonassisted calving. Calves being born with difficulties showed a significant reduction in milk yield in first lactation, demonstrating the lifelong effect of a difficult birth. Compared with nonassisted calves, veterinary-assisted calves showed a loss of 710 kg in accumulated 305-d milk yield, which was significant from 129 to 261 d in milk. This suggests that from birth to production, physiological effects of a bad calving are not negated. Results furthermore suggest a beneficial effect of farmer assistance at calving on the milk yield of both dam and calf, when moderate difficulties occurred. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Machine-smoking studies of cigarette filter color to estimate tar yield by visual assessment and through the use of a colorimeter.

PubMed

Morton, Michael J; Williams, David L; Hjorth, Heather B; Smith, Jennifer H

2010-04-01

This paper explores using the intensity of the stain on the end of the filter ("filter color") as a vehicle for estimating cigarette tar yield, both by instrument reading of the filter color and by visual comparison to a template. The correlation of machine-measured tar yield to filter color measured with a colorimeter was reasonably strong and was relatively unaffected by different puff volumes or different tobacco moistures. However, the correlation of filter color to machine-measured nicotine yield was affected by the moisture content of the cigarette. Filter color, as measured by a colorimeter, was generally comparable to filter extraction of either nicotine or solanesol in its correlation to machine-smoked tar yields. It was found that the color of the tar stain changes over time. Panelists could generally correctly order the filters from machine-smoked cigarettes by tar yield using the intensity of the tar stain. However, there was considerable variation in the panelist-to-panelist tar yield estimates. The wide person-to-person variation in tar yield estimates, and other factors discussed in the text could severely limit the usefulness and practicality of this approach for visually estimating the tar yield of machine-smoked cigarettes. Copyright 2009 Elsevier Inc. All rights reserved.

Aquifer response to stream-stage and recharge variations. II. Convolution method and applications

USGS Publications Warehouse

Barlow, P.M.; DeSimone, L.A.; Moench, A.F.

2000-01-01

In this second of two papers, analytical step-response functions, developed in the companion paper for several cases of transient hydraulic interaction between a fully penetrating stream and a confined, leaky, or water-table aquifer, are used in the convolution integral to calculate aquifer heads, streambank seepage rates, and bank storage that occur in response to streamstage fluctuations and basinwide recharge or evapotranspiration. Two computer programs developed on the basis of these step-response functions and the convolution integral are applied to the analysis of hydraulic interaction of two alluvial stream-aquifer systems in the northeastern and central United States. These applications demonstrate the utility of the analytical functions and computer programs for estimating aquifer and streambank hydraulic properties, recharge rates, streambank seepage rates, and bank storage. Analysis of the water-table aquifer adjacent to the Blackstone River in Massachusetts suggests that the very shallow depth of water table and associated thin unsaturated zone at the site cause the aquifer to behave like a confined aquifer (negligible specific yield). This finding is consistent with previous studies that have shown that the effective specific yield of an unconfined aquifer approaches zero when the capillary fringe, where sediment pores are saturated by tension, extends to land surface. Under this condition, the aquifer's response is determined by elastic storage only. Estimates of horizontal and vertical hydraulic conductivity, specific yield, specific storage, and recharge for a water-table aquifer adjacent to the Cedar River in eastern Iowa, determined by the use of analytical methods, are in close agreement with those estimated by use of a more complex, multilayer numerical model of the aquifer. Streambank leakance of the semipervious streambank materials also was estimated for the site. The streambank-leakance parameter may be considered to be a general (or lumped) parameter that accounts not only for the resistance of flow at the river-aquifer boundary, but also for the effects of partial penetration of the river and other near-stream flow phenomena not included in the theoretical development of the step-response functions.Analytical step-response functions, developed for several cases of transient hydraulic interaction between a fully penetrating stream and a confined, leaky, or water-table aquifer, are used in the convolution integral to calculate aquifer heads, streambank seepage rates, and bank storage that occur in response to stream-stage fluctuations and basinwide recharge or evapotranspiration. Two computer programs developed on the basis of these step-response functions and the convolution integral are applied to the analysis of hydraulic interaction of two alluvial stream-aquifer systems. These applications demonstrate the utility of the analytical functions and computer programs for estimating aquifer and streambank seepage rates and bank storage.

A computer program for predicting recharge with a master recession curve

USGS Publications Warehouse

Heppner, Christopher S.; Nimmo, John R.

2005-01-01

Water-table fluctuations occur in unconfined aquifers owing to ground-water recharge following precipitation and infiltration, and ground-water discharge to streams between storm events. Ground-water recharge can be estimated from well hydrograph data using the water-table fluctuation (WTF) principle, which states that recharge is equal to the product of the water-table rise and the specific yield of the subsurface porous medium. The water-table rise, however, must be expressed relative to the water level that would have occurred in the absence of recharge. This requires a means for estimating the recession pattern of the water-table at the site. For a given site there is often a characteristic relation between the water-table elevation and the water-table decline rate following a recharge event. A computer program was written which extracts the relation between decline rate and water-table elevation from well hydrograph data and uses it to construct a master recession curve (MRC). The MRC is a characteristic water-table recession hydrograph, representing the average behavior for a declining water-table at that site. The program then calculates recharge using the WTF method by comparing the measured well hydrograph with the hydrograph predicted by the MRC and multiplying the difference at each time step by the specific yield. This approach can be used to estimate recharge in a continuous fashion from long-term well records. Presented here is a description of the code including the WTF theory and instructions for running it to estimate recharge with continuous well hydrograph data.

Rice yields in tropical/subtropical Asia exhibit large but opposing sensitivities to minimum and maximum temperatures

PubMed Central

Welch, Jarrod R.; Vincent, Jeffrey R.; Auffhammer, Maximilian; Moya, Piedad F.; Dobermann, Achim; Dawe, David

2010-01-01

Data from farmer-managed fields have not been used previously to disentangle the impacts of daily minimum and maximum temperatures and solar radiation on rice yields in tropical/subtropical Asia. We used a multiple regression model to analyze data from 227 intensively managed irrigated rice farms in six important rice-producing countries. The farm-level detail, observed over multiple growing seasons, enabled us to construct farm-specific weather variables, control for unobserved factors that either were unique to each farm but did not vary over time or were common to all farms at a given site but varied by season and year, and obtain more precise estimates by including farm- and site-specific economic variables. Temperature and radiation had statistically significant impacts during both the vegetative and ripening phases of the rice plant. Higher minimum temperature reduced yield, whereas higher maximum temperature raised it; radiation impact varied by growth phase. Combined, these effects imply that yield at most sites would have grown more rapidly during the high-yielding season but less rapidly during the low-yielding season if observed temperature and radiation trends at the end of the 20th century had not occurred, with temperature trends being more influential. Looking ahead, they imply a net negative impact on yield from moderate warming in coming decades. Beyond that, the impact would likely become more negative, because prior research indicates that the impact of maximum temperature becomes negative at higher levels. Diurnal temperature variation must be considered when investigating the impacts of climate change on irrigated rice in Asia. PMID:20696908

Spatial variability effects on precision and power of forage yield estimation

USDA-ARS?s Scientific Manuscript database

Spatial analyses of yield trials are important, as they adjust cultivar means for spatial variation and improve the statistical precision of yield estimation. While the relative efficiency of spatial analysis has been frequently reported in several yield trials, its application on long-term forage y...

A wedge-based approach to estimating health co-benefits of climate change mitigation activities in the United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Balbus, John M.; Greenblatt, Jeffery B.; Chari, Ramya

While it has been recognized that actions reducing greenhouse gas (GHG) emissions can have significant positive and negative impacts on human health through reductions in ambient fine particulate matter (PM2.5) concentrations, these impacts are rarely taken into account when analyzing specific policies. This study presents a new framework for estimating the change in health outcomes resulting from implementation of specific carbon dioxide (CO 2) reduction activities, allowing comparison of different sectors and options for climate mitigation activities. Our estimates suggest that in the year 2020, the reductions in adverse health outcomes from lessened exposure to PM2.5 would yield economic benefitsmore » in the range of $6 to $14 billion (in 2008 USD), depending on the specific activity. This equates to between $40 and $93 per metric ton of CO 2 in health benefits. Specific climate interventions will vary in the health co-benefits they provide as well as in potential harms that may result from their implementation. Rigorous assessment of these health impacts is essential for guiding policy decisions as efforts to reduce GHG emissions increase in scope and intensity.« less

Contributions of atmospheric nitrogen deposition to U.S. estuaries: Summary and conclusions: Chapter 8

USGS Publications Warehouse

Stacey, Paul E.; Greening, Holly; Kremer, James N.; Peterson, David; Tomasko, David A.; Valigura, Richard A.; Alexander, Richard B.; Castro, Mark S.; Meyers, Tilden P.; Paerl, Hans W.; Stacey, Paul E.; Turner, R. Eugene

2001-01-01

A NOAA project was initiated in 1998, with support from the U.S. EPA, to develop state-of-the-art estimates of atmospheric N deposition to estuarine watersheds and water surfaces and its delivery to the estuaries. Work groups were formed to address N deposition rates, indirect (from the watershed) yields from atmospheric and other anthropogenic sources, and direct deposition on the estuarine waterbodies, and to evaluate the levels of uncertainty within the estimates. Watershed N yields were estimated using both a land-use based process approach and a national (SPARROW) model, compared to each other, and compared to estimates of N yield from the literature. The total N yields predicted by the national model were similar to values found in the literature and the land-use derived estimates were consistently higher. Atmospheric N yield estimates were within a similar range for the two approaches, but tended to be higher in the land-use based estimates and were not wellcorrelated. Median atmospheric N yields were around 15% of the total N yield for both groups, but ranged as high as 60% when both direct and indirect deposition were considered. Although not the dominant source of anthropogenic N, atmospheric N is, and will undoubtedly continue to be, an important factor in culturally eutrophied estuarine systems, warranting additional research and management attention.

Using Landsat to provide potato production estimates to Columbia Basin farmers and processors

NASA Technical Reports Server (NTRS)

1990-01-01

A summary of project activities relative to the estimation of potato yields in the Columbia Basin is given. Oregon State University is using a two-pronged approach to yield estimation, one using simulation models and the other using purely empirical models. The simulation modeling approach has used satellite observations to determine key dates in the development of the crop for each field identified as potatoes. In particular, these include planting dates, emergence dates, and harvest dates. These critical dates are fed into simulation models of crop growth and development to derive yield forecasts. Two empirical modeling approaches are illustrated. One relates tuber yield to estimates of cumulative intercepted solar radiation; the other relates tuber yield to the integral under the GVI curve.

Piecewise SALT sampling for estimating suspended sediment yields

Treesearch

Robert B. Thomas

1989-01-01

A probability sampling method called SALT (Selection At List Time) has been developed for collecting and summarizing data on delivery of suspended sediment in rivers. It is based on sampling and estimating yield using a suspended-sediment rating curve for high discharges and simple random sampling for low flows. The method gives unbiased estimates of total yield and...

Cotton yield estimation using very high-resolution digital images acquired on a low-cost small unmanned aerial vehicle

USDA-ARS?s Scientific Manuscript database

Yield estimation is a critical task in crop management. A number of traditional methods are available for crop yield estimation but they are costly, time-consuming and difficult to expand to a relatively large field. Remote sensing provides techniques to develop quick coverage over a field at any sc...

Reference tissue modeling with parameter coupling: application to a study of SERT binding in HIV

NASA Astrophysics Data System (ADS)

Endres, Christopher J.; Hammoud, Dima A.; Pomper, Martin G.

2011-04-01

When applicable, it is generally preferred to evaluate positron emission tomography (PET) studies using a reference tissue-based approach as that avoids the need for invasive arterial blood sampling. However, most reference tissue methods have been shown to have a bias that is dependent on the level of tracer binding, and the variability of parameter estimates may be substantially affected by noise level. In a study of serotonin transporter (SERT) binding in HIV dementia, it was determined that applying parameter coupling to the simplified reference tissue model (SRTM) reduced the variability of parameter estimates and yielded the strongest between-group significant differences in SERT binding. The use of parameter coupling makes the application of SRTM more consistent with conventional blood input models and reduces the total number of fitted parameters, thus should yield more robust parameter estimates. Here, we provide a detailed evaluation of the application of parameter constraint and parameter coupling to [11C]DASB PET studies. Five quantitative methods, including three methods that constrain the reference tissue clearance (kr2) to a common value across regions were applied to the clinical and simulated data to compare measurement of the tracer binding potential (BPND). Compared with standard SRTM, either coupling of kr2 across regions or constraining kr2 to a first-pass estimate improved the sensitivity of SRTM to measuring a significant difference in BPND between patients and controls. Parameter coupling was particularly effective in reducing the variance of parameter estimates, which was less than 50% of the variance obtained with standard SRTM. A linear approach was also improved when constraining kr2 to a first-pass estimate, although the SRTM-based methods yielded stronger significant differences when applied to the clinical study. This work shows that parameter coupling reduces the variance of parameter estimates and may better discriminate between-group differences in specific binding.

Brazilian Soybean Yields and Yield Gaps Vary with Farm Size

NASA Astrophysics Data System (ADS)

Jeffries, G. R.; Cohn, A.; Griffin, T. S.; Bragança, A.

2017-12-01

Understanding the farm size-specific characteristics of crop yields and yield gaps may help to improve yields by enabling better targeting of technical assistance and agricultural development programs. Linking remote sensing-based yield estimates with property boundaries provides a novel view of the relationship between farm size and yield structure (yield magnitude, gaps, and stability over time). A growing literature documents variations in yield gaps, but largely ignores the role of farm size as a factor shaping yield structure. Research on the inverse farm size-productivity relationship (IR) theory - that small farms are more productive than large ones all else equal - has documented that yield magnitude may vary by farm size, but has not considered other yield structure characteristics. We examined farm size - yield structure relationships for soybeans in Brazil for years 2001-2015. Using out-of-sample soybean yield predictions from a statistical model, we documented 1) gaps between the 95th percentile of attained yields and mean yields within counties and individual fields, and 2) yield stability defined as the standard deviation of time-detrended yields at given locations. We found a direct relationship between soy yields and farm size at the national level, while the strength and the sign of the relationship varied by region. Soybean yield gaps were found to be inversely related to farm size metrics, even when yields were only compared to farms of similar size. The relationship between farm size and yield stability was nonlinear, with mid-sized farms having the most stable yields. The work suggests that farm size is an important factor in understanding yield structure and that opportunities for improving soy yields in Brazil are greatest among smaller farms.

Large Area Crop Inventory Experiment (LACIE). First interim phase 3 evaluation report. [Great Plains and U.S.S.R.

NASA Technical Reports Server (NTRS)

1978-01-01

The author has identified the following significant results. LACIE acreage estimates were in close agreement with SRS estimates, and an operational system with a 14 day LANDSAT data turnaround could have produced an accurate acreage estimate (one which satisfied the 90/90 criterion) 1 1/2 to 2 months before harvest. Low yield estimates, resulting from agromet conditions not taken into account in the yield models, caused production estimates to be correspondingly low. However, both yield and production estimates satisfied the LACIE 90/90 criterion for winter wheat in the yardstick region.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stark, Christopher C.; Roberge, Aki; Mandell, Avi

ExoEarth yield is a critical science metric for future exoplanet imaging missions. Here we estimate exoEarth candidate yield using single visit completeness for a variety of mission design and astrophysical parameters. We review the methods used in previous yield calculations and show that the method choice can significantly impact yield estimates as well as how the yield responds to mission parameters. We introduce a method, called Altruistic Yield Optimization, that optimizes the target list and exposure times to maximize mission yield, adapts maximally to changes in mission parameters, and increases exoEarth candidate yield by up to 100% compared to previousmore » methods. We use Altruistic Yield Optimization to estimate exoEarth candidate yield for a large suite of mission and astrophysical parameters using single visit completeness. We find that exoEarth candidate yield is most sensitive to telescope diameter, followed by coronagraph inner working angle, followed by coronagraph contrast, and finally coronagraph contrast noise floor. We find a surprisingly weak dependence of exoEarth candidate yield on exozodi level. Additionally, we provide a quantitative approach to defining a yield goal for future exoEarth-imaging missions.« less

A Remote Sensing-Derived Corn Yield Assessment Model

NASA Astrophysics Data System (ADS)

Shrestha, Ranjay Man

Agricultural studies and food security have become critical research topics due to continuous growth in human population and simultaneous shrinkage in agricultural land. In spite of modern technological advancements to improve agricultural productivity, more studies on crop yield assessments and food productivities are still necessary to fulfill the constantly increasing food demands. Besides human activities, natural disasters such as flood and drought, along with rapid climate changes, also inflect an adverse effect on food productivities. Understanding the impact of these disasters on crop yield and making early impact estimations could help planning for any national or international food crisis. Similarly, the United States Department of Agriculture (USDA) Risk Management Agency (RMA) insurance management utilizes appropriately estimated crop yield and damage assessment information to sustain farmers' practice through timely and proper compensations. Through County Agricultural Production Survey (CAPS), the USDA National Agricultural Statistical Service (NASS) uses traditional methods of field interviews and farmer-reported survey data to perform annual crop condition monitoring and production estimations at the regional and state levels. As these manual approaches of yield estimations are highly inefficient and produce very limited samples to represent the entire area, NASS requires supplemental spatial data that provides continuous and timely information on crop production and annual yield. Compared to traditional methods, remote sensing data and products offer wider spatial extent, more accurate location information, higher temporal resolution and data distribution, and lower data cost--thus providing a complementary option for estimation of crop yield information. Remote sensing derived vegetation indices such as Normalized Difference Vegetation Index (NDVI) provide measurable statistics of potential crop growth based on the spectral reflectance and could be further associated with the actual yield. Utilizing satellite remote sensing products, such as daily NDVI derived from Moderate Resolution Imaging Spectroradiometer (MODIS) at 250 m pixel size, the crop yield estimation can be performed at a very fine spatial resolution. Therefore, this study examined the potential of these daily NDVI products within agricultural studies and crop yield assessments. In this study, a regression-based approach was proposed to estimate the annual corn yield through changes in MODIS daily NDVI time series. The relationship between daily NDVI and corn yield was well defined and established, and as changes in corn phenology and yield were directly reflected by the changes in NDVI within the growing season, these two entities were combined to develop a relational model. The model was trained using 15 years (2000-2014) of historical NDVI and county-level corn yield data for four major corn producing states: Kansas, Nebraska, Iowa, and Indiana, representing four climatic regions as South, West North Central, East North Central, and Central, respectively, within the U.S. Corn Belt area. The model's goodness of fit was well defined with a high coefficient of determination (R2>0.81). Similarly, using 2015 yield data for validation, 92% of average accuracy signified the performance of the model in estimating corn yield at county level. Besides providing the county-level corn yield estimations, the derived model was also accurate enough to estimate the yield at finer spatial resolution (field level). The model's assessment accuracy was evaluated using the randomly selected field level corn yield within the study area for 2014, 2015, and 2016. A total of over 120 plot level corn yield were used for validation, and the overall average accuracy was 87%, which statistically justified the model's capability to estimate plot-level corn yield. Additionally, the proposed model was applied to the impact estimation by examining the changes in corn yield due to flood events during the growing season. Using a 2011 Missouri River flood event as a case study, field-level flood impact map on corn yield throughout the flooded regions was produced and an overall agreement of over 82.2% was achieved when compared with the reference impact map. The future research direction of this dissertation research would be to examine other major crops outside the Corn Belt region of the U.S.

Using LANDSAT to provide potato production estimates to Columbia Basin farmers and processors

NASA Technical Reports Server (NTRS)

1991-01-01

The estimation of potato yields in the Columbia basin is described. The fundamental objective is to provide CROPIX with working models of potato production. A two-pronged approach was used to yield estimation: (1) using simulation models, and (2) using purely empirical models. The simulation modeling approach used satellite observations to determine certain key dates in the development of the crop for each field identified as potatoes. In particular, these include planting dates, emergence dates, and harvest dates. These critical dates are fed into simulation models of crop growth and development to derive yield forecasts. Purely empirical models were developed to relate yield to some spectrally derived measure of crop development. Two empirical approaches are presented: one relates tuber yield to estimates of cumulative intercepted solar radiation, the other relates tuber yield to the integral under GVI (Global Vegetation Index) curve.

Simulation of relationship between river discharge and sediment yield in the semi-arid river watersheds

NASA Astrophysics Data System (ADS)

Khaleghi, Mohammad Reza; Varvani, Javad

2018-02-01

Complex and variable nature of the river sediment yield caused many problems in estimating the long-term sediment yield and problems input into the reservoirs. Sediment Rating Curves (SRCs) are generally used to estimate the suspended sediment load of the rivers and drainage watersheds. Since the regression equations of the SRCs are obtained by logarithmic retransformation and have a little independent variable in this equation, they also overestimate or underestimate the true sediment load of the rivers. To evaluate the bias correction factors in Kalshor and Kashafroud watersheds, seven hydrometric stations of this region with suitable upstream watershed and spatial distribution were selected. Investigation of the accuracy index (ratio of estimated sediment yield to observed sediment yield) and the precision index of different bias correction factors of FAO, Quasi-Maximum Likelihood Estimator (QMLE), Smearing, and Minimum-Variance Unbiased Estimator (MVUE) with LSD test showed that FAO coefficient increases the estimated error in all of the stations. Application of MVUE in linear and mean load rating curves has not statistically meaningful effects. QMLE and smearing factors increased the estimated error in mean load rating curve, but that does not have any effect on linear rating curve estimation.

Sustainable-yield estimation for the Sparta Aquifer in Union County, Arkansas

USGS Publications Warehouse

Hays, Phillip D.

2000-01-01

Options for utilizing alternative sources of water to alleviate overdraft from the Sparta aquifer and ensure that the aquifer can continue to provide abundant water of excellent quality for the future are being evaluated by water managers in Union County. Sustainable yield is a critical element in identifying and designing viable water supply alternatives. With sustainable yield defined and a knowledge of total water demand in an area, any unmet demand can be calculated. The ground-water flow model of the Sparta aquifer was used to estimate sustainable yield using an iterative approach. The Sparta aquifer is a confined aquifer of regional importance that comprises a sequence of unconsolidated sand units that are contained within the Sparta Sand. Currently, the rate of withdrawal in some areas greatly exceeds the rate of recharge to the aquifer and considerable water-level declines have occurred. Ground-water flow model results indicate that the aquifer cannot continue to meet growing water-use demands indefinitely and that water levels will drop below the top of the primary producing sand unit in Union County (locally termed the El Dorado sand) by 2008 if current water-use trends continue. Declines of that magnitude will initiate dewatering of the El Dorado sand. The sustainable yield of the aquifer was calculated by targeting a specified minimum acceptable water level within Union County and varying Union County pumpage within the model to achieve the target water level. Selection of the minimum target water level for sustainable-yield estimation was an important criterion for the modeling effort. In keeping with the State Critical Ground-Water Area designation criteria and the desire of water managers in Union County to improve aquifer conditions and bring the area out of the Critical Ground-Water Area designation, the approximate altitude of the top of the Sparta Sand in central Union County was used as the minimum water level target for estimation of sustainable yield in the county. A specific category of sustainable yield? stabilization yield, reflecting the amount of water that the aquifer can provide while maintaining current water levels? also was determined and provides information for short-term management. The top of the primary producing sand unit (the El Dorado sand) was used as the minimum water-level target for estimating stabilization yield in the county because current minimum water levels in central Union County are near the top of the El Dorado sand. Model results show that withdrawals from the Sparta aquifer in Union County must be reduced to 28 percent of 1997 values to achieve sustainable yield and maintain water levels at the top of the Sparta Sand if future pumpage outside of Union County is assumed to increase at the rate observed from 1985-1997. Results of the simulation define a very large current unmet demand and represent a substantial reduction in the county?s current dependence upon the aquifer. If future pumpage outside of Union County is assumed to increase at double the rate observed from 1985-1997, withdrawals from the Sparta aquifer in Union County must be reduced to 25 percent of 1997 values to achieve sustainable yield. Withdrawals from the Sparta aquifer in Union County must be reduced to about 88 to 91 percent (depending on pumpage growth outside of the county) of 1997 values to stabilize water levels at the top of the El Dorado sand. This result shows that 1997 rate of withdrawal in the county is considerably greater than the rate needed to halt the rapid decline in water levels.

Sensitivity analysis of add-on price estimate for select silicon wafering technologies

NASA Technical Reports Server (NTRS)

Mokashi, A. R.

1982-01-01

The cost of producing wafers from silicon ingots is a major component of the add-on price of silicon sheet. Economic analyses of the add-on price estimates and their sensitivity internal-diameter (ID) sawing, multiblade slurry (MBS) sawing and fixed-abrasive slicing technique (FAST) are presented. Interim price estimation guidelines (IPEG) are used for estimating a process add-on price. Sensitivity analysis of price is performed with respect to cost parameters such as equipment, space, direct labor, materials (blade life) and utilities, and the production parameters such as slicing rate, slices per centimeter and process yield, using a computer program specifically developed to do sensitivity analysis with IPEG. The results aid in identifying the important cost parameters and assist in deciding the direction of technology development efforts.

Forecasting of cereals yields in a semi-arid area using the agrometeorological model «SAFY» combined to optical SPOT/HRV images

NASA Astrophysics Data System (ADS)

Chahbi, Aicha; Zribi, Mehrez; Lili-Chabaane, Zohra; Mougenot, Bernard

2015-10-01

In semi-arid areas, an operational grain yield forecasting system, which could help decision-makers to plan annual imports, is needed. It can be challenging to monitor the crop canopy and production capacity of plants, especially cereals. Many models, based on the use of remote sensing or agro-meteorological models, have been developed to estimate the biomass and grain yield of cereals. Remote sensing has demonstrated its strong potential for the monitoring of the vegetation's dynamics and temporal variations. Through the use of a rich database, acquired over a period of two years for more than 60 test fields, and from 20 optical satellite SPOT/HRV images, the aim of the present study is to evaluate the feasibility of two approaches to estimate the dynamics and yields of cereals in the context of semi-arid, low productivity regions in North Africa. The first approach is based on the application of the semi-empirical growth model SAFY "Simple Algorithm For Yield estimation", developed to simulate the dynamics of the leaf area index and the grain yield, at the field scale. The model is able to reproduce the time evolution of the LAI of all fields. However, the yields are under-estimated. Therefore, we developed a new approach to improve the SAFY model. The grain yield is function of LAI area in the growth period between 25 March and 5 April. This approach is robust, the measured and estimated grain yield are well correlated. Finally, this model is used in combination with remotely sensed LAI measurements to estimate yield for the entire studied site.

Soil Water Availability Modulation Over Estimated Relative Yield Losses in Wheat (Triticum aestivum L.) Due to Ozone Exposure

PubMed Central

De la Torre, Daniel; Sierra, Maria Jose

2007-01-01

The approach developed by Fuhrer in 1995 to estimate wheat yield losses induced by ozone and modulated by the soil water content (SWC) was applied to the data on Catalonian wheat yields. The aim of our work was to apply this approach and adjust it to Mediterranean environmental conditions by means of the necessary corrections. The main objective pursued was to prove the importance of soil water availability in the estimation of relative wheat yield losses as a factor that modifies the effects of tropospheric ozone on wheat, and to develop the algorithms required for the estimation of relative yield losses, adapted to the Mediterranean environmental conditions. The results show that this is an easy way to estimate relative yield losses just using meteorological data, without using ozone fluxes, which are much more difficult to calculate. Soil water availability is very important as a modulating factor of the effects of ozone on wheat; when soil water availability decreases, almost twice the amount of accumulated exposure to ozone is required to induce the same percentage of yield loss as in years when soil water availability is high. PMID:17619747

Extensively Parameterized Mutation-Selection Models Reliably Capture Site-Specific Selective Constraint.

PubMed

Spielman, Stephanie J; Wilke, Claus O

2016-11-01

The mutation-selection model of coding sequence evolution has received renewed attention for its use in estimating site-specific amino acid propensities and selection coefficient distributions. Two computationally tractable mutation-selection inference frameworks have been introduced: One framework employs a fixed-effects, highly parameterized maximum likelihood approach, whereas the other employs a random-effects Bayesian Dirichlet Process approach. While both implementations follow the same model, they appear to make distinct predictions about the distribution of selection coefficients. The fixed-effects framework estimates a large proportion of highly deleterious substitutions, whereas the random-effects framework estimates that all substitutions are either nearly neutral or weakly deleterious. It remains unknown, however, how accurately each method infers evolutionary constraints at individual sites. Indeed, selection coefficient distributions pool all site-specific inferences, thereby obscuring a precise assessment of site-specific estimates. Therefore, in this study, we use a simulation-based strategy to determine how accurately each approach recapitulates the selective constraint at individual sites. We find that the fixed-effects approach, despite its extensive parameterization, consistently and accurately estimates site-specific evolutionary constraint. By contrast, the random-effects Bayesian approach systematically underestimates the strength of natural selection, particularly for slowly evolving sites. We also find that, despite the strong differences between their inferred selection coefficient distributions, the fixed- and random-effects approaches yield surprisingly similar inferences of site-specific selective constraint. We conclude that the fixed-effects mutation-selection framework provides the more reliable software platform for model application and future development. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Cow-specific diet digestibility predictions based on near-infrared reflectance spectroscopy scans of faecal samples.

PubMed

Mehtiö, T; Rinne, M; Nyholm, L; Mäntysaari, P; Sairanen, A; Mäntysaari, E A; Pitkänen, T; Lidauer, M H

2016-04-01

This study was designed to obtain information on prediction of diet digestibility from near-infrared reflectance spectroscopy (NIRS) scans of faecal spot samples from dairy cows at different stages of lactation and to develop a faecal sampling protocol. NIRS was used to predict diet organic matter digestibility (OMD) and indigestible neutral detergent fibre content (iNDF) from faecal samples, and dry matter digestibility (DMD) using iNDF in feed and faecal samples as an internal marker. Acid-insoluble ash (AIA) as an internal digestibility marker was used as a reference method to evaluate the reliability of NIRS predictions. Feed and composite faecal samples were collected from 44 cows at approximately 50, 150 and 250 days in milk (DIM). The estimated standard deviation for cow-specific organic matter digestibility analysed by AIA was 12.3 g/kg, which is small considering that the average was 724 g/kg. The phenotypic correlation between direct faecal OMD prediction by NIRS and OMD by AIA over the lactation was 0.51. The low repeatability and small variability estimates for direct OMD predictions by NIRS were not accurate enough to quantify small differences in OMD between cows. In contrast to OMD, the repeatability estimates for DMD by iNDF and especially for direct faecal iNDF predictions were 0.32 and 0.46, respectively, indicating that developing of NIRS predictions for cow-specific digestibility is possible. A data subset of 20 cows with daily individual faecal samples was used to develop an on-farm sampling protocol. Based on the assessment of correlations between individual sample combinations and composite samples as well as repeatability estimates for individual sample combinations, we found that collecting up to three individual samples yields a representative composite sample. Collection of samples from all the cows of a herd every third month might be a good choice, because it would yield a better accuracy. © 2015 Blackwell Verlag GmbH.

SPATIO-TEMPORAL MODELING OF AGRICULTURAL YIELD DATA WITH AN APPLICATION TO PRICING CROP INSURANCE CONTRACTS

PubMed Central

Ozaki, Vitor A.; Ghosh, Sujit K.; Goodwin, Barry K.; Shirota, Ricardo

2009-01-01

This article presents a statistical model of agricultural yield data based on a set of hierarchical Bayesian models that allows joint modeling of temporal and spatial autocorrelation. This method captures a comprehensive range of the various uncertainties involved in predicting crop insurance premium rates as opposed to the more traditional ad hoc, two-stage methods that are typically based on independent estimation and prediction. A panel data set of county-average yield data was analyzed for 290 counties in the State of Paraná (Brazil) for the period of 1990 through 2002. Posterior predictive criteria are used to evaluate different model specifications. This article provides substantial improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to situations where data are limited. PMID:19890450

Methane production through anaerobic digestion of various energy crops grown in sustainable crop rotations.

PubMed

Amon, Thomas; Amon, Barbara; Kryvoruchko, Vitaliy; Machmüller, Andrea; Hopfner-Sixt, Katharina; Bodiroza, Vitomir; Hrbek, Regina; Friedel, Jürgen; Pötsch, Erich; Wagentristl, Helmut; Schreiner, Matthias; Zollitsch, Werner

2007-12-01

Biogas production is of major importance for the sustainable use of agrarian biomass as renewable energy source. Economic biogas production depends on high biogas yields. The project aimed at optimising anaerobic digestion of energy crops. The following aspects were investigated: suitability of different crop species and varieties, optimum time of harvesting, specific methane yield and methane yield per hectare. The experiments covered 7 maize, 2 winter wheat, 2 triticale varieties, 1 winter rye, and 2 sunflower varieties and 6 variants with permanent grassland. In the course of the vegetation period, biomass yield and biomass composition were measured. Anaerobic digestion was carried out in eudiometer batch digesters. The highest methane yields of 7500-10200 m(N)(3)ha(-1) were achieved from maize varieties with FAO numbers (value for the maturity of the maize) of 300 to 600 harvested at "wax ripeness". Methane yields of cereals ranged from 3200 to 4500 m(N)(3)ha(-1). Cereals should be harvested at "grain in the milk stage" to "grain in the dough stage". With sunflowers, methane yields between 2600 and 4550 m(N)(3)ha(-1) were achieved. There were distinct differences between the investigated sunflower varieties. Alpine grassland can yield 2700-3500 m(N)(3)CH(4)ha(-1). The methane energy value model (MEVM) was developed for the different energy crops. It estimates the specific methane yield from the nutrient composition of the energy crops. Energy crops for biogas production need to be grown in sustainable crop rotations. The paper outlines possibilities for optimising methane yield from versatile crop rotations that integrate the production of food, feed, raw materials and energy. These integrated crop rotations are highly efficient and can provide up to 320 million t COE which is 96% of the total energy demand of the road traffic of the EU-25 (the 25 Member States of the European Union).

Crop suitability monitoring for improved yield estimations with 100m PROBA-V data

NASA Astrophysics Data System (ADS)

Özüm Durgun, Yetkin; Gilliams, Sven; Gobin, Anne; Duveiller, Grégory; Djaby, Bakary; Tychon, Bernard

2015-04-01

This study has been realised within the framework of a PhD targeting to advance agricultural monitoring with improved yield estimations using SPOT VEGETATION remotely sensed data. For the first research question, the aim was to improve dry matter productivity (DMP) for C3 and C4 plants by adding a water stress factor. Additionally, the relation between the actual crop yield and DMP was studied. One of the limitations was the lack of crop specific maps which leads to the second research question on 'crop suitability monitoring'. The objective of this work is to create a methodological approach based on the spectral and temporal characteristics of PROBA-V images and ancillary data such as meteorology, soil and topographic data to improve the estimation of annual crop yields. The PROBA-V satellite was launched on 6th May 2013, and was designed to bridge the gap in space-borne vegetation measurements between SPOT-VGT (March 1998 - May 2014) and the upcoming Sentinel-3 satellites scheduled for launch in 2015/2016. PROBA -V has products in four spectral bands: BLUE (centred at 0.463 µm), RED (0.655 µm), NIR (0.845 µm), and SWIR (1.600 µm) with a spatial resolution ranging from 1km to 300m. Due to the construction of the sensor, the central camera can provide a 100m data product with a 5 to 8 days revisiting time. Although the 100m data product is still in test phase a methodology for crop suitability monitoring was developed. The multi-spectral composites, NDVI (Normalised Difference Vegetation Index) (NIR_RED/NIR+RED) and NDII (Normalised Difference Infrared Index) (NIR-SWIR/NIR+SWIR) profiles are used in addition to secondary data such as digital elevation data, precipitation, temperature, soil types and administrative boundaries to improve the accuracy of crop yield estimations. The methodology is evaluated on several FP7 SIGMA test sites for the 2014 - 2015 period. Reference data in the form of vector GIS with boundaries and cover type of agricultural fields are available through the SIGMA site partners. References http://proba-v.vgt.vito.be/ http://www.geoglam-sigma.info/

Predicting red meat yields in carcasses from beef-type and calf-fed Holstein steers using the United States Department of Agriculture calculated yield grade.

PubMed

Lawrence, T E; Elam, N A; Miller, M F; Brooks, J C; Hilton, G G; VanOverbeke, D L; McKeith, F K; Killefer, J; Montgomery, T H; Allen, D M; Griffin, D B; Delmore, R J; Nichols, W T; Streeter, M N; Yates, D A; Hutcheson, J P

2010-06-01

Analyses were conducted to evaluate the ability of the USDA yield grade equation to detect differences in subprimal yield of beef-type steers and calf-fed Holstein steers that had been fed zilpaterol hydrochloride (ZH; Intervet Inc., Millsboro, DE) as well as those that had not been fed ZH. Beef-type steer (n = 801) and calf-fed Holstein steer (n = 235) carcasses were fabricated into subprimal cuts and trim. Simple correlations between calculated yield grades and total red meat yields ranged from -0.56 to -0.62 for beef-type steers. Reliable correlations from calf-fed Holstein steers were unobtainable; the probability of a type I error met or exceeded 0.39. Linear models were developed for the beef-type steers to predict total red meat yield based on calculated USDA yield grade within each ZH duration. At an average calculated USDA yield grade of 2.9, beef-type steer carcasses that had not been fed ZH had an estimated 69.4% red meat yield, whereas those fed ZH had an estimated 70.7% red meat yield. These results indicate that feeding ZH increased red meat yield by 1.3% at a constant calculated yield grade. However, these data also suggest that the calculated USDA yield grade score is a poor and variable estimator (adjusted R(2) of 0.31 to 0.38) of total red meat yield of beef-type steer carcasses, regardless of ZH feeding. Moreover, no relationship existed (adjusted R(2) of 0.00 to 0.01) for calf-fed Holstein steer carcasses, suggesting the USDA yield grade is not a valid estimate of calf-fed Holstein red meat yield.

Modeling Fetal Weight for Gestational Age: A Comparison of a Flexible Multi-level Spline-based Model with Other Approaches

PubMed Central

Villandré, Luc; Hutcheon, Jennifer A; Perez Trejo, Maria Esther; Abenhaim, Haim; Jacobsen, Geir; Platt, Robert W

2011-01-01

We present a model for longitudinal measures of fetal weight as a function of gestational age. We use a linear mixed model, with a Box-Cox transformation of fetal weight values, and restricted cubic splines, in order to flexibly but parsimoniously model median fetal weight. We systematically compare our model to other proposed approaches. All proposed methods are shown to yield similar median estimates, as evidenced by overlapping pointwise confidence bands, except after 40 completed weeks, where our method seems to produce estimates more consistent with observed data. Sex-based stratification affects the estimates of the random effects variance-covariance structure, without significantly changing sex-specific fitted median values. We illustrate the benefits of including sex-gestational age interaction terms in the model over stratification. The comparison leads to the conclusion that the selection of a model for fetal weight for gestational age can be based on the specific goals and configuration of a given study without affecting the precision or value of median estimates for most gestational ages of interest. PMID:21931571

Fat water decomposition using globally optimal surface estimation (GOOSE) algorithm.

PubMed

Cui, Chen; Wu, Xiaodong; Newell, John D; Jacob, Mathews

2015-03-01

This article focuses on developing a novel noniterative fat water decomposition algorithm more robust to fat water swaps and related ambiguities. Field map estimation is reformulated as a constrained surface estimation problem to exploit the spatial smoothness of the field, thus minimizing the ambiguities in the recovery. Specifically, the differences in the field map-induced frequency shift between adjacent voxels are constrained to be in a finite range. The discretization of the above problem yields a graph optimization scheme, where each node of the graph is only connected with few other nodes. Thanks to the low graph connectivity, the problem is solved efficiently using a noniterative graph cut algorithm. The global minimum of the constrained optimization problem is guaranteed. The performance of the algorithm is compared with that of state-of-the-art schemes. Quantitative comparisons are also made against reference data. The proposed algorithm is observed to yield more robust fat water estimates with fewer fat water swaps and better quantitative results than other state-of-the-art algorithms in a range of challenging applications. The proposed algorithm is capable of considerably reducing the swaps in challenging fat water decomposition problems. The experiments demonstrate the benefit of using explicit smoothness constraints in field map estimation and solving the problem using a globally convergent graph-cut optimization algorithm. © 2014 Wiley Periodicals, Inc.

Impact of covariate models on the assessment of the air pollution-mortality association in a single- and multipollutant context.

PubMed

Sacks, Jason D; Ito, Kazuhiko; Wilson, William E; Neas, Lucas M

2012-10-01

With the advent of multicity studies, uniform statistical approaches have been developed to examine air pollution-mortality associations across cities. To assess the sensitivity of the air pollution-mortality association to different model specifications in a single and multipollutant context, the authors applied various regression models developed in previous multicity time-series studies of air pollution and mortality to data from Philadelphia, Pennsylvania (May 1992-September 1995). Single-pollutant analyses used daily cardiovascular mortality, fine particulate matter (particles with an aerodynamic diameter ≤2.5 µm; PM(2.5)), speciated PM(2.5), and gaseous pollutant data, while multipollutant analyses used source factors identified through principal component analysis. In single-pollutant analyses, risk estimates were relatively consistent across models for most PM(2.5) components and gaseous pollutants. However, risk estimates were inconsistent for ozone in all-year and warm-season analyses. Principal component analysis yielded factors with species associated with traffic, crustal material, residual oil, and coal. Risk estimates for these factors exhibited less sensitivity to alternative regression models compared with single-pollutant models. Factors associated with traffic and crustal material showed consistently positive associations in the warm season, while the coal combustion factor showed consistently positive associations in the cold season. Overall, mortality risk estimates examined using a source-oriented approach yielded more stable and precise risk estimates, compared with single-pollutant analyses.

A comparison of fisheries biological reference points estimated from temperature-specific multi-species and single-species climate-enhanced stock assessment models

NASA Astrophysics Data System (ADS)

Holsman, Kirstin K.; Ianelli, James; Aydin, Kerim; Punt, André E.; Moffitt, Elizabeth A.

2016-12-01

Multi-species statistical catch at age models (MSCAA) can quantify interacting effects of climate and fisheries harvest on species populations, and evaluate management trade-offs for fisheries that target several species in a food web. We modified an existing MSCAA model to include temperature-specific growth and predation rates and applied the modified model to three fish species, walleye pollock (Gadus chalcogrammus), Pacific cod (Gadus macrocephalus) and arrowtooth flounder (Atheresthes stomias), from the eastern Bering Sea (USA). We fit the model to data from 1979 through 2012, with and without trophic interactions and temperature effects, and use projections to derive single- and multi-species biological reference points (BRP and MBRP, respectively) for fisheries management. The multi-species model achieved a higher over-all goodness of fit to the data (i.e. lower negative log-likelihood) for pollock and Pacific cod. Variability from water temperature typically resulted in 5-15% changes in spawning, survey, and total biomasses, but did not strongly impact recruitment estimates or mortality. Despite this, inclusion of temperature in projections did have a strong effect on BRPs, including recommended yield, which were higher in single-species models for Pacific cod and arrowtooth flounder that included temperature compared to the same models without temperature effects. While the temperature-driven multi-species model resulted in higher yield MBPRs for arrowtooth flounder than the same model without temperature, we did not observe the same patterns in multi-species models for pollock and Pacific cod, where variability between harvest scenarios and predation greatly exceeded temperature-driven variability in yield MBRPs. Annual predation on juvenile pollock (primarily cannibalism) in the multi-species model was 2-5 times the annual harvest of adult fish in the system, thus predation represents a strong control on population dynamics that exceeds temperature-driven changes to growth and is attenuated through harvest-driven reductions in predator populations. Additionally, although we observed differences in spawning biomasses at the accepted biological catch (ABC) proxy between harvest scenarios and single- and multi-species models, discrepancies in spawning stock biomass estimates did not translate to large differences in yield. We found that multi-species models produced higher estimates of combined yield for aggregate maximum sustainable yield (MSY) targets than single species models, but were more conservative than single-species models when individual MSY targets were used, with the exception of scenarios where minimum biomass thresholds were imposed. Collectively our results suggest that climate and trophic drivers can interact to affect MBRPs, but for prey species with high predation rates, trophic- and management-driven changes may exceed direct effects of temperature on growth and predation. Additionally, MBRPs are not inherently more conservative than single-species BRPs. This framework provides a basis for the application of MSCAA models for tactical ecosystem-based fisheries management decisions under changing climate conditions.

NASA Earth Science Research Results for Improved Regional Crop Yield Prediction

NASA Astrophysics Data System (ADS)

Mali, P.; O'Hara, C. G.; Shrestha, B.; Sinclair, T. R.; G de Goncalves, L. G.; Salado Navarro, L. R.

2007-12-01

National agencies such as USDA Foreign Agricultural Service (FAS), Production Estimation and Crop Assessment Division (PECAD) work specifically to analyze and generate timely crop yield estimates that help define national as well as global food policies. The USDA/FAS/PECAD utilizes a Decision Support System (DSS) called CADRE (Crop Condition and Data Retrieval Evaluation) mainly through an automated database management system that integrates various meteorological datasets, crop and soil models, and remote sensing data; providing significant contribution to the national and international crop production estimates. The "Sinclair" soybean growth model has been used inside CADRE DSS as one of the crop models. This project uses Sinclair model (a semi-mechanistic crop growth model) for its potential to be effectively used in a geo-processing environment with remote-sensing-based inputs. The main objective of this proposed work is to verify, validate and benchmark current and future NASA earth science research results for the benefit in the operational decision making process of the PECAD/CADRE DSS. For this purpose, the NASA South American Land Data Assimilation System (SALDAS) meteorological dataset is tested for its applicability as a surrogate meteorological input in the Sinclair model meteorological input requirements. Similarly, NASA sensor MODIS products is tested for its applicability in the improvement of the crop yield prediction through improving precision of planting date estimation, plant vigor and growth monitoring. The project also analyzes simulated Visible/Infrared Imager/Radiometer Suite (VIIRS, a future NASA sensor) vegetation product for its applicability in crop growth prediction to accelerate the process of transition of VIIRS research results for the operational use of USDA/FAS/PECAD DSS. The research results will help in providing improved decision making capacity to the USDA/FAS/PECAD DSS through improved vegetation growth monitoring from high spatial and temporal resolution remote sensing datasets; improved time-series meteorological inputs required for crop growth models; and regional prediction capability through geo-processing-based yield modeling.

Medical marijuana laws and adolescent marijuana use in the United States: a systematic review and meta‐analysis

PubMed Central

Sarvet, Aaron L.; Wall, Melanie M.; Fink, David S.; Greene, Emily; Le, Aline; Boustead, Anne E.; Pacula, Rosalie Liccardo; Keyes, Katherine M.; Cerdá, Magdalena; Galea, Sandro

2018-01-01

Abstract Aims To conduct a systematic review and meta‐analysis of studies in order to estimate the effect of US medical marijuana laws (MMLs) on past‐month marijuana use prevalence among adolescents. Methods A total of 2999 papers from 17 literature sources were screened systematically. Eleven studies, developed from four ongoing large national surveys, were meta‐analyzed. Estimates of MML effects on any past‐month marijuana use prevalence from included studies were obtained from comparisons of pre–post MML changes in MML states to changes in non‐MML states over comparable time‐periods. These estimates were standardized and entered into a meta‐analysis model with fixed‐effects for each study. Heterogeneity among the study estimates by national data survey was tested with an omnibus F‐test. Estimates of effects on additional marijuana outcomes, of MML provisions (e.g. dispensaries) and among demographic subgroups were abstracted and summarized. Key methodological and modeling characteristics were also described. Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) guidelines were followed. Results None of the 11 studies found significant estimates of pre–post MML changes compared with contemporaneous changes in non‐MML states for marijuana use prevalence among adolescents. The meta‐analysis yielded a non‐significant pooled estimate (standardized mean difference) of −0.003 (95% confidence interval = −0.012, +0.007). Four studies compared MML with non‐MML states on pre‐MML differences and all found higher rates of past‐month marijuana use in MML states pre‐MML passage. Additional tests of specific MML provisions, of MML effects on additional marijuana outcomes and among subgroups generally yielded non‐significant results, although limited heterogeneity may warrant further study. Conclusions Synthesis of the current evidence does not support the hypothesis that US medical marijuana laws (MMLs) until 2014 have led to increases in adolescent marijuana use prevalence. Limited heterogeneity exists among estimates of effects of MMLs on other patterns of marijuana use, of effects within particular population subgroups and of effects of specific MML provisions. PMID:29468763

Linking ecophysiological modelling with quantitative genetics to support marker-assisted crop design for improved yields of rice (Oryza sativa) under drought stress.

PubMed

Gu, Junfei; Yin, Xinyou; Zhang, Chengwei; Wang, Huaqi; Struik, Paul C

2014-09-01

Genetic markers can be used in combination with ecophysiological crop models to predict the performance of genotypes. Crop models can estimate the contribution of individual markers to crop performance in given environments. The objectives of this study were to explore the use of crop models to design markers and virtual ideotypes for improving yields of rice (Oryza sativa) under drought stress. Using the model GECROS, crop yield was dissected into seven easily measured parameters. Loci for these parameters were identified for a rice population of 94 introgression lines (ILs) derived from two parents differing in drought tolerance. Marker-based values of ILs for each of these parameters were estimated from additive allele effects of the loci, and were fed to the model in order to simulate yields of the ILs grown under well-watered and drought conditions and in order to design virtual ideotypes for those conditions. To account for genotypic yield differences, it was necessary to parameterize the model for differences in an additional trait 'total crop nitrogen uptake' (Nmax) among the ILs. Genetic variation in Nmax had the most significant effect on yield; five other parameters also significantly influenced yield, but seed weight and leaf photosynthesis did not. Using the marker-based parameter values, GECROS also simulated yield variation among 251 recombinant inbred lines of the same parents. The model-based dissection approach detected more markers than the analysis using only yield per se. Model-based sensitivity analysis ranked all markers for their importance in determining yield differences among the ILs. Virtual ideotypes based on markers identified by modelling had 10-36 % more yield than those based on markers for yield per se. This study outlines a genotype-to-phenotype approach that exploits the potential value of marker-based crop modelling in developing new plant types with high yields. The approach can provide more markers for selection programmes for specific environments whilst also allowing for prioritization. Crop modelling is thus a powerful tool for marker design for improved rice yields and for ideotyping under contrasting conditions. © The Author 2014. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Modelling soil erosion in a Mediterranean watershed: Comparison between SWAT and AnnAGNPS models.

PubMed

Abdelwahab, O M M; Ricci, G F; De Girolamo, A M; Gentile, F

2018-06-20

In this study, the simulations generated by two of the most widely used hydrological basin-scale models, the Annualized Agricultural Non-Point Source (AnnAGNPS) and the Soil and Water Assessment Tool (SWAT), were compared in a Mediterranean watershed, the Carapelle (Apulia, Southern Italy). Input data requirements, time and efforts needed for input preparation, strength and weakness points of each model, ease of use and limitations were evaluated in order to give information to users. Models were calibrated and validated at monthly time scale for hydrology and sediment load using a four year period of observations (streamflow and suspended sediment concentrations). In the driest year, the specific sediment load measured at the outlet was 0.89 t ha -1 yr -1 , while the simulated values were 0.83 t ha -1 yr -1 and 1.99 t ha -1 yr -1 for SWAT and AnnAGNPS, respectively. In the wettest year, the specific measured sediment load was 7.45 t ha -1 yr -1 , and the simulated values were 8.27 t ha -1 yr -1 and 6.23 t ha -1 yr -1 for SWAT and AnnAGNPS, respectively. Both models showed from fair to a very good correlation between observed and simulated streamflow and satisfactory for sediment load. Results showed that most of the basin is under moderate (1.4-10 t ha -1 yr -1 ) and high-risk erosion (> 10 t ha -1 yr -1 ). The sediment yield predicted by the SWAT and AnnAGNPS models were compared with estimates of soil erosion simulated by models for Europe (PESERA and RUSLE2015). The average gross erosion estimated by the RUSLE2015 model (12.5 t ha -1 yr -1 ) resulted comparable with the average specific sediment yield estimated by SWAT (8.8 t ha -1 yr -1 ) and AnnAGNPS (5.6 t ha -1 yr -1 ), while it was found that the average soil erosion estimated by PESERA is lower than the other estimates (1.2 t ha -1 yr -1 ). Copyright © 2018 Elsevier Inc. All rights reserved.

Evaluation of the CEAS trend and monthly weather data models for soybean yields in Iowa, Illinois, and Indiana

NASA Technical Reports Server (NTRS)

French, V. (Principal Investigator)

1982-01-01

The CEAS models evaluated use historic trend and meteorological and agroclimatic variables to forecast soybean yields in Iowa, Illinois, and Indiana. Indicators of yield reliability and current measures of modeled yield reliability were obtained from bootstrap tests on the end of season models. Indicators of yield reliability show that the state models are consistently better than the crop reporting district (CRD) models. One CRD model is especially poor. At the state level, the bias of each model is less than one half quintal/hectare. The standard deviation is between one and two quintals/hectare. The models are adequate in terms of coverage and are to a certain extent consistent with scientific knowledge. Timely yield estimates can be made during the growing season using truncated models. The models are easy to understand and use and are not costly to operate. Other than the specification of values used to determine evapotranspiration, the models are objective. Because the method of variable selection used in the model development is adequately documented, no evaluation can be made of the objectivity and cost of redevelopment of the model.

Future possible crop yield scenarios under multiple SSP and RCP scenarios.

NASA Astrophysics Data System (ADS)

Sakurai, G.; Yokozawa, M.; Nishimori, M.; Okada, M.

2016-12-01

Understanding the effect of future climate change on global crop yields is one of the most important tasks for global food security. Future crop yields would be influenced by climatic factors such as the changes of temperature, precipitation and atmospheric carbon dioxide concentration. On the other hand, the effect of the changes of agricultural technologies such as crop varieties, pesticide and fertilizer input on crop yields have large uncertainty. However, not much is available on the contribution ratio of each factor under the future climate change scenario. We estimated the future global yields of four major crops (maize, soybean, rice and wheat) under three Shared Socio Economic Pathways (SSPs) and four Representative Concentration Pathways (RCPs). For this purpose, firstly, we estimated a parameter of a process based model (PRYSBI2) using a Bayesian method for each 1.125 degree spatial grid. The model parameter is relevant to the agricultural technology (we call "technological parameter" here after). Then, we analyzed the relationship between the values of technological parameter and GDP values. We found that the estimated values of the technological parameter were positively correlated with the GDP. Using the estimated relationship, we predicted future crop yield during 2020 and 2100 under SSP1, SSP2 and SSP3 scenarios and RCP 2.6, 4.5, 6.0 and 8.5. The estimated crop yields were different among SSP scenarios. However, we found that the yield difference attributable to SSPs were smaller than those attributable to CO2 fertilization effects and climate change. Particularly, the estimated effect of the change of atmospheric carbon dioxide concentration on global yields was more than four times larger than that of GDP for C3 crops.

Outcomes analysis of new entrant screening for active tuberculosis in Heathrow and Gatwick airports, United Kingdom 2009/2010.

PubMed

Severi, Ettore; Maguire, Helen; Ihekweazu, Chikwe; Bickler, Graham; Abubakar, Ibrahim

2016-04-22

In 2012, the United Kingdom (UK) Government announced that the new entrant screening for active tuberculosis (TB) in Heathrow and Gatwick airports would end. Our study objective was to estimate screening yield and diagnostic accuracy, and identify those at risk of active TB after entry. We designed a retrospective cohort study and linked new entrants screened from June 2009 to September 2010 through probabilistic matching with UK Enhanced TB Surveillance (ETS) data (June 2009 to December 2010). Yield was the proportion of cases reported to ETS within three months of airport screening in the screened population. To estimate screening diagnostic accuracy we assessed sensitivity, specificity, positive and negative predictive values. Through Poisson regression we identified groups at increased risk of TB diagnosis after entry. We identified 200,199 screened entrants, of these 59 had suspected TB at screening and were reported within 3 months to ETS (yield = 0.03 %). Sensitivity was 26 %; specificity was 99.7 %; positive predictive value was 13.2 %; negative predictive value was 99.9 %. Overall, 350 entrants were reported in ETS. Persons from countries with annual TB incidence higher than 150 cases per 100,000 population and refugees and asylum seekers were at increased risk of TB diagnosis after entry (population attributable risk 77 and 3 % respectively). Airport screening has very low screening yields, sensitivity and positive predictive value. New entrants coming from countries with annual TB incidence higher than 150 per 100,000 population, refugees and asylum seekers should be prioritised at pre- or post-entry screening.

Prediction of the optimum hybridization conditions of dot-blot-SNP analysis using estimated melting temperature of oligonucleotide probes.

PubMed

Shiokai, Sachiko; Kitashiba, Hiroyasu; Nishio, Takeshi

2010-08-01

Although the dot-blot-SNP technique is a simple cost-saving technique suitable for genotyping of many plant individuals, optimization of hybridization and washing conditions for each SNP marker requires much time and labor. For prediction of the optimum hybridization conditions for each probe, we compared T (m) values estimated from nucleotide sequences using the DINAMelt web server, measured T (m) values, and hybridization conditions yielding allele-specific signals. The estimated T (m) values were comparable to the measured T (m) values with small differences of less than 3 degrees C for most of the probes. There were differences of approximately 14 degrees C between the specific signal detection conditions and estimated T (m) values. Change of one level of SSC concentrations of 0.1, 0.2, 0.5, and 1.0x SSC corresponded to a difference of approximately 5 degrees C in optimum signal detection temperature. Increasing the sensitivity of signal detection by shortening the exposure time to X-ray film changed the optimum hybridization condition for specific signal detection. Addition of competitive oligonucleotides to the hybridization mixture increased the suitable hybridization conditions by 1.8. Based on these results, optimum hybridization conditions for newly produced dot-blot-SNP markers will become predictable.

Estimating soybean genetic gain for yield in the northern United States – Influence of cropping history

USDA-ARS?s Scientific Manuscript database

Mean on-farm USA soybean yield increased at a rate of 21.3 kg per ha per year between 1924 and 2010, due to adoption of yield-enhancing genetic and agronomic technologies. To estimate annual rates of genetic yield gain in three northern USA soybean maturity groups (MG) and determine if these estimat...

Efficient scalable solid-state neutron detector.

PubMed

Moses, Daniel

2015-06-01

We report on scalable solid-state neutron detector system that is specifically designed to yield high thermal neutron detection sensitivity. The basic detector unit in this system is made of a (6)Li foil coupled to two crystalline silicon diodes. The theoretical intrinsic efficiency of a detector-unit is 23.8% and that of detector element comprising a stack of five detector-units is 60%. Based on the measured performance of this detector-unit, the performance of a detector system comprising a planar array of detector elements, scaled to encompass effective area of 0.43 m(2), is estimated to yield the minimum absolute efficiency required of radiological portal monitors used in homeland security.

Classical and Bayesian Seismic Yield Estimation: The 1998 Indian and Pakistani Tests

NASA Astrophysics Data System (ADS)

Shumway, R. H.

2001-10-01

- The nuclear tests in May, 1998, in India and Pakistan have stimulated a renewed interest in yield estimation, based on limited data from uncalibrated test sites. We study here the problem of estimating yields using classical and Bayesian methods developed by Shumway (1992), utilizing calibration data from the Semipalatinsk test site and measured magnitudes for the 1998 Indian and Pakistani tests given by Murphy (1998). Calibration is done using multivariate classical or Bayesian linear regression, depending on the availability of measured magnitude-yield data and prior information. Confidence intervals for the classical approach are derived applying an extension of Fieller's method suggested by Brown (1982). In the case where prior information is available, the posterior predictive magnitude densities are inverted to give posterior intervals for yield. Intervals obtained using the joint distribution of magnitudes are comparable to the single-magnitude estimates produced by Murphy (1998) and reinforce the conclusion that the announced yields of the Indian and Pakistani tests were too high.

Classical and Bayesian Seismic Yield Estimation: The 1998 Indian and Pakistani Tests

NASA Astrophysics Data System (ADS)

Shumway, R. H.

The nuclear tests in May, 1998, in India and Pakistan have stimulated a renewed interest in yield estimation, based on limited data from uncalibrated test sites. We study here the problem of estimating yields using classical and Bayesian methods developed by Shumway (1992), utilizing calibration data from the Semipalatinsk test site and measured magnitudes for the 1998 Indian and Pakistani tests given by Murphy (1998). Calibration is done using multivariate classical or Bayesian linear regression, depending on the availability of measured magnitude-yield data and prior information. Confidence intervals for the classical approach are derived applying an extension of Fieller's method suggested by Brown (1982). In the case where prior information is available, the posterior predictive magnitude densities are inverted to give posterior intervals for yield. Intervals obtained using the joint distribution of magnitudes are comparable to the single-magnitude estimates produced by Murphy (1998) and reinforce the conclusion that the announced yields of the Indian and Pakistani tests were too high.

Consequences of a fixed-top DOB assumption on the estimation of pine chip-n-saw and sawtimber tons

Treesearch

G. Kenneth Xydias

2010-01-01

Many pine plantation growth and yield simulators allow the user to define products based on the size classes and top diameters corresponding to local market specs. Top d.o.b. is typically set at a constant corresponding to the local product specification. Examination of individual tree data collected in cruises of loblolly pine stands across the South show that the top...

Intra- and inter-basin mercury comparisons: Importance of basin scale and time-weighted methylmercury estimates

USGS Publications Warehouse

Bradley, Paul M.; Journey, Celeste A.; Bringham, Mark E.; Burns, Douglas A.; Button, Daniel T.; Riva-Murray, Karen

2013-01-01

To assess inter-comparability of fluvial mercury (Hg) observations at substantially different scales, Hg concentrations, yields, and bivariate-relations were evaluated at nested-basin locations in the Edisto River, South Carolina and Hudson River, New York. Differences between scales were observed for filtered methylmercury (FMeHg) in the Edisto (attributed to wetland coverage differences) but not in the Hudson. Total mercury (THg) concentrations and bivariate-relationships did not vary substantially with scale in either basin. Combining results of this and a previously published multi-basin study, fish Hg correlated strongly with sampled water FMeHg concentration (p = 0.78; p = 0.003) and annual FMeHg basin yield (p = 0.66; p = 0.026). Improved correlation (p = 0.88; p < 0.0001) was achieved with time-weighted mean annual FMeHg concentrations estimated from basin-specific LOADEST models and daily streamflow. Results suggest reasonable scalability and inter-comparability for different basin sizes if wetland area or related MeHg-source-area metrics are considered.

Comparison Between the Use of SAR and Optical Data for Wheat Yield Estimations Using Crop Model Assimilation

NASA Astrophysics Data System (ADS)

Silvestro, Paolo Cosmo; Yang, Hao; Jin, X. L.; Yang, Guijun; Casa, Raffaele; Pignatti, Stefano

2016-08-01

The ultimate aim of this work is to develop methods for the assimilation of the biophysical variables estimated by remote sensing in a suitable crop growth model. Two strategies were followed, one based on the use of Leaf Area Index (LAI) estimated by optical data, and the other based on the use of biomass estimated by SAR. The first one estimates LAI from the reflectance measured by the optical sensors on board of HJ1A, HJ1B and Landsat, using a method based on the training of artificial neural networks (ANN) with PROSAIL model simulations. The retrieved LAI is used to improve wheat yield estimation, using assimilation methods based on the Ensemble Kalman Filter, which assimilate the biophysical variables into growth crop model. The second strategy estimates biomass from SAR imagery. Polarimetric decomposition methods were used based on multi-temporal fully polarimetric Radarsat-2 data during the entire growing season. The estimated biomass was assimilating to FAO Aqua crop model for improving the winter wheat yield estimation, with the Particle Swarm Optimization (PSO) method. These procedures were used in a spatial application with data collected in the rural area of Yangling (Shaanxi Province) in 2014 and were validated for a number of wheat fields for which ground yield data had been recorded and according to statistical yield data for the area.

Direct and correlated responses to selection for milk yield: results and conclusions of regional project NC-2, "improvement of dairy cattle through breeding, with emphasis on selection". NC-2 Technical Committee.

PubMed

Kelm, S C; Freeman, A E

2000-12-01

Measurement of direct and correlated responses to single-trait selection for milk yield was the major objective of regional project NC-2. The NC-2 Technical Committee included representatives from Alaska, Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Nebraska, South Dakota, Wisconsin, and the USDA. All representatives, except Illinois, Kansas and Nebraska, maintained a selection line formed by using AI sires selected for high estimated transmitting abilities for milk and a second line that served as some type of a control. Stations varied in criteria for selection of bulls for control lines. Farms were managed similarly, including feeding and management of selection and control lines as one herd, random mating within line, and restricted culling policies. Selection for milk yield effectively increased milk production. All selection lines increased milk and net income per lactation more than control lines. Realized gains matched or exceeded gains expected from estimates of breeding values. Yields of milk components increased, but component percentages decreased appreciably for selection lines. Reproduction of nulliparous animals was not affected, but days open for lactating selection cows increased in some of the individual projects. Selected cows tended to have larger health costs, specifically for mammary treatment. Udder and conformation traits did not deteriorate for selection lines, although control lines with selection of sires on genetic evaluations for type received higher type scores. There should be few reservations about undesirable responses correlated with selection for milk yield.

Diagnostic Yield of Computed Tomography Scan for Pediatric Hearing Loss: A Systematic Review

PubMed Central

Chen, Jenny X.; Kachniarz, Bart; Shin, Jennifer J.

2015-01-01

Background Computed tomography (CT) has been used in the assessment of pediatric hearing loss, but concern regarding radiation risk and increased utilization of magnetic resonance imaging (MRI) have prompted us toward a more quantitative and sophisticated understanding of CT’s potential diagnostic yield. Objective To perform a systematic review to analyze the diagnostic yield of CT for pediatric hearing loss, including subgroup evaluation according to impairment severity and laterality, as well as the specific findings of enlarged vestibular aqueduct and narrow cochlear nerve canal. Data Sources PubMed, EMBASE, and the Cochrane Library were assessed from the date of their inception to December 2013. In addition, manual searches of bibliographies were performed and topic experts were contacted. Review Methods Data from studies describing the use of CT in the diagnostic evaluation of pediatric patients with hearing loss of unknown etiology were evaluated, according to a priori inclusion/exclusion criteria. Two independent evaluators corroborated the extracted data. Heterogeneity was evaluated according to the I2 statistic. Results In 50 criteria-meeting studies, the overall diagnostic yield of CT ranged from 7% to 74%, with the strongest and aggregate data demonstrating a point estimate of 30%. This estimate corresponded to a number needed to image of 4 (range, 2–15). The most commonly identified findings were enlarged vestibular aqueduct and cochlear anomalies. The largest studies showed a 4% to 7% yield for narrow cochlear nerve canal. Conclusion These data, along with similar analyses of radiation risk and risks/benefits of sedated MRI, may be used to help guide the choice of diagnostic imaging. PMID:25186339

Identification of Cyclin-dependent Kinase 1 Specific Phosphorylation Sites by an In Vitro Kinase Assay.

PubMed

Cui, Heying; Loftus, Kyle M; Noell, Crystal R; Solmaz, Sozanne R

2018-05-03

Cyclin-dependent kinase 1 (Cdk1) is a master controller for the cell cycle in all eukaryotes and phosphorylates an estimated 8 - 13% of the proteome; however, the number of identified targets for Cdk1, particularly in human cells is still low. The identification of Cdk1-specific phosphorylation sites is important, as they provide mechanistic insights into how Cdk1 controls the cell cycle. Cell cycle regulation is critical for faithful chromosome segregation, and defects in this complicated process lead to chromosomal aberrations and cancer. Here, we describe an in vitro kinase assay that is used to identify Cdk1-specific phosphorylation sites. In this assay, a purified protein is phosphorylated in vitro by commercially available human Cdk1/cyclin B. Successful phosphorylation is confirmed by SDS-PAGE, and phosphorylation sites are subsequently identified by mass spectrometry. We also describe purification protocols that yield highly pure and homogeneous protein preparations suitable for the kinase assay, and a binding assay for the functional verification of the identified phosphorylation sites, which probes the interaction between a classical nuclear localization signal (cNLS) and its nuclear transport receptor karyopherin α. To aid with experimental design, we review approaches for the prediction of Cdk1-specific phosphorylation sites from protein sequences. Together these protocols present a very powerful approach that yields Cdk1-specific phosphorylation sites and enables mechanistic studies into how Cdk1 controls the cell cycle. Since this method relies on purified proteins, it can be applied to any model organism and yields reliable results, especially when combined with cell functional studies.

Research in the application of spectral data to crop identification and assessment, volume 2

NASA Technical Reports Server (NTRS)

Daughtry, C. S. T. (Principal Investigator); Hixson, M. M.; Bauer, M. E.

1980-01-01

The development of spectrometry crop development stage models is discussed with emphasis on models for corn and soybeans. One photothermal and four thermal meteorological models are evaluated. Spectral data were investigated as a source of information for crop yield models. Intercepted solar radiation and soil productivity are identified as factors related to yield which can be estimated from spectral data. Several techniques for machine classification of remotely sensed data for crop inventory were evaluated. Early season estimation, training procedures, the relationship of scene characteristics to classification performance, and full frame classification methods were studied. The optimal level for combining area and yield estimates of corn and soybeans is assessed utilizing current technology: digital analysis of LANDSAT MSS data on sample segments to provide area estimates and regression models to provide yield estimates.

The influence of random element displacement on DOA estimates obtained with (Khatri-Rao-)root-MUSIC.

PubMed

Inghelbrecht, Veronique; Verhaevert, Jo; van Hecke, Tanja; Rogier, Hendrik

2014-11-11

Although a wide range of direction of arrival (DOA) estimation algorithms has been described for a diverse range of array configurations, no specific stochastic analysis framework has been established to assess the probability density function of the error on DOA estimates due to random errors in the array geometry. Therefore, we propose a stochastic collocation method that relies on a generalized polynomial chaos expansion to connect the statistical distribution of random position errors to the resulting distribution of the DOA estimates. We apply this technique to the conventional root-MUSIC and the Khatri-Rao-root-MUSIC methods. According to Monte-Carlo simulations, this novel approach yields a speedup by a factor of more than 100 in terms of CPU-time for a one-dimensional case and by a factor of 56 for a two-dimensional case.

Field design factors affecting the precision of ryegrass forage yield estimation

USDA-ARS?s Scientific Manuscript database

Field-based agronomic and genetic research relies heavily on the data generated from field evaluations. Therefore, it is imperative to optimize the precision and accuracy of yield estimates in cultivar evaluation trials to make reliable selections. Experimental error in yield trials is sensitive to ...

Linear unmixing of multidate hyperspectral imagery for crop yield estimation

USDA-ARS?s Scientific Manuscript database

In this paper, we have evaluated an unsupervised unmixing approach, vertex component analysis (VCA), for the application of crop yield estimation. The results show that abundance maps of the vegetation extracted by the approach are strongly correlated to the yield data (the correlation coefficients ...

Further Improvements to Linear Mixed Models for Genome-Wide Association Studies

PubMed Central

Widmer, Christian; Lippert, Christoph; Weissbrod, Omer; Fusi, Nicolo; Kadie, Carl; Davidson, Robert; Listgarten, Jennifer; Heckerman, David

2014-01-01

We examine improvements to the linear mixed model (LMM) that better correct for population structure and family relatedness in genome-wide association studies (GWAS). LMMs rely on the estimation of a genetic similarity matrix (GSM), which encodes the pairwise similarity between every two individuals in a cohort. These similarities are estimated from single nucleotide polymorphisms (SNPs) or other genetic variants. Traditionally, all available SNPs are used to estimate the GSM. In empirical studies across a wide range of synthetic and real data, we find that modifications to this approach improve GWAS performance as measured by type I error control and power. Specifically, when only population structure is present, a GSM constructed from SNPs that well predict the phenotype in combination with principal components as covariates controls type I error and yields more power than the traditional LMM. In any setting, with or without population structure or family relatedness, a GSM consisting of a mixture of two component GSMs, one constructed from all SNPs and another constructed from SNPs that well predict the phenotype again controls type I error and yields more power than the traditional LMM. Software implementing these improvements and the experimental comparisons are available at http://microsoft.com/science. PMID:25387525

Reducing CO2 Emissions through Lightweight Design and Manufacturing

NASA Astrophysics Data System (ADS)

Carruth, Mark A.; Allwood, Julian M.; Milford, Rachel L.

2011-05-01

To meet targeted 50% reductions in industrial CO2 emissions by 2050, demand for steel and aluminium must be cut. Many steel and aluminium products include redundant material, and the manufacturing routes to produce them use more material than is necessary. Lightweight design and optimized manufacturing processes offer a means of demand reduction, whilst creating products to perform the same service as existing ones. This paper examines two strategies for demand reduction: lightweight product design; and minimizing yield losses through the product supply chain. Possible mass savings are estimated for specific case-studies on metal-intensive products, such as I-beams and food cans. These estimates are then extrapolated to other sectors to produce a global estimate for possible demand reductions. Results show that lightweight product design may offer potential mass savings of up to 30% for some products, whilst yield in the production of others could be improved by over 20%. If these two strategies could be combined for all products, global demand for steel and aluminium would be reduced by nearly 50%. The impact of demand reduction on CO2 emissions is presented, and barriers to the adoption of new, lightweight technologies are discussed.

Further Improvements to Linear Mixed Models for Genome-Wide Association Studies

NASA Astrophysics Data System (ADS)

Widmer, Christian; Lippert, Christoph; Weissbrod, Omer; Fusi, Nicolo; Kadie, Carl; Davidson, Robert; Listgarten, Jennifer; Heckerman, David

2014-11-01

We examine improvements to the linear mixed model (LMM) that better correct for population structure and family relatedness in genome-wide association studies (GWAS). LMMs rely on the estimation of a genetic similarity matrix (GSM), which encodes the pairwise similarity between every two individuals in a cohort. These similarities are estimated from single nucleotide polymorphisms (SNPs) or other genetic variants. Traditionally, all available SNPs are used to estimate the GSM. In empirical studies across a wide range of synthetic and real data, we find that modifications to this approach improve GWAS performance as measured by type I error control and power. Specifically, when only population structure is present, a GSM constructed from SNPs that well predict the phenotype in combination with principal components as covariates controls type I error and yields more power than the traditional LMM. In any setting, with or without population structure or family relatedness, a GSM consisting of a mixture of two component GSMs, one constructed from all SNPs and another constructed from SNPs that well predict the phenotype again controls type I error and yields more power than the traditional LMM. Software implementing these improvements and the experimental comparisons are available at http://microsoft.com/science.

Further improvements to linear mixed models for genome-wide association studies.

PubMed

Widmer, Christian; Lippert, Christoph; Weissbrod, Omer; Fusi, Nicolo; Kadie, Carl; Davidson, Robert; Listgarten, Jennifer; Heckerman, David

2014-11-12

We examine improvements to the linear mixed model (LMM) that better correct for population structure and family relatedness in genome-wide association studies (GWAS). LMMs rely on the estimation of a genetic similarity matrix (GSM), which encodes the pairwise similarity between every two individuals in a cohort. These similarities are estimated from single nucleotide polymorphisms (SNPs) or other genetic variants. Traditionally, all available SNPs are used to estimate the GSM. In empirical studies across a wide range of synthetic and real data, we find that modifications to this approach improve GWAS performance as measured by type I error control and power. Specifically, when only population structure is present, a GSM constructed from SNPs that well predict the phenotype in combination with principal components as covariates controls type I error and yields more power than the traditional LMM. In any setting, with or without population structure or family relatedness, a GSM consisting of a mixture of two component GSMs, one constructed from all SNPs and another constructed from SNPs that well predict the phenotype again controls type I error and yields more power than the traditional LMM. Software implementing these improvements and the experimental comparisons are available at http://microsoft.com/science.

Spectral estimates of solar radiation intercepted by corn canopies

NASA Technical Reports Server (NTRS)

Bauer, M. E. (Principal Investigator); Daughtry, C. S. T.; Gallo, K. P.

1982-01-01

Reflectance factor data were acquired with a Landsat band radiometer throughout two growing seasons for corn (Zea mays L.) canopies differing in planting dates, populations, and soil types. Agronomic data collected included leaf area index (LAI), biomass, development stage, and final grain yields. The spectral variable, greenness, was associated with 78 percent of the variation in LAI over all treatments. Single observations of LAI or greenness have limited value in predicting corn yields. The proportions of solar radiation intercepted (SRI) by these canopies were estimated using either measured LAI or greenness. Both SRI estimates, when accumulated over the growing season, accounted for approximately 65 percent of the variation in yields. Models which simulated the daily effects of weather and intercepted solar radiation on growth had the highest correlations to grain yields. This concept of estimating intercepted solar radiation using spectral data represents a viable approach for merging spectral and meteorological data for crop yield models.

Evaluating soil moisture and yield of winter wheat in the Great Plains using Landsat data

NASA Technical Reports Server (NTRS)

Heilman, J. L.; Kanemasu, E. T.; Bagley, J. O.; Rasmussen, V. P.

1977-01-01

Locating areas where soil moisture is limiting to crop growth is important for estimating winter-wheat yields on a regional basis. In the 1975-76 growing season, we evaluated soil-moisture conditions and winter-wheat yields for a five-state region of the Great Plains using Landsat estimates of leaf area index (LAI) and an evapotranspiration (ET) model described by Kanemasu et al (1977). Because LAI was used as an input, the ET model responded to changes in crop growth. Estimated soil-water depletions were high for the Nebraska Panhandle, southwestern Kansas, southeastern Colorado, and the Texas Panhandle. Estimated yields in five-state region ranged from 1.0 to 2.9 metric ton/ha.

Effect of blood pressure lowering on markers of kidney disease progression.

PubMed

Udani, Suneel M; Koyner, Jay L

2009-10-01

Hypertension remains a common comorbidity and cause of chronic kidney disease (CKD). As the number of patients with CKD grows, so does the need to identify modifiable risk factors for CKD progression. Data on slowing progression of CKD or preventing end-stage renal disease with aggressive blood pressure control have not yielded definitive conclusions regarding ideal blood pressure targets. Shifting the focus of antihypertensive therapy to alternative markers of end-organ damage, specifically proteinuria, has yielded some promise in preventing the progression of CKD. Nevertheless, proteinuria and decline in estimated GFR may represent an irreversible degree of injury to the kidney that limits the impact of any therapy. The identification and use of novel markers of kidney injury to assess the impact of antihyper-tensive therapy may yield clearer direction with regard to optimal management of hypertension in the setting of CKD.

Adapting the CROPGRO cotton model to simulate cotton biomass and yield under southern root-knot nematode parasitism

USDA-ARS?s Scientific Manuscript database

Cotton (Gossypium hirsutum L.) yield losses by southern root-knot nematode [Meloidogyne incognita (Kofoid & White) Chitwood] (RKN) are usually estimated after significant damage has been caused. However, estimation of potential yield reduction before planting is possible by using crop simulation mod...

19 CFR 151.65 - Duties.

Code of Federal Regulations, 2014 CFR

2014-04-01

...) EXAMINATION, SAMPLING, AND TESTING OF MERCHANDISE Wool and Hair § 151.65 Duties. Duties on wool or hair... determination of clean yield. Estimated and liquidated duties on wool or hair tested for clean yield pursuant to... appropriate adjustment of the estimated percentage clean yield shown on the entry summary for the wool or hair...

19 CFR 151.65 - Duties.

Code of Federal Regulations, 2010 CFR

2010-04-01

...) EXAMINATION, SAMPLING, AND TESTING OF MERCHANDISE Wool and Hair § 151.65 Duties. Duties on wool or hair... determination of clean yield. Estimated and liquidated duties on wool or hair tested for clean yield pursuant to... appropriate adjustment of the estimated percentage clean yield shown on the entry summary for the wool or hair...

19 CFR 151.65 - Duties.

Code of Federal Regulations, 2013 CFR

2013-04-01

...) EXAMINATION, SAMPLING, AND TESTING OF MERCHANDISE Wool and Hair § 151.65 Duties. Duties on wool or hair... determination of clean yield. Estimated and liquidated duties on wool or hair tested for clean yield pursuant to... appropriate adjustment of the estimated percentage clean yield shown on the entry summary for the wool or hair...

19 CFR 151.65 - Duties.

Code of Federal Regulations, 2012 CFR

2012-04-01

...) EXAMINATION, SAMPLING, AND TESTING OF MERCHANDISE Wool and Hair § 151.65 Duties. Duties on wool or hair... determination of clean yield. Estimated and liquidated duties on wool or hair tested for clean yield pursuant to... appropriate adjustment of the estimated percentage clean yield shown on the entry summary for the wool or hair...

19 CFR 151.65 - Duties.

Code of Federal Regulations, 2011 CFR

2011-04-01

...) EXAMINATION, SAMPLING, AND TESTING OF MERCHANDISE Wool and Hair § 151.65 Duties. Duties on wool or hair... determination of clean yield. Estimated and liquidated duties on wool or hair tested for clean yield pursuant to... appropriate adjustment of the estimated percentage clean yield shown on the entry summary for the wool or hair...

Relative efficiency of joint-model and full-conditional-specification multiple imputation when conditional models are compatible: The general location model.

PubMed

Seaman, Shaun R; Hughes, Rachael A

2018-06-01

Estimating the parameters of a regression model of interest is complicated by missing data on the variables in that model. Multiple imputation is commonly used to handle these missing data. Joint model multiple imputation and full-conditional specification multiple imputation are known to yield imputed data with the same asymptotic distribution when the conditional models of full-conditional specification are compatible with that joint model. We show that this asymptotic equivalence of imputation distributions does not imply that joint model multiple imputation and full-conditional specification multiple imputation will also yield asymptotically equally efficient inference about the parameters of the model of interest, nor that they will be equally robust to misspecification of the joint model. When the conditional models used by full-conditional specification multiple imputation are linear, logistic and multinomial regressions, these are compatible with a restricted general location joint model. We show that multiple imputation using the restricted general location joint model can be substantially more asymptotically efficient than full-conditional specification multiple imputation, but this typically requires very strong associations between variables. When associations are weaker, the efficiency gain is small. Moreover, full-conditional specification multiple imputation is shown to be potentially much more robust than joint model multiple imputation using the restricted general location model to mispecification of that model when there is substantial missingness in the outcome variable.

Evaluation of Thompson-type trend and monthly weather data models for corn yields in Iowa, Illinois, and Indiana

NASA Technical Reports Server (NTRS)

French, V. (Principal Investigator)

1982-01-01

An evaluation was made of Thompson-Type models which use trend terms (as a surrogate for technology), meteorological variables based on monthly average temperature, and total precipitation to forecast and estimate corn yields in Iowa, Illinois, and Indiana. Pooled and unpooled Thompson-type models were compared. Neither was found to be consistently superior to the other. Yield reliability indicators show that the models are of limited use for large area yield estimation. The models are objective and consistent with scientific knowledge. Timely yield forecasts and estimates can be made during the growing season by using normals or long range weather forecasts. The models are not costly to operate and are easy to use and understand. The model standard errors of prediction do not provide a useful current measure of modeled yield reliability.

Infrasound radiated by the Gerdec and Chelopechene explosions: propagation along unexpected paths

NASA Astrophysics Data System (ADS)

Green, David N.; Vergoz, Julien; Gibson, Robert; Le Pichon, Alexis; Ceranna, Lars

2011-05-01

Infrasound propagation paths through the atmosphere are controlled by the temporally and spatially varying sound speed and wind speed amplitudes. Because of the complexity of atmospheric acoustic propagation it is often difficult to reconcile observed infrasonic arrivals with the sound speed profiles predicted by meteorological specifications. This paper provides analyses of unexpected arrivals recorded in Europe and north Africa from two series of accidental munitions dump explosions, recorded at ranges greater than 1000 km: two explosions at Gerdec, Albania, on 2008 March 15 and four explosions at Chelopechene, Bulgaria, on 2008 July 3. The recorded signal characteristics include multiple pulsed arrivals, celerities between 0.24 and 0.34 km s-1 and some signal frequency content above 1 Hz. Often such characteristics are associated with waves that have propagated within a ground-to-stratosphere waveguide, although the observed celerities extend both above and below the conventional range for stratospheric arrivals. However, state-of-the-art meteorological specifications indicate that either weak, or no, ground-to-stratosphere waveguides are present along the source-to-receiver paths. By incorporating realistic gravity-wave induced horizontal velocity fluctuations into time-domain Parabolic Equation models the pulsed nature of the signals is simulated, and arrival times are predicted to within 30 s of the observed values (<1 per cent of the source-to-receiver transit time). Modelling amplitudes is highly dependent upon estimates of the unknown acoustic source strength (or equivalent chemical explosive yield). Current empirical explosive yield relationships, derived from infrasonic amplitude measurements from point-source chemical explosions, suggest that the equivalent chemical yield of the largest Gerdec explosion was of the order of 1 kt and the largest Chelopechene explosion was of the order of 100 t. When incorporating these assumed yields, the Parabolic Equation simulations predict peak signal amplitudes to within an order of magnitude of the observed values. As gravity wave velocity perturbations can significantly influence both infrasonic arrival times and signal amplitudes they need to be accounted for in source location and yield estimation routines, both of which are important for explosion monitoring, especially in the context of the Comprehensive Nuclear-Test-Ban Treaty.

A spectral-spatial-dynamic hierarchical Bayesian (SSD-HB) model for estimating soybean yield

NASA Astrophysics Data System (ADS)

Kazama, Yoriko; Kujirai, Toshihiro

2014-10-01

A method called a "spectral-spatial-dynamic hierarchical-Bayesian (SSD-HB) model," which can deal with many parameters (such as spectral and weather information all together) by reducing the occurrence of multicollinearity, is proposed. Experiments conducted on soybean yields in Brazil fields with a RapidEye satellite image indicate that the proposed SSD-HB model can predict soybean yield with a higher degree of accuracy than other estimation methods commonly used in remote-sensing applications. In the case of the SSD-HB model, the mean absolute error between estimated yield of the target area and actual yield is 0.28 t/ha, compared to 0.34 t/ha when conventional PLS regression was applied, showing the potential effectiveness of the proposed model.

Determination of the optimal level for combining area and yield estimates

NASA Technical Reports Server (NTRS)

Bauer, M. E. (Principal Investigator); Hixson, M. M.; Jobusch, C. D.

1981-01-01

Several levels of obtaining both area and yield estimates of corn and soybeans in Iowa were considered: county, refined strata, refined/split strata, crop reporting district, and state. Using the CCEA model form and smoothed weather data, regression coefficients at each level were derived to compute yield and its variance. Variances were also computed with stratum level. The variance of the yield estimates was largest at the state and smallest at the county level for both crops. The refined strata had somewhat larger variances than those associated with the refined/split strata and CRD. For production estimates, the difference in standard deviations among levels was not large for corn, but for soybeans the standard deviation at the state level was more than 50% greater than for the other levels. The refined strata had the smallest standard deviations. The county level was not considered in evaluation of production estimates due to lack of county area variances.

Total suspended solids concentrations and yields for water-quality monitoring stations in Gwinnett County, Georgia, 1996-2009

USGS Publications Warehouse

Landers, Mark N.

2013-01-01

The U.S. Geological Survey, in cooperation with the Gwinnett County Department of Water Resources, established a water-quality monitoring program during late 1996 to collect comprehensive, consistent, high-quality data for use by watershed managers. As of 2009, continuous streamflow and water-quality data as well as discrete water-quality samples were being collected for 14 watershed monitoring stations in Gwinnett County. This report provides statistical summaries of total suspended solids (TSS) concentrations for 730 stormflow and 710 base-flow water-quality samples collected between 1996 and 2009 for 14 watershed monitoring stations in Gwinnett County. Annual yields of TSS were estimated for each of the 14 watersheds using methods described in previous studies. TSS yield was estimated using linear, ordinary least-squares regression of TSS and explanatory variables of discharge, turbidity, season, date, and flow condition. The error of prediction for estimated yields ranged from 1 to 42 percent for the stations in this report; however, the actual overall uncertainty of the estimated yields cannot be less than that of the observed yields (± 15 to 20 percent). These watershed yields provide a basis for evaluation of how watershed characteristics, climate, and watershed management practices affect suspended sediment yield.

Application of an Optimal Tuner Selection Approach for On-Board Self-Tuning Engine Models

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Armstrong, Jeffrey B.; Garg, Sanjay

2012-01-01

An enhanced design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented in this paper. It specific-ally addresses the under-determined estimation problem, in which there are more unknown parameters than available sensor measurements. This work builds upon an existing technique for systematically selecting a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. While the existing technique was optimized for open-loop engine operation at a fixed design point, in this paper an alternative formulation is presented that enables the technique to be optimized for an engine operating under closed-loop control throughout the flight envelope. The theoretical Kalman filter mean squared estimation error at a steady-state closed-loop operating point is derived, and the tuner selection approach applied to minimize this error is discussed. A technique for constructing a globally optimal tuning parameter vector, which enables full-envelope application of the technology, is also presented, along with design steps for adjusting the dynamic response of the Kalman filter state estimates. Results from the application of the technique to linear and nonlinear aircraft engine simulations are presented and compared to the conventional approach of tuner selection. The new methodology is shown to yield a significant improvement in on-line Kalman filter estimation accuracy.

Estimates of general combining ability in Hevea breeding at the Rubber Research Institute of Malaysia : I. Phases II and III A.

PubMed

Tan, H

1977-01-01

Estimates of general combining ability of parents for yield and girth obtained separately from seedlings and their corresponding clonal families in Phases II and IIIA of the RRIM breeding programme are compared. A highly significant positive correlation (r = 0.71***) is found between GCA estimates from seedling and clonal families for yield in Phase IIIA, but not in Phase II (r = -0.03(NS)) nor for girth (r= -0.27(NS)) in Phase IIIA. The correlations for Phase II yield and Phase IIIA girth, however, improve when the GCA estimates based on small sample size or reversed rankings are excluded.When the best selections (based on present clonal and seedling information) are compared, all five of the parents top-ranking for yield are common in Phase IIIA but only two parents are common for yield and girth in Phases II and IIIA respectively. However, only one parent for yield in Phase II and two parents for girth in Phase IIIA would, if selected on clonal performance, have been omitted from the top ranking selections made by previous workers using seedling information.These findings, therefore, justify the choice of parents based on GCA estimates for yield obtained from seedling performance. Similar justification cannot be offered for girth, for which analysis is confounded by uninterpretable site and seasonal effects.

Species richness and occupancy estimation in communities subject to temporary emigration

USGS Publications Warehouse

Kery, M.; Royle, J. Andrew; Plattner, M.; Dorazio, R.M.

2009-01-01

Species richness is the most common biodiversity metric, although typically some species remain unobserved. Therefore, estimates of species richness and related quantities should account for imperfect detectability. Community dynamics can often be represented as superposition of species-specific phenologies (e. g., in taxa with well-defined flight [insects], activity [rodents], or vegetation periods [plants]). We develop a model for such predictably open communities wherein species richness is expressed as the sum over observed and unobserved species of estimated species-specific and site-specific occurrence indicators and where seasonal occurrence is modeled as a species-specific function of time. Our model is a multispecies extension of a multistate model with one unobservable state and represents a parsimonious way of dealing with a widespread form of 'temporary emigration.'' For illustration we use Swiss butterfly monitoring data collected under a robust design (RD); species were recorded on 13 transects during two secondary periods within <= 7 primary sampling periods. We compare estimates with those under a variation of the model applied to standard data, where secondary samples are pooled. The latter model yielded unrealistically high estimates of total community size of 274 species. In contrast, estimates were similar under models applied to RD data with constant (122) or seasonally varying (126) detectability for each species, but the former was more parsimonious and therefore used for inference. Per transect, 6 44 (mean 21.1) species were detected. Species richness estimates averaged 29.3; therefore only 71% (range 32-92%) of all species present were ever detected. In any primary period, 0.4-5.6 species present were overlooked. Detectability varied by species and averaged 0.88 per primary sampling period. Our modeling framework is extremely flexible; extensions such as covariates for the occurrence or detectability of individual species are easy. It should be useful for communities with a predictable form of temporary emigration where rigorous estimation of community metrics has proved challenging so far.

Spatial Distribution of Hydrologic Ecosystem Service Estimates: Comparing Two Models

NASA Astrophysics Data System (ADS)

Dennedy-Frank, P. J.; Ghile, Y.; Gorelick, S.; Logsdon, R. A.; Chaubey, I.; Ziv, G.

2014-12-01

We compare estimates of the spatial distribution of water quantity provided (annual water yield) from two ecohydrologic models: the widely-used Soil and Water Assessment Tool (SWAT) and the much simpler water models from the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) toolbox. These two models differ significantly in terms of complexity, timescale of operation, effort, and data required for calibration, and so are often used in different management contexts. We compare two study sites in the US: the Wildcat Creek Watershed (2083 km2) in Indiana, a largely agricultural watershed in a cold aseasonal climate, and the Upper Upatoi Creek Watershed (876 km2) in Georgia, a mostly forested watershed in a temperate aseasonal climate. We evaluate (1) quantitative estimates of water yield to explore how well each model represents this process, and (2) ranked estimates of water yield to indicate how useful the models are for management purposes where other social and financial factors may play significant roles. The SWAT and InVEST models provide very similar estimates of the water yield of individual subbasins in the Wildcat Creek Watershed (Pearson r = 0.92, slope = 0.89), and a similar ranking of the relative water yield of those subbasins (Spearman r = 0.86). However, the two models provide relatively different estimates of the water yield of individual subbasins in the Upper Upatoi Watershed (Pearson r = 0.25, slope = 0.14), and very different ranking of the relative water yield of those subbasins (Spearman r = -0.10). The Upper Upatoi watershed has a significant baseflow contribution due to its sandy, well-drained soils. InVEST's simple seasonality terms, which assume no change in storage over the time of the model run, may not accurately estimate water yield processes when baseflow provides such a strong contribution. Our results suggest that InVEST users take care in situations where storage changes are significant.

The grain drain. Ozone effects on historical maize and soybean yields

USDA-ARS?s Scientific Manuscript database

Numerous controlled experiments find that elevated ground-level ozone concentrations ([O3]) damage crops and reduce yield. There have been no estimates of the actual field yield losses in the USA from [O3], even though such estimates would be valuable for projections of future food production and fo...

Hydrogeologic framework and estimates of ground-water volumes in Tertiary and upper Cretaceous hydrogeologic units in the Powder River basin, Wyoming

USGS Publications Warehouse

Hinaman, Kurt

2005-01-01

The Powder River Basin in Wyoming and Montana is an important source of energy resources for the United States. Coalbed methane gas is contained in Tertiary and upper Cretaceous hydrogeologic units in the Powder River Basin. This gas is released when water pressure in coalbeds is lowered, usually by pumping ground water. Issues related to disposal and uses of by-product water from coalbed methane production have developed, in part, due to uncertainties in hydrologic properties. One hydrologic property of primary interest is the amount of water contained in Tertiary and upper Cretaceous hydrogeologic units in the Powder River Basin. The U.S. Geological Survey, in cooperation with the Bureau of Land Management, conducted a study to describe the hydrogeologic framework and to estimate ground-water volumes in different facies of Tertiary and upper Cretaceous hydrogeologic units in the Powder River Basin in Wyoming. A geographic information system was used to compile and utilize hydrogeologic maps, to describe the hydrogeologic framework, and to estimate the volume of ground water in Tertiary and upper Cretaceous hydrogeologic units in the Powder River structural basin in Wyoming. Maps of the altitudes of potentiometric surfaces, altitudes of the tops and bottoms of hydrogeologic units, thicknesses of hydrogeologic units, percent sand of hydrogeologic units, and outcrop boundaries for the following hydrogeologic units were used: Tongue River-Wasatch aquifer, Lebo confining unit, Tullock aquifer, Upper Hell Creek confining unit, and the Fox Hills-Lower Hell Creek aquifer. Literature porosity values of 30 percent for sand and 35 percent for non-sand facies were used to calculate the volume of total ground water in each hydrogeologic unit. Literature specific yield values of 26 percent for sand and 10 percent for non-sand facies, and literature specific storage values of 0.0001 ft-1 (1/foot) for sand facies and 0.00001 ft-1 for non-sand facies, were used to calculate a second volume of ground water for each hydrogeologic unit. Significant figure considerations limited estimates of ground-water volumes to two significant digits. A total ground-water volume of 2.0x1014 ft3 (cubic feet) was calculated using porosity values, and a total ground-water volume of 3.6x1013 ft3 was calculated using specific yield and specific storage values. These results are consistent with retention properties, which would have some of the total water being retained in the sediments. Sensitivity analysis shows that the estimates of ground-water volume are most sensitive to porosity. The estimates also are sensitive to confined thickness and saturated thickness. Better spatial information for hydrogeologic units could help refine the ground-water volume estimates.

Closing Yield Gaps: How Sustainable Can We Be?

PubMed

Pradhan, Prajal; Fischer, Günther; van Velthuizen, Harrij; Reusser, Dominik E; Kropp, Juergen P

2015-01-01

Global food production needs to be increased by 60-110% between 2005 and 2050 to meet growing food and feed demand. Intensification and/or expansion of agriculture are the two main options available to meet the growing crop demands. Land conversion to expand cultivated land increases GHG emissions and impacts biodiversity and ecosystem services. Closing yield gaps to attain potential yields may be a viable option to increase the global crop production. Traditional methods of agricultural intensification often have negative externalities. Therefore, there is a need to explore location-specific methods of sustainable agricultural intensification. We identified regions where the achievement of potential crop calorie production on currently cultivated land will meet the present and future food demand based on scenario analyses considering population growth and changes in dietary habits. By closing yield gaps in the current irrigated and rain-fed cultivated land, about 24% and 80% more crop calories can respectively be produced compared to 2000. Most countries will reach food self-sufficiency or improve their current food self-sufficiency levels if potential crop production levels are achieved. As a novel approach, we defined specific input and agricultural management strategies required to achieve the potential production by overcoming biophysical and socioeconomic constraints causing yield gaps. The management strategies include: fertilizers, pesticides, advanced soil management, land improvement, management strategies coping with weather induced yield variability, and improving market accessibility. Finally, we estimated the required fertilizers (N, P2O5, and K2O) to attain the potential yields. Globally, N-fertilizer application needs to increase by 45-73%, P2O5-fertilizer by 22-46%, and K2O-fertilizer by 2-3 times compared to the year 2010 to attain potential crop production. The sustainability of such agricultural intensification largely depends on the way management strategies for closing yield gaps are chosen and implemented.

Closing Yield Gaps: How Sustainable Can We Be?

PubMed Central

Pradhan, Prajal; Fischer, Günther; van Velthuizen, Harrij; Reusser, Dominik E.; Kropp, Juergen P.

2015-01-01

Global food production needs to be increased by 60–110% between 2005 and 2050 to meet growing food and feed demand. Intensification and/or expansion of agriculture are the two main options available to meet the growing crop demands. Land conversion to expand cultivated land increases GHG emissions and impacts biodiversity and ecosystem services. Closing yield gaps to attain potential yields may be a viable option to increase the global crop production. Traditional methods of agricultural intensification often have negative externalities. Therefore, there is a need to explore location-specific methods of sustainable agricultural intensification. We identified regions where the achievement of potential crop calorie production on currently cultivated land will meet the present and future food demand based on scenario analyses considering population growth and changes in dietary habits. By closing yield gaps in the current irrigated and rain-fed cultivated land, about 24% and 80% more crop calories can respectively be produced compared to 2000. Most countries will reach food self-sufficiency or improve their current food self-sufficiency levels if potential crop production levels are achieved. As a novel approach, we defined specific input and agricultural management strategies required to achieve the potential production by overcoming biophysical and socioeconomic constraints causing yield gaps. The management strategies include: fertilizers, pesticides, advanced soil management, land improvement, management strategies coping with weather induced yield variability, and improving market accessibility. Finally, we estimated the required fertilizers (N, P2O5, and K2O) to attain the potential yields. Globally, N-fertilizer application needs to increase by 45–73%, P2O5-fertilizer by 22–46%, and K2O-fertilizer by 2–3 times compared to the year 2010 to attain potential crop production. The sustainability of such agricultural intensification largely depends on the way management strategies for closing yield gaps are chosen and implemented. PMID:26083456

Yield Estimation for Semipalatinsk Underground Nuclear Explosions Using Seismic Surface-wave Observations at Near-regional Distances

NASA Astrophysics Data System (ADS)

Adushkin, V. V.

- A statistical procedure is described for estimating the yields of underground nuclear tests at the former Soviet Semipalatinsk test site using the peak amplitudes of short-period surface waves observed at near-regional distances (Δ < 150 km) from these explosions. This methodology is then applied to data recorded from a large sample of the Semipalatinsk explosions, including the Soviet JVE explosion of September 14, 1988, and it is demonstrated that it provides seismic estimates of explosion yield which are typically within 20% of the yields determined for these same explosions using more accurate, non-seismic techniques based on near-source observations.

Increasing influence of heat stress on French maize yields from the 1960s to the 2030s

PubMed Central

Hawkins, Ed; Fricker, Thomas E; Challinor, Andrew J; Ferro, Christopher A T; Kit Ho, Chun; Osborne, Tom M

2013-01-01

Improved crop yield forecasts could enable more effective adaptation to climate variability and change. Here, we explore how to combine historical observations of crop yields and weather with climate model simulations to produce crop yield projections for decision relevant timescales. Firstly, the effects on historical crop yields of improved technology, precipitation and daily maximum temperatures are modelled empirically, accounting for a nonlinear technology trend and interactions between temperature and precipitation, and applied specifically for a case study of maize in France. The relative importance of precipitation variability for maize yields in France has decreased significantly since the 1960s, likely due to increased irrigation. In addition, heat stress is found to be as important for yield as precipitation since around 2000. A significant reduction in maize yield is found for each day with a maximum temperature above 32 °C, in broad agreement with previous estimates. The recent increase in such hot days has likely contributed to the observed yield stagnation. Furthermore, a general method for producing near-term crop yield projections, based on climate model simulations, is developed and utilized. We use projections of future daily maximum temperatures to assess the likely change in yields due to variations in climate. Importantly, we calibrate the climate model projections using observed data to ensure both reliable temperature mean and daily variability characteristics, and demonstrate that these methods work using retrospective predictions. We conclude that, to offset the projected increased daily maximum temperatures over France, improved technology will need to increase base level yields by 12% to be confident about maintaining current levels of yield for the period 2016–2035; the current rate of yield technology increase is not sufficient to meet this target. PMID:23504849

Streamflow, Water Quality, and Constituent Loads and Yields, Scituate Reservoir Drainage Area, Rhode Island,Water Year 2002

USGS Publications Warehouse

Breault, Robert F.

2009-01-01

Streamflow and water-quality data were collected by the U.S. Geological Survey (USGS) or the Providence Water Supply Board, Rhode Island's largest drinking-water supplier. Streamflow was measured or estimated by the USGS following standard methods at 23 streamflow-gaging stations; 10 of these stations were also equipped with instrumentation capable of continuously monitoring specific conductance. Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate instantaneous (15-minute) loads of sodium and chloride during water year (WY) 2002 (October 1, 2001 to September 30, 2002). Water-quality samples were also collected at 35 of 37 sampling stations in the Scituate Reservoir drainage area by the Providence Water Supply Board during WY 2002 as part of a long-term sampling program. Water-quality data are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2002. The largest tributary to the reservoir (the Ponaganset River, which was monitored by the USGS) contributed about 12.6 cubic feet per second (ft3/s) to the reservoir during WY 2002. For the same time period, annual mean streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.14 to 8.1 ft3/s. Together, tributary streams (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 534,000 kilograms (kg) of sodium and 851,000 kg of chloride to the Scituate Reservoir during WY 2002; sodium and chloride yields for the tributaries ranged from 2,900 to 40,200 kilograms per square mile (kg/mi2) and from 4,200 to 68,200 kg/mi2, respectively. At the stations where water-quality samples were collected by the Providence Water Supply Board, the median of the median chloride concentrations was 16.8 milligrams per liter (mg/L), median nitrate concentration was 0.02 mg/L as N, median nitrite concentration was 0.002 mg/L as N, median orthophosphate concentration was 0.03 mg/L as P, and median concentrations of total coliform and Escherichia coli (E. coli) bacteria were 22 and 14 colony forming units per 100 milliliters (CFU/100 mL), respectively. The medians of the median daily loads (and yields) of chloride, nitrate, nitrite, orthophosphate and total coliform and E. coli bacteria were 21 kg/d (12 kg/d/mi2), 0.04 kg/d (0.014 kg/d/mi2), 0.005 kg/d (0.002 kg/d/mi2), 0.08 kg/d (0.035 kg/d/mi2), and 370 million colony forming units per day (CFUx106/d) (120 CFUx106/d/ mi2) and 300 CFUx106/d (75 CFUx106/d/mi2), respectively.

Streamflow, Water Quality, and Constituent Loads and Yields, Scituate Reservoir Drainage Area, Rhode Island, Water Year 2006

USGS Publications Warehouse

Breault, Robert F.; Campbell, Jean P.

2010-01-01

Streamflow and water-quality data were collected by the U.S. Geological Survey (USGS) or the Providence Water Supply Board, Rhode Island's largest drinking-water supplier. Streamflow was measured or estimated by the USGS following standard methods at 23 streamgage stations; 10 of these stations were also equipped with instrumentation capable of continuously monitoring specific conductance. Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate instantaneous (15-minute) loads of sodium and chloride during water year (WY) 2006 (October 1, 2005, to September 30, 2006). Water-quality samples were also collected at 37 sampling stations in the Scituate Reservoir drainage area by the Providence Water Supply Board during WY 2006 as part of a long-term sampling program. Water-quality data are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2006. The largest tributary to the reservoir (the Ponaganset River, which was monitored by the USGS) contributed about 42 cubic feet per second (ft3/s) to the reservoir during WY 2006. For the same time period, annual mean streamflows1 measured (or estimated) for the other monitoring stations in this study ranged from about 0.60 to 26 ft3/s. Together, tributary streams (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 1,600,000 kilograms (kg) of sodium and 2,500,000 kg of chloride to the Scituate Reservoir during WY 2006; sodium and chloride yields for the tributaries ranged from 15,000 to 100,000 kilograms per square mile (kg/mi2) and from 22,000 to 180,000 kg/mi2, respectively. At the stations where water-quality samples were collected by the Providence Water Supply Board, the median of the median chloride concentrations was 24.6 milligrams per liter (mg/L), median nitrite concentration was 0.001 mg/L as N, median nitrate concentration was 0.02 mg/L as N, median orthophosphate concentration was 0.07 mg/L as P, and median concentrations of total coliform and Escherichia coli (E. coli) bacteria were 43 and 23 colony forming units per 100 milliliters (CFU/100 mL), respectively. The medians of the median daily loads (and yields) of chloride, nitrite, nitrate, orthophosphate, and total coliform and E. coli bacteria were 230 kg/d (81 kg/d/mi2), 17 g/d (4.4 g/d/mi2), 130 g/d (50 g/d/mi2), 470 g/d (210 g/d/mi2), and 2,100 million colony forming units per day (CFU?106/d) (1,300 CFU?106/d/mi2) and 670 CFU?106/d (420 CFU?106/d/mi2), respectively. 1The arithmetic mean of the individual daily mean discharges for the year noted or for the designated period.

Streamflow, Water Quality, and Constituent Loads and Yields, Scituate Reservoir Drainage Area, Rhode Island, Water Year 2005

USGS Publications Warehouse

Breault, Robert F.; Campbell, Jean P.

2010-01-01

Streamflow and water-quality data were collected by the U.S. Geological Survey (USGS) or the Providence Water Supply Board, Rhode Island’s largest drinking-water supplier. Streamflow was measured or estimated by the USGS following standard methods at 23 streamgage stations; 10 of these stations were also equipped with instrumentation capable of continuously monitoring specific conductance. Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate instantaneous (15-minute) loads of sodium and chloride during water year (WY) 2005 (October 1, 2004, to September 30, 2005). Water-quality samples were also collected at 37 sampling stations in the Scituate Reservoir drainage area by the Providence Water Supply Board during WY 2005 as part of a long-term sampling program. Water-quality data are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2005. The largest tributary to the reservoir (the Ponaganset River, which was monitored by the USGS) contributed about 30 cubic feet per second (ft3/s) to the reservoir during WY 2005. For the same time period, annual mean streamflows1 measured (or estimated) for the other monitoring stations in this study ranged from about 0.42 to 19 ft3/s. Together, tributary streams (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 1,300,000 kilograms (kg) of sodium and 2,000,000 kg of chloride to the Scituate Reservoir during WY 2005; sodium and chloride yields for the tributaries ranged from 13,000 to 77,000 kilograms per square mile (kg/mi2) and from 19,000 to 130,000 kg/mi2, respectively. At the stations where water-quality samples were collected by the Providence Water Supply Board, the median of the median chloride concentrations was 25.3 milligrams per liter (mg/L), median nitrite concentration was 0.002 mg/L as N, median nitrate concentration was 0.02 mg/L as N, median orthophosphate concentration was 0.07 mg/L as P, and median concentrations of total coliform and Escherichia coli (E. coli) bacteria were 23 and 15 colony forming units per 100 milliliters (CFU/100 mL), respectively. The medians of the median daily loads (and yields) of chloride, nitrite, nitrate, orthophosphate, and total coliform and E. coli bacteria were 230 kg/d (93 kg/d/mi2), 16 g/d (6.1 g/d/mi2), 150 g/d (71 g/d/mi2), 530 g/d (250 g/d/mi2), and 1,500 million colony forming units per day (CFU×106/d) (630 CFU×106/d/mi2) and 420 CFU×106/d (290 CFU×106/d/mi2), respectively. 1The arithmetic mean of the individual daily mean discharges for the year noted or for the designated period.

Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2010

USGS Publications Warehouse

Smith, Kirk P.; Breault, Robert F.

2011-01-01

Streamflow and water-quality data were collected by the U.S. Geological Survey (USGS) or the Providence Water Supply Board (PWSB), Rhode Island's largest drinking-water supplier. Streamflow was measured or estimated by the USGS following standard methods at 23 streamgages; 14 of these stations were also equipped with instrumentation capable of continuously monitoring specific conductance and water temperature. Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate loads of sodium and chloride during water year (WY) 2010 (October 1, 2009, to September 30, 2010). Water-quality samples also were collected at 37 sampling stations by the PWSB and at 14 monitoring stations by the USGS during WY 2010 as part of a long sampling program; all stations are in the Scituate Reservoir drainage area. Waterquality data collected by PWSB are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2010. The largest tributary to the reservoir (the Ponaganset River, which was monitored by the USGS) contributed a mean streamflow of about 39 cubic feet per second (ft3/s) to the reservoir during WY 2010. For the same time period, annual mean streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.7 to 27 ft3/s. Together, tributary streams (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 1,500,000 kilograms (kg) of sodium and 2,500,000 kg of chloride to the Scituate Reservoir during WY 2010; sodium and chloride yields for the tributaries ranged from 11,000 to 66,000 kilograms per square mile (kg/mi2) and from 18,000 to 110,000 kg/mi2, respectively. At the stations where water-quality samples were collected by the PWSB, the median of the median chloride concentrations was 20.2 milligrams per liter (mg/L), median nitrite concentration was 0.002 mg/L as nitrogen (N), median nitrate concentration was 0.01 mg/L as N, median orthophosphate concentration was 0.06 mg/L as phosphorus, and median concentrations of total coliform and Escherichia coli (E. coli) bacteria were 93 and 16 colony forming units per 100 milliliters (CFU/100mL), respectively. The medians of the median daily loads (and yields) of chloride, nitrite, nitrate, orthophosphate, and total coliform and E. coli bacteria were 170 kg/d (73 kg/d/mi2), 11 g/d (5.3 g/d/mi2), 74 g/d (39 g/d/mi2), 340 g/d (170 g/d/mi2), 5,700 million colony forming units per day (CFUx106/d) (2,300 CFUx106/d/mi2), and 620 CFUx106/d (440 CFUx106/d/mi2), respectively.

Sediment yield estimation in mountain catchments of the Camastra reservoir, southern Italy: a comparison among different empirical methods

NASA Astrophysics Data System (ADS)

Lazzari, Maurizio; Danese, Maria; Gioia, Dario; Piccarreta, Marco

2013-04-01

Sedimentary budget estimation is an important topic for both scientific and social community, because it is crucial to understand both dynamics of orogenic belts and many practical problems, such as soil conservation and sediment accumulation in reservoir. Estimations of sediment yield or denudation rates in southern-central Italy are generally obtained by simple empirical relationships based on statistical regression between geomorphic parameters of the drainage network and the measured suspended sediment yield at the outlet of several drainage basins or through the use of models based on sediment delivery ratio or on soil loss equations. In this work, we perform a study of catchment dynamics and an estimation of sedimentary yield for several mountain catchments of the central-western sector of the Basilicata region, southern Italy. Sediment yield estimation has been obtained through both an indirect estimation of suspended sediment yield based on the Tu index (mean annual suspension sediment yield, Ciccacci et al., 1980) and the application of the Rusle (Renard et al., 1997) and the USPED (Mitasova et al., 1996) empirical methods. The preliminary results indicate a reliable difference between the RUSLE and USPED methods and the estimation based on the Tu index; a critical data analysis of results has been carried out considering also the present-day spatial distribution of erosion, transport and depositional processes in relation to the maps obtained from the application of those different empirical methods. The studied catchments drain an artificial reservoir (i.e. the Camastra dam), where a detailed evaluation of the amount of historical sediment storage has been collected. Sediment yield estimation obtained by means of the empirical methods have been compared and checked with historical data of sediment accumulation measured in the artificial reservoir of the Camastra dam. The validation of such estimations of sediment yield at the scale of large catchments using sediment storage in reservoirs provides a good opportunity: i) to test the reliability of the empirical methods used to estimate the sediment yield; ii) to investigate the catchment dynamics and its spatial and temporal evolution in terms of erosion, transport and deposition. References Ciccacci S., Fredi F., Lupia Palmieri E., Pugliese F., 1980. Contributo dell'analisi geomorfica quantitativa alla valutazione dell'entita dell'erosione nei bacini fluviali. Bollettino della Società Geologica Italiana 99: 455-516. Mitasova H, Hofierka J, Zlocha M, Iverson LR. 1996. Modeling topographic potential for erosion and deposition using GIS. International Journal of Geographical Information Systems 10: 629-641. Renard K.G., Foster G.R., Weesies G.A., McCool D.K., Yoder D.C., 1997. Predicting soil erosion by water: a guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE), USDA-ARS, Agricultural Handbook No. 703.

Prediction of industrial tomato hybrids from agronomic traits and ISSR molecular markers.

PubMed

Figueiredo, A S T; Resende, J T V; Faria, M V; Da-Silva, P R; Fagundes, B S; Morales, R G F

2016-05-13

Heterosis is a highly relevant phenomenon in plant breeding. This condition is usually established in hybrids derived from crosses of highly divergent parents. The success of a breeder in obtaining heterosis is directly related to the correct identification of genetically contrasting parents. Currently, the diallel cross is the most commonly used methodology to detect contrasting parents; however, it is a time- and cost-consuming procedure. Therefore, new tools capable of performing this task quickly and accurately are required. Thus, the purpose of this study was to estimate the genetic divergence in industrial tomato lines, based on agronomic traits, and to compare with estimates obtained using inter-simple sequence repeat (ISSR) molecular markers. The genetic divergence among 10 industrial tomato lines, based on nine morphological characters and 12 ISSR primers was analyzed. For data analysis, Pearson and Spearman correlation coefficients were calculated between the genetic dissimilarity measures estimated by Mahalanobis distance and Jaccard's coefficient of genetic dissimilarity from the heterosis estimates, combining ability, and means of important traits of industrial tomato. The ISSR markers efficiently detected contrasting parents for hybrid production in tomato. Parent RVTD-08 was indicated as the most divergent, both by molecular and morphological markers, that positively contributed to increased heterosis and by the specific combining ability in the crosses in which it participated. The genetic dissimilarity estimated by ISSR molecular markers aided the identification of the best hybrids of the experiment in terms of total fruit yield, pulp yield, and soluble solids content.

Estimating Elevation Angles From SAR Crosstalk

NASA Technical Reports Server (NTRS)

Freeman, Anthony

1994-01-01

Scheme for processing polarimetric synthetic-aperture-radar (SAR) image data yields estimates of elevation angles along radar beam to target resolution cells. By use of estimated elevation angles, measured distances along radar beam to targets (slant ranges), and measured altitude of aircraft carrying SAR equipment, one can estimate height of target terrain in each resolution cell. Monopulselike scheme yields low-resolution topographical data.

Climate change impacts on crop yield: evidence from China.

PubMed

Wei, Taoyuan; Cherry, Todd L; Glomrød, Solveig; Zhang, Tianyi

2014-11-15

When estimating climate change impact on crop yield, a typical assumption is constant elasticity of yield with respect to a climate variable even though the elasticity may be inconstant. After estimating both constant and inconstant elasticities with respect to temperature and precipitation based on provincial panel data in China 1980-2008, our results show that during that period, the temperature change contributes positively to total yield growth by 1.3% and 0.4% for wheat and rice, respectively, but negatively by 12% for maize. The impacts of precipitation change are marginal. We also compare our estimates with other studies and highlight the implications of the inconstant elasticities for crop yield, harvest and food security. We conclude that climate change impact on crop yield would not be an issue in China if positive impacts of other socio-economic factors continue in the future. Copyright © 2014 Elsevier B.V. All rights reserved.

Adaptation of an articulated fetal skeleton model to three-dimensional fetal image data

NASA Astrophysics Data System (ADS)

Klinder, Tobias; Wendland, Hannes; Wachter-Stehle, Irina; Roundhill, David; Lorenz, Cristian

2015-03-01

The automatic interpretation of three-dimensional fetal images poses specific challenges compared to other three-dimensional diagnostic data, especially since the orientation of the fetus in the uterus and the position of the extremities is highly variable. In this paper, we present a comprehensive articulated model of the fetal skeleton and the adaptation of the articulation for pose estimation in three-dimensional fetal images. The model is composed out of rigid bodies where the articulations are represented as rigid body transformations. Given a set of target landmarks, the model constellation can be estimated by optimization of the pose parameters. Experiments are carried out on 3D fetal MRI data yielding an average error per case of 12.03+/-3.36 mm between target and estimated landmark positions.

Application of wheat yield model to United States and India. [Great Plains

NASA Technical Reports Server (NTRS)

Feyerherm, A. M. (Principal Investigator)

1977-01-01

The author has identified the following significant results. The wheat yield model was applied to the major wheat-growing areas of the US and India. In the US Great Plains, estimates from the winter and spring wheat models agreed closely with USDA-SRS values in years with the lowest yields, but underestimated in years with the highest yields. Application to the Eastern Plains and Northwest indicated the importance of cultural factors, as well as meteorological ones in the model. It also demonstrated that the model could be used, in conjunction with USDA-SRRS estimates, to estimate yield losses due to factors not included in the model, particularly diseases and freezes. A fixed crop calendar for India was built from a limited amount of available plot data from that country. Application of the yield model gave measurable evidence that yield variation from state to state was due to different mixes of levels of meteorological and cultural factors.

Application guide for AFINCH (Analysis of Flows in Networks of Channels) described by NHDPlus

USGS Publications Warehouse

Holtschlag, David J.

2009-01-01

AFINCH (Analysis of Flows in Networks of CHannels) is a computer application that can be used to generate a time series of monthly flows at stream segments (flowlines) and water yields for catchments defined in the National Hydrography Dataset Plus (NHDPlus) value-added attribute system. AFINCH provides a basis for integrating monthly flow data from streamgages, water-use data, monthly climatic data, and land-cover characteristics to estimate natural monthly water yields from catchments by user-defined regression equations. Images of monthly water yields for active streamgages are generated in AFINCH and provide a basis for detecting anomalies in water yields, which may be associated with undocumented flow diversions or augmentations. Water yields are multiplied by the drainage areas of the corresponding catchments to estimate monthly flows. Flows from catchments are accumulated downstream through the streamflow network described by the stream segments. For stream segments where streamgages are active, ratios of measured to accumulated flows are computed. These ratios are applied to upstream water yields to proportionally adjust estimated flows to match measured flows. Flow is conserved through the NHDPlus network. A time series of monthly flows can be generated for stream segments that average about 1-mile long, or monthly water yields from catchments that average about 1 square mile. Estimated monthly flows can be displayed within AFINCH, examined for nonstationarity, and tested for monotonic trends. Monthly flows also can be used to estimate flow-duration characteristics at stream segments. AFINCH generates output files of monthly flows and water yields that are compatible with ArcMap, a geographical information system analysis and display environment. Chloropleth maps of monthly water yield and flow can be generated and analyzed within ArcMap by joining NHDPlus data structures with AFINCH output. Matlab code for the AFINCH application is presented.

Comparison of DSM-IV-TR and DSM-5 Criteria in Diagnosing Autism Spectrum Disorders in Singapore.

PubMed

Sung, Min; Goh, Tze Jui; Tan, Bei Lin Joelene; Chan, Jialei Stephanie; Liew, Hwee Sen Alvin

2018-04-28

Our study examines the Diagnostic and Statistical Manual-Fifth Edition (DSM-5) and Diagnostic and Statistical Manual-Fourth Edition, Text Revision (DSM-IV-TR) when applied concurrently against the best estimate clinical diagnoses for 110 children (5.1-19.6 years old) referred for diagnostic assessments of Autism Spectrum Disorder (ASD) in a Singaporean outpatient speciality clinic. DSM-IV-TR performed slightly better, yielding sensitivity of 0.946 and specificity of 0.889, compared to DSM-5 (sensitivity = 0.837; specificity = 0.833). When considering the ASD sub-categories, sensitivity ranged from 0.667 to 0.933, and specificity ranged from 0.900 to 0.975. More participants with a PDD-NOS best estimate clinical diagnosis (40%) were misclassified on DSM-5. Merits and weaknesses to both classification systems, and implications for access to services and policy changes are discussed.

Simulation of groundwater flow and streamflow depletion in the Branch Brook, Merriland River, and parts of the Mousam River watersheds in southern Maine

USGS Publications Warehouse

Nielsen, Martha G.; Locke, Daniel B.

2015-01-01

The study evaluated two different methods of calculating in-stream flow requirements for Branch Brook and the Merriland River—a set of statewide equations used to calculate monthly median flows and the MOVE.1 record-extension technique used on site-specific streamflow measurements. The August median in-stream flow requirement in the Merriland River was calculated as 7.18 ft3/s using the statewide equations but was 3.07 ft3/s using the MOVE.1 analysis. In Branch Brook, the August median in-stream flow requirements were calculated as 20.3 ft3/s using the statewide equations and 11.8 ft3/s using the MOVE.1 analysis. In each case, using site-specific data yields an estimate of in-stream flow that is much lower than an estimate the statewide equations provide.

Mean glandular dose to patients from stereotactic breast biopsy procedures.

PubMed

Paixão, Lucas; Chevalier, Margarita; Hurtado-Romero, Antonio E; Garayoa, Julia

2018-06-07

The aim of this work is to study the radiation doses delivered to a group of patients that underwent a stereotactic breast biopsy (SBB) procedure. Mean glandular doses (MGD) were estimated from the air-kerma measured at the breast surface entrance multiplying by specific conversion coefficients (DgN) that were estimated using Monte Carlo simulations. DgN were calculated for the 0º and ±15º projections used in SBB and for the particular beam quality. Data on 61 patients were collected showing that a typical SBB procedure is composed by 10 images. MGD was on average (4 ± 2) mGy with (0.38 ± 0.06) mGy per image. The use of specific conversion coefficients instead of typical DgN for mammography/tomosynthesis yields to obtain MGD values for SBB that are around a 65% lower on average. © 2018 Institute of Physics and Engineering in Medicine.

Optimal Tuner Selection for Kalman Filter-Based Aircraft Engine Performance Estimation

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Garg, Sanjay

2010-01-01

A linear point design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. This paper derives theoretical Kalman filter estimation error bias and variance values at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the conventional approach of tuner selection. Experimental simulation results are found to be in agreement with theoretical predictions. The new methodology is shown to yield a significant improvement in on-line engine performance estimation accuracy

A Hybrid of Optical Remote Sensing and Hydrological Modeling Improves Water Balance Estimation

NASA Astrophysics Data System (ADS)

Gleason, Colin J.; Wada, Yoshihide; Wang, Jida

2018-01-01

Declining gauging infrastructure and fractious water politics have decreased available information about river flows globally. Remote sensing and water balance modeling are frequently cited as potential solutions, but these techniques largely rely on these same in-decline gauge data to make accurate discharge estimates. A different approach is therefore needed, and we here combine remotely sensed discharge estimates made via at-many-stations hydraulic geometry (AMHG) and the PCR-GLOBWB hydrological model to estimate discharge over the Lower Nile. Specifically, we first estimate initial discharges from 87 Landsat images and AMHG (1984-2015), and then use these flow estimates to tune the model, all without using gauge data. The resulting tuned modeled hydrograph shows a large improvement in flow magnitude: validation of the tuned monthly hydrograph against a historical gauge (1978-1984) yields an RMSE of 439 m3/s (40.8%). By contrast, the original simulation had an order-of-magnitude flow error. This improvement is substantial but not perfect: tuned flows have a 1-2 month wet season lag and a negative base flow bias. Accounting for this 2 month lag yields a hydrograph RMSE of 270 m3/s (25.7%). Thus, our results coupling physical models and remote sensing is a promising first step and proof of concept toward future modeling of ungauged flows, especially as developments in cloud computing for remote sensing make our method easily applicable to any basin. Finally, we purposefully do not offer prescriptive solutions for Nile management, and rather hope that the methods demonstrated herein can prove useful to river stakeholders in managing their own water.

A Priori Estimation of Organic Reaction Yields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Emami, Fateme S.; Vahid, Amir; Wylie, Elizabeth K.

2015-07-21

A thermodynamically guided calculation of free energies of substrate and product molecules allows for the estimation of the yields of organic reactions. The non-ideality of the system and the solvent effects are taken into account through the activity coefficients calculated at the molecular level by perturbed-chain statistical associating fluid theory (PC-SAFT). The model is iteratively trained using a diverse set of reactions with yields that have been reported previously. This trained model can then estimate a priori the yields of reactions not included in the training set with an accuracy of ca. ±15 %. This ability has the potential tomore » translate into significant economic savings through the selection and then execution of only those reactions that can proceed in good yields.« less

An alternative approach to estimating rainfall rate by radar using propagation differential phase shift

NASA Technical Reports Server (NTRS)

Jameson, A. R.

1994-01-01

In this work it is shown that for frequencies from 3 to 13 GHz, the ratio of the specific propagation differential phase shift phi(sub DP) to the rainfall rate can be specified essentially independently of the form of the drop size distribution by a function only of the mass-weighted mean drop size D(sub m). This significantly reduces one source of substantial bias errors common to most other techniques for measuring rain by radar. For frequencies 9 GHz and greater, the coefficient can be well estimated from the ratio of the specific differential attenuation to phi(sub DP), while at nonattenuating frequencies such as 3 GHz, the coefficient can be well estimated using the differential reflectivity. In practice it appears that this approach yields better estimates of the rainfall rate than any other current technique. The best results are most likely at 13.80 GHz, followed by those at 2.80 GHz. An optimum radar system for measuring rain should probably include components at a both frequencies so that when signals at 13.8 GHz are lost because of attenuation, good measurements are still possible at the lower frequency.

Capacity of Lemna gibba L. (duckweed) for uranium and arsenic phytoremediation in mine tailing waters.

PubMed

Mkandawire, Martin; Taubert, Barbara; Dudel, E Gert

2004-01-01

The potential of Lemna gibba L. to clean uranium and arsenic contamination from mine surface waters was investigated in wetlands of two former uranium mines in eastern Germany and in laboratory hydroponic culture. Water and plants were sampled and L gibba growth and yield were monitored in tailing ponds from the field study sites. Contaminant accumulation, growth and yield experiments were conducted in the laboratory using synthetic tailing water. Mean background concentrations of the surface waters were 186.0+/-81.2 microg l(-1) uranium and 47.0+/-21.3 microg l(-1) arsenic in Site one and 293.7+/-121.3 microg l(-1) uranium and 41.37+/-24.7 microg l(-1) arsenic in Site two. The initial concentration of both uranium and arsenic in the culture solutions was 100 microg l(-1). The plant samples were either not leached, leached with deionized H2O or ethylenediaminetetracetic (EDTA). The results revealed high bioaccumulation coefficients for both uranium and arsenic. Uranium and arsenic content of L gibba dry biomass of the field samples were as follows: nonleached samples > deionized H2O leached (insignificant ANOVA p = 0.05) > EDTA leached. The difference in both arsenic and uranium enrichment were significantly high between the nonleached and the other two lead samples tested at ANOVA p > 0.001. Estimated mean L gibba density in surface water was 85,344.8+/-1843.4 fronds m(-2) (approximately 1319.7 g m(-2)). The maximum specific growth rate was 0.47+/-0.2 d(-1), which exceeded reported specific growth rates for L gibba in the literature. Average yield was estimated at 20.2+/-6.7 g m(-2) d(-1), giving approximately 73.6+/-21.4 t ha(-1) y(-1) as the annual yield. The highest accumulations observed were 896.9+/-203.8 mg kg(-1) uranium and 1021.7+/-250.8 mg kg(-1) arsenic dry biomass for a 21-d test period in the laboratory steady-state experiments. The potential extractions from surface waters with L gibba L. were estimated to be 662.7 kg uranium ha(-1) yr(-1) and 751.9 kg arsenic ha(-1) yr(-1) under the above conditions.

Quantifying components of the hydrologic cycle in Virginia using chemical hydrograph separation and multiple regression analysis

USGS Publications Warehouse

Sanford, Ward E.; Nelms, David L.; Pope, Jason P.; Selnick, David L.

2012-01-01

This study by the U.S. Geological Survey, prepared in cooperation with the Virginia Department of Environmental Quality, quantifies the components of the hydrologic cycle across the Commonwealth of Virginia. Long-term, mean fluxes were calculated for precipitation, surface runoff, infiltration, total evapotranspiration (ET), riparian ET, recharge, base flow (or groundwater discharge) and net total outflow. Fluxes of these components were first estimated on a number of real-time-gaged watersheds across Virginia. Specific conductance was used to distinguish and separate surface runoff from base flow. Specific-conductance data were collected every 15 minutes at 75 real-time gages for approximately 18 months between March 2007 and August 2008. Precipitation was estimated for 1971–2000 using PRISM climate data. Precipitation and temperature from the PRISM data were used to develop a regression-based relation to estimate total ET. The proportion of watershed precipitation that becomes surface runoff was related to physiographic province and rock type in a runoff regression equation. Component flux estimates from the watersheds were transferred to flux estimates for counties and independent cities using the ET and runoff regression equations. Only 48 of the 75 watersheds yielded sufficient data, and data from these 48 were used in the final runoff regression equation. The base-flow proportion for the 48 watersheds averaged 72 percent using specific conductance, a value that was substantially higher than the 61 percent average calculated using a graphical-separation technique (the USGS program PART). Final results for the study are presented as component flux estimates for all counties and independent cities in Virginia.

Large Area Crop Inventory Experiment (LACIE). Feasibility of assessing crop condition and yield from LANDSAT data

NASA Technical Reports Server (NTRS)

1978-01-01

The author has identified the following significant results. Yield modelling for crop production estimation derived a means of predicting the within-a-year yield and the year-to-year variability of yield over some fixed or randomly located unit of area. Preliminary studies indicated that the requirements for interpreting LANDSAT data for yield may be sufficiently similar to those of signature extension that it is feasible to investigate the automated estimation of production. The concept of an advanced yield model consisting of both spectral and meteorological components was endorsed. Rationale for using meteorological parameters originated from known between season and near harvest dynamics in crop environmental-condition-yield relationships.

Monte Carlo Approach for Estimating Density and Atomic Number From Dual-Energy Computed Tomography Images of Carbonate Rocks

NASA Astrophysics Data System (ADS)

Victor, Rodolfo A.; Prodanović, Maša.; Torres-Verdín, Carlos

2017-12-01

We develop a new Monte Carlo-based inversion method for estimating electron density and effective atomic number from 3-D dual-energy computed tomography (CT) core scans. The method accounts for uncertainties in X-ray attenuation coefficients resulting from the polychromatic nature of X-ray beam sources of medical and industrial scanners, in addition to delivering uncertainty estimates of inversion products. Estimation of electron density and effective atomic number from CT core scans enables direct deterministic or statistical correlations with salient rock properties for improved petrophysical evaluation; this condition is specifically important in media such as vuggy carbonates where CT resolution better captures core heterogeneity that dominates fluid flow properties. Verification tests of the inversion method performed on a set of highly heterogeneous carbonate cores yield very good agreement with in situ borehole measurements of density and photoelectric factor.

GROWTH AND INEQUALITY: MODEL EVALUATION BASED ON AN ESTIMATION-CALIBRATION STRATEGY

PubMed Central

Jeong, Hyeok; Townsend, Robert

2010-01-01

This paper evaluates two well-known models of growth with inequality that have explicit micro underpinnings related to household choice. With incomplete markets or transactions costs, wealth can constrain investment in business and the choice of occupation and also constrain the timing of entry into the formal financial sector. Using the Thai Socio-Economic Survey (SES), we estimate the distribution of wealth and the key parameters that best fit cross-sectional data on household choices and wealth. We then simulate the model economies for two decades at the estimated initial wealth distribution and analyze whether the model economies at those micro-fit parameter estimates can explain the observed macro and sectoral aspects of income growth and inequality change. Both models capture important features of Thai reality. Anomalies and comparisons across the two distinct models yield specific suggestions for improved research on the micro foundations of growth and inequality. PMID:20448833

A posteriori noise estimation in variable data sets. With applications to spectra and light curves

NASA Astrophysics Data System (ADS)

Czesla, S.; Molle, T.; Schmitt, J. H. M. M.

2018-01-01

Most physical data sets contain a stochastic contribution produced by measurement noise or other random sources along with the signal. Usually, neither the signal nor the noise are accurately known prior to the measurement so that both have to be estimated a posteriori. We have studied a procedure to estimate the standard deviation of the stochastic contribution assuming normality and independence, requiring a sufficiently well-sampled data set to yield reliable results. This procedure is based on estimating the standard deviation in a sample of weighted sums of arbitrarily sampled data points and is identical to the so-called DER_SNR algorithm for specific parameter settings. To demonstrate the applicability of our procedure, we present applications to synthetic data, high-resolution spectra, and a large sample of space-based light curves and, finally, give guidelines to apply the procedure in situation not explicitly considered here to promote its adoption in data analysis.

Global estimates of shark catches using trade records from commercial markets.

PubMed

Clarke, Shelley C; McAllister, Murdoch K; Milner-Gulland, E J; Kirkwood, G P; Michielsens, Catherine G J; Agnew, David J; Pikitch, Ellen K; Nakano, Hideki; Shivji, Mahmood S

2006-10-01

Despite growing concerns about overexploitation of sharks, lack of accurate, species-specific harvest data often hampers quantitative stock assessment. In such cases, trade studies can provide insights into exploitation unavailable from traditional monitoring. We applied Bayesian statistical methods to trade data in combination with genetic identification to estimate by species, the annual number of globally traded shark fins, the most commercially valuable product from a group of species often unrecorded in harvest statistics. Our results provide the first fishery-independent estimate of the scale of shark catches worldwide and indicate that shark biomass in the fin trade is three to four times higher than shark catch figures reported in the only global data base. Comparison of our estimates to approximated stock assessment reference points for one of the most commonly traded species, blue shark, suggests that current trade volumes in numbers of sharks are close to or possibly exceeding the maximum sustainable yield levels.

Direct estimation of the oxygen requirements of Achromobacter xylosoxidans for aerobic degradation of monoaromatic hydrocarbons (BTEX) in a bioscrubber.

PubMed

Nielsen, David R; McLellan, P James; Daugulis, Andrew J

2006-08-01

The O2 requirements for biomass production and supplying maintenance energy demands during the degradation of both benzene and ethylbenzene by Achromobacter xylosoxidans Y234 were measured using a newly proposed technique involving a bioscrubber. Using this approach, relevant microbial parameter estimates were directly and simultaneously obtained via linear regression of pseudo steady-state data. For benzene and ethylbenzene, the biomass yield on O2, Y(X/O2), was estimated on a cell dry weight (CDW) basis as 1.96 +/- 0.25 mg CDW mgO2(-1) and 0.98 +/- 0.17 mg CDW mgO2(-1), while the specific rate of O2 consumption for maintenance, m(O2), was estimated as 0.041 +/- 0.008 mgO(2) mg CDW(-1) h(-1) and 0.053 +/- 0.022 mgO(2) mg CDW(-1) h(-1), respectively.

Use of metabolic inhibitors to estimate protozooplankton grazing and bacterial production in a monomictic eutrophic lake with an anaerobic hypolimnion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sanders, R.W.; Porter, K.G.

Inhibitors of eucaryotes (cycloheximide and amphotericin B) and procaryotes (penicillin and chloramphenical) were used to estimate bacterivory and bacterial production in a eutrophic lake. Bacterial production appeared to be slightly greater than protozoan grazing in the aerobic waters of Lake Oglethorpe. Use of penicillin and cycloheximide yielded inconsistent results in anaerobic water and in aerobic water when bacterial production was low. Production measured by inhibiting eucaryotes with cycloheximide did not always agree with (/sup 3/H)thymidine estimates or differential filtration methods. Laboratory experiments showed that several common freshwater protozoans continued to swim and ingest bacterium-size latex beads in the presence ofmore » the eucaryote inhibitor. Penicillin also affected grazing rates of some ciliates. The authors recommended that caution and a corroborating method be used when estimating ecologically important parameters with specific inhibitors.« less

Chance of Vulnerability Reduction in Application-Specific NoC through Distance Aware Mapping Algorithm

NASA Astrophysics Data System (ADS)

Janidarmian, Majid; Fekr, Atena Roshan; Bokharaei, Vahhab Samadi

2011-08-01

Mapping algorithm which means which core should be linked to which router is one of the key issues in the design flow of network-on-chip. To achieve an application-specific NoC design procedure that minimizes the communication cost and improves the fault tolerant property, first a heuristic mapping algorithm that produces a set of different mappings in a reasonable time is presented. This algorithm allows the designers to identify the set of most promising solutions in a large design space, which has low communication costs while yielding optimum communication costs in some cases. Another evaluated parameter, vulnerability index, is then considered as a principle of estimating the fault-tolerance property in all produced mappings. Finally, in order to yield a mapping which considers trade-offs between these two parameters, a linear function is defined and introduced. It is also observed that more flexibility to prioritize solutions within the design space is possible by adjusting a set of if-then rules in fuzzy logic.

A time series approach to inferring groundwater recharge using the water table fluctuation method

NASA Astrophysics Data System (ADS)

Crosbie, Russell S.; Binning, Philip; Kalma, Jetse D.

2005-01-01

The water table fluctuation method for determining recharge from precipitation and water table measurements was originally developed on an event basis. Here a new multievent time series approach is presented for inferring groundwater recharge from long-term water table and precipitation records. Additional new features are the incorporation of a variable specific yield based upon the soil moisture retention curve, proper accounting for the Lisse effect on the water table, and the incorporation of aquifer drainage so that recharge can be detected even if the water table does not rise. A methodology for filtering noise and non-rainfall-related water table fluctuations is also presented. The model has been applied to 2 years of field data collected in the Tomago sand beds near Newcastle, Australia. It is shown that gross recharge estimates are very sensitive to time step size and specific yield. Properly accounting for the Lisse effect is also important to determining recharge.

Estimation of Enthalpy of Formation of Liquid Transition Metal Alloys: A Modified Prescription Based on Macroscopic Atom Model of Cohesion

NASA Astrophysics Data System (ADS)

Raju, Subramanian; Saibaba, Saroja

2016-09-01

The enthalpy of formation Δo H f is an important thermodynamic quantity, which sheds significant light on fundamental cohesive and structural characteristics of an alloy. However, being a difficult one to determine accurately through experiments, simple estimation procedures are often desirable. In the present study, a modified prescription for estimating Δo H f L of liquid transition metal alloys is outlined, based on the Macroscopic Atom Model of cohesion. This prescription relies on self-consistent estimation of liquid-specific model parameters, namely electronegativity ( ϕ L) and bonding electron density ( n b L ). Such unique identification is made through the use of well-established relationships connecting surface tension, compressibility, and molar volume of a metallic liquid with bonding charge density. The electronegativity is obtained through a consistent linear scaling procedure. The preliminary set of values for ϕ L and n b L , together with other auxiliary model parameters, is subsequently optimized to obtain a good numerical agreement between calculated and experimental values of Δo H f L for sixty liquid transition metal alloys. It is found that, with few exceptions, the use of liquid-specific model parameters in Macroscopic Atom Model yields a physically consistent methodology for reliable estimation of mixing enthalpies of liquid alloys.

A Growth and Yield Model for Thinned Stands of Yellow-Poplar

Treesearch

Bruce R. Knoebel; Harold E. Burkhart; Donald E. Beck

1986-01-01

Simultaneous growth and yield equations were developed for predicting basal area growth and cubic-foot volume growth and yield in thinned stands of yellow-poplar. A joint loss function involving both volume and basal area was used to estimate the coefficients in the system of equations. The estimates obtained were analytically compatible, invariant for projection...

Model-assisted forest yield estimation with light detection and ranging

Treesearch

Jacob L. Strunk; Stephen E. Reutebuch; Hans-Erik Andersen; Peter J. Gould; Robert J. McGaughey

2012-01-01

Previous studies have demonstrated that light detection and ranging (LiDAR)-derived variables can be used to model forest yield variables, such as biomass, volume, and number of stems. However, the next step is underrepresented in the literature: estimation of forest yield with appropriate confidence intervals. It is of great importance that the procedures required for...

Precision and recall estimates for two-hybrid screens

PubMed Central

Huang, Hailiang; Bader, Joel S.

2009-01-01

Motivation: Yeast two-hybrid screens are an important method to map pairwise protein interactions. This method can generate spurious interactions (false discoveries), and true interactions can be missed (false negatives). Previously, we reported a capture–recapture estimator for bait-specific precision and recall. Here, we present an improved method that better accounts for heterogeneity in bait-specific error rates. Result: For yeast, worm and fly screens, we estimate the overall false discovery rates (FDRs) to be 9.9%, 13.2% and 17.0% and the false negative rates (FNRs) to be 51%, 42% and 28%. Bait-specific FDRs and the estimated protein degrees are then used to identify protein categories that yield more (or fewer) false positive interactions and more (or fewer) interaction partners. While membrane proteins have been suggested to have elevated FDRs, the current analysis suggests that intrinsic membrane proteins may actually have reduced FDRs. Hydrophobicity is positively correlated with decreased error rates and fewer interaction partners. These methods will be useful for future two-hybrid screens, which could use ultra-high-throughput sequencing for deeper sampling of interacting bait–prey pairs. Availability: All software (C source) and datasets are available as supplemental files and at http://www.baderzone.org under the Lesser GPL v. 3 license. Contact: joel.bader@jhu.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19091773

Evaluation of Projected Agricultural Climate Risk over the Contiguous US

NASA Astrophysics Data System (ADS)

Zhu, X.; Troy, T. J.; Devineni, N.

2017-12-01

Food demands are rising due to an increasing population with changing food preferences, which places pressure on agricultural production. Additionally, climate extremes have recently highlighted the vulnerability of our agricultural system to climate variability. This study seeks to fill two important gaps in current knowledge: how does the widespread response of irrigated crops differ from rainfed and how can we best account for uncertainty in yield responses. We developed a stochastic approach to evaluate climate risk quantitatively to better understand the historical impacts of climate change and estimate the future impacts it may bring about to agricultural system. Our model consists of Bayesian regression, distribution fitting, and Monte Carlo simulation to simulate rainfed and irrigated crop yields at the US county level. The model was fit using historical data for 1970-2010 and was then applied over different climate regions in the contiguous US using the CMIP5 climate projections. The relative importance of many major growing season climate indices, such as consecutive dry days without rainfall or heavy precipitation, was evaluated to determine what climate indices play a role in affecting future crop yields. The statistical modeling framework also evaluated the impact of irrigation by using county-level irrigated and rainfed yields separately. Furthermore, the projected years with negative yield anomalies were specifically evaluated in terms of magnitude, trend and potential climate drivers. This framework provides estimates of the agricultural climate risk for the 21st century that account for the full uncertainty of climate occurrences, range of crop response, and spatial correlation in climate. The results of this study can contribute to decision making about crop choice and water use in an uncertain future climate.

The limits of crop productivity: validating theoretical estimates and determining the factors that limit crop yields in optimal environments

NASA Technical Reports Server (NTRS)

Bugbee, B.; Monje, O.

1992-01-01

Plant scientists have sought to maximize the yield of food crops since the beginning of agriculture. There are numerous reports of record food and biomass yields (per unit area) in all major crop plants, but many of the record yield reports are in error because they exceed the maximal theoretical rates of the component processes. In this article, we review the component processes that govern yield limits and describe how each process can be individually measured. This procedure has helped us validate theoretical estimates and determine what factors limit yields in optimal environments.

Analysis of MINIE2013 Explosion Air-Blast Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schnurr, Julie M.; Rodgers, Arthur J.; Kim, Keehoon

We report analysis of air-blast overpressure measurements from the MINIE2013 explosive experiments. The MINIE2013 experiment involved a series of nearly 70 near-surface (height-ofburst, HOB, ranging from -1 to +4 m) low-yield (W=2-20 kg TNT equivalent) chemical highexplosives tests that were recorded at local distances (230 m – 28.5 km). Many of the W and HOB combinations were repeated, allowing for quantification of the variability in air-blast features and corresponding yield estimates. We measured canonical signal features (peak overpressure, impulse per unit area, and positive pulse duration) from the air-blast data and compared these to existing air-blast models. Peak overpressure measurementsmore » showed good agreement with the models at close ranges but tended to attenuate more rapidly at longer range (~ 1 km), which is likely caused by upward refraction of acoustic waves due to a negative vertical gradient of sound speed. We estimated yields of the MINIE2013 explosions using the Integrated Yield Determination Tool (IYDT). Errors of the estimated yields were on average within 30% of the reported yields, and there were no significant differences in the accuracy of the IYDT predictions grouped by yield. IYDT estimates tend to be lower than ground truth yields, possibly because of reduced overpressure amplitudes by upward refraction. Finally, we report preliminary results on a development of a new parameterized air-blast waveform.« less

Estimates of nitrate loads and yields from groundwater to streams in the Chesapeake Bay watershed based on land use and geology

USGS Publications Warehouse

Terziotti, Silvia; Capel, Paul D.; Tesoriero, Anthony J.; Hopple, Jessica A.; Kronholm, Scott C.

2018-03-07

The water quality of the Chesapeake Bay may be adversely affected by dissolved nitrate carried in groundwater discharge to streams. To estimate the concentrations, loads, and yields of nitrate from groundwater to streams for the Chesapeake Bay watershed, a regression model was developed based on measured nitrate concentrations from 156 small streams with watersheds less than 500 square miles (mi2 ) at baseflow. The regression model has three predictive variables: geologic unit, percent developed land, and percent agricultural land. Comparisons of estimated and actual values within geologic units were closely matched. The coefficient of determination (R2 ) for the model was 0.6906. The model was used to calculate baseflow nitrate concentrations at over 83,000 National Hydrography Dataset Plus Version 2 catchments and aggregated to 1,966 total 12-digit hydrologic units in the Chesapeake Bay watershed. The modeled output geospatial data layers provided estimated annual loads and yields of nitrate from groundwater into streams. The spatial distribution of annual nitrate yields from groundwater estimated by this method was compared to the total watershed yields of all sources estimated from a Chesapeake Bay SPAtially Referenced Regressions On Watershed attributes (SPARROW) water-quality model. The comparison showed similar spatial patterns. The regression model for groundwater contribution had similar but lower yields, suggesting that groundwater is an important source of nitrogen for streams in the Chesapeake Bay watershed.

Fusion of multi-source remote sensing data for agriculture monitoring tasks

NASA Astrophysics Data System (ADS)

Skakun, S.; Franch, B.; Vermote, E.; Roger, J. C.; Becker Reshef, I.; Justice, C. O.; Masek, J. G.; Murphy, E.

2016-12-01

Remote sensing data is essential source of information for enabling monitoring and quantification of crop state at global and regional scales. Crop mapping, state assessment, area estimation and yield forecasting are the main tasks that are being addressed within GEO-GLAM. Efficiency of agriculture monitoring can be improved when heterogeneous multi-source remote sensing datasets are integrated. Here, we present several case studies of utilizing MODIS, Landsat-8 and Sentinel-2 data along with meteorological data (growing degree days - GDD) for winter wheat yield forecasting, mapping and area estimation. Archived coarse spatial resolution data, such as MODIS, VIIRS and AVHRR, can provide daily global observations that coupled with statistical data on crop yield can enable the development of empirical models for timely yield forecasting at national level. With the availability of high-temporal and high spatial resolution Landsat-8 and Sentinel-2A imagery, course resolution empirical yield models can be downscaled to provide yield estimates at regional and field scale. In particular, we present the case study of downscaling the MODIS CMG based generalized winter wheat yield forecasting model to high spatial resolution data sets, namely harmonized Landsat-8 - Sentinel-2A surface reflectance product (HLS). Since the yield model requires corresponding in season crop masks, we propose an automatic approach to extract winter crop maps from MODIS NDVI and MERRA2 derived GDD using Gaussian mixture model (GMM). Validation for the state of Kansas (US) and Ukraine showed that the approach can yield accuracies > 90% without using reference (ground truth) data sets. Another application of yearly derived winter crop maps is their use for stratification purposes within area frame sampling for crop area estimation. In particular, one can simulate the dependence of error (coefficient of variation) on the number of samples and strata size. This approach was used for estimating the area of winter crops in Ukraine for 2013-2016. The GMM-GDD approach is further extended for HLS data to provide automatic winter crop mapping at 30 m resolution for crop yield model and area estimation. In case of persistent cloudiness, addition of Sentinel-1A synthetic aperture radar (SAR) images is explored for automatic winter crop mapping.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Streets, D. G.; Yarber, K. F.; Woo, J.-H.

Estimates of biomass burning in Asia are developed to facilitate the modeling of Asian and global air quality. A survey of national, regional, and international publications on biomass burning is conducted to yield consensus estimates of 'typical' (i.e., non-year-specific) estimates of open burning (excluding biofuels). We conclude that 730 Tg of biomass are burned in a typical year from both anthropogenic and natural causes. Forest burning comprises 45% of the total, the burning of crop residues in the field comprises 34%, and 20% comes from the burning of grassland and savanna. China contributes 25% of the total, India 18%, Indonesiamore » 13%, and Myanmar 8%. Regionally, forest burning in Southeast Asia dominates. National, annual totals are converted to daily and monthly estimates at 1{sup o} x 1{sup o} spatial resolution using distributions based on AVHRR fire counts for 1999--2000. Several adjustment schemes are applied to correct for the deficiencies of AVHRR data, including the use of moving averages, normalization, TOMS Aerosol Index, and masks for dust, clouds, landcover, and other fire sources. Good agreement between the national estimates of biomass burning and adjusted fire counts is obtained (R{sup 2} = 0.71--0.78). Biomass burning amounts are converted to atmospheric emissions, yielding the following estimates: 0.37 Tg of SO{sub 2}, 2.8 Tg of NO{sub x}, 1100 Tg of CO{sub 2}, 67 Tg of CO, 3.1 Tg of CH{sub 4}, 12 Tg of NMVOC, 0.45 Tg of BC, 3.3 Tg of OC, and 0.92 Tg of NH{sub 3}. Uncertainties in the emission estimates, measured as 95% confidence intervals, range from a low of {+-}65% for CO{sub 2} emissions in Japan to a high of {+-}700% for BC emissions in India.« less

Genetic parameters for growth performance, fillet traits, and fat percentage of male Nile tilapia (Oreochromis niloticus).

PubMed

Garcia, André Luiz Seccatto; de Oliveira, Carlos Antonio Lopes; Karim, Hanner Mahmud; Sary, César; Todesco, Humberto; Ribeiro, Ricardo Pereira

2017-11-01

Improvement of fillet traits and flesh quality attributes are of great interest in farmed tilapia and other aquaculture species. The main objective of this study was to estimate genetic parameters for fillet traits (fillet weight and fillet yield) and the fat content of fillets from 1136 males combined with 2585 data records on growth traits (body weight at 290 days, weight at slaughter, and daily weight gain) of 1485 males and 1100 females from a third generation of the Aquaamerica tilapia strain. Different models were tested for each trait, and the best models were used to estimate genetic parameters for the fat content, fillet, and growth traits. Genetic and phenotypic correlations were estimated using two-trait animal models. The heritability estimates were moderate for the fat content of fillets and fillet yield (0.2-0.32) and slightly higher for body weight at slaughter (0.41). The genetic correlation between fillet yield and fat was significant (0.6), but the genetic correlations were not significant between body weight and fillet yield, body weight and fat content, daily weight gain and fillet yield, and daily weight gain and fat content (- 0.032, - 0.1, - 0.09, and - 0.4, respectively). Based on the genetic correlation estimates, it is unlikely that changes in fillet yield and fat content will occur when using growth performance as a selection criterion, but indirect changes may be expected in fat content if selecting for higher fillet yield.

Longitudinal data analysis of polymorphisms in the κ-casein and β-lactoglobulin genes shows differential effects along the trajectory of the lactation curve in tropical dairy goats.

PubMed

Cardona, Samir Julián Calvo; Cadavid, Henry Cardona; Corrales, Juan David; Munilla, Sebastián; Cantet, Rodolfo J C; Rogberg-Muñoz, Andrés

2016-09-01

The κ-casein (CSN-3) and β-lactoglobulin (BLG) genes are extensively polymorphic in ruminants. Several association studies have estimated the effects of polymorphisms in these genes on milk yield, milk composition, and cheese-manufacturing properties. Usually, these results are based on production integrated over the lactation curve or on cross-sectional studies at specific days in milk (DIM). However, as differential expression of milk protein genes occurs over lactation, the effect of the polymorphisms may change over time. In this study, we fitted a mixed-effects regression model to test-day records of milk yield and milk quality traits (fat, protein, and total solids yields) from Colombian tropical dairy goats. We used the well-characterized A/B polymorphisms in the CSN-3 and BLG genes. We argued that this approach provided more efficient estimators than cross-sectional designs, given the same number and pattern of observations, and allowed exclusion of between-subject variation from model error. The BLG genotype AA showed a greater performance than the BB genotype for all traits along the whole lactation curve, whereas the heterozygote showed an intermediate performance. We observed no such constant pattern for the CSN-3 gene between the AA homozygote and the heterozygote (the BB genotype was absent from the sample). The differences among the genotypic effects of the BLG and the CSN-3 polymorphisms were statistically significant during peak and mid lactation (around 40-160 DIM) for the BLG gene and only for mid lactation (80-145 DIM) for the CSN-3 gene. We also estimated the additive and dominant effects of the BLG locus. The locus showed a statistically significant additive behavior along the whole lactation trajectory for all quality traits, whereas for milk yield the effect was not significant at later stages. In turn, we detected a statistically significant dominance effect only for fat yield in the early and peak stages of lactation (at about 1-45 DIM). The longitudinal analysis of test-day records allowed us to estimate the differential effects of polymorphisms along the lactation curve, pointing toward stages that could be affected by the gene. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Ground-Water Storage Change and Land Subsidence in Tucson Basin and Avra Valley, Southeastern Arizona, 1998-2002

USGS Publications Warehouse

Pool, Donald R.; Anderson, Mark T.

2008-01-01

Gravity and land subsidence were measured annually at wells and benchmarks within two networks in Tucson Basin and Avra Valley from 1998 to 2002. Both networks are within the Tucson Active Management Area. Annual estimates of ground-water storage change, ground-water budgets, and land subsidence were made based on the data. Additionally, estimates of specific yield were made at wells within the monitored region. Increases in gravity and water-level rises followed above-average natural recharge during winter 1998 in Tucson Basin. Overall declining gravity and water-level trends from 1999 to 2002 in Tucson Basin reflected general declining ground-water storage conditions and redistribution of the recent recharge throughout a larger region of the aquifer. The volume of stored ground-water in the monitored portion of Tucson Basin increased 200,000 acre-feet from December 1997 to February 1999; however, thereafter an imbalance in ground-water pumpage in excess of recharge led to a net storage loss for the monitoring period by February 2002. Ground-water storage in Avra Valley increased 70,000 acre-feet during the monitoring period, largely as a result of artificial and incidental recharge in the monitored region. The water-budget for the combined monitored regions of Tucson Basin and Avra Valley was dominated by about 460,000 acre-feet of recharge during 1998 followed by an average-annual recharge rate of about 80,000 acre-feet per year from 1999 to 2002. Above-average recharge during winter 1998, followed by average-annual deficit conditions, resulted in an overall balanced water budget for the monitored period. Monitored variations in storage compared well with simulated average-annual conditions, except for above-average recharge from 1998 to 1999. The difference in observed and simulated conditions indicate that ground-water flow models can be improved by including climate-related variations in recharge rates rather than invariable rates of average-annual recharge. Observed land-subsidence during the monitoring period was less than 1 inch except in the central part of Tucson Basin where land subsidence was about 2-3 inches. Correlations of gravity-based storage and water-level change at 37 wells were variable and illustrate the complex nature of the aquifer system. Storage and water-level variations were insufficient to estimate specific yield at many wells. Correlations at several wells were poor, inverse, or resulted in unreasonably large values of specific yield. Causes of anomalously correlated gravity and water levels include significant storage change in thick unsaturated zones, especially near major ephemeral channels, and multiple aquifers that are poorly connected hydraulically. Good correlation of storage and water-level change at 10 wells that were not near major streams where significant changes in unsaturated zone storage occur resulted in an average specific-yield value of 0.27.

Biogas and methane yield in response to co- and separate digestion of biomass wastes.

PubMed

Adelard, Laetitia; Poulsen, Tjalfe G; Rakotoniaina, Volana

2015-01-01

The impact of co-digestion as opposed to separate digestion, on biogas and methane yield (apparent synergetic effects) was investigated for three biomass materials (pig manure, cow manure and food waste) under mesophilic conditions over a 36 day period. In addition to the three biomass materials (digested separately), 13 biomass mixtures (co-digested) were used. Two approaches for modelling biogas and methane yield during co-digestion, based on volatile solids concentration and ultimate gas and methane potentials, were evaluated. The dependency of apparent synergetic effects on digestion time and biomass mixture composition was further assessed using measured cumulative biogas and methane yields and specific biogas and methane generation rates. Results indicated that it is possible, based on known volatile solids concentration and ultimate biogas or methane yields for a set of biomass materials digested separately, to accurately estimate gas yields for biomass mixtures made from these materials using calibrated models. For the biomass materials considered here, modelling indicated that the addition of pig manure is the main cause of synergetic effects. Co-digestion generally resulted in improved ultimate biogas and methane yields compared to separate digestion. Biogas and methane production was furthermore significantly higher early (0-7 days) and to some degree also late (above 20 days) in the digestion process during co-digestion. © The Author(s) 2014.

Ethiopian Wheat Yield and Yield Gap Estimation: A Spatial Small Area Integrated Data Approach

NASA Astrophysics Data System (ADS)

Mann, M.; Warner, J.

2015-12-01

Despite the collection of routine annual agricultural surveys and significant advances in GIS and remote sensing products, little econometric research has been undertaken in predicting developing nation's agricultural yields. In this paper, we explore the determinants of wheat output per hectare in Ethiopia during the 2011-2013 Meher crop seasons aggregated to the woreda administrative area. Using a panel data approach, combining national agricultural field surveys with relevant GIS and remote sensing products, the model explains nearly 40% of the total variation in wheat output per hectare across the country. The model also identifies specific contributors to wheat yields that include farm management techniques (eg. area planted, improved seed, fertilizer, irrigation), weather (eg. rainfall), water availability (vegetation and moisture deficit indexes) and policy intervention. Our findings suggest that woredas produce between 9.8 and 86.5% of their potential wheat output per hectare given their altitude, weather conditions, terrain, and plant health. At the median, Amhara, Oromiya, SNNP, and Tigray produce 48.6, 51.5, 49.7, and 61.3% of their local attainable yields, respectively. This research has a broad range of applications, especially from a public policy perspective: identifying causes of yield fluctuations, remotely evaluating larger agricultural intervention packages, and analyzing relative yield potential. Overall, the combination of field surveys with spatial data can be used to identify management priorities for improving production at a variety of administrative levels.

Calibrating SALT: a sampling scheme to improve estimates of suspended sediment yield

Treesearch

Robert B. Thomas

1986-01-01

Abstract - SALT (Selection At List Time) is a variable probability sampling scheme that provides unbiased estimates of suspended sediment yield and its variance. SALT performs better than standard schemes which are estimate variance. Sampling probabilities are based on a sediment rating function which promotes greater sampling intensity during periods of high...

Simulation of a long-term aquifer test conducted near the Rio Grande, Albuquerque, New Mexico

USGS Publications Warehouse

McAda, Douglas P.

2001-01-01

A long-term aquifer test was conducted near the Rio Grande in Albuquerque during January and February 1995 using 22 wells and piezometers at nine sites, with the City of Albuquerque Griegos 1 production well as the pumped well. Griegos 1 discharge averaged about 2,330 gallons per minute for 54.4 days. A three-dimensional finite-difference ground-water-flow model was used to estimate aquifer properties in the vicinity of the Griegos well field and the amount of infiltration induced into the aquifer system from the Rio Grande and riverside drains as a result of pumping during the test. The model was initially calibrated by trial-and-error adjustments of the aquifer properties. The model was recalibrated using a nonlinear least-squares regression technique. The aquifer system in the area includes the middle Tertiary to Quaternary Santa Fe Group and post-Santa Fe Group valley- and basin-fill deposits of the Albuquerque Basin. The Rio Grande and adjacent riverside drains are in hydraulic connection with the aquifer system. The hydraulic-conductivity values of the upper part of the Santa Fe Group resulting from the model calibrated by trial and error varied by zone in the model and ranged from 12 to 33 feet per day. The hydraulic conductivity of the inner-valley alluvium was 45 feet per day. The vertical to horizontal anisotropy ratio was 1:140. Specific storage was 4 x 10-6 per foot of aquifer thickness, and specific yield was 0.15 (dimensionless). The sum of squared errors between the observed and simulated drawdowns was 130 feet squared. Not all aquifer properties could be estimated using nonlinear regression because of model insensitivity to some aquifer properties at observation locations. Hydraulic conductivity of the inner-valley alluvium, middle part of the Santa Fe Group, and riverbed and riverside-drain bed and specific yield had low sensitivity values and therefore could not be estimated. Of the properties estimated, hydraulic conductivity of the upper part of the Santa Fe Group was estimated to be 12 feet per day, the vertical to horizontal anisotropy ratio was estimated to be 1:82, and specific storage was estimated to be 1.2 x 10-6 per foot of aquifer thickness. The overall sum of squared errors between the observed and simulated drawdowns was 87 feet squared, a significant improvement over the model calibrated by trial and error. At the end of aquifer-test pumping, induced infiltration from the Rio Grande and riverside drains was simulated to be 13 percent of the total amount of water pumped. The remainder was water removed from aquifer storage. After pumping stopped, induced infiltration continued to replenish aquifer storage. Simulations estimated that 5 years after pumping began (about 4.85 years after pumping stopped), 58 to 72 percent of the total amount of water pumped was replenished by induced infiltration from the Rio Grande surface-water system.

Comparative study of transient hydraulic tomography with varying parameterizations and zonations: Laboratory sandbox investigation

NASA Astrophysics Data System (ADS)

Luo, Ning; Zhao, Zhanfeng; Illman, Walter A.; Berg, Steven J.

2017-11-01

Transient hydraulic tomography (THT) is a robust method of aquifer characterization to estimate the spatial distributions (or tomograms) of both hydraulic conductivity (K) and specific storage (Ss). However, the highly-parameterized nature of the geostatistical inversion approach renders it computationally intensive for large-scale investigations. In addition, geostatistics-based THT may produce overly smooth tomograms when head data used to constrain the inversion is limited. Therefore, alternative model conceptualizations for THT need to be examined. To investigate this, we simultaneously calibrated different groundwater models with varying parameterizations and zonations using two cases of different pumping and monitoring data densities from a laboratory sandbox. Specifically, one effective parameter model, four geology-based zonation models with varying accuracy and resolution, and five geostatistical models with different prior information are calibrated. Model performance is quantitatively assessed by examining the calibration and validation results. Our study reveals that highly parameterized geostatistical models perform the best among the models compared, while the zonation model with excellent knowledge of stratigraphy also yields comparable results. When few pumping tests with sparse monitoring intervals are available, the incorporation of accurate or simplified geological information into geostatistical models reveals more details in heterogeneity and yields more robust validation results. However, results deteriorate when inaccurate geological information are incorporated. Finally, our study reveals that transient inversions are necessary to obtain reliable K and Ss estimates for making accurate predictions of transient drawdown events.

Benefits of seasonal forecasts of crop yields

NASA Astrophysics Data System (ADS)

Sakurai, G.; Okada, M.; Nishimori, M.; Yokozawa, M.

2017-12-01

Major factors behind recent fluctuations in food prices include increased biofuel production and oil price fluctuations. In addition, several extreme climate events that reduced worldwide food production coincided with upward spikes in food prices. The stabilization of crop yields is one of the most important tasks to stabilize food prices and thereby enhance food security. Recent development of technologies related to crop modeling and seasonal weather forecasting has made it possible to forecast future crop yields for maize and soybean. However, the effective use of these technologies remains limited. Here we present the potential benefits of seasonal crop-yield forecasts on a global scale for choice of planting day. For this purpose, we used a model (PRYSBI-2) that can well replicate past crop yields both for maize and soybean. This model system uses a Bayesian statistical approach to estimate the parameters of a basic process-based model of crop growth. The spatial variability of model parameters was considered by estimating the posterior distribution of the parameters from historical yield data by using the Markov-chain Monte Carlo (MCMC) method with a resolution of 1.125° × 1.125°. The posterior distributions of model parameters were estimated for each spatial grid with 30 000 MCMC steps of 10 chains each. By using this model and the estimated parameter distributions, we were able to estimate not only crop yield but also levels of associated uncertainty. We found that the global average crop yield increased about 30% as the result of the optimal selection of planting day and that the seasonal forecast of crop yield had a large benefit in and near the eastern part of Brazil and India for maize and the northern area of China for soybean. In these countries, the effects of El Niño and Indian Ocean dipole are large. The results highlight the importance of developing a system to forecast global crop yields.

Differential activity staining: its use in characterization of guanylyl-specific ribonuclease in the genus Ustilago.

PubMed Central

Blank, A; Dekker, C A

1975-01-01

Guanylyl-specific ribonuclease can be identified by a novel technique employing electrophoresis in polyacrylamide slabs followed by differential activity staining. The technique requires as little as 7 ng of enzyme which may be grossly admixed with contaminants, including other ribonucleases. Upon electrophoresis and activity staining, a variety of ribonucleases can be visualized as light or clear bands in a colored background formed by toluidine blue complexed with oligonucleotide substrate. Guanylyl-specific ribonuclease, which is detectable when using an oligonucleotide substrate of random base sequence, does not yield a band when using oligonucleotides bearing guanylyl residues at the 3'-termini only and containing, therefore, no susceptible internucleotide bonds; in contrast, a ribonuclease with a different base specificity or no base specificity yields a band with either substrate. This differential activity staining method for establishing guanylyl specificity permits estimation of the extent of nonspecific cleavage of internucleotide linkages by a putatively guanylyl-specific enzyme and is at least as sensitive as conventional procedures for determination of base specificity. With this new technique guanyloribonuclease has been identified in the unfractionated culture medium of 10 organisms belonging to the phytopathogenic fungal genus Ustilago. It is suggested that guanylyl-specific ribonuclease is widely distributed among Ustilago species; its electrophoretic properties may be revealing of phylogenetic relationships among these plant parasites and among their hosts. The general technique of differential activity staining, developed for determination of the base specificity of ribonucleases, may be widely applicable to analysis of enzymes catalyzing depolymerization reactions. Images PMID:813217

Modeling precipitation-runoff relationships to determine water yield from a ponderosa pine forest watershed

Treesearch

Assefa S. Desta

2006-01-01

A stochastic precipitation-runoff modeling is used to estimate a cold and warm-seasons water yield from a ponderosa pine forested watershed in the north-central Arizona. The model consists of two parts namely, simulation of the temporal and spatial distribution of precipitation using a stochastic, event-based approach and estimation of water yield from the watershed...

Explosion yield estimation from pressure wave template matching

PubMed Central

Arrowsmith, Stephen; Bowman, Daniel

2017-01-01

A method for estimating the yield of explosions from shock-wave and acoustic-wave measurements is presented. The method exploits full waveforms by comparing pressure measurements against an empirical stack of prior observations using scaling laws. The approach can be applied to measurements across a wide-range of source-to-receiver distances. The method is applied to data from two explosion experiments in different regions, leading to mean relative errors in yield estimates of 0.13 using prior data from the same region, and 0.2 when applied to a new region. PMID:28618805

Operation of the yield estimation subsystem

NASA Technical Reports Server (NTRS)

Mccrary, D. G.; Rogers, J. L.; Hill, J. D. (Principal Investigator)

1979-01-01

The organization and products of the yield estimation subsystem (YES) are described with particular emphasis on meteorological data acquisition, yield estimation, crop calendars, weekly weather summaries, and project reports. During the three phases of LACIE, YES demonstrated that it is possible to use the flow of global meteorological data and provide valuable information regarding global wheat production. It was able to establish a capability to collect, in a timely manner, detailed weather data from all regions of the world, and to evaluate and convert that data into information appropriate to the project's needs.

Onorbit IMU alignment error budget

NASA Technical Reports Server (NTRS)

Corson, R. W.

1980-01-01

The Star Tracker, Crew Optical Alignment Sight (COAS), and Inertial Measurement Unit (IMU) from a complex navigation system with a multitude of error sources were combined. A complete list of the system errors is presented. The errors were combined in a rational way to yield an estimate of the IMU alignment accuracy for STS-1. The expected standard deviation in the IMU alignment error for STS-1 type alignments was determined to be 72 arc seconds per axis for star tracker alignments and 188 arc seconds per axis for COAS alignments. These estimates are based on current knowledge of the star tracker, COAS, IMU, and navigation base error specifications, and were partially verified by preliminary Monte Carlo analysis.

Remote Estimation of Vegetation Fraction and Yield in Oilseed Rape with Unmanned Aerial Vehicle Data

NASA Astrophysics Data System (ADS)

Peng, Y.; Fang, S.; Liu, K.; Gong, Y.

2017-12-01

This study developed an approach for remote estimation of Vegetation Fraction (VF) and yield in oilseed rape, which is a crop species with conspicuous flowers during reproduction. Canopy reflectance in green, red, red edge and NIR bands was obtained by a camera system mounted on an unmanned aerial vehicle (UAV) when oilseed rape was in the vegetative growth and flowering stage. The relationship of several widely-used Vegetation Indices (VI) vs. VF was tested and found to be different in different phenology stages. At the same VF when oilseed rape was flowering, canopy reflectance increased in all bands, and the tested VI decreased. Therefore, two algorithms to estimate VF were calibrated respectively, one for samples during vegetative growth and the other for samples during flowering stage. During the flowering season, we also explored the potential of using canopy reflectance or VIs to estimate Flower Fraction (FF) in oilseed rape. Based on FF estimates, rape yield can be estimated using canopy reflectance data. Our model was validated in oilseed rape planted under different nitrogen fertilization applications and in different phenology stages. The results showed that it was able to predict VF and FF accurately in oilseed rape with estimation error below 6% and predict yield with estimation error below 20%.

Age-related differences in recommended anthropometric cut-off point validity to identify cardiovascular risk factors in ostensibly healthy women

PubMed Central

Björkelund, Cecilia; Guo, Xinxin; Skoog, Ingmar; Bosaeus, Ingvar; Lissner, Lauren

2014-01-01

Aim: To investigate validity of widely recommended anthropometric and total fat percentage cut-off points in screening for cardiovascular risk factors in women of different ages. Methods: A population-based sample of 1002 Swedish women aged 38, 50, 75 (younger, middle-aged and elderly, respectively) underwent anthropometry, health examinations and blood tests. Total fat was estimated (bioimpedance) in 670 women. Sensitivity, specificity of body mass index (BMI; ≥25 and ≥30), waist circumference (WC; ≥80 cm and ≥88 cm) and total fat percentage (TF; ≥35%) cut-off points for cardiovascular risk factors (dyslipidaemias, hypertension and hyperglycaemia) were calculated for each age. Cut-off points yielding high sensitivity together with modest specificity were considered valid. Women reporting hospital admission for cardiovascular disease were excluded. Results: The sensitivity of WC ≥80 cm for one or more risk factors was ~60% in younger and middle-aged women, and 80% in elderly women. The specificity of WC ≥80 cm for one or more risk factors was 69%, 57% and 40% at the three ages (p < .05 for age trends). WC ≥80 cm yielded ~80% sensitivity for two or more risk factors across all ages. However, specificity decreased with increasing age (p < .0001), being 33% in elderly. WC ≥88 cm provided better specificity in elderly women. BMI and TF % cut-off points were not better than WC. Conclusions: Validity of recommended anthropometric cut-off points in screening asymptomatic women varies with age. In younger and middle-age, WC ≥80 cm yielded high sensitivity and modest specificity for two or more risk factors, however, sensitivity for one or more risk factor was less than optimal. WC ≥88 cm showed better validity than WC ≥80 cm in elderly. Our results support age-specific screening cut-off points for women. PMID:25294689

Age-related differences in recommended anthropometric cut-off point validity to identify cardiovascular risk factors in ostensibly healthy women.

PubMed

Subramoney, Sreevidya; Björkelund, Cecilia; Guo, Xinxin; Skoog, Ingmar; Bosaeus, Ingvar; Lissner, Lauren

2014-12-01

To investigate validity of widely recommended anthropometric and total fat percentage cut-off points in screening for cardiovascular risk factors in women of different ages. A population-based sample of 1002 Swedish women aged 38, 50, 75 (younger, middle-aged and elderly, respectively) underwent anthropometry, health examinations and blood tests. Total fat was estimated (bioimpedance) in 670 women. Sensitivity, specificity of body mass index (BMI; ≥25 and ≥30), waist circumference (WC; ≥80 cm and ≥88 cm) and total fat percentage (TF; ≥35%) cut-off points for cardiovascular risk factors (dyslipidaemias, hypertension and hyperglycaemia) were calculated for each age. Cut-off points yielding high sensitivity together with modest specificity were considered valid. Women reporting hospital admission for cardiovascular disease were excluded. The sensitivity of WC ≥80 cm for one or more risk factors was ~60% in younger and middle-aged women, and 80% in elderly women. The specificity of WC ≥80 cm for one or more risk factors was 69%, 57% and 40% at the three ages (p < .05 for age trends). WC ≥80 cm yielded ~80% sensitivity for two or more risk factors across all ages. However, specificity decreased with increasing age (p < .0001), being 33% in elderly. WC ≥88 cm provided better specificity in elderly women. BMI and TF % cut-off points were not better than WC. Validity of recommended anthropometric cut-off points in screening asymptomatic women varies with age. In younger and middle-age, WC ≥80 cm yielded high sensitivity and modest specificity for two or more risk factors, however, sensitivity for one or more risk factor was less than optimal. WC ≥88 cm showed better validity than WC ≥80 cm in elderly. Our results support age-specific screening cut-off points for women. © 2014 the Nordic Societies of Public Health.

Improvement of Prediction Ability for Genomic Selection of Dairy Cattle by Including Dominance Effects

PubMed Central

Sun, Chuanyu; VanRaden, Paul M.; Cole, John B.; O'Connell, Jeffrey R.

2014-01-01

Dominance may be an important source of non-additive genetic variance for many traits of dairy cattle. However, nearly all prediction models for dairy cattle have included only additive effects because of the limited number of cows with both genotypes and phenotypes. The role of dominance in the Holstein and Jersey breeds was investigated for eight traits: milk, fat, and protein yields; productive life; daughter pregnancy rate; somatic cell score; fat percent and protein percent. Additive and dominance variance components were estimated and then used to estimate additive and dominance effects of single nucleotide polymorphisms (SNPs). The predictive abilities of three models with both additive and dominance effects and a model with additive effects only were assessed using ten-fold cross-validation. One procedure estimated dominance values, and another estimated dominance deviations; calculation of the dominance relationship matrix was different for the two methods. The third approach enlarged the dataset by including cows with genotype probabilities derived using genotyped ancestors. For yield traits, dominance variance accounted for 5 and 7% of total variance for Holsteins and Jerseys, respectively; using dominance deviations resulted in smaller dominance and larger additive variance estimates. For non-yield traits, dominance variances were very small for both breeds. For yield traits, including additive and dominance effects fit the data better than including only additive effects; average correlations between estimated genetic effects and phenotypes showed that prediction accuracy increased when both effects rather than just additive effects were included. No corresponding gains in prediction ability were found for non-yield traits. Including cows with derived genotype probabilities from genotyped ancestors did not improve prediction accuracy. The largest additive effects were located on chromosome 14 near DGAT1 for yield traits for both breeds; those SNPs also showed the largest dominance effects for fat yield (both breeds) as well as for Holstein milk yield. PMID:25084281

Salience Assignment for Multiple-Instance Data and Its Application to Crop Yield Prediction

NASA Technical Reports Server (NTRS)

Wagstaff, Kiri L.; Lane, Terran

2010-01-01

An algorithm was developed to generate crop yield predictions from orbital remote sensing observations, by analyzing thousands of pixels per county and the associated historical crop yield data for those counties. The algorithm determines which pixels contain which crop. Since each known yield value is associated with thousands of individual pixels, this is a multiple instance learning problem. Because individual crop growth is related to the resulting yield, this relationship has been leveraged to identify pixels that are individually related to corn, wheat, cotton, and soybean yield. Those that have the strongest relationship to a given crop s yield values are most likely to contain fields with that crop. Remote sensing time series data (a new observation every 8 days) was examined for each pixel, which contains information for that pixel s growth curve, peak greenness, and other relevant features. An alternating-projection (AP) technique was used to first estimate the "salience" of each pixel, with respect to the given target (crop yield), and then those estimates were used to build a regression model that relates input data (remote sensing observations) to the target. This is achieved by constructing an exemplar for each crop in each county that is a weighted average of all the pixels within the county; the pixels are weighted according to the salience values. The new regression model estimate then informs the next estimate of the salience values. By iterating between these two steps, the algorithm converges to a stable estimate of both the salience of each pixel and the regression model. The salience values indicate which pixels are most relevant to each crop under consideration.

Estimation of evaporation from equilibrium diurnal boundary layer humidity

NASA Astrophysics Data System (ADS)

Salvucci, G.; Rigden, A. J.; Li, D.; Gentine, P.

2017-12-01

Simplified conceptual models of the convective boundary layer as a well mixed profile of potential temperature (theta) and specific humidity (q) impinging on an initially stably stratified linear potential temperature profile have a long history in atmospheric sciences. These one dimensional representations of complex mixing are useful for gaining insights into land-atmosphere interactions and for prediction when state of the art LES approaches are infeasible. As previously shown (e.g. Betts), if one neglects the role of q in bouyancy, the framework yields a unique relation between mixed layer Theta, mixed layer height (h), and cumulative sensible heat flux (SH) throughout the day. Similarly assuming an initially q profile yields a simple relation between q, h, and cumulative latent heat flux (LH). The diurnal dynamics of theta and q are strongly dependent on SH and the initial lapse rates of theta (gamma_thet) and q (gamma q). In the estimation method proposed here, we further constrain these relations with two more assumptions: 1) The specific humidity is the same at the start of the period of boundary layer growth and at the collapse; and 2) Once the mixed layer reaches the LCL, further drying occurs proportionally to the deardorff convective velocity scale (omega) multiplied by q. Assumption (1) is based on the idea that below the cloud layer, there are no sinks of moisture within the mixed layer (neglecting lateral humidity divergence). Thus the net mixing of dry air aloft with evaporation from the surface must balance. Inclusion of the simple model of moisture loss above the LCL into the bulk-CBL model allows definition of an equilibrium humidity (q) condition at which the diurnal cycle of q repeats (i.e. additions of q from surface balance entrainment of dry air from above). Surprisingly, this framework allows estimation of LH from q, theta, and estimated net radiation by solving for the value of Evaporative Fraction (EF) for which the diurnal cycle of q repeats. Three parameters need specification: cloud area fraction, entrainment factor, and morning lapse rate. Surprisingly, a single set of values for these parameters are adequate to estimate EF at over 70 tested Ameriflux sites to within about 20%, though improvements are gained using a single regression model for gamma_thet that has been fitted to radiosonde data.

Search for supersymmetry in pp collisions at $$\\sqrt{s} =7$$ TeV in events with a single lepton, jets, and missing transverse momentum

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chatrchyan, S.; Khachatryan, V.; Sirunyan, A. M.

Results are reported from a search for new physics processes in events containing a single isolated high-transverse-momentum lepton (electron or muon), energetic jets, and large missing transverse momentum. The analysis is based on a 4.98 fb -1 sample of proton–proton collisions at a center-of-mass energy of 7 TeV, obtained with the CMS detector at the LHC. Three separate background estimation methods, each relying primarily on control samples in the data, are applied to a range of signal regions, providing complementary approaches for estimating the background yields. The observed yields are consistent with the predicted standard model backgrounds. The results are interpreted inmore » terms of limits on the parameter space for the constrained minimal supersymmetric extension of the standard model, as well as on cross sections for simplified models, which provide a generic description of the production and decay of new particles in specific, topology based final states.« less

Methods for estimating water consumption for thermoelectric power plants in the United States

USGS Publications Warehouse

Diehl, Timothy H.; Harris, Melissa; Murphy, Jennifer C.; Hutson, Susan S.; Ladd, David E.

2013-01-01

Heat budgets were constructed for the first four generation-type categories; data at solar thermal plants were insufficient for heat budgets. These heat budgets yielded estimates of the amount of heat transferred to the condenser. The ratio of evaporation to the heat discharged through the condenser was estimated using existing heat balance models that are sensitive to environmental data; this feature allows estimation of consumption under different climatic conditions. These two estimates were multiplied to yield an estimate of consumption at each power plant.

Genetic parameters for milk, fat and protein yields in Murrah buffaloes (Bubalus bubalis Artiodactyla, Bovidae)

PubMed Central

2010-01-01

The objective of the present study was to estimate genetic parameters for test-day milk, fat and protein yields and 305-day-yields in Murrah buffaloes. 4,757 complete lactations of Murrah buffaloes were analyzed. Co-variance components were estimated by the restricted maximum likelihood method. The models included additive direct genetic and permanent environmental effects as random effects, and the fixed effects of contemporary group, milking number and age of the cow at calving as linear and quadratic covariables. Contemporary groups were defined by herd-year-month of test for test-day yields and by herd-year-season of calving for 305-day yields. The heritability estimates obtained by two-trait analysis ranged from 0.15 to 0.24 for milk, 0.16 to 0.23 for protein and 0.13 to 0.22 for fat, yields. Genetic and phenotypic correlations were all positive. The observed population additive genetic variation indicated that selection might be an effective tool in changing population means in milk, fat and protein yields. PMID:21637608

Breeding Potential of Introgression Lines Developed from Interspecific Crossing between Upland Cotton (Gossypium hirsutum) and Gossypium barbadense: Heterosis, Combining Ability and Genetic Effects

PubMed Central

Li, Xingli; Pei, Wenfeng

2016-01-01

Upland cotton (Gossypium hirstum L.), which produces more than 95% of the world natural cotton fibers, has a narrow genetic base which hinders progress in cotton breeding. Introducing germplasm from exotic sources especially from another cultivated tetraploid G. barbadense L. can broaden the genetic base of Upland cotton. However, the breeding potential of introgression lines (ILs) in Upland cotton with G. barbadense germplasm integration has not been well addressed. This study involved six ILs developed from an interspecific crossing and backcrossing between Upland cotton and G. barbadense and represented one of the first studies to investigate breeding potentials of a set of ILs using a full diallel analysis. High mid-parent heterosis was detected in several hybrids between ILs and a commercial cultivar, which also out-yielded the high-yielding cultivar parent in F1, F2 and F3 generations. A further analysis indicated that general ability (GCA) variance was predominant for all the traits, while specific combining ability (SCA) variance was either non-existent or much lower than GCA. The estimated GCA effects and predicted additive effects for parents in each trait were positively correlated (at P<0.01). Furthermore, GCA and additive effects for each trait were also positively correlated among generations (at P<0.05), suggesting that F2 and F3 generations can be used as a proxy to F1 in analyzing combining abilities and estimating genetic parameters. In addition, differences between reciprocal crosses in F1 and F2 were not significant for yield, yield components and fiber quality traits. But maternal effects appeared to be present for seed oil and protein contents in F3. This study identified introgression lines as good general combiners for yield and fiber quality improvement and hybrids with high heterotic vigor in yield, and therefore provided useful information for further utilization of introgression lines in cotton breeding. PMID:26730964

Impacts of management practices on bioenergy feedstock yield and economic feasibility on Conservation Reserve Program grasslands

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anderson, Eric K.; Aberle, Ezra; Chen, Chengci

Perennial grass mixtures planted on Conservation Reserve Program (CRP) land are a potential source of dedicated bioenergy feedstock. Long-term nitrogen (N) and harvest management are critical factors for maximizing biomass yield while maintaining the longevity of grass stands. A six-year farm-scale study was conducted to understand the impact of weather variability on biomass yield, determine optimal N fertilization and harvest timing management practices for sustainable biomass production, and estimate economic viability at six CRP sites in the United States. Precipitation during the growing season was a critical factor for annual biomass production across all regions, and annual biomass production wasmore » severely reduced when growing season precipitation was below 50% of average. The N rate of 112 kg ha -1 produced the highest biomass yield at each location. Harvest timing resulting in the highest biomass yield was site-specific and was a factor of predominant grass type, seasonal precipitation, and the number of harvests taken per year. The use of N fertilizer for yield enhancement unambiguously increased the cost of biomass regardless of the harvest timing for all six sites. The breakeven price of biomass at the farmgate ranged from 37 dollars to 311 dollars Mg -1 depending on the rate of N application, timing of harvesting, and location when foregone opportunity costs were not considered. Breakeven prices ranged from 69 dollars to 526 dollars Mg -1 when the loss of CRP land rental payments was included as an opportunity cost. Annual cost of the CRP to the federal government could be reduced by over 8% in the states included in this study; however, this would require the biomass price to be much higher than in the case where the landowner receives the CRP land rent. Lastly, this field research demonstrated the importance of long-term, farm-scale research for accurate estimation of biomass feedstock production and economic viability from perennial grasslands.« less

Impacts of management practices on bioenergy feedstock yield and economic feasibility on Conservation Reserve Program grasslands

DOE PAGES

Anderson, Eric K.; Aberle, Ezra; Chen, Chengci; ...

2015-12-21

Perennial grass mixtures planted on Conservation Reserve Program (CRP) land are a potential source of dedicated bioenergy feedstock. Long-term nitrogen (N) and harvest management are critical factors for maximizing biomass yield while maintaining the longevity of grass stands. A six-year farm-scale study was conducted to understand the impact of weather variability on biomass yield, determine optimal N fertilization and harvest timing management practices for sustainable biomass production, and estimate economic viability at six CRP sites in the United States. Precipitation during the growing season was a critical factor for annual biomass production across all regions, and annual biomass production wasmore » severely reduced when growing season precipitation was below 50% of average. The N rate of 112 kg ha -1 produced the highest biomass yield at each location. Harvest timing resulting in the highest biomass yield was site-specific and was a factor of predominant grass type, seasonal precipitation, and the number of harvests taken per year. The use of N fertilizer for yield enhancement unambiguously increased the cost of biomass regardless of the harvest timing for all six sites. The breakeven price of biomass at the farmgate ranged from 37 dollars to 311 dollars Mg -1 depending on the rate of N application, timing of harvesting, and location when foregone opportunity costs were not considered. Breakeven prices ranged from 69 dollars to 526 dollars Mg -1 when the loss of CRP land rental payments was included as an opportunity cost. Annual cost of the CRP to the federal government could be reduced by over 8% in the states included in this study; however, this would require the biomass price to be much higher than in the case where the landowner receives the CRP land rent. Lastly, this field research demonstrated the importance of long-term, farm-scale research for accurate estimation of biomass feedstock production and economic viability from perennial grasslands.« less

Breeding Potential of Introgression Lines Developed from Interspecific Crossing between Upland Cotton (Gossypium hirsutum) and Gossypium barbadense: Heterosis, Combining Ability and Genetic Effects.

PubMed

Zhang, Jinfa; Wu, Man; Yu, Jiwen; Li, Xingli; Pei, Wenfeng

2016-01-01

Upland cotton (Gossypium hirstum L.), which produces more than 95% of the world natural cotton fibers, has a narrow genetic base which hinders progress in cotton breeding. Introducing germplasm from exotic sources especially from another cultivated tetraploid G. barbadense L. can broaden the genetic base of Upland cotton. However, the breeding potential of introgression lines (ILs) in Upland cotton with G. barbadense germplasm integration has not been well addressed. This study involved six ILs developed from an interspecific crossing and backcrossing between Upland cotton and G. barbadense and represented one of the first studies to investigate breeding potentials of a set of ILs using a full diallel analysis. High mid-parent heterosis was detected in several hybrids between ILs and a commercial cultivar, which also out-yielded the high-yielding cultivar parent in F1, F2 and F3 generations. A further analysis indicated that general ability (GCA) variance was predominant for all the traits, while specific combining ability (SCA) variance was either non-existent or much lower than GCA. The estimated GCA effects and predicted additive effects for parents in each trait were positively correlated (at P<0.01). Furthermore, GCA and additive effects for each trait were also positively correlated among generations (at P<0.05), suggesting that F2 and F3 generations can be used as a proxy to F1 in analyzing combining abilities and estimating genetic parameters. In addition, differences between reciprocal crosses in F1 and F2 were not significant for yield, yield components and fiber quality traits. But maternal effects appeared to be present for seed oil and protein contents in F3. This study identified introgression lines as good general combiners for yield and fiber quality improvement and hybrids with high heterotic vigor in yield, and therefore provided useful information for further utilization of introgression lines in cotton breeding.

Pine Needles as Potential Energy Feedstock: Availability in the Central Himalayan State of Uttarakhand, India

NASA Astrophysics Data System (ADS)

Kala, L. D.; Subbarao, P. M. V.

2017-11-01

The amount of pine needles (pinus roxburgii) potentially available for use as energy feedstock in the Central Himalayan state of Uttarakhand in India has been estimated. It involves estimating the gross annual amount of pine needle yield followed by a comprehensive identification and quantification of the factors that affect the net annual pine needle yield available as energy feedstock. These factors include considerations such as accessibility, alternative uses, forest fires, other losses, etc., that are influenced by aspects ranging from physical constraints to traditional societal traits. Tree canopy cover method has been used for estimating the gross annual pine needle yield. The information on canopy density is obtained from remote sensing data, that forms the basis for forest classification. The annual gross pine needle yield has been estimated at 1.9 million tonnes while the annual net pine needle yield at 1.33 million tonnes. The annual primary energy potential of pine needles available as energy feedstock has also been estimated. For annual net energy potential estimation, thermal and electrical routes are considered. Electrical energy generation from pine needles using thermochemical conversion has been examined and the corresponding potential for electricity generation been estimated. An installed capacity of 789 MW can be supported with pine needles feedstock for supplying electricity in rural areas for five hours a day. For round the clock generation, an installed capacity of 165 MW can be supported by the pine needle energy feedstock.

Use of reservoir deposits to reconstruct the recent changes in sediment yields from a small granite catchment in the Yimeng Mountain region, China

NASA Astrophysics Data System (ADS)

Zhang, Yunqi; Long, Yi; Li, Bao; Xu, Shujian; Wang, Xiaoli; Liao, Jia

2017-09-01

Information on recent changes in sediment yields from small catchments provides a better understanding of temporal trends in soil loss from certain physical and human-influenced landscapes that have been subjected to recent environmental changes, and will help bridge the current knowledge gap that exists between hillslope erosion and sediment transport in rivers. The Yimeng Mountain region, characterized by alternating granite and limestone, is one of the most susceptible regions to soil erosion in northern China, and has been subjected to intensive anthropogenic activity in recent years. Soil loss from areas underlain by granite is particularly obvious, and is the main sediment source for the Yihe River. In this study, we used reservoir deposits to estimate the changes in sediment yields over the past 50 years from a small catchment underlain by granite, namely the Jiangzhuang catchment in the Yimeng Mountain region. Three cores were collected from the Jiangzhuang Reservoir in the catchment. The activities of 137Cs and 210Pbex at different depths, clay (grain size < 5 μm) contents, and sedimentary organic carbon (SOC) contents in the cores were analysed with reference to human activity and environmental change in the catchment. The chronologies of the cores were established by 137Cs and 210Pbex dating. The area-specific sediment yield (SSY) for different time periods since dam construction was estimated from each core by referring to the original capacity curve of the reservoir. The results indicate that the depth profiles of 137Cs, 210Pbex, clay, and SOC contents in cores from the Jiangzhuang Reservoir reflect the general history of human disturbances on the catchment over the past 50 years. The estimated SSY value from each core for each period ranged from 7.2 ± 2.7 to 23.7 ± 8.3 t ha- 1 y- 1, with a mean of 12.5 ± 4.6 t ha- 1 y- 1. SSY decreased during 1954-1972, and then showed a general tendency to increase. The temporal pattern of the sediment yield largely reflects the history of environmental change influenced by human activity in the catchment.

Effect of Anisotropic Yield Function Evolution on Estimation of Forming Limit Diagram

NASA Astrophysics Data System (ADS)

Bandyopadhyay, K.; Basak, S.; Choi, H. J.; Panda, S. K.; Lee, M. G.

2017-09-01

In case of theoretical prediction of the FLD, the variations in yield stress and R-values along different material directions, were long been implemented to enhance the accuracy. Although influences of different yield models and hardening laws on formability were well addressed, anisotropic evolution of yield loci under monotonic loading with different deformation modes is yet to be explored. In the present study, Marciniak-Kuckzinsky (M-K) model was modified to incorporate the change in the shape of the initial yield function with evolution due to anisotropic hardening. Swift’s hardening law along with two different anisotropic yield criteria, namely Hill48 and Yld2000-2d were implemented in the model. The Hill48 yield model was applied with non-associated flow rule to comprehend the effect of variations in both yield stress and R-values. The numerically estimated FLDs were validated after comparing with FLD evaluated through experiments. A low carbon steel was selected, and hemispherical punch stretching test was performed for FLD evaluation. Additionally, the numerically estimated FLDs were incorporated in FE simulations to predict limiting dome heights for validation purpose. Other formability performances like strain distributions over the deformed cup surface were validated with experimental results.

Results of a Neutronic Simulation of HTR-Proteus Core 4.2 using PEBBED and other INL Reactor Physics Tools: FY-09 Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hans D. Gougar

The Idaho National Laboratory’s deterministic neutronics analysis codes and methods were applied to the computation of the core multiplication factor of the HTR-Proteus pebble bed reactor critical facility. A combination of unit cell calculations (COMBINE-PEBDAN), 1-D discrete ordinates transport (SCAMP), and nodal diffusion calculations (PEBBED) were employed to yield keff and flux profiles. Preliminary results indicate that these tools, as currently configured and used, do not yield satisfactory estimates of keff. If control rods are not modeled, these methods can deliver much better agreement with experimental core eigenvalues which suggests that development efforts should focus on modeling control rod andmore » other absorber regions. Under some assumptions and in 1D subcore analyses, diffusion theory agrees well with transport. This suggests that developments in specific areas can produce a viable core simulation approach. Some corrections have been identified and can be further developed, specifically: treatment of the upper void region, treatment of inter-pebble streaming, and explicit (multiscale) transport modeling of TRISO fuel particles as a first step in cross section generation. Until corrections are made that yield better agreement with experiment, conclusions from core design and burnup analyses should be regarded as qualitative and not benchmark quality.« less

Ground-water data for the alluvial, buried channel, Basel Pleistocene and Dakota aquifer in West-Central Iowa

USGS Publications Warehouse

Hunt, Pamela K.B.; Runkle, Donna L.

1985-01-01

The purpose of this investigation was to determine the availability, quantity and quality of groundwater from three principal aquifers in West-Central Iowa, the alluvial, buried channel, Basal Pleistocene and the Dakota aquifers. Specific objectives were to: (1) determine the location, extent and the nature of these aquifers; (2) evaluate the occurrence and movement of groundwater, including the sources of recharge and discharge; (3) estimate the quantities of water stored in the aquifers; (4) estimate the potential yields of wells tapping the aquifers; (5) estimate the water use; and (6) describe the chemical quality of the groundwater. This report is the compilation of the data collected during the investigation and has the purpose of providing a reference for an interpretive report describing groundwater resources and a bedrock topography map of the study area.

Yield of bedrock wells in the Nashoba terrane, central and eastern Massachusetts

USGS Publications Warehouse

DeSimone, Leslie A.; Barbaro, Jeffrey R.

2012-01-01

The yield of bedrock wells in the fractured-bedrock aquifers of the Nashoba terrane and surrounding area, central and eastern Massachusetts, was investigated with analyses of existing data. Reported well yield was compiled for 7,287 wells from Massachusetts Department of Environmental Protection and U.S. Geological Survey databases. Yield of these wells ranged from 0.04 to 625 gallons per minute. In a comparison with data from 103 supply wells, yield and specific capacity from aquifer tests were well correlated, indicating that reported well yield was a reasonable measure of aquifer characteristics in the study area. Statistically significant relations were determined between well yield and a number of cultural and hydrogeologic factors. Cultural variables included intended water use, well depth, year of construction, and method of yield measurement. Bedrock geology, topography, surficial geology, and proximity to surface waters were statistically significant hydrogeologic factors. Yield of wells was higher in areas of granites, mafic intrusive rocks, and amphibolites than in areas of schists and gneisses or pelitic rocks; higher in valleys and low-slope areas than on hills, ridges, or high slopes; higher in areas overlain by stratified glacial deposits than in areas overlain by till; and higher in close proximity to streams, ponds, and wetlands than at greater distances from these surface-water features. Proximity to mapped faults and to lineaments from aerial photographs also were related to well yield by some measures in three quadrangles in the study area. Although the statistical significance of these relations was high, their predictive power was low, and these relations explained little of the variability in the well-yield data. Similar results were determined from a multivariate regression analysis. Multivariate regression models for the Nashoba terrane and for a three-quadrangle subarea included, as significant variables, many of the cultural and hydrogeologic factors that were individually related to well yield, in ways that are consistent with conceptual understanding of their effects, but the models explained only 21 percent (regional model for the entire terrane) and 30 percent (quadrangle model) of the overall variance in yield. Moreover, most of the explained variance was due to well characteristics rather than hydrogeologic factors. Hydrogeologic factors such as topography and geology are likely important. However, the overall high variability in the well-yield data, which results from the high variability in aquifer hydraulic properties as well as from limitations of the dataset, would make it difficult to use hydrogeologic factors to predict well yield in the study area. Geostatistical analysis (variograms), on the other hand, indicated that, although highly variable, the well-yield data are spatially correlated. The spatial continuity appears greater in the northeast-southwest direction and less in the southeast-northwest direction, directions that are parallel and perpendicular, respectively, to the regional geologic structural trends. Geostatistical analysis (kriging), used to estimate yield values throughout the study area, identified regional-scale areas of higher and lower yield that may be related to regional structural features—in particular, to a northeast-southwest trending regional fault zone within the Nashoba terrane. It also would be difficult to use kriging to predict yield at specific locations, however, because of the spatial variability in yield, particularly at small scales. The regional-scale analyses in this study, both with hydrogeologic variables and geostatistics, provide a context for understanding the variability in well yield, rather a basis for precise predictions, and site-specific information would be needed to understand local conditions.

Estimation of corn yield using multi-temporal optical and radar satellite data and artificial neural networks

NASA Astrophysics Data System (ADS)

Fieuzal, R.; Marais Sicre, C.; Baup, F.

2017-05-01

The yield forecasting of corn constitutes a key issue in agricultural management, particularly in the context of demographic pressure and climate change. This study presents two methods to estimate yields using artificial neural networks: a diagnostic approach based on all the satellite data acquired throughout the agricultural season, and a real-time approach, where estimates are updated after each image was acquired in the microwave and optical domains (Formosat-2, Spot-4/5, TerraSAR-X, and Radarsat-2) throughout the crop cycle. The results are based on the Multispectral Crop Monitoring experimental campaign conducted by the CESBIO (Centre d'Études de la BIOsphère) laboratory in 2010 over an agricultural region in southwestern France. Among the tested sensor configurations (multi-frequency, multi-polarization or multi-source data), the best yield estimation performance (using the diagnostic approach) is obtained with reflectance acquired in the red wavelength region, with a coefficient of determination of 0.77 and an RMSE of 6.6 q ha-1. In the real-time approach the combination of red reflectance and CHH backscattering coefficients provides the best compromise between the accuracy and earliness of the yield estimate (more than 3 months before the harvest), with an R2 of 0.69 and an RMSE of 7.0 q ha-1 during the development of the central stem. The two best yield estimates are similar in most cases (for more than 80% of the monitored fields), and the differences are related to discrepancies in the crop growth cycle and/or the consequences of pests.

Soils Activity Mobility Study: Methodology and Application

DOE Office of Scientific and Technical Information (OSTI.GOV)

None, None

2014-09-29

This report presents a three-level approach for estimation of sediment transport to provide an assessment of potential erosion risk for sites at the Nevada National Security Site (NNSS) that are posted for radiological purposes and where migration is suspected or known to occur due to storm runoff. Based on the assessed risk, the appropriate level of effort can be determined for analysis of radiological surveys, field experiments to quantify erosion and transport rates, and long-term monitoring. The method is demonstrated at contaminated sites, including Plutonium Valley, Shasta, Smoky, and T-1. The Pacific Southwest Interagency Committee (PSIAC) procedure is selected asmore » the Level 1 analysis tool. The PSIAC method provides an estimation of the total annual sediment yield based on factors derived from the climatic and physical characteristics of a watershed. If the results indicate low risk, then further analysis is not warranted. If the Level 1 analysis indicates high risk or is deemed uncertain, a Level 2 analysis using the Modified Universal Soil Loss Equation (MUSLE) is proposed. In addition, if a sediment yield for a storm event rather than an annual sediment yield is needed, then the proposed Level 2 analysis should be performed. MUSLE only provides sheet and rill erosion estimates. The U.S. Army Corps of Engineers Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) provides storm peak runoff rate and storm volumes, the inputs necessary for MUSLE. Channel Sediment Transport (CHAN-SED) I and II models are proposed for estimating sediment deposition or erosion in a channel reach from a storm event. These models require storm hydrograph associated sediment concentration and bed load particle size distribution data. When the Level 2 analysis indicates high risk for sediment yield and associated contaminant migration or when there is high uncertainty in the Level 2 results, the sites can be further evaluated with a Level 3 analysis using more complex and labor- and data-intensive methods. For the watersheds analyzed in this report using the Level 1 PSIAC method, the risk of erosion is low. The field reconnaissance surveys of these watersheds confirm the conclusion that the sediment yield of undisturbed areas at the NNSS would be low. The climate, geology, soils, ground cover, land use, and runoff potential are similar among these watersheds. There are no well-defined ephemeral channels except at the Smoky and Plutonium Valley sites. Topography seems to have the strongest influence on sediment yields, as sediment yields are higher on the steeper hill slopes. Lack of measured sediment yield data at the NNSS does not allow for a direct evaluation of the yield estimates by the PSIAC method. Level 2 MUSLE estimates in all the analyzed watersheds except Shasta are a small percentage of the estimates from PSIAC because MUSLE is not inclusive of channel erosion. This indicates that channel erosion dominates the total sediment yield in these watersheds. Annual sediment yields for these watersheds are estimated using the CHAN-SEDI and CHAN-SEDII channel sediment transport models. Both transport models give similar results and exceed the estimates obtained from PSIAC and MUSLE. It is recommended that the total watershed sediment yield of watersheds at the NNSS with flow channels be obtained by adding the washload estimate (rill and inter-rill erosion) from MUSLE to that obtained from channel transport models (bed load and suspended sediment). PSIAC will give comparable results if factor scores for channel erosion are revised towards the high erosion level. Application of the Level 3 process-based models to estimate sediment yields at the NNSS cannot be recommended at this time. Increased model complexity alone will not improve the certainty of the sediment yield estimates. Models must be calibrated against measured data before model results are accepted as certain. Because no measurements of sediment yields at the NNSS are available, model validation cannot be performed. This is also true for the models used in the Level 2 analyses presented in this study. The need to calibrate MUSLE to local conditions has been discussed. Likewise, the transport equations of CHAN-SEDI and CHAN-SEDII need to be calibrated against local data to assess their applicability under semi-arid conditions and for the ephemeral channels at the NNSS. Before these validations and calibration exercises can be undertaken, a long-term measured sediment yield data set must be developed. Development of long-term measured sediment yield data cannot be overemphasized. Long-term monitoring is essential for accurate characterization of watershed processes. It is recommended that a long-term monitoring program be set up to measure watershed erosion rates and channel sediment transport rates.« less

Growth and yield predictions for upland oak stands. 10 years after initial thinning

Treesearch

Martin E. Dale; Martin E. Dale

1972-01-01

The purpose of this paper is to furnish part of the needed information, that is, quantitative estimates of growth and yield 10 years after initial thinning of upland oak stands. All estimates are computed from a system of equations. These predictions are presented here in tabular form for convenient visual inspection of growth and yield trends. The tables show growth...

Spectral estimates of intercepted solar radiation by corn and soybean canopies

NASA Technical Reports Server (NTRS)

Gallo, K. P.; Brooks, C. C.; Daughtry, C. S. T.; Bauer, M. E.; Vanderbilt, V. C.

1982-01-01

Attention is given to the development of methods for combining spectral and meteorological data in crop yield models which are capable of providing accurate estimates of crop condition and yields throughout the growing season. The present investigation is concerned with initial tests of these concepts using spectral and agronomic data acquired in controlled experiments. The data were acquired at the Purdue University Agronomy Farm, 10 km northwest of West Lafayette, Indiana. Data were obtained throughout several growing seasons for corn and soybeans. Five methods or models for predicting yields were examined. On the basis of the obtained results, it is concluded that estimating intercepted solar radiation using spectral data is a viable approach for merging spectral and meteorological data in crop yield models.

Comparison of statistical models for analyzing wheat yield time series.

PubMed

Michel, Lucie; Makowski, David

2013-01-01

The world's population is predicted to exceed nine billion by 2050 and there is increasing concern about the capability of agriculture to feed such a large population. Foresight studies on food security are frequently based on crop yield trends estimated from yield time series provided by national and regional statistical agencies. Various types of statistical models have been proposed for the analysis of yield time series, but the predictive performances of these models have not yet been evaluated in detail. In this study, we present eight statistical models for analyzing yield time series and compare their ability to predict wheat yield at the national and regional scales, using data provided by the Food and Agriculture Organization of the United Nations and by the French Ministry of Agriculture. The Holt-Winters and dynamic linear models performed equally well, giving the most accurate predictions of wheat yield. However, dynamic linear models have two advantages over Holt-Winters models: they can be used to reconstruct past yield trends retrospectively and to analyze uncertainty. The results obtained with dynamic linear models indicated a stagnation of wheat yields in many countries, but the estimated rate of increase of wheat yield remained above 0.06 t ha⁻¹ year⁻¹ in several countries in Europe, Asia, Africa and America, and the estimated values were highly uncertain for several major wheat producing countries. The rate of yield increase differed considerably between French regions, suggesting that efforts to identify the main causes of yield stagnation should focus on a subnational scale.

Estimates of genetic and environmental (co)variances for first lactation on milk yield, survival, and calving interval.

PubMed

Dong, M C; van Vleck, L D

1989-03-01

Variance and covariance components for milk yield, survival to second freshening, calving interval in first lactation were estimated by REML with the expectation and maximization algorithm for an animal model which included herd-year-season effects. Cows without calving interval but with milk yield were included. Each of the four data sets of 15 herds included about 3000 Holstein cows. Relationships across herds were ignored to enable inversion of the coefficient matrix of mixed model equations. Quadratics and their expectations were accumulated herd by herd. Heritability of milk yield (.32) agrees with reports by same methods. Heritabilities of survival (.11) and calving interval(.15) are slightly larger and genetic correlations smaller than results from different methods of estimation. Genetic correlation between milk yield and calving interval (.09) indicates genetic ability to produce more milk is lightly associated with decreased fertility.

A Comparison of Machine Learning Approaches for Corn Yield Estimation

NASA Astrophysics Data System (ADS)

Kim, N.; Lee, Y. W.

2017-12-01

Machine learning is an efficient empirical method for classification and prediction, and it is another approach to crop yield estimation. The objective of this study is to estimate corn yield in the Midwestern United States by employing the machine learning approaches such as the support vector machine (SVM), random forest (RF), and deep neural networks (DNN), and to perform the comprehensive comparison for their results. We constructed the database using satellite images from MODIS, the climate data of PRISM climate group, and GLDAS soil moisture data. In addition, to examine the seasonal sensitivities of corn yields, two period groups were set up: May to September (MJJAS) and July and August (JA). In overall, the DNN showed the highest accuracies in term of the correlation coefficient for the two period groups. The differences between our predictions and USDA yield statistics were about 10-11 %.

Algorithms for Brownian first-passage-time estimation

NASA Astrophysics Data System (ADS)

Adib, Artur B.

2009-09-01

A class of algorithms in discrete space and continuous time for Brownian first-passage-time estimation is considered. A simple algorithm is derived that yields exact mean first-passage times (MFPTs) for linear potentials in one dimension, regardless of the lattice spacing. When applied to nonlinear potentials and/or higher spatial dimensions, numerical evidence suggests that this algorithm yields MFPT estimates that either outperform or rival Langevin-based (discrete time and continuous space) estimates.

Sedimentation and Its Impacts/Effects on River System and Reservoir Water Quality: case Study of Mazowe Catchment, Zimbabwe

NASA Astrophysics Data System (ADS)

Tundu, Colleta; Tumbare, Michael James; Kileshye Onema, Jean-Marie

2018-04-01

Sediment delivery into water sources and bodies results in the reduction of water quantity and quality, increasing costs of water purification whilst reducing the available water for various other uses. The paper gives an analysis of sedimentation in one of Zimbabwe's seven rivers, the Mazowe Catchment, and its impact on water quality. The Revised Universal Soil Loss Equation (RUSLE) model was used to compute soil lost from the catchment as a result of soil erosion. The model was used in conjunction with GIS remotely sensed data and limited ground observations. The estimated annual soil loss in the catchment indicates soil loss ranging from 0 to 65 t ha yr-1. Bathymetric survey at Chimhanda Dam showed that the capacity of the dam had reduced by 39 % as a result of sedimentation and the annual sediment deposition into Chimhanda Dam was estimated to be 330 t with a specific yield of 226 t km-2 yr-1. Relationship between selected water quality parameters, TSS, DO, NO3, pH, TDS, turbidity and sediment yield for selected water sampling points and Chimhanda Dam was analyzed. It was established that there is a strong positive relationship between the sediment yield and the water quality parameters. Sediment yield showed high positive correlation with turbidity (0.63) and TDS (0.64). Water quality data from Chimhanda treatment plant water works revealed that the quality of water is deteriorating as a result of increase in sediment accumulation in the dam. The study concluded that sedimentation can affect the water quality of water sources.

Source Term Estimates of Radioxenon Released from the BaTek Medical Isotope Production Facility Using External Measured Air Concentrations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eslinger, Paul W.; Cameron, Ian M.; Dumais, Johannes R.

2015-10-01

Abstract Batan Teknologi (BaTek) operates an isotope production facility in Serpong, Indonesia that supplies 99mTc for use in medical procedures. Atmospheric releases of Xe-133 in the production process at BaTek are known to influence the measurements taken at the closest stations of the International Monitoring System (IMS). The purpose of the IMS is to detect evidence of nuclear explosions, including atmospheric releases of radionuclides. The xenon isotopes released from BaTek are the same as those produced in a nuclear explosion, but the isotopic ratios are different. Knowledge of the magnitude of releases from the isotope production facility helps inform analystsmore » trying to decide whether a specific measurement result came from a nuclear explosion. A stack monitor deployed at BaTek in 2013 measured releases to the atmosphere for several isotopes. The facility operates on a weekly cycle, and the stack data for June 15-21, 2013 show a release of 1.84E13 Bq of Xe-133. Concentrations of Xe-133 in the air are available at the same time from a xenon sampler located 14 km from BaTek. An optimization process using atmospheric transport modeling and the sampler air concentrations produced a release estimate of 1.88E13 Bq. The same optimization process yielded a release estimate of 1.70E13 Bq for a different week in 2012. The stack release value and the two optimized estimates are all within 10 percent of each other. Weekly release estimates of 1.8E13 Bq and a 40 percent facility operation rate yields a rough annual release estimate of 3.7E13 Bq of Xe-133. This value is consistent with previously published estimates of annual releases for this facility, which are based on measurements at three IMS stations. These multiple lines of evidence cross-validate the stack release estimates and the release estimates from atmospheric samplers.« less

MRI-guided fluorescence tomography of the breast: a phantom study

NASA Astrophysics Data System (ADS)

Davis, Scott C.; Pogue, Brian W.; Dehghani, Hamid; Paulsen, Keith D.

2009-02-01

Tissue phantoms simulating the human breast were used to demonstrate the imaging capabilities of an MRI-coupled fluorescence molecular tomography (FMT) imaging system. Specifically, phantoms with low tumor-to-normal drug contrast and complex internal structure were imaged with the MR-coupled FMT system. Images of indocyanine green (ICG) fluorescence yield were recovered using a diffusion model-based approach capable of estimating the distribution of fluorescence activity in a tissue volume from tissue-boundary measurements of transmitted light. Tissue structural information, which can be determined from standard T1 and T2 MR images, was used to guide the recovery of fluorescence activity. The study revealed that this spatial guidance is critical for recovering images of fluorescence yield in tissue with low tumor-to-normal drug contrast.

The feasibility of a regional CTDI{sub vol} to estimate organ dose from tube current modulated CT exams

DOE Office of Scientific and Technical Information (OSTI.GOV)

Khatonabadi, Maryam; Kim, Hyun J.; Lu, Peiyun

Purpose: In AAPM Task Group 204, the size-specific dose estimate (SSDE) was developed by providing size adjustment factors which are applied to the Computed Tomography (CT) standardized dose metric, CTDI{sub vol}. However, that work focused on fixed tube current scans and did not specifically address tube current modulation (TCM) scans, which are currently the majority of clinical scans performed. The purpose of this study was to extend the SSDE concept to account for TCM by investigating the feasibility of using anatomic and organ specific regions of scanner output to improve accuracy of dose estimates. Methods: Thirty-nine adult abdomen/pelvis and 32more » chest scans from clinically indicated CT exams acquired on a multidetector CT using TCM were obtained with Institutional Review Board approval for generating voxelized models. Along with image data, raw projection data were obtained to extract TCM functions for use in Monte Carlo simulations. Patient size was calculated using the effective diameter described in TG 204. In addition, the scanner-reported CTDI{sub vol} (CTDI{sub vol,global}) was obtained for each patient, which is based on the average tube current across the entire scan. For the abdomen/pelvis scans, liver, spleen, and kidneys were manually segmented from the patient datasets; for the chest scans, lungs and for female models only, glandular breast tissue were segmented. For each patient organ doses were estimated using Monte Carlo Methods. To investigate the utility of regional measures of scanner output, regional and organ anatomic boundaries were identified from image data and used to calculate regional and organ-specific average tube current values. From these regional and organ-specific averages, CTDI{sub vol} values, referred to as regional and organ-specific CTDI{sub vol}, were calculated for each patient. Using an approach similar to TG 204, all CTDI{sub vol} values were used to normalize simulated organ doses; and the ability of each normalized dose to correlate with patient size was investigated. Results: For all five organs, the correlations with patient size increased when organ doses were normalized by regional and organ-specific CTDI{sub vol} values. For example, when estimating dose to the liver, CTDI{sub vol,global} yielded a R{sup 2} value of 0.26, which improved to 0.77 and 0.86, when using the regional and organ-specific CTDI{sub vol} for abdomen and liver, respectively. For breast dose, the global CTDI{sub vol} yielded a R{sup 2} value of 0.08, which improved to 0.58 and 0.83, when using the regional and organ-specific CTDI{sub vol} for chest and breasts, respectively. The R{sup 2} values also increased once the thoracic models were separated for the analysis into females and males, indicating differences between genders in this region not explained by a simple measure of effective diameter. Conclusions: This work demonstrated the utility of regional and organ-specific CTDI{sub vol} as normalization factors when using TCM. It was demonstrated that CTDI{sub vol,global} is not an effective normalization factor in TCM exams where attenuation (and therefore tube current) varies considerably throughout the scan, such as abdomen/pelvis and even thorax. These exams can be more accurately assessed for dose using regional CTDI{sub vol} descriptors that account for local variations in scanner output present when TCM is employed.« less

The problem of the second wind turbine - a note on a common but flawed wind power estimation method

NASA Astrophysics Data System (ADS)

Gans, F.; Miller, L. M.; Kleidon, A.

2012-06-01

Several recent wind power estimates suggest that this renewable energy resource can meet all of the current and future global energy demand with little impact on the atmosphere. These estimates are calculated using observed wind speeds in combination with specifications of wind turbine size and density to quantify the extractable wind power. However, this approach neglects the effects of momentum extraction by the turbines on the atmospheric flow that would have effects outside the turbine wake. Here we show with a simple momentum balance model of the atmospheric boundary layer that this common methodology to derive wind power potentials requires unrealistically high increases in the generation of kinetic energy by the atmosphere. This increase by an order of magnitude is needed to ensure momentum conservation in the atmospheric boundary layer. In the context of this simple model, we then compare the effect of three different assumptions regarding the boundary conditions at the top of the boundary layer, with prescribed hub height velocity, momentum transport, or kinetic energy transfer into the boundary layer. We then use simulations with an atmospheric general circulation model that explicitly simulate generation of kinetic energy with momentum conservation. These simulations show that the assumption of prescribed momentum import into the atmospheric boundary layer yields the most realistic behavior of the simple model, while the assumption of prescribed hub height velocity can clearly be disregarded. We also show that the assumptions yield similar estimates for extracted wind power when less than 10% of the kinetic energy flux in the boundary layer is extracted by the turbines. We conclude that the common method significantly overestimates wind power potentials by an order of magnitude in the limit of high wind power extraction. Ultimately, environmental constraints set the upper limit on wind power potential at larger scales rather than detailed engineering specifications of wind turbine design and placement.

Invited review: A commentary on predictive cheese yield formulas.

PubMed

Emmons, D B; Modler, H W

2010-12-01

Predictive cheese yield formulas have evolved from one based only on casein and fat in 1895. Refinements have included moisture and salt in cheese and whey solids as separate factors, paracasein instead of casein, and exclusion of whey solids from moisture associated with cheese protein. The General, Barbano, and Van Slyke formulas were tested critically using yield and composition of milk, whey, and cheese from 22 vats of Cheddar cheese. The General formula is based on the sum of cheese components: fat, protein, moisture, salt, whey solids free of fat and protein, as well as milk salts associated with paracasein. The testing yielded unexpected revelations. It was startling that the sum of components in cheese was <100%; the mean was 99.51% (N × 6.31). The mean predicted yield was only 99.17% as a percentage of actual yields (PY%AY); PY%AY is a useful term for comparisons of yields among vats. The PY%AY correlated positively with the sum of components (SofC) in cheese. The apparent low estimation of SofC led to the idea of adjusting upwards, for each vat, the 5 measured components in the formula by the observed SofC, as a fraction. The mean of the adjusted predicted yields as percentages of actual yields was 99.99%. The adjusted forms of the General, Barbano, and Van Slyke formulas gave predicted yields equal to the actual yields. It was apparent that unadjusted yield formulas did not accurately predict yield; however, unadjusted PY%AY can be useful as a control tool for analyses of cheese and milk. It was unexpected that total milk protein in the adjusted General formula gave the same predicted yields as casein and paracasein, indicating that casein or paracasein may not always be necessary for successful yield prediction. The use of constants for recovery of fat and protein in the adjusted General formula gave adjusted predicted yields equal to actual yields, indicating that analyses of cheese for protein and fat may not always be necessary for yield prediction. Composition of cheese was estimated using a predictive formula; actual yield was needed for estimation of composition. Adjusted formulas are recommended for estimating target yields and cheese yield efficiency. Constants for solute exclusion, protein-associated milk salts, and whey solids could be used and reduced the complexity of the General formula. Normalization of fat recovery increased variability of predicted yields. Copyright © 2010 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Estimating the Effect of Climate Change on Crop Yields and Farmland Values: The Importance of Extreme Temperatures

EPA Pesticide Factsheets

This is a presentation titled Estimating the Effect of Climate Change on Crop Yields and Farmland Values: The Importance of Extreme Temperatures that was given for the National Center for Environmental Economics

The Cost of Crime to Society: New Crime-Specific Estimates for Policy and Program Evaluation

PubMed Central

French, Michael T.; Fang, Hai

2010-01-01

Estimating the cost to society of individual crimes is essential to the economic evaluation of many social programs, such as substance abuse treatment and community policing. A review of the crime-costing literature reveals multiple sources, including published articles and government reports, which collectively represent the alternative approaches for estimating the economic losses associated with criminal activity. Many of these sources are based upon data that are more than ten years old, indicating a need for updated figures. This study presents a comprehensive methodology for calculating the cost of society of various criminal acts. Tangible and intangible losses are estimated using the most current data available. The selected approach, which incorporates both the cost-of-illness and the jury compensation methods, yields cost estimates for more than a dozen major crime categories, including several categories not found in previous studies. Updated crime cost estimates can help government agencies and other organizations execute more prudent policy evaluations, particularly benefit-cost analyses of substance abuse treatment or other interventions that reduce crime. PMID:20071107

The cost of crime to society: new crime-specific estimates for policy and program evaluation.

PubMed

McCollister, Kathryn E; French, Michael T; Fang, Hai

2010-04-01

Estimating the cost to society of individual crimes is essential to the economic evaluation of many social programs, such as substance abuse treatment and community policing. A review of the crime-costing literature reveals multiple sources, including published articles and government reports, which collectively represent the alternative approaches for estimating the economic losses associated with criminal activity. Many of these sources are based upon data that are more than 10 years old, indicating a need for updated figures. This study presents a comprehensive methodology for calculating the cost to society of various criminal acts. Tangible and intangible losses are estimated using the most current data available. The selected approach, which incorporates both the cost-of-illness and the jury compensation methods, yields cost estimates for more than a dozen major crime categories, including several categories not found in previous studies. Updated crime cost estimates can help government agencies and other organizations execute more prudent policy evaluations, particularly benefit-cost analyses of substance abuse treatment or other interventions that reduce crime. Copyright 2010 Elsevier Ireland Ltd. All rights reserved.

Nascent energy distribution of the Criegee intermediate CH2OO from direct dynamics calculations of primary ozonide dissociation.

PubMed

Pfeifle, Mark; Ma, Yong-Tao; Jasper, Ahren W; Harding, Lawrence B; Hase, William L; Klippenstein, Stephen J

2018-05-07

Ozonolysis produces chemically activated carbonyl oxides (Criegee intermediates, CIs) that are either stabilized or decompose directly. This branching has an important impact on atmospheric chemistry. Prior theoretical studies have employed statistical models for energy partitioning to the CI arising from dissociation of the initially formed primary ozonide (POZ). Here, we used direct dynamics simulations to explore this partitioning for decomposition of c-C 2 H 4 O 3 , the POZ in ethylene ozonolysis. A priori estimates for the overall stabilization probability were then obtained by coupling the direct dynamics results with master equation simulations. Trajectories were initiated at the concerted cycloreversion transition state, as well as the second transition state of a stepwise dissociation pathway, both leading to a CI (H 2 COO) and formaldehyde (H 2 CO). The resulting CI energy distributions were incorporated in master equation simulations of CI decomposition to obtain channel-specific stabilized CI (sCI) yields. Master equation simulations of POZ formation and decomposition, based on new high-level electronic structure calculations, were used to predict yields for the different POZ decomposition channels. A non-negligible contribution of stepwise POZ dissociation was found, and new mechanistic aspects of this pathway were elucidated. By combining the trajectory-based channel-specific sCI yields with the channel branching fractions, an overall sCI yield of (48 ± 5)% was obtained. Non-statistical energy release was shown to measurably affect sCI formation, with statistical models predicting significantly lower overall sCI yields (∼30%). Within the range of experimental literature values (35%-54%), our trajectory-based calculations favor those clustered at the upper end of the spectrum.

Nascent energy distribution of the Criegee intermediate CH2OO from direct dynamics calculations of primary ozonide dissociation

NASA Astrophysics Data System (ADS)

Pfeifle, Mark; Ma, Yong-Tao; Jasper, Ahren W.; Harding, Lawrence B.; Hase, William L.; Klippenstein, Stephen J.

2018-05-01

Ozonolysis produces chemically activated carbonyl oxides (Criegee intermediates, CIs) that are either stabilized or decompose directly. This branching has an important impact on atmospheric chemistry. Prior theoretical studies have employed statistical models for energy partitioning to the CI arising from dissociation of the initially formed primary ozonide (POZ). Here, we used direct dynamics simulations to explore this partitioning for decomposition of c-C2H4O3, the POZ in ethylene ozonolysis. A priori estimates for the overall stabilization probability were then obtained by coupling the direct dynamics results with master equation simulations. Trajectories were initiated at the concerted cycloreversion transition state, as well as the second transition state of a stepwise dissociation pathway, both leading to a CI (H2COO) and formaldehyde (H2CO). The resulting CI energy distributions were incorporated in master equation simulations of CI decomposition to obtain channel-specific stabilized CI (sCI) yields. Master equation simulations of POZ formation and decomposition, based on new high-level electronic structure calculations, were used to predict yields for the different POZ decomposition channels. A non-negligible contribution of stepwise POZ dissociation was found, and new mechanistic aspects of this pathway were elucidated. By combining the trajectory-based channel-specific sCI yields with the channel branching fractions, an overall sCI yield of (48 ± 5)% was obtained. Non-statistical energy release was shown to measurably affect sCI formation, with statistical models predicting significantly lower overall sCI yields (˜30%). Within the range of experimental literature values (35%-54%), our trajectory-based calculations favor those clustered at the upper end of the spectrum.

Methods for Remote Determination of CO2 Emissions

DTIC Science & Technology

2011-01-01

support monitoring of compliance with international agreements. • It is difficult to predict when direct measurements of CO2 will yield useful emission...level of reasonable prior information, which is combined with the direct measurements to yield an emissions estimate. This prior information might...infrastructure of a country could yield a “proxy” estimate of CO2 emissions by assuming emission factors for various supply and demand sectors a

Estimation of monthly water yields and flows for 1951-2012 for the United States portion of the Great Lakes Basin with AFINCH

USGS Publications Warehouse

Luukkonen, Carol L.; Holtschlag, David J.; Reeves, Howard W.; Hoard, Christopher J.; Fuller, Lori M.

2015-01-01

Monthly water yields from 105,829 catchments and corresponding flows in 107,691 stream segments were estimated for water years 1951–2012 in the Great Lakes Basin in the United States. Both sets of estimates were computed by using the Analysis of Flows In Networks of CHannels (AFINCH) application within the NHDPlus geospatial data framework. AFINCH provides an environment to develop constrained regression models to integrate monthly streamflow and water-use data with monthly climatic data and fixed basin characteristics data available within NHDPlus or supplied by the user. For this study, the U.S. Great Lakes Basin was partitioned into seven study areas by grouping selected hydrologic subregions and adjoining cataloguing units. This report documents the regression models and data used to estimate monthly water yields and flows in each study area. Estimates of monthly water yields and flows are presented in a Web-based mapper application. Monthly flow time series for individual stream segments can be retrieved from the Web application and used to approximate monthly flow-duration characteristics and to identify possible trends.

Yield of active screening for tuberculosis among asylum seekers in Germany: a systematic review and meta-analysis

PubMed Central

Bozorgmehr, Kayvan; Razum, Oliver; Saure, Daniel; Joggerst, Brigitte; Szecsenyi, Joachim; Stock, Christian

2017-01-01

All asylum seekers in Germany undergo upon-entry screening for tuberculosis TB, but comprehensive evidence on the yield is lacking. We compared the national estimates with the international literature in a systematic review and meta-analysis of studies reporting the yield of TB, defined as the fraction of active TB cases detected among asylum seekers screened in Germany upon entry. We searched 11 national and international databases for empirical studies and the internet for grey literature published in English or German without restrictions on publication time. Among 1,253 screened articles, we identified six articles reporting the yield of active TB based on German data, ranging from 0.72 (95% confidence interval (CI): 0.45–1.10) to 6.41 (95% CI: 4.19–9.37) per 1,000 asylum seekers. The pooled estimate across all studies was 3.47 (95% CI: 1.78–5.73; I2 = 94.9%; p < 0.0001) per 1,000 asylum seekers. This estimate was in line with international evidence (I2 = 0%; p for heterogeneity 0.55). The meta-analysis of available international estimates resulted in a pooled yield of 3.04 (95% CI: 2.24–3.96) per 1,000. This study provides an estimate across several German federal states for the yield of TB screening in asylum seekers. Further research is needed to develop more targeted screening programmes. PMID:28367795

Graphical user interface for yield and dose estimations for cyclotron-produced technetium

NASA Astrophysics Data System (ADS)

Hou, X.; Vuckovic, M.; Buckley, K.; Bénard, F.; Schaffer, P.; Ruth, T.; Celler, A.

2014-07-01

The cyclotron-based 100Mo(p,2n)99mTc reaction has been proposed as an alternative method for solving the shortage of 99mTc. With this production method, however, even if highly enriched molybdenum is used, various radioactive and stable isotopes will be produced simultaneously with 99mTc. In order to optimize reaction parameters and estimate potential patient doses from radiotracers labeled with cyclotron produced 99mTc, the yields for all reaction products must be estimated. Such calculations, however, are extremely complex and time consuming. Therefore, the objective of this study was to design a graphical user interface (GUI) that would automate these calculations, facilitate analysis of the experimental data, and predict dosimetry. The resulting GUI, named Cyclotron production Yields and Dosimetry (CYD), is based on Matlab®. It has three parts providing (a) reaction yield calculations, (b) predictions of gamma emissions and (c) dosimetry estimations. The paper presents the outline of the GUI, lists the parameters that must be provided by the user, discusses the details of calculations and provides examples of the results. Our initial experience shows that the proposed GUI allows the user to very efficiently calculate the yields of reaction products and analyze gamma spectroscopy data. However, it is expected that the main advantage of this GUI will be at the later clinical stage when entering reaction parameters will allow the user to predict production yields and estimate radiation doses to patients for each particular cyclotron run.

Graphical user interface for yield and dose estimations for cyclotron-produced technetium.

PubMed

Hou, X; Vuckovic, M; Buckley, K; Bénard, F; Schaffer, P; Ruth, T; Celler, A

2014-07-07

The cyclotron-based (100)Mo(p,2n)(99m)Tc reaction has been proposed as an alternative method for solving the shortage of (99m)Tc. With this production method, however, even if highly enriched molybdenum is used, various radioactive and stable isotopes will be produced simultaneously with (99m)Tc. In order to optimize reaction parameters and estimate potential patient doses from radiotracers labeled with cyclotron produced (99m)Tc, the yields for all reaction products must be estimated. Such calculations, however, are extremely complex and time consuming. Therefore, the objective of this study was to design a graphical user interface (GUI) that would automate these calculations, facilitate analysis of the experimental data, and predict dosimetry. The resulting GUI, named Cyclotron production Yields and Dosimetry (CYD), is based on Matlab®. It has three parts providing (a) reaction yield calculations, (b) predictions of gamma emissions and (c) dosimetry estimations. The paper presents the outline of the GUI, lists the parameters that must be provided by the user, discusses the details of calculations and provides examples of the results. Our initial experience shows that the proposed GUI allows the user to very efficiently calculate the yields of reaction products and analyze gamma spectroscopy data. However, it is expected that the main advantage of this GUI will be at the later clinical stage when entering reaction parameters will allow the user to predict production yields and estimate radiation doses to patients for each particular cyclotron run.

Multidimensional density shaping by sigmoids.

PubMed

Roth, Z; Baram, Y

1996-01-01

An estimate of the probability density function of a random vector is obtained by maximizing the output entropy of a feedforward network of sigmoidal units with respect to the input weights. Classification problems can be solved by selecting the class associated with the maximal estimated density. Newton's optimization method, applied to the estimated density, yields a recursive estimator for a random variable or a random sequence. A constrained connectivity structure yields a linear estimator, which is particularly suitable for "real time" prediction. A Gaussian nonlinearity yields a closed-form solution for the network's parameters, which may also be used for initializing the optimization algorithm when other nonlinearities are employed. A triangular connectivity between the neurons and the input, which is naturally suggested by the statistical setting, reduces the number of parameters. Applications to classification and forecasting problems are demonstrated.

Reliable evaluation of the quantal determinants of synaptic efficacy using Bayesian analysis

PubMed Central

Beato, M.

2013-01-01

Communication between neurones in the central nervous system depends on synaptic transmission. The efficacy of synapses is determined by pre- and postsynaptic factors that can be characterized using quantal parameters such as the probability of neurotransmitter release, number of release sites, and quantal size. Existing methods of estimating the quantal parameters based on multiple probability fluctuation analysis (MPFA) are limited by their requirement for long recordings to acquire substantial data sets. We therefore devised an algorithm, termed Bayesian Quantal Analysis (BQA), that can yield accurate estimates of the quantal parameters from data sets of as small a size as 60 observations for each of only 2 conditions of release probability. Computer simulations are used to compare its performance in accuracy with that of MPFA, while varying the number of observations and the simulated range in release probability. We challenge BQA with realistic complexities characteristic of complex synapses, such as increases in the intra- or intersite variances, and heterogeneity in release probabilities. Finally, we validate the method using experimental data obtained from electrophysiological recordings to show that the effect of an antagonist on postsynaptic receptors is correctly characterized by BQA by a specific reduction in the estimates of quantal size. Since BQA routinely yields reliable estimates of the quantal parameters from small data sets, it is ideally suited to identify the locus of synaptic plasticity for experiments in which repeated manipulations of the recording environment are unfeasible. PMID:23076101

Crop yields response to water pressures in the Ebro basin in Spain: risk and water policy implications

NASA Astrophysics Data System (ADS)

Quiroga, S.; Fernández-Haddad, Z.; Iglesias, A.

2011-02-01

The increasing pressure on water systems in the Mediterranean enhances existing water conflicts and threatens water supply for agriculture. In this context, one of the main priorities for agricultural research and public policy is the adaptation of crop yields to water pressures. This paper focuses on the evaluation of hydrological risk and water policy implications for food production. Our methodological approach includes four steps. For the first step, we estimate the impacts of rainfall and irrigation water on crop yields. However, this study is not limited to general crop production functions since it also considers the linkages between those economic and biophysical aspects which may have an important effect on crop productivity. We use statistical models of yield response to address how hydrological variables affect the yield of the main Mediterranean crops in the Ebro river basin. In the second step, this study takes into consideration the effects of those interactions and analyzes gross value added sensitivity to crop production changes. We then use Montecarlo simulations to characterize crop yield risk to water variability. Finally we evaluate some policy scenarios with irrigated area adjustments that could cope in a context of increased water scarcity. A substantial decrease in irrigated land, of up to 30% of total, results in only moderate losses of crop productivity. The response is crop and region specific and may serve to prioritise adaptation strategies.

Streamflow, water quality, and constituent loads and yields, Scituate Reservoir Drainage Area, Rhode Island, water year 2015

USGS Publications Warehouse

Smith, Kirk P.

2018-05-11

Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate loads of sodium and chloride during water year (WY) 2015 (October 1, 2014, through September 30, 2015) for tributaries to the Scituate Reservoir, Rhode Island. Streamflow and water-quality data used in the study were collected by the U.S. Geological Survey and the Providence Water Supply Board. Streamflow was measured or estimated by the U.S. Geological Survey following standard methods at 23 streamgages; 14 of these streamgages are equipped with instrumentation capable of continuously monitoring water level, specific conductance, and water temperature. Water-quality samples were collected at 36 sampling stations by the Providence Water Supply Board and at 14 continuous-record streamgages by the U.S. Geological Survey during WY 2015 as part of a long-term sampling program; all stations are in the Scituate Reservoir drainage area. Water-quality data collected by the Providence Water Supply Board are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2015.The largest tributary to the reservoir (the Ponaganset River, which was monitored by the U.S. Geological Survey) contributed a mean streamflow of 25 cubic feet per second to the reservoir during WY 2015. For the same time period, annual mean streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.38 to about 14 cubic feet per second. Together, tributaries (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 1,500,000 kilograms of sodium and 2,400,000 kilograms of chloride to the Scituate Reservoir during WY 2015; sodium and chloride yields for the tributaries ranged from 8,000 to 54,000 kilograms per square mile and from 12,000 to 91,000 kilograms per square mile, respectively.At the stations where water-quality samples were collected by the Providence Water Supply Board, the medians of the median concentrations were the following: for chloride, 29.5 milligrams per liter; for nitrite, 0.002 milligrams per liter as nitrogen; for nitrate, 0.05 milligrams per liter as nitrogen; for orthophosphate, 0.08 milligrams per liter as phosphate; and for total coliform bacteria and Escherichia coli, 440 and 20 colony forming units per 100 milliliters, respectively. The medians of the median daily loads (and yields) of chloride, nitrite, nitrate, orthophosphate, and total coliform and Escherichia coli bacteria were 170 kilograms per day (79 kilograms per day per square mile), 14 grams per day (5.2 grams per day per square mile), 670 grams per day (190 grams per day per square mile), 640 grams per day (210 grams per day per square mile), 18,000 million colony forming units per day (7,600 million colony forming units per day per square mile), and 1,200 million colony forming units per day (810 million colony forming units per day per square mile), respectively.

Streamflow, water quality and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2014

USGS Publications Warehouse

Smith, Kirk P.

2016-05-03

Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate loads of sodium and chloride during water year (WY) 2014 (October 1, 2013, through September 30, 2014) for tributaries to the Scituate Reservoir, Rhode Island. Streamflow and water-quality data used in the study were collected by the U.S. Geological Survey and the Providence Water Supply Board in the cooperative study. Streamflow was measured or estimated by the U.S. Geological Survey following standard methods at 23 streamgages; 14 of these streamgages are equipped with instrumentation capable of continuously monitoring water level, specific conductance, and water temperature. Water-quality samples were collected at 37 sampling stations by the Providence Water Supply Board and at 14 continuous-record streamgages by the U.S. Geological Survey during WY 2014 as part of a long-term sampling program; all stations are in the Scituate Reservoir drainage area. Water-quality data collected by the Providence Water Supply Board are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2014.The largest tributary to the reservoir (the Ponaganset River, which was monitored by the U.S. Geological Survey) contributed a mean streamflow of 23 cubic feet per second to the reservoir during WY 2014. For the same time period, annual mean streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.35 to about 14 cubic feet per second. Together, tributaries (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 1,200,000 kilograms of sodium and 2,100,000 kilograms of chloride to the Scituate Reservoir during WY 2014; sodium and chloride yields for the tributaries ranged from 7,700 to 45,000 kilograms per year per square mile and from 12,000 to 75,000 kilograms per year per square mile, respectively.At the stations where water-quality samples were collected by the Providence Water Supply Board, the median of the median chloride concentrations was 24 milligrams per liter, median nitrite concentration was 0.002 milligrams per liter as nitrogen (N), median nitrate concentration was 0.01 milligrams per liter as N, median orthophosphate concentration was 0.07 milligrams per liter as phosphate, and median concentrations of total coliform bacteria and Escherichia coli were 320 and 20 colony forming units per 100 milliliters, respectively. The medians of the median daily loads (and yields) of chloride, nitrite, nitrate, orthophosphate, and total coliform and Escherichia coli bacteria were 62 kilograms per day (42 kilograms per day per square mile), 19 grams per day (6.1 grams per day per square mile), 79 grams per day (36 grams per day per square mile), 380 grams per day (150 grams per day per square mile), 13,000 million colony forming units per day (8,300 million colony forming units per day per square mile), and 1,000 million colony forming units per day (470 million colony forming units per day per square mile), respectively.

Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2012

USGS Publications Warehouse

Smith, Kirk P.

2014-01-01

Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate loads of sodium and chloride during water year (WY) 2012 (October 1, 2011, through September 30, 2012), for tributaries to the Scituate Reservoir, Rhode Island. Streamflow and water-quality data used in the study were collected by the U.S. Geological Survey (USGS) or the Providence Water Supply Board (PWSB). Streamflow was measured or estimated by the USGS following standard methods at 23 streamgages; 14 of these streamgages were equipped with instrumentation capable of continuously monitoring water level, specific conductance, and water temperature. Water-quality samples were collected at 37 sampling stations by the PWSB and at 14 continuous-record streamgages by the USGS during WY 2012 as part of a long-term sampling program; all stations were in the Scituate Reservoir drainage area. Water-quality data collected by the PWSB were summarized by using values of central tendency and used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2012. The largest tributary to the reservoir (the Ponaganset River, which was monitored by the USGS) contributed a mean streamflow of about 26 cubic feet per second (ft3/s) to the reservoir during WY 2012. For the same time period, annual mean1 streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.40 to about 17 ft3/s. Together, tributaries (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 1,100,000 kilograms (kg) of sodium and 1,900,000 kg of chloride to the Scituate Reservoir during WY 2012; sodium and chloride yields for the tributaries ranged from 8,700 to 51,000 kilograms per square mile (kg/mi2) and from 14,000 to 87,000 kg/mi2, respectively. At the stations where water-quality samples were collected by the PWSB, the median of the median chloride concentrations was 19 milligrams per liter (mg/L), median nitrite concentration was 0.002 mg/L as nitrogen (N), median nitrate concentration was less than 0.01 mg/L as N, median orthophosphate concentration was 0.06 mg/L as phosphorus, and median concentrations of total coliform and Escherichia coli (E. coli) bacteria were 43 and 16 colony forming units per 100 milliliters (CFU/100mL), respectively. The medians of the median daily loads (and yields) of chloride, nitrite, nitrate, orthophosphate, and total coliform and E. coli bacteria were 200 kilograms per day (kg/d) (71 kilograms per day per square mile (kg/d/mi2)); 15 grams per day (g/d) (5.4 grams per day per square mile (g/d/mi2)); 100 g/d (38 g/d/mi2); 500 g/d (260 g/d/mi2); 4,300 million colony forming units per day (CFUx106/d) (1,500 CFUx106/d/mi2); and 1,000 CFUx106/d (360 CFUx106/d/mi2), respectively.

Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2011

USGS Publications Warehouse

Smith, Kirk P.

2013-01-01

Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate loads of sodium and chloride during water year (WY) 2011 (October 1, 2010, to September 30, 2011), for tributaries to the Scituate Reservoir, Rhode Island. Streamflow and water-quality data used in the study were collected by the U.S. Geological Survey (USGS) or the Providence Water Supply Board (PWSB). Streamflow was measured or estimated by the USGS following standard methods at 23 streamgages; 14 of these streamgages were also equipped with instrumentation capable of continuously monitoring water level, specific conductance, and water temperature. Water-quality samples also were collected at 37 sampling stations by the PWSB and at 14 continuous-record streamgages by the USGS during WY 2011 as part of a long-term sampling program; all stations were in the Scituate Reservoir drainage area. Water-quality data collected by PWSB are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2011. The largest tributary to the reservoir (the Ponaganset River, which was monitored by the USGS) contributed a mean streamflow of about 37 cubic feet per second (ft3/s) to the reservoir during WY 2011. For the same time period, annual mean1 streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.5 to about 21 ft3/s. Together, tributaries (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 1,600,000 kg (kilograms) of sodium and 2,600,000 kg of chloride to the Scituate Reservoir during WY 2011; sodium and chloride yields for the tributaries ranged from 9,800 to 53,000 kilograms per square mile (kg/mi2) and from 15,000 to 90,000 kg/mi2, respectively. At the stations where water-quality samples were collected by the PWSB, the median of the median chloride concentrations was 20.0 milligrams per liter (mg/L), median nitrite concentration was 0.002 mg/L as nitrogen (N), median nitrate concentration was 0.01 mg/L as N, median orthophosphate concentration was 0.07 mg/L as phosphorus, and median concentrations of total coliform and Escherichia coli (E. coli) bacteria were 33 and 23 colony forming units per 100 milliliters (CFU/100mL), respectively. The medians of the median daily loads (and yields) of chloride, nitrite, nitrate, orthophosphate, and total coliform and E. coli bacteria were 230 kilograms per day (kg/d) (80 kilograms per day per square mile (kg/d/mi2)); 10 grams per day (g/d) (6.3 grams per day per square mile (g/d/mi2)); 110 g/d (29 g/d/mi2); 610 g/d (270 g/d/mi2); 4,600 million colony forming units per day (CFUx106/d) (2,500 CFUx106/d/mi2); and 1,800 CFUx106/d (810 CFUx106/d/mi2), respectively.

Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2003

USGS Publications Warehouse

Breault, Robert F.; Campbell, Jean P.

2010-01-01

Streamflow and water-quality data were collected by the U.S. Geological Survey (USGS) or the Providence Water Supply Board, Rhode Island's largest drinking-water supplier. Streamflow was measured or estimated by the USGS following standard methods at 23 streamgage stations; 10 of these stations were also equipped with instrumentation capable of continuously monitoring specific conductance. Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate instantaneous (15-minute) loads of sodium and chloride during water year (WY) 2003 (October 1, 2002, to September 30, 2003). Water-quality samples were also collected at 37 sampling stations in the Scituate Reservoir drainage area by the Providence Water Supply Board during WY 2003 as part of a long-term sampling program. Water-quality data are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2003. The largest tributary to the reservoir (the Ponaganset River, which was monitored by the USGS) contributed about 31 cubic feet per second (ft3/s) to the reservoir during WY 2003. For the same time period, annual mean streamflows1 measured (or estimated) for the other monitoring stations in this study ranged from about 0.44 to 20 ft3/s. Together, tributary streams (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 1,200,000 kilograms (kg) of sodium and 1,900,000 kg of chloride to the Scituate Reservoir during WY 2003; sodium and chloride yields for the tributaries ranged from 10,000 to 61,000 kilograms per square mile (kg/mi2) and from 15,000 to 100,000 kg/mi2, respectively. At the stations where water-quality samples were collected by the Providence Water Supply Board, the median of the median chloride concentrations was 21.3 milligrams per liter (mg/L), median nitrite concentration was 0.002 mg/L as N, median nitrate concentration was 0.02 mg/L as N, median orthophosphate concentration was 0.06 mg/L as P, and median concentrations of total coliform and Escherichia coli (E. coli) bacteria were 38 and 9 CFU/100 mL (colony forming units per 100 milliliters), respectively. The medians of the median daily loads (and yields) of chloride, nitrite, nitrate, orthophosphate, and total coliform and E. coli bacteria were 140 kg/d (67 kg/d/mi2), 15 g/d (6.5 g/d/mi2), 140 g/d (62 g/d/mi2), 340 g/d (180 g/d/mi2), and 2,200 million colony forming units per day (CFU x 106/d) (1,200 CFU x 106/d/mi2) and 940 CFU x 106/d (490 CFU x 106/d/mi2), respectively. 1The arithmetic mean of the individual daily mean discharges for the year noted or for the designated period.

Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2009

USGS Publications Warehouse

Breault, Robert F.; Smith, Kirk P.

2010-01-01

Streamflow and water-quality data were collected by the U.S. Geological Survey (USGS) or the Providence Water Supply Board (PWSB), Rhode Island's largest drinking-water supplier. Streamflow was measured or estimated by the USGS following standard methods at 23 streamgage stations; 13 of these stations were also equipped with instrumentation capable of continuously monitoring specific conductance and water temperature. Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate loads of sodium and chloride during water year (WY) 2009 (October 1, 2008, to September 30, 2009). Water-quality samples also were collected at 37 sampling stations by the PWSB and at 14 monitoring stations by the USGS during WY 2009 as part of a long-term sampling program; all stations are in the Scituate Reservoir drainage area. Water-quality data collected by PWSB are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2009. The largest tributary to the reservoir (the Ponaganset River, which was monitored by the USGS) contributed a mean streamflow of about 27 cubic feet per second (ft3/s) to the reservoir during WY 2009. For the same time period, annual mean1 streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.50 to 17 ft3/s. Together, tributary streams (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 1,400,000 kilograms (kg) of sodium and 2,200,000 kg of chloride to the Scituate Reservoir during WY 2009; sodium and chloride yields for the tributaries ranged from 10,000 to 64,000 kilograms per square mile (kg/mi2) and from 15,000 to 110,000 kg/mi2, respectively. At the stations where water-quality samples were collected by the PWSB, the median of the median chloride concentrations was 21.7 milligrams per liter (mg/L), median nitrite concentration was 0.001 mg/L as N, median nitrate concentration was 0.02 mg/L as N, median orthophosphate concentration was 0.09 mg/L as P, and median concentrations of total coliform and Escherichia coli (E. coli) bacteria were 61 and 16 colony forming units per 100 milliliters (CFU/100 mL), respectively. The medians of the median daily loads (and yields) of chloride, nitrite, nitrate, orthophosphate, and total coliform and E. coli bacteria were 190 kg/d (61 kg/d/mi2), 12 g/d (4.5 g/d/mi2), 93 g/d (32 g/d/mi2), 420 g/d (290 g/d/mi2), 6,200 million colony forming units per day (CFU?106/d) (2,600 CFU?106/d/mi2), and 1,100 CFU?106/d (340 CFU?106/d/mi2), respectively. 1The arithmetic mean of the individual daily mean discharges for the year noted or for the designated period.

Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2004

USGS Publications Warehouse

Breault, Robert F.; Campbell, Jean P.

2010-01-01

Streamflow and water-quality data were collected by the U.S. Geological Survey (USGS) or the Providence Water Supply Board, Rhode Island's largest drinking-water supplier. Streamflow was measured or estimated by the USGS following standard methods at 23 streamgage stations; 10 of these stations were also equipped with instrumentation capable of continuously monitoring specific conductance. Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate instantaneous (15-minute) loads of sodium and chloride during water year (WY) 2004 (October 1, 2003, to September 30, 2004). Water-quality samples were also collected at 37 sampling stations in the Scituate Reservoir drainage area by the Providence Water Supply Board during WY 2004 as part of a long-term sampling program. Water-quality data are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2004. The largest tributary to the reservoir (the Ponaganset River, which was monitored by the USGS) contributed about 27 cubic feet per second (ft3/s) to the reservoir during WY 2004. For the same time period, annual mean1 streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.42 to 19 ft3/s. Together, tributary streams (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 1,100,000 kilograms (kg) of sodium and 1,700,000 kg of chloride to the Scituate Reservoir during WY 2004; sodium and chloride yields for the tributaries ranged from 12,000 to 61,000 kilograms per square mile (kg/mi2) and from 17,000 to 100,000 kg/mi2, respectively. At the stations where water-quality samples were collected by the Providence Water Supply Board, the median of the median chloride concentrations was 24.8 milligrams per liter (mg/L), median nitrite concentration was 0.001 mg/L as N, median nitrate concentration was 0.03 mg/L as N, median orthophosphate concentration was 0.07 mg/L as P, and median concentrations of total coliform and Escherichia coli (E. coli) bacteria were 33 and 23 colony forming units per 100 milliliters (CFU/100 mL), respectively. The medians of the median daily loads (and yields) of chloride, nitrite, nitrate, orthophosphate, and total coliform and E. coli bacteria were 160 kg/d (81 kg/d/mi2), 9.1 g/d (5.2 g/d/mi2), 280 g/d (110 g/d/mi2), 760 g/d (340 g/d/mi2), and 4,700 million colony forming units per day (CFU x 106/d) (1,700 CFU x 106/d/mi2) and 1,900 CFU x 106/d (520 CFU x 106/d/mi2), respectively. 1The arithmetic mean of the individual daily mean discharges for the year noted or for the designated period

Estimating variability in grain legume yields across Europe and the Americas

NASA Astrophysics Data System (ADS)

Cernay, Charles; Ben-Ari, Tamara; Pelzer, Elise; Meynard, Jean-Marc; Makowski, David

2015-06-01

Grain legume production in Europe has recently come under scrutiny. Although legume crops are often promoted to provide environmental services, European farmers tend to turn to non-legume crops. It is assumed that high variability in legume yields explains this aversion, but so far this hypothesis has not been tested. Here, we estimate the variability of major grain legume and non-legume yields in Europe and the Americas from yield time series over 1961-2013. Results show that grain legume yields are significantly more variable than non-legume yields in Europe. These differences are smaller in the Americas. Our results are robust at the level of the statistical methods. In all regions, crops with high yield variability are allocated to less than 1% of cultivated areas. Although the expansion of grain legumes in Europe may be hindered by high yield variability, some species display risk levels compatible with the development of specialized supply chains.

[Mapping of seedlessness gene in grapes using SCAR markers].

PubMed

Yang, Ke-Qiang; Wang, Yue-Jin; Zhang, Jin-Jin; Wang, Xi-Ping; W A N, Yi-Zhen; Zhang, Jian-Xia

2005-03-01

Nine primers (including UBC-269 and GSLP1) were designed and synthesized based on DNA sequences of UBC-269(484) and GSLP1(569). The template DNA from Red Globe (seeded paternal parent) and Flame Seedless (seedless maternal parent) were screened using these primers. For Flame Seedless,GSLP1 yielded specific marker GSLP1(569); No. 39970524-5 primer yielded specific marker 39970524-5-564; and No. 6 primer yielded specific marker 39970524-6-1538 and 39970524-6-1200. GSLP1, No. 39970524-5, and No. 39970524-6 primers were used specifically to screen template DNA from the experimental plant materials. The results showed that the specific markers GSLP1(569), 39970524-5-564,39970524-6-1538 and 39970524-6-1200 were cosegregating with the major seedlessness gene. All these specific loci were also present in Thompson Seedless which was the initial donor of the seedlessness gene. It suggests that these SCAR markers are linked to a major grape seedlessness gene S. Markers order and map distance were estimated using the software 'QTXb17'. This showed that GSLP1(569), 39970524-5-564,39970524-6-1538 and 39970524-6-1200 were tightly linked to gene S. When P = 0.01,confidence limits for map distance ranged from 0.2 to 9.9; standard errors of map distance were from 0.6 to 1.9; LOD for linkage were from 32.7 to 46.4. These markers and the gene S were found to be in the same group. The markers were located on either side of gene S, covering 12.3 cM of the grape genome. The genetic distances between gene S and 39970524-5-564, GSLP1(569), 39970524-6-1538 and 39970524-6-1200 were 0.6 cM, 1.2 cM, 4.9 cM and 11.1 cM respectively.

Frequency response of electrochemical cells

NASA Technical Reports Server (NTRS)

Thomas, Daniel L.

1989-01-01

Impedance concepts can be applied to the analysis of battery electrodes, yielding information about the structure of the electrode and the processes occurring in the electrode. Structural parameters such as the specific area (surface area per gram of electrode) can be estimated. Electrode variables such as surface overpotential, ohmic losses, and diffusion limitations may be studied. Nickel and cadmium electrodes were studied by measuring the ac impedance as a function of frequency, and the specific areas that were determined were well within the range of specific areas determined from BET measurements. Impedance spectra were measured for the nickel and cadmium electrodes, and for a 20 A-hr NiCd battery as functions of the state of charge. More work is needed to determine the feasibility of using frequency response as a nondestructive testing technique for batteries.

Reliable yields of public water-supply wells in the fractured-rock aquifers of central Maryland, USA

NASA Astrophysics Data System (ADS)

Hammond, Patrick A.

2018-02-01

Most studies of fractured-rock aquifers are about analytical models used for evaluating aquifer tests or numerical methods for describing groundwater flow, but there have been few investigations on how to estimate the reliable long-term drought yields of individual hard-rock wells. During the drought period of 1998 to 2002, many municipal water suppliers in the Piedmont/Blue Ridge areas of central Maryland (USA) had to institute water restrictions due to declining well yields. Previous estimates of the yields of those wells were commonly based on extrapolating drawdowns, measured during short-term single-well hydraulic pumping tests, to the first primary water-bearing fracture in a well. The extrapolations were often made from pseudo-equilibrium phases, frequently resulting in substantially over-estimated well yields. The methods developed in the present study to predict yields consist of extrapolating drawdown data from infinite acting radial flow periods or by fitting type curves of other conceptual models to the data, using diagnostic plots, inverse analysis and derivative analysis. Available drawdowns were determined by the positions of transition zones in crystalline rocks or thin-bedded consolidated sandstone/limestone layers (reservoir rocks). Aquifer dewatering effects were detected by type-curve matching of step-test data or by breaks in the drawdown curves constructed from hydraulic tests. Operational data were then used to confirm the predicted yields and compared to regional groundwater levels to determine seasonal variations in well yields. Such well yield estimates are needed by hydrogeologists and water engineers for the engineering design of water systems, but should be verified by the collection of long-term monitoring data.

Added-values of high spatiotemporal remote sensing data in crop yield estimation

NASA Astrophysics Data System (ADS)

Gao, F.; Anderson, M. C.

2017-12-01

Timely and accurate estimation of crop yield before harvest is critical for food market and administrative planning. Remote sensing derived parameters have been used for estimating crop yield by using either empirical or crop growth models. The uses of remote sensing vegetation index (VI) in crop yield modeling have been typically evaluated at regional and country scales using coarse spatial resolution (a few hundred to kilo-meters) data or assessed over a small region at field level using moderate resolution spatial resolution data (10-100m). Both data sources have shown great potential in capturing spatial and temporal variability in crop yield. However, the added value of data with both high spatial and temporal resolution data has not been evaluated due to the lack of such data source with routine, global coverage. In recent years, more moderate resolution data have become freely available and data fusion approaches that combine data acquired from different spatial and temporal resolutions have been developed. These make the monitoring crop condition and estimating crop yield at field scale become possible. Here we investigate the added value of the high spatial and temporal VI for describing variability of crop yield. The explanatory ability of crop yield based on high spatial and temporal resolution remote sensing data was evaluated in a rain-fed agricultural area in the U.S. Corn Belt. Results show that the fused Landsat-MODIS (high spatial and temporal) VI explains yield variability better than single data source (Landsat or MODIS alone), with EVI2 performing slightly better than NDVI. The maximum VI describes yield variability better than cumulative VI. Even though VI is effective in explaining yield variability within season, the inter-annual variability is more complex and need additional information (e.g. weather, water use and management). Our findings augment the importance of high spatiotemporal remote sensing data and supports new moderate resolution satellite missions for agricultural applications.

Genomic selection across multiple breeding cycles in applied bread wheat breeding.

PubMed

Michel, Sebastian; Ametz, Christian; Gungor, Huseyin; Epure, Doru; Grausgruber, Heinrich; Löschenberger, Franziska; Buerstmayr, Hermann

2016-06-01

We evaluated genomic selection across five breeding cycles of bread wheat breeding. Bias of within-cycle cross-validation and methods for improving the prediction accuracy were assessed. The prospect of genomic selection has been frequently shown by cross-validation studies using the same genetic material across multiple environments, but studies investigating genomic selection across multiple breeding cycles in applied bread wheat breeding are lacking. We estimated the prediction accuracy of grain yield, protein content and protein yield of 659 inbred lines across five independent breeding cycles and assessed the bias of within-cycle cross-validation. We investigated the influence of outliers on the prediction accuracy and predicted protein yield by its components traits. A high average heritability was estimated for protein content, followed by grain yield and protein yield. The bias of the prediction accuracy using populations from individual cycles using fivefold cross-validation was accordingly substantial for protein yield (17-712 %) and less pronounced for protein content (8-86 %). Cross-validation using the cycles as folds aimed to avoid this bias and reached a maximum prediction accuracy of [Formula: see text] = 0.51 for protein content, [Formula: see text] = 0.38 for grain yield and [Formula: see text] = 0.16 for protein yield. Dropping outlier cycles increased the prediction accuracy of grain yield to [Formula: see text] = 0.41 as estimated by cross-validation, while dropping outlier environments did not have a significant effect on the prediction accuracy. Independent validation suggests, on the other hand, that careful consideration is necessary before an outlier correction is undertaken, which removes lines from the training population. Predicting protein yield by multiplying genomic estimated breeding values of grain yield and protein content raised the prediction accuracy to [Formula: see text] = 0.19 for this derived trait.

Simulation of groundwater flow, effects of artificial recharge, and storage volume changes in the Equus Beds aquifer near the city of Wichita, Kansas well field, 1935–2008

USGS Publications Warehouse

Kelly, Brian P.; Pickett, Linda L.; Hansen, Cristi V.; Ziegler, Andrew C.

2013-01-01

The Equus Beds aquifer is a primary water-supply source for Wichita, Kansas and the surrounding area because of shallow depth to water, large saturated thickness, and generally good water quality. Substantial water-level declines in the Equus Beds aquifer have resulted from pumping groundwater for agricultural and municipal needs, as well as periodic drought conditions. In March 2006, the city of Wichita began construction of the Equus Beds Aquifer Storage and Recovery project to store and later recover groundwater, and to form a hydraulic barrier to the known chloride-brine plume near Burrton, Kansas. In October 2009, the U.S. Geological Survey, in cooperation with the city of Wichita, began a study to determine groundwater flow in the area of the Wichita well field, and chloride transport from the Arkansas River and Burrton oilfield to the Wichita well field. Groundwater flow was simulated for the Equus Beds aquifer using the three-dimensional finite-difference groundwater-flow model MODFLOW-2000. The model simulates steady-state and transient conditions. The groundwater-flow model was calibrated by adjusting model input data and model geometry until model results matched field observations within an acceptable level of accuracy. The root mean square (RMS) error for water-level observations for the steady-state calibration simulation is 9.82 feet. The ratio of the RMS error to the total head loss in the model area is 0.049 and the mean error for water-level observations is 3.86 feet. The difference between flow into the model and flow out of the model across all model boundaries is -0.08 percent of total flow for the steady-state calibration. The RMS error for water-level observations for the transient calibration simulation is 2.48 feet, the ratio of the RMS error to the total head loss in the model area is 0.0124, and the mean error for water-level observations is 0.03 feet. The RMS error calculated for observed and simulated base flow gains or losses for the Arkansas River for the transient simulation is 7,916,564 cubic feet per day (91.6 cubic feet per second) and the RMS error divided by (/) the total range in streamflow (7,916,564/37,461,669 cubic feet per day) is 22 percent. The RMS error calculated for observed and simulated streamflow gains or losses for the Little Arkansas River for the transient simulation is 5,610,089 cubic feet per day(64.9 cubic feet per second) and the RMS error divided by the total range in streamflow (5,612,918/41,791,091 cubic feet per day) is 13 percent. The mean error between observed and simulated base flow gains or losses was 29,999 cubic feet per day (0.34 cubic feet per second) for the Arkansas River and -1,369,250 cubic feet per day (-15.8 cubic feet per second) for the Little Arkansas River. Cumulative streamflow gain and loss observations are similar to the cumulative simulated equivalents. Average percent mass balance difference for individual stress periods ranged from -0.46 to 0.51 percent. The cumulative mass balance for the transient calibration was 0.01 percent. Composite scaled sensitivities indicate the simulations are most sensitive to parameters with a large areal distribution. For the steady-state calibration, these parameters include recharge, hydraulic conductivity, and vertical conductance. For the transient simulation, these parameters include evapotranspiration, recharge, and hydraulic conductivity. The ability of the calibrated model to account for the additional groundwater recharged to the Equus Beds aquifer as part of the Aquifer Storage and Recovery project was assessed by using the U.S. Geological Survey subregional water budget program ZONEBUDGET and comparing those results to metered recharge for 2007 and 2008 and previous estimates of artificial recharge. The change in storage between simulations is the volume of water that estimates the recharge credit for the aquifer storage and recovery system. The estimated increase in storage of 1,607 acre-ft in the basin storage area compared to metered recharge of 1,796 acre-ft indicates some loss of metered recharge. Increased storage outside of the basin storage area of 183 acre-ft accounts for all but 6 acre-ft or 0.33 percent of the total. Previously estimated recharge credits for 2007 and 2008 are 1,018 and 600 acre-ft, respectively, and a total estimated recharge credit of 1,618 acre-ft. Storage changes calculated for this study are 4.42 percent less for 2007 and 5.67 percent more for 2008 than previous estimates. Total storage change for 2007 and 2008 is 0.68 percent less than previous estimates. The small difference between the increase in storage from artificial recharge estimated with the groundwater-flow model and metered recharge indicates the groundwater model correctly accounts for the additional water recharged to the Equus Beds aquifer as part of the Aquifer Storage and Recovery project. Small percent differences between inflows and outflows for all stress periods and all index cells in the basin storage area, improved calibration compared to the previous model, and a reasonable match between simulated and measured long-term base flow indicates the groundwater model accurately simulates groundwater flow in the study area. The change in groundwater level through recent years compared to the August 1940 groundwater level map has been documented and used to assess the change of storage volume of the Equus Beds aquifer in and near the Wichita well field for three different areas. Two methods were used to estimate changes in storage from simulation results using simulated change in groundwater levels in layer 1 between stress periods, and using ZONEBUDGET to calculate the change in storage in the same way the effects of artificial recharge were estimated within the basin storage area. The three methods indicate similar trends although the magnitude of storage changes differ. Information about the change in storage in response to hydrologic stresses is important for managing groundwater resources in the study area. The comparison between the three methods indicates similar storage change trends are estimated and each could be used to determine relative increases or decreases in storage. Use of groundwater level changes that do not include storage changes that occur in confined or semi-confined parts of the aquifer will slightly underestimate storage changes; however, use of specific yield and groundwater level changes to estimate storage change in confined or semi-confined parts of the aquifer will overestimate storage changes. Using only changes in shallow groundwater levels would provide more accurate storage change estimates for the measured groundwater levels method. The value used for specific yield is also an important consideration when estimating storage. For the Equus Beds aquifer the reported specific yield ranges between 0.08 and 0.35 and the storage coefficient (for confined conditions) ranges between 0.0004 and 0.16. Considering the importance of the value of specific yield and storage coefficient to estimates of storage change over time, and the wide range and substantial overlap for the reported values for specific yield and storage coefficient in the study area, further information on the distribution of specific yield and storage coefficient within the Equus Beds aquifer in the study area would greatly enhance the accuracy of estimated storage changes using both simulated groundwater level, simulated groundwater budget, or measured groundwater level methods.

Comparison of Statistical Models for Analyzing Wheat Yield Time Series

PubMed Central

Michel, Lucie; Makowski, David

2013-01-01

The world's population is predicted to exceed nine billion by 2050 and there is increasing concern about the capability of agriculture to feed such a large population. Foresight studies on food security are frequently based on crop yield trends estimated from yield time series provided by national and regional statistical agencies. Various types of statistical models have been proposed for the analysis of yield time series, but the predictive performances of these models have not yet been evaluated in detail. In this study, we present eight statistical models for analyzing yield time series and compare their ability to predict wheat yield at the national and regional scales, using data provided by the Food and Agriculture Organization of the United Nations and by the French Ministry of Agriculture. The Holt-Winters and dynamic linear models performed equally well, giving the most accurate predictions of wheat yield. However, dynamic linear models have two advantages over Holt-Winters models: they can be used to reconstruct past yield trends retrospectively and to analyze uncertainty. The results obtained with dynamic linear models indicated a stagnation of wheat yields in many countries, but the estimated rate of increase of wheat yield remained above 0.06 t ha−1 year−1 in several countries in Europe, Asia, Africa and America, and the estimated values were highly uncertain for several major wheat producing countries. The rate of yield increase differed considerably between French regions, suggesting that efforts to identify the main causes of yield stagnation should focus on a subnational scale. PMID:24205280

Dual-component video image analysis system (VIASCAN) as a predictor of beef carcass red meat yield percentage and for augmenting application of USDA yield grades.

PubMed

Cannell, R C; Tatum, J D; Belk, K E; Wise, J W; Clayton, R P; Smith, G C

1999-11-01

An improved ability to quantify differences in the fabrication yields of beef carcasses would facilitate the application of value-based marketing. This study was conducted to evaluate the ability of the Dual-Component Australian VIASCAN to 1) predict fabricated beef subprimal yields as a percentage of carcass weight at each of three fat-trim levels and 2) augment USDA yield grading, thereby improving accuracy of grade placement. Steer and heifer carcasses (n = 240) were evaluated using VIASCAN, as well as by USDA expert and online graders, before fabrication of carcasses to each of three fat-trim levels. Expert yield grade (YG), online YG, VIASCAN estimates, and VIASCAN estimated ribeye area used to augment actual and expert grader estimates of the remaining YG factors (adjusted fat thickness, percentage of kidney-pelvic-heart fat, and hot carcass weight), respectively, 1) accounted for 51, 37, 46, and 55% of the variation in fabricated yields of commodity-trimmed subprimals, 2) accounted for 74, 54, 66, and 75% of the variation in fabricated yields of closely trimmed subprimals, and 3) accounted for 74, 54, 71, and 75% of the variation in fabricated yields of very closely trimmed subprimals. The VIASCAN system predicted fabrication yields more accurately than current online yield grading and, when certain VIASCAN-measured traits were combined with some USDA yield grade factors in an augmentation system, the accuracy of cutability prediction was improved, at packing plant line speeds, to a level matching that of expert graders applying grades at a comfortable rate.

Joint Bayesian inference for near-surface explosion yield

NASA Astrophysics Data System (ADS)

Bulaevskaya, V.; Ford, S. R.; Ramirez, A. L.; Rodgers, A. J.

2016-12-01

A near-surface explosion generates seismo-acoustic motion that is related to its yield. However, the recorded motion is affected by near-source effects such as depth-of-burial, and propagation-path effects such as variable geology. We incorporate these effects in a forward model relating yield to seismo-acoustic motion, and use Bayesian inference to estimate yield given recordings of the seismo-acoustic wavefield. The Bayesian approach to this inverse problem allows us to obtain the probability distribution of plausible yield values and thus quantify the uncertainty in the yield estimate. Moreover, the sensitivity of the acoustic signal falls as a function of the depth-of-burial, while the opposite relationship holds for the seismic signal. Therefore, using both the acoustic and seismic wavefield data allows us to avoid the trade-offs associated with using only one of these signals alone. In addition, our inference framework allows for correlated features of the same data type (seismic or acoustic) to be incorporated in the estimation of yield in order to make use of as much information from the same waveform as possible. We demonstrate our approach with a historical dataset and a contemporary field experiment.

Iraq War mortality estimates: a systematic review.

PubMed

Tapp, Christine; Burkle, Frederick M; Wilson, Kumanan; Takaro, Tim; Guyatt, Gordon H; Amad, Hani; Mills, Edward J

2008-03-07

In March 2003, the United States invaded Iraq. The subsequent number, rates, and causes of mortality in Iraq resulting from the war remain unclear, despite intense international attention. Understanding mortality estimates from modern warfare, where the majority of casualties are civilian, is of critical importance for public health and protection afforded under international humanitarian law. We aimed to review the studies, reports and counts on Iraqi deaths since the start of the war and assessed their methodological quality and results. We performed a systematic search of 15 electronic databases from inception to January 2008. In addition, we conducted a non-structured search of 3 other databases, reviewed study reference lists and contacted subject matter experts. We included studies that provided estimates of Iraqi deaths based on primary research over a reported period of time since the invasion. We excluded studies that summarized mortality estimates and combined non-fatal injuries and also studies of specific sub-populations, e.g. under-5 mortality. We calculated crude and cause-specific mortality rates attributable to violence and average deaths per day for each study, where not already provided. Thirteen studies met the eligibility criteria. The studies used a wide range of methodologies, varying from sentinel-data collection to population-based surveys. Studies assessed as the highest quality, those using population-based methods, yielded the highest estimates. Average deaths per day ranged from 48 to 759. The cause-specific mortality rates attributable to violence ranged from 0.64 to 10.25 per 1,000 per year. Our review indicates that, despite varying estimates, the mortality burden of the war and its sequelae on Iraq is large. The use of established epidemiological methods is rare. This review illustrates the pressing need to promote sound epidemiologic approaches to determining mortality estimates and to establish guidelines for policy-makers, the media and the public on how to interpret these estimates.

Estimated suspended-sediment loads and yields in the French and Brandywine Creek Basins, Chester County, Pennsylvania, water years 2008-09

USGS Publications Warehouse

Sloto, Ronald A.; Olson, Leif E.

2011-01-01

Turbidity and suspended-sediment concentration data were collected by the U.S. Geological Survey (USGS) at four stream stations--French Creek near Phoenixville, West Branch Brandywine Creek near Honey Brook, West Branch Brandywine Creek at Modena, and East Branch Brandywine Creek below Downingtown--in Chester County, Pa. Sedimentation and siltation is the leading cause of stream impairment in Chester County, and these data are critical for quantifying sediment transport. This study was conducted by the USGS in cooperation with the Chester County Water Resources Authority and the Chester County Health Department. Data from optical turbidity sensors deployed at the four stations were recorded at 15- or 30-minute intervals by a data logger and uploaded every 1 to 4 hours to the USGS database. Most of the suspended-sediment samples were collected using automated samplers. The use of optical sensors to continuously monitor turbidity provided an accurate estimate of sediment fluctuations without the collection and analysis costs associated with intensive sampling during storms. Turbidity was used as a surrogate for suspended-sediment concentration (SSC), which is a measure of sedimentation and siltation. Regression models were developed between SSC and turbidity for each of the monitoring stations using SSC data collected from the automated samplers and turbidity data collected at each station. Instantaneous suspended-sediment loads (SSL) were computed from time-series turbidity and discharge data for the 2008 and 2009 water years using the regression equations. The instantaneous computations of SSL were summed to provide daily, storm, and water year annual loads. The annual SSL contributed from each basin was divided by the upstream drainage area to estimate the annual sediment yield. For all four basins, storms provided more than 96 percent of the annual SSL. In each basin, four storms generally provided over half the annual SSL each water year. Stormflows with the highest peak discharges generally carried the highest SSLs. For all stations, the greatest SSLs occurred during the late winter in February and March during the 2008 water year. During the 2009 water year, the greatest SSLs occurred during December and August. For French Creek near Phoenixville, the estimated annual SSL was 3,500 tons, and the estimated yield was 59.1 tons per square mile (ton/mi2) for the 2008 water year. For the 2009 water year, the annual SSL was 4,390 tons, and the yield was 74.3 ton/mi2. For West Branch Brandywine Creek near Honey Brook, the estimated annual SSL was 4,580 tons, and the estimated yield was 245 ton/mi2 for the 2008 water year. For the 2009 water year, the annual SSL was 2,300 tons, and the yield was 123 ton/mi2. For West Branch Brandywine Creek at Modena, the estimated annual SSL was 7,480 tons, and the estimated yield was 136 ton/mi2 for the 2008 water year. For the 2009 water year, the annual SSL was 4,930 tons, and the yield was 90 ton/mi2. For East Branch Brandywine Creek below Downingtown, the estimated annual SSL was 8,900 tons, and the estimated yield was 100 ton/mi2 for the 2008 water year. For the 2009 water year, the annual SSL was 7,590 tons, and the yield was 84 ton/mi2.

A Taxonomic Reduced-Space Pollen Model for Paleoclimate Reconstruction

NASA Astrophysics Data System (ADS)

Wahl, E. R.; Schoelzel, C.

2010-12-01

Paleoenvironmental reconstruction from fossil pollen often attempts to take advantage of the rich taxonomic diversity in such data. Here, a taxonomically "reduced-space" reconstruction model is explored that would be parsimonious in introducing parameters needing to be estimated within a Bayesian Hierarchical Modeling context. This work involves a refinement of the traditional pollen ratio method. This method is useful when one (or a few) dominant pollen type(s) in a region have a strong positive correlation with a climate variable of interest and another (or a few) dominant pollen type(s) have a strong negative correlation. When, e.g., counts of pollen taxa a and b (r >0) are combined with pollen types c and d (r <0) to form ratios of the form (a + b) / (a + b + c + d), an appropriate estimation form is the binomial logistic generalized linear model (GLM). The GLM can readily model this relationship in the forward form, pollen = g(climate), which is more physically realistic than inverse models often used in paleoclimate reconstruction [climate = f(pollen)]. The specification of the model is: rnum Bin(n,p), where E(r|T) = p = exp(η)/[1+exp(η)], and η = α + β(T); r is the pollen ratio formed as above, rnum is the ratio numerator, n is the ratio denominator (i.e., the sum of pollen counts), the denominator-specific count is (n - rnum), and T is the temperature at each site corresponding to a specific value of r. Ecological and empirical screening identified the model (Spruce+Birch) / (Spruce+Birch+Oak+Hickory) for use in temperate eastern N. America. α and β were estimated using both "traditional" and Bayesian GLM algorithms (in R). Although it includes only four pollen types, the ratio model yields more explained variation ( 80%) in the pollen-temperature relationship of the study region than a 64-taxon modern analog technique (MAT). Thus, the new pollen ratio method represents an information-rich, reduced space data model that can be efficiently employed in a BHM framework. The ratio model can directly reconstruct past temperature by solving the GLM equations for T as a function of α, β, and E(r|T): T = {ln[E(r|T)/{1-E(r|T)}]-α}/β. To enable use in paleoreconstruction, the observed r values from fossil pollen data are, by assumption, treated as unbiased estimators of the true r value at each time sampled, which can be substituted for E(r|T). Uncertainty in this reconstruction is systematically evaluated in two parts: 1) the observed r values and their corresponding n values are input as parameters into the binomial distribution, Monte Carlo random pollen count draws are made, and a new ratio value is determined for each iteration; and 2) in the "traditional" GLM the estimated SEs for α and β are used with the α and β EV estimates to yield Monte Carlo random draws for each binomial draw (assuming α and β are Gaussian), in the Bayesian GLM random draws for α and β are taken directly from their estimated posterior distribution. Both methods yield nearly identical reconstructions from varved lakes in Wisconsin where the model has been tested; slightly narrower uncertainty ranges are produced by the Bayesian model. The Little Ice Age is readily identified. Pine:Oak and Fir:Oak versions of the model used in S. California show differences from MAT-based reconstructions.

Source term estimates of radioxenon released from the BaTek medical isotope production facility using external measured air concentrations.

PubMed

Eslinger, Paul W; Cameron, Ian M; Dumais, Johannes Robert; Imardjoko, Yudi; Marsoem, Pujadi; McIntyre, Justin I; Miley, Harry S; Stoehlker, Ulrich; Widodo, Susilo; Woods, Vincent T

2015-10-01

BATAN Teknologi (BaTek) operates an isotope production facility in Serpong, Indonesia that supplies (99m)Tc for use in medical procedures. Atmospheric releases of (133)Xe in the production process at BaTek are known to influence the measurements taken at the closest stations of the radionuclide network of the International Monitoring System (IMS). The purpose of the IMS is to detect evidence of nuclear explosions, including atmospheric releases of radionuclides. The major xenon isotopes released from BaTek are also produced in a nuclear explosion, but the isotopic ratios are different. Knowledge of the magnitude of releases from the isotope production facility helps inform analysts trying to decide if a specific measurement result could have originated from a nuclear explosion. A stack monitor deployed at BaTek in 2013 measured releases to the atmosphere for several isotopes. The facility operates on a weekly cycle, and the stack data for June 15-21, 2013 show a release of 1.84 × 10(13) Bq of (133)Xe. Concentrations of (133)Xe in the air are available at the same time from a xenon sampler located 14 km from BaTek. An optimization process using atmospheric transport modeling and the sampler air concentrations produced a release estimate of 1.88 × 10(13) Bq. The same optimization process yielded a release estimate of 1.70 × 10(13) Bq for a different week in 2012. The stack release value and the two optimized estimates are all within 10% of each other. Unpublished production data and the release estimate from June 2013 yield a rough annual release estimate of 8 × 10(14) Bq of (133)Xe in 2014. These multiple lines of evidence cross-validate the stack release estimates and the release estimates based on atmospheric samplers. Copyright © 2015 Elsevier Ltd. All rights reserved.

Pumping Test Determination of Unsaturated Aquifer Properties

NASA Astrophysics Data System (ADS)

Mishra, P. K.; Neuman, S. P.

2008-12-01

Tartakovsky and Neuman [2007] presented a new analytical solution for flow to a partially penetrating well pumping at a constant rate from a compressible unconfined aquifer considering the unsaturated zone. In their solution three-dimensional, axially symmetric unsaturated flow is described by a linearized version of Richards' equation in which both hydraulic conductivity and water content vary exponentially with incremental capillary pressure head relative to its air entry value, the latter defining the interface between the saturated and unsaturated zones. Both exponential functions are characterized by a common exponent k having the dimension of inverse length, or equivalently a dimensionless exponent kd=kb where b is initial saturated thickness. The authors used their solution to analyze drawdown data from a pumping test conducted by Moench et al. [2001] in a Glacial Outwash Deposit at Cape Cod, Massachusetts. Their analysis yielded estimates of horizontal and vertical saturated hydraulic conductivities, specific storage, specific yield and k . Recognizing that hydraulic conductivity and water content seldom vary identically with incremental capillary pressure head, as assumed by Tartakovsky and Neuman [2007], we note that k is at best an effective rather than a directly measurable soil parameter. We therefore ask to what extent does interpretation of a pumping test based on the Tartakovsky-Neuman solution allow estimating aquifer unsaturated parameters as described by more common constitutive water retention and relative hydraulic conductivity models such as those of Brooks and Corey [1964] or van Genuchten [1980] and Mualem [1976a]? We address this question by showing how may be used to estimate the capillary air entry pressure head k and the parameters of such constitutive models directly, without a need for inverse unsaturated numerical simulations of the kind described by Moench [2003]. To assess the validity of such direct estimates we use maximum likelihood- based model selection criteria to compare the abilities of numerical models based on the STOMP code to reproduce observed drawdowns during the test when saturated and unsaturated aquifer parameters are estimated either in the above manner or by means of the inverse code PEST.

Property Grids for the Kansas High Plains Aquifer from Water Well Drillers' Logs

NASA Astrophysics Data System (ADS)

Bohling, G.; Adkins-Heljeson, D.; Wilson, B. B.

2017-12-01

Like a number of state and provincial geological agencies, the Kansas Geological Survey hosts a database of water well drillers' logs, containing the records of sediments and lithologies characterized during drilling. At the moment, the KGS database contains records associated with over 90,000 wells statewide. Over 60,000 of these wells are within the High Plains aquifer (HPA) in Kansas, with the corresponding logs containing descriptions of over 500,000 individual depth intervals. We will present grids of hydrogeological properties for the Kansas HPA developed from this extensive, but highly qualitative, data resource. The process of converting the logs into quantitative form consists of first translating the vast number of unique (and often idiosyncratic) sediment descriptions into a fairly comprehensive set of standardized lithology codes and then mapping the standardized lithologies into a smaller number of property categories. A grid is superimposed on the region and the proportion of each property category is computed within each grid cell, with category proportions in empty grid cells computed by interpolation. Grids of properties such as hydraulic conductivity and specific yield are then computed based on the category proportion grids and category-specific property values. A two-dimensional grid is employed for this large-scale, regional application, with category proportions averaged between two surfaces, such as bedrock and the water table at a particular time (to estimate transmissivity at that time) or water tables at two different times (to estimate specific yield over the intervening time period). We have employed a sequence of water tables for different years, based on annual measurements from an extensive network of wells, providing an assessment of temporal variations in the vertically averaged aquifer properties resulting from water level variations (primarily declines) over time.

Large electroweak penguin contribution in B{yields}K{pi} and {pi}{pi} decay modes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mishima, Satoshi; Yoshikawa, Tadashi

2004-11-01

We discuss a possibility of large electroweak penguin contribution in B{yields}K{pi} and {pi}{pi} from recent experimental data. The experimental data may be suggesting that there are some discrepancies between the data and theoretical estimation in the branching ratios of them. In B{yields}K{pi} decays, to explain it, a large electroweak penguin contribution and large strong phase differences seem to be needed. The contributions should appear also in B{yields}{pi}{pi}. We show, as an example, a solution to solve the discrepancies in both B{yields}K{pi} and B{yields}{pi}{pi}. However the magnitude of the parameters and the strong phase estimated from experimental data are quite largemore » compared with the theoretical estimations. It may be suggesting some new physics effects are included in these processes. We will have to discuss about the dependence of the new physics. To explain both modes at once, we may need large electroweak penguin contribution with new weak phases and some SU(3) breaking effects by new physics in both QCD and electroweak penguin-type processes.« less

A comprehensively quantitative method of evaluating the impact of drought on crop yield using daily multi-scale SPEI and crop growth process model.

PubMed

Wang, Qianfeng; Wu, Jianjun; Li, Xiaohan; Zhou, Hongkui; Yang, Jianhua; Geng, Guangpo; An, Xueli; Liu, Leizhen; Tang, Zhenghong

2017-04-01

The quantitative evaluation of the impact of drought on crop yield is one of the most important aspects in agricultural water resource management. To assess the impact of drought on wheat yield, the Environmental Policy Integrated Climate (EPIC) crop growth model and daily Standardized Precipitation Evapotranspiration Index (SPEI), which is based on daily meteorological data, are adopted in the Huang Huai Hai Plain. The winter wheat crop yields are estimated at 28 stations, after calibrating the cultivar coefficients based on the experimental site data, and SPEI data was taken 11 times across the growth season from 1981 to 2010. The relationship between estimated yield and multi-scale SPEI were analyzed. The optimum time scale SPEI to monitor drought during the crop growth period was determined. The reference yield was determined by averaging the yields from numerous non-drought years. From this data, we propose a comprehensive quantitative method which can be used to predict the impact of drought on wheat yields by combining the daily multi-scale SPEI and crop growth process model. This method was tested in the Huang Huai Hai Plain. The results suggested that estimation of calibrated EPIC was a good predictor of crop yield in the Huang Huai Hai Plain, with lower RMSE (15.4 %) between estimated yield and observed yield at six agrometeorological stations. The soil moisture at planting time was affected by the precipitation and evapotranspiration during the previous 90 days (about 3 months) in the Huang Huai Hai Plain. SPEI G90 was adopted as the optimum time scale SPEI to identify the drought and non-drought years, and identified a drought year in 2000. The water deficit in the year 2000 was significant, and the rate of crop yield reduction did not completely correspond with the volume of water deficit. Our proposed comprehensive method which quantitatively evaluates the impact of drought on crop yield is reliable. The results of this study further our understanding why the adoption of counter measures against drought is important and direct farmers to choose drought-resistant crops.

Estimation of sediments in urban drainage areas and relation analysis between sediments and inundation risk using GIS.

PubMed

Moojong, Park; Hwandon, Jun; Minchul, Shin

2008-01-01

Sediments entering the sewer in urban areas reduce the conveyance in sewer pipes, which increases inundation risk. To estimate sediment yields, individual landuse areas in each sub-basin should be obtained. However, because of the complex nature of an urban area, this is almost impossible to obtain manually. Thus, a methodology to obtain individual landuse areas for each sub-basin has been suggested for estimating sediment yields. Using GIS, an urban area is divided into sub-basins with respect to the sewer layout, with the area of individual landuse estimated for each sub-basin. The sediment yield per unit area for each sub-basin is then calculated. The suggested method was applied to the GunJa basin in Seoul. For a relation analysis between sediments and inundation risk, sub-basins were ordered by the sediment yields per unit area and compared with historical inundation areas. From this analysis, sub-basins with higher order were found to match the historical inundation areas. Copyright IWA Publishing 2008.

Using normalized difference vegetation index (NDVI) to estimate sugarcane yield and yield components

USDA-ARS?s Scientific Manuscript database

Sugarcane (Saccharum spp.) yield and yield components are important traits for growers and scientists to evaluate and select cultivars. Collection of these yield data would be labor intensive and time consuming in the early selection stages of sugarcane breeding cultivar development programs with a ...

Genotype × environment interaction analysis of North American shrub willow yield trials confirms superior performance of triploid hybrids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fabio, Eric S.; Volk, Timothy A.; Miller, Raymond O.

Development of dedicated bioenergy crop production systems will require accurate yield estimates, which will be important for determining many of the associated environmental and economic impacts of their production. Shrub willow (Salix spp) is being promoted in areas of the USA and Canada due to its adaption to cool climates and wide genetic diversity available for breeding improvement. Willow breeding in North America is in an early stage, and selection of elite genotypes for commercialization will require testing across broad geographic regions to gain an understanding of how shrub willow interacts with the environment. We analyzed a dataset of first-rotationmore » shrub willow yields of 16 genotypes across 10 trial environments in the USA and Canada for genotype-by-environment interactions using the additive main effects and multiplicative interactions (AMMI) model. Mean genotype yields ranged from 5.22 to 8.58 oven-dry Mg ha -1 yr -1. Analysis of the main effect of genotype showed that one round of breeding improved yields by as much as 20% over check cultivars and that triploid hybrids, most notably Salix viminalis × S. miyabeana, exhibited superior yields. We also found important variability in genotypic response to environments, which suggests specific adaptability could be exploited among 16 genotypes for yield gains. Strong positive correlations were found between environment main effects and AMMI parameters and growing environment temperatures. These findings demonstrate yield improvements are possible in one generation and will be important for developing cultivar recommendations and for future breeding efforts.« less

Genotype × environment interaction analysis of North American shrub willow yield trials confirms superior performance of triploid hybrids

DOE PAGES

Fabio, Eric S.; Volk, Timothy A.; Miller, Raymond O.; ...

2016-01-30

Development of dedicated bioenergy crop production systems will require accurate yield estimates, which will be important for determining many of the associated environmental and economic impacts of their production. Shrub willow (Salix spp) is being promoted in areas of the USA and Canada due to its adaption to cool climates and wide genetic diversity available for breeding improvement. Willow breeding in North America is in an early stage, and selection of elite genotypes for commercialization will require testing across broad geographic regions to gain an understanding of how shrub willow interacts with the environment. We analyzed a dataset of first-rotationmore » shrub willow yields of 16 genotypes across 10 trial environments in the USA and Canada for genotype-by-environment interactions using the additive main effects and multiplicative interactions (AMMI) model. Mean genotype yields ranged from 5.22 to 8.58 oven-dry Mg ha -1 yr -1. Analysis of the main effect of genotype showed that one round of breeding improved yields by as much as 20% over check cultivars and that triploid hybrids, most notably Salix viminalis × S. miyabeana, exhibited superior yields. We also found important variability in genotypic response to environments, which suggests specific adaptability could be exploited among 16 genotypes for yield gains. Strong positive correlations were found between environment main effects and AMMI parameters and growing environment temperatures. These findings demonstrate yield improvements are possible in one generation and will be important for developing cultivar recommendations and for future breeding efforts.« less

Update of the α - n Yields for Reactor Fuel Materials for the Interest of Nuclear Safeguards

NASA Astrophysics Data System (ADS)

Simakov, S. P.; van den Berg, Q. Y.

2017-01-01

The neutron yields caused by spontaneous α-decay of actinides and subsequent (α,xn) reactions were re-evaluated for the reactor fuel materials UO2, UF6, PuO2 and PuF4. For this purpose, the most recent reference data for decay parameters, α-particle stopping powers and (α,xn) cross sections were collected, analysed and used in calculations. The input data and elaborated code were validated against available thick target neutron yields in pure and compound materials measured at accelerators or with radioactive sources. This paper provides the specific neutron yields and their uncertainties resultant from α-decay of actinides 241Am, 249Bk, 252Cf, 242,244Cm, 237Np, 238-242Pu, 232Th and 232-236,238U in oxide and fluoride compounds. The obtained results are an update of previous reference tables issued by the Los Alamos National Laboratory in 1991 which were used for the safeguarding of radioactive materials by passive non-destructive techniques. The comparison of the updated values with previous ones shows an agreement within one estimated uncertainty (≈ 10%) for oxides, and deviations of up to 50% for fluorides.

Cotton growth modeling and assessment using unmanned aircraft system visual-band imagery

NASA Astrophysics Data System (ADS)

Chu, Tianxing; Chen, Ruizhi; Landivar, Juan A.; Maeda, Murilo M.; Yang, Chenghai; Starek, Michael J.

2016-07-01

This paper explores the potential of using unmanned aircraft system (UAS)-based visible-band images to assess cotton growth. By applying the structure-from-motion algorithm, the cotton plant height (ph) and canopy cover (cc) information were retrieved from the point cloud-based digital surface models (DSMs) and orthomosaic images. Both UAS-based ph and cc follow a sigmoid growth pattern as confirmed by ground-based studies. By applying an empirical model that converts the cotton ph to cc, the estimated cc shows strong correlation (R2=0.990) with the observed cc. An attempt for modeling cotton yield was carried out using the ph and cc information obtained on June 26, 2015, the date when sigmoid growth curves for both ph and cc tended to decline in slope. In a cross-validation test, the correlation between the ground-measured yield and the estimated equivalent derived from the ph and/or cc was compared. Generally, combining ph and cc, the performance of the yield estimation is most comparable against the observed yield. On the other hand, the observed yield and cc-based estimation produce the second strongest correlation, regardless of the complexity of the models.

Snijders's correction of Infit and Outfit indexes with estimated ability level: an analysis with the Rasch model.

PubMed

Magis, David; Beland, Sebastien; Raiche, Gilles

2014-01-01

The Infit mean square W and the Outfit mean square U are commonly used person fit indexes under Rasch measurement. However, they suffer from two major weaknesses. First, their asymptotic distribution is usually derived by assuming that the true ability levels are known. Second, such distributions are even not clearly stated for indexes U and W. Both issues can seriously affect the selection of an appropriate cut-score for person fit identification. Snijders (2001) proposed a general approach to correct some person fit indexes when specific ability estimators are used. The purpose of this paper is to adapt this approach to U and W indexes. First, a brief sketch of the methodology and its application to U and W is proposed. Then, the corrected indexes are compared to their classical versions through a simulation study. The suggested correction yields controlled Type I errors against both conservatism and inflation, while the power to detect specific misfitting response patterns gets significantly increased.

Development of a validated algorithm for the diagnosis of paediatric asthma in electronic medical records

PubMed Central

Cave, Andrew J; Davey, Christina; Ahmadi, Elaheh; Drummond, Neil; Fuentes, Sonia; Kazemi-Bajestani, Seyyed Mohammad Reza; Sharpe, Heather; Taylor, Matt

2016-01-01

An accurate estimation of the prevalence of paediatric asthma in Alberta and elsewhere is hampered by uncertainty regarding disease definition and diagnosis. Electronic medical records (EMRs) provide a rich source of clinical data from primary-care practices that can be used in better understanding the occurrence of the disease. The Canadian Primary Care Sentinel Surveillance Network (CPCSSN) database includes cleaned data extracted from the EMRs of primary-care practitioners. The purpose of the study was to develop and validate a case definition of asthma in children 1–17 who consult family physicians, in order to provide primary-care estimates of childhood asthma in Alberta as accurately as possible. The validation involved the comparison of the application of a theoretical algorithm (to identify patients with asthma) to a physician review of records included in the CPCSSN database (to confirm an accurate diagnosis). The comparison yielded 87.4% sensitivity, 98.6% specificity and a positive and negative predictive value of 91.2% and 97.9%, respectively, in the age group 1–17 years. The algorithm was also run for ages 3–17 and 6–17 years, and was found to have comparable statistical values. Overall, the case definition and algorithm yielded strong sensitivity and specificity metrics and was found valid for use in research in CPCSSN primary-care practices. The use of the validated asthma algorithm may improve insight into the prevalence, diagnosis, and management of paediatric asthma in Alberta and Canada. PMID:27882997

Development of a validated algorithm for the diagnosis of paediatric asthma in electronic medical records.

PubMed

Cave, Andrew J; Davey, Christina; Ahmadi, Elaheh; Drummond, Neil; Fuentes, Sonia; Kazemi-Bajestani, Seyyed Mohammad Reza; Sharpe, Heather; Taylor, Matt

2016-11-24

An accurate estimation of the prevalence of paediatric asthma in Alberta and elsewhere is hampered by uncertainty regarding disease definition and diagnosis. Electronic medical records (EMRs) provide a rich source of clinical data from primary-care practices that can be used in better understanding the occurrence of the disease. The Canadian Primary Care Sentinel Surveillance Network (CPCSSN) database includes cleaned data extracted from the EMRs of primary-care practitioners. The purpose of the study was to develop and validate a case definition of asthma in children 1-17 who consult family physicians, in order to provide primary-care estimates of childhood asthma in Alberta as accurately as possible. The validation involved the comparison of the application of a theoretical algorithm (to identify patients with asthma) to a physician review of records included in the CPCSSN database (to confirm an accurate diagnosis). The comparison yielded 87.4% sensitivity, 98.6% specificity and a positive and negative predictive value of 91.2% and 97.9%, respectively, in the age group 1-17 years. The algorithm was also run for ages 3-17 and 6-17 years, and was found to have comparable statistical values. Overall, the case definition and algorithm yielded strong sensitivity and specificity metrics and was found valid for use in research in CPCSSN primary-care practices. The use of the validated asthma algorithm may improve insight into the prevalence, diagnosis, and management of paediatric asthma in Alberta and Canada.

Wheat yield estimation at the farm level using TM Landsat and agrometeorological data

NASA Technical Reports Server (NTRS)

Rudorff, B. F. T.; Batista, G. T.

1991-01-01

A model for estimating wheat yields on the farm level was developed, that integrates the Landsat TM data and agrometeorological information. Results obtained for a test site in southern Brasil for years of 1986 and 1987 show that the vegetation index derived from Landsat TM could account for the 60 to 40 percent wheat-yield variability observed between the two crop years. Compared to results using either the Landsat TM vegetation index or the agrometeorological data alone, the joint use of both types of data in a single model yielded a significant improvement.

Factors Affecting Firm Yield and the Estimation of Firm Yield for Selected Streamflow-Dominated Drinking-Water-Supply Reservoirs in Massachusetts

USGS Publications Warehouse

Waldron, Marcus C.; Archfield, Stacey A.

2006-01-01

Factors affecting reservoir firm yield, as determined by application of the Massachusetts Department of Environmental Protection's Firm Yield Estimator (FYE) model, were evaluated, modified, and tested on 46 streamflow-dominated reservoirs representing 15 Massachusetts drinking-water supplies. The model uses a mass-balance approach to determine the maximum average daily withdrawal rate that can be sustained during a period of record that includes the 1960s drought-of-record. The FYE methodology to estimate streamflow to the reservoir at an ungaged site was tested by simulating streamflow at two streamflow-gaging stations in Massachusetts and comparing the simulated streamflow to the observed streamflow. In general, the FYE-simulated flows agreed well with observed flows. There were substantial deviations from the measured values for extreme high and low flows. A sensitivity analysis determined that the model's streamflow estimates are most sensitive to input values for average annual precipitation, reservoir drainage area, and the soil-retention number-a term that describes the amount of precipitation retained by the soil in the basin. The FYE model currently provides the option of using a 1,000-year synthetic record constructed by randomly sampling 2-year blocks of concurrent streamflow and precipitation records 500 times; however, the synthetic record has the potential to generate records of precipitation and streamflow that do not reflect the worst historical drought in Massachusetts. For reservoirs that do not have periods of drawdown greater than 2 years, the bootstrap does not offer any additional information about the firm yield of a reservoir than the historical record does. For some reservoirs, the use of a synthetic record to determine firm yield resulted in as much as a 30-percent difference between firm-yield values from one simulation to the next. Furthermore, the assumption that the synthetic traces of streamflow are statistically equivalent to the historical record is not valid. For multiple-reservoir systems, the firm-yield estimate was dependent on the reservoir system's configuration. The firm yield of a system is sensitive to how the water is transferred from one reservoir to another, the capacity of the connection between the reservoirs, and how seasonal variations in demand are represented in the FYE model. Firm yields for 25 (14 single-reservoir systems and 11 multiple-reservoir systems) reservoir systems were determined by using the historical records of streamflow and precipitation. Current water-use data indicate that, on average, 20 of the 25 reservoir systems in the study were operating below their estimated firm yield; during months with peak demands, withdrawals exceeded the firm yield for 8 reservoir systems.

Questa baseline and pre-mining ground-water quality investigation. 21. Hydrology and water balance of the Red River basin, New Mexico 1930-2004

USGS Publications Warehouse

Naus, Cheryl A.; McAda, Douglas P.; Myers, Nathan C.

2006-01-01

A study of the hydrology of the Red River Basin of northern New Mexico, including development of a pre- mining water balance, contributes to a greater understanding of processes affecting the flow and chemistry of water in the Red River and its alluvial aquifer. Estimates of mean annual precipitation for the Red River Basin ranged from 22.32 to 25.19 inches. Estimates of evapotranspiration for the Red River Basin ranged from 15.02 to 22.45 inches or 63.23 to 94.49 percent of mean annual precipitation. Mean annual yield from the Red River Basin estimated using regression equations ranged from 45.26 to 51.57 cubic feet per second. Mean annual yield from the Red River Basin estimated by subtracting evapotranspiration from mean annual precipitation ranged from 55.58 to 93.15 cubic feet per second. In comparison, naturalized 1930-2004 mean annual streamflow at the Red River near Questa gage was 48.9 cubic feet per second. Although estimates developed using regression equations appear to be a good representation of yield from the Red River Basin as a whole, the methods that consider evapotranspiration may more accurately represent yield from smaller basins that have a substantial amount of sparsely vegetated scar area. Hydrograph separation using the HYSEP computer program indicated that subsurface flow for 1930-2004 ranged from 76 to 94 percent of streamflow for individual years with a mean of 87 percent of streamflow. By using a chloride mass-balance method, ground-water recharge was estimated to range from 7 to 17 percent of mean annual precipitation for water samples from wells in Capulin Canyon and the Hansen, Hottentot, La Bobita, and Straight Creek Basins and was 21 percent of mean annual precipitation for water samples from the Red River. Comparisons of mean annual basin yield and measured streamflow indicate that streamflow does not consistently increase as cumulative estimated mean annual basin yield increases. Comparisons of estimated mean annual yield and measured streamflow profiles indicates that, in general, the river is gaining ground water from the alluvium in the reach from the town of Red River to between Hottentot and Straight Creeks, and from Columbine Creek to near Thunder Bridge. The river is losing water to the alluvium from upstream of the mill area to Columbine Creek. Interpretations of ground- and surface-water interactions based on comparisons of mean annual basin yield and measured streamflow are supported further with water-level data from piezometers, wells, and the Red River.

Similar Estimates of Temperature Impacts on Global Wheat Yield by Three Independent Methods

NASA Technical Reports Server (NTRS)

Liu, Bing; Asseng, Senthold; Muller, Christoph; Ewart, Frank; Elliott, Joshua; Lobell, David B.; Martre, Pierre; Ruane, Alex C.; Wallach, Daniel; Jones, James W.;

Similar estimates of temperature impacts on global wheat yield by three independent methods

NASA Astrophysics Data System (ADS)

Liu, Bing; Asseng, Senthold; Müller, Christoph; Ewert, Frank; Elliott, Joshua; Lobell, David B.; Martre, Pierre; Ruane, Alex C.; Wallach, Daniel; Jones, James W.; Rosenzweig, Cynthia; Aggarwal, Pramod K.; Alderman, Phillip D.; Anothai, Jakarat; Basso, Bruno; Biernath, Christian; Cammarano, Davide; Challinor, Andy; Deryng, Delphine; Sanctis, Giacomo De; Doltra, Jordi; Fereres, Elias; Folberth, Christian; Garcia-Vila, Margarita; Gayler, Sebastian; Hoogenboom, Gerrit; Hunt, Leslie A.; Izaurralde, Roberto C.; Jabloun, Mohamed; Jones, Curtis D.; Kersebaum, Kurt C.; Kimball, Bruce A.; Koehler, Ann-Kristin; Kumar, Soora Naresh; Nendel, Claas; O'Leary, Garry J.; Olesen, Jørgen E.; Ottman, Michael J.; Palosuo, Taru; Prasad, P. V. Vara; Priesack, Eckart; Pugh, Thomas A. M.; Reynolds, Matthew; Rezaei, Ehsan E.; Rötter, Reimund P.; Schmid, Erwin; Semenov, Mikhail A.; Shcherbak, Iurii; Stehfest, Elke; Stöckle, Claudio O.; Stratonovitch, Pierre; Streck, Thilo; Supit, Iwan; Tao, Fulu; Thorburn, Peter; Waha, Katharina; Wall, Gerard W.; Wang, Enli; White, Jeffrey W.; Wolf, Joost; Zhao, Zhigan; Zhu, Yan

2016-12-01

The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO2 fertilization effects, produce similar estimates of temperature impact on wheat yields at global and national scales. With a 1 °C global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%. Projected relative temperature impacts from different methods were similar for major wheat-producing countries China, India, USA and France, but less so for Russia. Point-based and grid-based simulations, and to some extent the statistical regressions, were consistent in projecting that warmer regions are likely to suffer more yield loss with increasing temperature than cooler regions. By forming a multi-method ensemble, it was possible to quantify `method uncertainty’ in addition to model uncertainty. This significantly improves confidence in estimates of climate impacts on global food security.

Estimation of demographic parameters in a tiger population from long-term camera trap data

USGS Publications Warehouse

Karanth, K. Ullas; Nichols, James D.; O'Connell, Allan F.; Nichols, James D.; Karanth, K. Ullas

2011-01-01

Chapter 7 (Karanth et al.) illustrated the use of camera trapping in combination with closed population capture–recapture (CR) models to estimate densities of tigers Panthera tigris. Such estimates can be very useful for investigating variation across space for a particular species (e.g., Karanth et al. 2004) or variation among species at a specific location. In addition, estimates of density continued at the same site(s) over multiple years are very useful for understanding and managing populations of large carnivores. Such multi-year studies can yield estimates of rates of change in abundance. Additionally, because the fates of marked individuals are tracked through time, biologists can delve deeper into factors driving changes in abundance such as rates of survival, recruitment and movement (Williams et al. 2002). Fortunately, modern CR approaches permit the modeling of populations that change between sampling occasions as a result of births, deaths, immigration and emigration (Pollock et al. 1990; Nichols 1992). Some of these early “open population” models focused on estimation of survival rates and, to a lesser extent, abundance, but more recent models permit estimation of recruitment and movement rates as well.

Nut crop yield records show that budbreak-based chilling requirements may not reflect yield decline chill thresholds

NASA Astrophysics Data System (ADS)

Pope, Katherine S.; Dose, Volker; Da Silva, David; Brown, Patrick H.; DeJong, Theodore M.

2015-06-01

Warming winters due to climate change may critically affect temperate tree species. Insufficiently cold winters are thought to result in fewer viable flower buds and the subsequent development of fewer fruits or nuts, decreasing the yield of an orchard or fecundity of a species. The best existing approximation for a threshold of sufficient cold accumulation, the "chilling requirement" of a species or variety, has been quantified by manipulating or modeling the conditions that result in dormant bud breaking. However, the physiological processes that affect budbreak are not the same as those that determine yield. This study sought to test whether budbreak-based chilling thresholds can reasonably approximate the thresholds that affect yield, particularly regarding the potential impacts of climate change on temperate tree crop yields. County-wide yield records for almond ( Prunus dulcis), pistachio ( Pistacia vera), and walnut ( Juglans regia) in the Central Valley of California were compared with 50 years of weather records. Bayesian nonparametric function estimation was used to model yield potentials at varying amounts of chill accumulation. In almonds, average yields occurred when chill accumulation was close to the budbreak-based chilling requirement. However, in the other two crops, pistachios and walnuts, the best previous estimate of the budbreak-based chilling requirements was 19-32 % higher than the chilling accumulations associated with average or above average yields. This research indicates that physiological processes beyond requirements for budbreak should be considered when estimating chill accumulation thresholds of yield decline and potential impacts of climate change.

Online evaluation of a commercial video image analysis system (Computer Vision System) to predict beef carcass red meat yield and for augmenting the assignment of USDA yield grades. United States Department of Agriculture.

PubMed

Cannell, R C; Belk, K E; Tatum, J D; Wise, J W; Chapman, P L; Scanga, J A; Smith, G C

2002-05-01

Objective quantification of differences in wholesale cut yields of beef carcasses at plant chain speeds is important for the application of value-based marketing. This study was conducted to evaluate the ability of a commercial video image analysis system, the Computer Vision System (CVS) to 1) predict commercially fabricated beef subprimal yield and 2) augment USDA yield grading, in order to improve accuracy of grade assessment. The CVS was evaluated as a fully installed production system, operating on a full-time basis at chain speeds. Steer and heifer carcasses (n = 296) were evaluated using CVS, as well as by USDA expert and online graders, before the fabrication of carcasses into industry-standard subprimal cuts. Expert yield grade (YG), online YG, CVS estimated carcass yield, and CVS measured ribeye area in conjunction with expert grader estimates of the remaining YG factors (adjusted fat thickness, percentage of kidney-pelvic-heart fat, hot carcass weight) accounted for 67, 39, 64, and 65% of the observed variation in fabricated yields of closely trimmed subprimals. The dual component CVS predicted wholesale cut yields more accurately than current online yield grading, and, in an augmentation system, CVS ribeye measurement replaced estimated ribeye area in determination of USDA yield grade, and the accuracy of cutability prediction was improved, under packing plant conditions and speeds, to a level close to that of expert graders applying grades at a comfortable rate of speed offline.

Wechsler Intelligence Scale for Children-fourth edition (WISC-IV) short-form validity: a comparison study in pediatric epilepsy.

PubMed

Hrabok, Marianne; Brooks, Brian L; Fay-McClymont, Taryn B; Sherman, Elisabeth M S

2014-01-01

The purpose of this article was to investigate the accuracy of the WISC-IV short forms in estimating Full Scale Intelligence Quotient (FSIQ) and General Ability Index (GAI) in pediatric epilepsy. One hundred and four children with epilepsy completed the WISC-IV as part of a neuropsychological assessment at a tertiary-level children's hospital. The clinical accuracy of eight short forms was assessed in two ways: (a) accuracy within +/- 5 index points of FSIQ and (b) the clinical classification rate according to Wechsler conventions. The sample was further subdivided into low FSIQ (≤ 80) and high FSIQ (> 80). All short forms were significantly correlated with FSIQ. Seven-subtest (Crawford et al. [2010] FSIQ) and 5-subtest (BdSiCdVcLn) short forms yielded the highest clinical accuracy rates (77%-89%). Overall, a 2-subtest (VcMr) short form yielded the lowest clinical classification rates for FSIQ (35%-63%). The short form yielding the most accurate estimate of GAI was VcSiMrBd (73%-84%). Short forms show promise as useful estimates. The 7-subtest (Crawford et al., 2010) and 5-subtest (BdSiVcLnCd) short forms yielded the most accurate estimates of FSIQ. VcSiMrBd yielded the most accurate estimate of GAI. Clinical recommendations are provided for use of short forms in pediatric epilepsy.

A review of the application of propensity score methods yielded increasing use, advantages in specific settings, but not substantially different estimates compared with conventional multivariable methods

PubMed Central

Stürmer, Til; Joshi, Manisha; Glynn, Robert J.; Avorn, Jerry; Rothman, Kenneth J.; Schneeweiss, Sebastian

2006-01-01

Objective Propensity score analyses attempt to control for confounding in non-experimental studies by adjusting for the likelihood that a given patient is exposed. Such analyses have been proposed to address confounding by indication, but there is little empirical evidence that they achieve better control than conventional multivariate outcome modeling. Study design and methods Using PubMed and Science Citation Index, we assessed the use of propensity scores over time and critically evaluated studies published through 2003. Results Use of propensity scores increased from a total of 8 papers before 1998 to 71 in 2003. Most of the 177 published studies abstracted assessed medications (N=60) or surgical interventions (N=51), mainly in cardiology and cardiac surgery (N=90). Whether PS methods or conventional outcome models were used to control for confounding had little effect on results in those studies in which such comparison was possible. Only 9 out of 69 studies (13%) had an effect estimate that differed by more than 20% from that obtained with a conventional outcome model in all PS analyses presented. Conclusions Publication of results based on propensity score methods has increased dramatically, but there is little evidence that these methods yield substantially different estimates compared with conventional multivariable methods. PMID:16632131

Building and using a statistical 3D motion atlas for analyzing myocardial contraction in MRI

NASA Astrophysics Data System (ADS)

Rougon, Nicolas F.; Petitjean, Caroline; Preteux, Francoise J.

2004-05-01

We address the issue of modeling and quantifying myocardial contraction from 4D MR sequences, and present an unsupervised approach for building and using a statistical 3D motion atlas for the normal heart. This approach relies on a state-of-the-art variational non rigid registration (NRR) technique using generalized information measures, which allows for robust intra-subject motion estimation and inter-subject anatomical alignment. The atlas is built from a collection of jointly acquired tagged and cine MR exams in short- and long-axis views. Subject-specific non parametric motion estimates are first obtained by incremental NRR of tagged images onto the end-diastolic (ED) frame. Individual motion data are then transformed into the coordinate system of a reference subject using subject-to-reference mappings derived by NRR of cine ED images. Finally, principal component analysis of aligned motion data is performed for each cardiac phase, yielding a mean model and a set of eigenfields encoding kinematic ariability. The latter define an organ-dedicated hierarchical motion basis which enables parametric motion measurement from arbitrary tagged MR exams. To this end, the atlas is transformed into subject coordinates by reference-to-subject NRR of ED cine frames. Atlas-based motion estimation is then achieved by parametric NRR of tagged images onto the ED frame, yielding a compact description of myocardial contraction during diastole.

Management of the Northern Chesapeake Bay American Shad Fishery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Foerster, J.W.; Reagan, S.P.

1977-11-01

The Shad fisheries of the Chesapeake Bay in Maryland have been declining since an 1897 peak of 7860 x 10/sup 3/ kg. No periods of stability have been recorded. Data are presented to trace the decline not only as a function of specific areas within the Northern Chesapeake Bay but also in terms of environmental problems including reduction of spawning grounds and predation by dams and recruitment overfishing. The problem is related to improving the commercial fishing yield. An estimation of a maximum effort of 200,000 man-hours is suggested if a stable yield is to be approached. Methods for obtainingmore » this goal include alternating of closed fishing areas, adoption of rest days, enforcement of fisheries regulations and reduction of the number of meters of gill net used per fisherman.« less

Preliminary assessment of chloride concentrations, loads, and yields in selected watersheds along the Interstate 95 corridor, southeastern Connecticut, 2008-09

USGS Publications Warehouse

Brown, Craig J.; Mullaney, John R.; Morrison, Jonathan; Mondazzi, Remo

2011-01-01

Water-quality conditions were assessed to evaluate potential effects of road-deicer applications on stream-water quality in four watersheds along Interstate 95 (I-95) in southeastern Connecticut from November 1, 2008, through September 30, 2009. This preliminary study is part of a four-year cooperative study by the U.S. Geological Survey (USGS), the Federal Highway Administration (FHWA), and the Connecticut Department of Transportation (ConnDOT). Streamflow and water quality were studied at four watersheds?Four Mile River, Oil Mill Brook, Stony Brook, and Jordan Brook. Water-quality samples were collected and specific conductance was measured continuously at paired water-quality monitoring sites upstream and downstream from I-95. Specific conductance values were related to chloride (Cl) concentrations to assist in determining the effects of road-deicing operations on the levels of Cl in the streams. Streamflow and water-quality data were compared with weather data and with the timing, amount, and composition of deicers applied to state highways. Grab samples were collected during winter stormwater-runoff events, such as winter storms or periods of rain or warm temperatures in which melting takes place, and periodically during the spring and summer. Cl concentrations at the eight water-quality monitoring sites were well below the U.S. Environmental Protection Agency (USEPA) recommended chronic and acute Cl toxicity criteria of 230 and 860 milligrams per liter (mg/L), respectively. Specific conductance and estimated Cl concentrations in streams, particularly at sites downstream from I-95, peaked during discharge events in the winter and early spring as a result of deicers applied to roads and washed off by stormwater or meltwater. During winter storms, deicing activities, or subsequent periods of melting, specific conductance and estimated Cl concentrations peaked as high as 703 microsiemens per centimeter (?S/cm) and 160 mg/L at the downstream sites. During most of the spring and summer, specific conductance and estimated Cl concentrations decreased during discharge events because the low-ionic strength of stormwater had a diluting effect on stream-water quality. However, peaks in specific conductance and estimated Cl concentrations at Jordan Brook and Stony Brook corresponded to peaks in streamflow well after winter snow or ice events; these delayed peaks in Cl concentration likely resulted from deicing salts that remained in melting snow piles and (or) that were flushed from soils and shallow groundwater, then discharged downstream. Cl loads in streams generally were highest in the winter and early spring. The estimated load for the period of record at the four monitoring sites downstream from I-95 ranged from 0.33 ton per day (ton/d) at the Stony Brook watershed to 0.59 ton/d at the Jordan Brook watershed. The Cl yields ranged from 0.07 ton per day per square mile (ton/d/)mi2) at Oil Mill Brook, one of the least developed watersheds, to 0.21 (ton/d)/mi2) at Jordan Brook, the watershed with the highest percentage of urban development and impervious surfaces. The median estimates of Cl load from atmospheric deposition ranged from 11 to 19 tons, and contributed 4.3 to 7.1 percent of the Cl load in streamflow from the watershed areas. A comparison of the Cl load input and output estimates indicates that less Cl is leaving the watersheds than is entering through atmospheric deposition and application of deicers. The lag time between introduction of Cl to the watershed and transport to the stream, and uncertainty in the load estimates may be the reasons for this discrepancy. In addition, estimates of direct infiltration of Cl to groundwater from atmospheric deposition, deicer applications, and septic-tank drainfields to groundwater were outside the scope of the November 2008 to September 2009 assessment. However, increased concentrations of ions were observed between upstream and downstream sites and could result from deicer appli

Cancer incidence estimates at the national and district levels in Colombia.

PubMed

Piñeros, Marion; Ferlay, Jacques; Murillo, Raúl

2006-01-01

To estimate national and district cancer incidence for 18 major cancer sites in Colombia. National and district incidence was estimated by applying a set of age, sex and site-specific incidence/mortality ratios, obtained from a population-based cancer registry, to national and regional mortality. The work was done in Bogotá (Colombia) and Lyon (France) between May 2003 and August 2004. The annual total number of cases expected (all cancers but skin) was 17 819 in men and 18 772 in women. Among males the most frequent cancers were those of the prostate (45.8 per 100 000), stomach (36.0), and lung (20.0). In females the most frequent were those of the cervix uteri (36.8 per 100 000), breast (30.0), and stomach (20.7). Districts with the lowest death certification coverage yielded the highest incidence rates. In the absence of national population-based cancer registry data, estimates of incidence provide valuable information at national and regional levels. As mortality data are an important source for the estimation,the quality of death certification should be considered as a possible cause of bias.

Evaluation of unconfined-aquifer parameters from pumping test data by nonlinear least squares

NASA Astrophysics Data System (ADS)

Heidari, Manoutchehr; Wench, Allen

1997-05-01

Nonlinear least squares (NLS) with automatic differentiation was used to estimate aquifer parameters from drawdown data obtained from published pumping tests conducted in homogeneous, water-table aquifers. The method is based on a technique that seeks to minimize the squares of residuals between observed and calculated drawdown subject to bounds that are placed on the parameter of interest. The analytical model developed by Neuman for flow to a partially penetrating well of infinitesimal diameter situated in an infinite, homogeneous and anisotropic aquifer was used to obtain calculated drawdown. NLS was first applied to synthetic drawdown data from a hypothetical but realistic aquifer to demonstrate that the relevant hydraulic parameters (storativity, specific yield, and horizontal and vertical hydraulic conductivity) can be evaluated accurately. Next the method was used to estimate the parameters at three field sites with widely varying hydraulic properties. NLS produced unbiased estimates of the aquifer parameters that are close to the estimates obtained with the same data using a visual curve-matching approach. Small differences in the estimates are a consequence of subjective interpretation introduced in the visual approach.

Evaluation of unconfined-aquifer parameters from pumping test data by nonlinear least squares

USGS Publications Warehouse

Heidari, M.; Moench, A.

1997-01-01

Nonlinear least squares (NLS) with automatic differentiation was used to estimate aquifer parameters from drawdown data obtained from published pumping tests conducted in homogeneous, water-table aquifers. The method is based on a technique that seeks to minimize the squares of residuals between observed and calculated drawdown subject to bounds that are placed on the parameter of interest. The analytical model developed by Neuman for flow to a partially penetrating well of infinitesimal diameter situated in an infinite, homogeneous and anisotropic aquifer was used to obtain calculated drawdown. NLS was first applied to synthetic drawdown data from a hypothetical but realistic aquifer to demonstrate that the relevant hydraulic parameters (storativity, specific yield, and horizontal and vertical hydraulic conductivity) can be evaluated accurately. Next the method was used to estimate the parameters at three field sites with widely varying hydraulic properties. NLS produced unbiased estimates of the aquifer parameters that are close to the estimates obtained with the same data using a visual curve-matching approach. Small differences in the estimates are a consequence of subjective interpretation introduced in the visual approach.

Independent Peer Evaluation of the Large Area Crop Inventory Experiment (LACIE): The LACIE Symposium

NASA Technical Reports Server (NTRS)

1978-01-01

Yield models and crop estimate accuracy are discussed within the Large Area Crop Inventory Experiment. The wheat yield estimates in the United States, Canada, and U.S.S.R. are emphasized. Experimental results design, system implementation, data processing systems, and applications were considered.

2017 Louisiana variety development program infield trials

USDA-ARS?s Scientific Manuscript database

The infield stage of variety development is the first stage in which yield estimates are based on plot weights instead of estimated yields derived from stalk population and stalk weight. Varieties from the LSU AgCenter program (L’ s) are planted in infield tests the year after assignment while vari...

76 FR 30265 - Fisheries of the Northeastern United States; Monkfish; Amendment 5

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-25

....nefmc.org . Written comments regarding the burden-hour estimates or other aspects of the collection-of... are not overfished. Furthermore, the current estimated fishing mortality rate for each stock is below... establishes control rules to specify maximum sustainable yield (MSY), optimum yield (OY), overfishing level...

Estimated dose rates to members of the public from external exposure to patients with 131I thyroid treatment

DOE PAGES

Dewji, S.; Bellamy, M.; Hertel, N.; ...

2015-03-25

The purpose of this study is to estimate dose rates that may result from exposure to patients who had been administered iodine-131 ( 131I) as part of medical therapy were calculated. These effective dose rate estimates were compared with simplified assumptions under United States Nuclear Regulatory Commission Regulatory Guide 8.39, which does not consider body tissue attenuation nor time-dependent redistribution and excretion of the administered 131I. Methods: Dose rates were estimated for members of the public potentially exposed to external irradiation from patients recently treated with 131I. Tissue attenuation and iodine biokinetics were considered in the patient in a largermore » comprehensive effort to improve external dose rate estimates. The external dose rate estimates are based on Monte Carlo simulations using the Phantom with Movable Arms and Legs (PIMAL), previously developed by Oak Ridge National Laboratory and the United States Nuclear Regulatory Commission. PIMAL was employed to model the relative positions of the 131I patient and members of the public in three exposure scenarios: (1) traveling on a bus in a total of six seated or standing permutations, (2) two nursing home cases where a caregiver is seated at 30 cm from the patient’s bedside and a nursing home resident seated 250 cm away from the patient in an adjacent bed, and (3) two hotel cases where the patient and a guest are in adjacent rooms with beds on opposite sides of the common wall, with the patient and guest both in bed and either seated back-to-back or lying head to head. The biokinetic model predictions of the retention and distribution of 131I in the patient assumed a single voiding of urinary bladder contents that occurred during the trip at 2, 4, or 8 h after 131I administration for the public transportation cases, continuous first-order voiding for the nursing home cases, and regular periodic voiding at 4, 8, or 12 h after administration for the hotel room cases. Organ specific activities of 131I in the thyroid, bladder, and combined remaining tissues were calculated as a function of time after administration. Exposures to members of the public were considered for 131I patients with normal thyroid uptake (peak thyroid uptake of ~27% of administered 131I), differentiated thyroid cancer (DTC, 5% uptake), and hyperthyroidism (80% uptake). Results: The scenario with the patient seated behind the member of the public yielded the highest dose rate estimate of seated public transportation exposure cases. The dose rate to the adjacent room guest was highest for the exposure scenario in which the hotel guest and patient are seated by a factor of ~4 for the normal and differentiated thyroid cancer uptake cases and by a factor of ~3 for the hyperthyroid case. Conclusions: It was determined that for all modeled cases, the DTC case yielded the lowest external dose rates, whereas the hyperthyroid case yielded the highest dose rates. In estimating external dose to members of the public from patients with 131I therapy, consideration must be given to (patient- and case-specific) administered 131I activities and duration of exposure for a more complete estimate. The method implemented here included a detailed calculation model, which provides a means to determine dose rate estimates for a range of scenarios. Finally, the method was demonstrated for variations of three scenarios, showing how dose rates are expected to vary with uptake, voiding pattern, and patient location.« less

Estimated dose rates to members of the public from external exposure to patients with 131I thyroid treatment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dewji, S.; Bellamy, M.; Hertel, N.

The purpose of this study is to estimate dose rates that may result from exposure to patients who had been administered iodine-131 ( 131I) as part of medical therapy were calculated. These effective dose rate estimates were compared with simplified assumptions under United States Nuclear Regulatory Commission Regulatory Guide 8.39, which does not consider body tissue attenuation nor time-dependent redistribution and excretion of the administered 131I. Methods: Dose rates were estimated for members of the public potentially exposed to external irradiation from patients recently treated with 131I. Tissue attenuation and iodine biokinetics were considered in the patient in a largermore » comprehensive effort to improve external dose rate estimates. The external dose rate estimates are based on Monte Carlo simulations using the Phantom with Movable Arms and Legs (PIMAL), previously developed by Oak Ridge National Laboratory and the United States Nuclear Regulatory Commission. PIMAL was employed to model the relative positions of the 131I patient and members of the public in three exposure scenarios: (1) traveling on a bus in a total of six seated or standing permutations, (2) two nursing home cases where a caregiver is seated at 30 cm from the patient’s bedside and a nursing home resident seated 250 cm away from the patient in an adjacent bed, and (3) two hotel cases where the patient and a guest are in adjacent rooms with beds on opposite sides of the common wall, with the patient and guest both in bed and either seated back-to-back or lying head to head. The biokinetic model predictions of the retention and distribution of 131I in the patient assumed a single voiding of urinary bladder contents that occurred during the trip at 2, 4, or 8 h after 131I administration for the public transportation cases, continuous first-order voiding for the nursing home cases, and regular periodic voiding at 4, 8, or 12 h after administration for the hotel room cases. Organ specific activities of 131I in the thyroid, bladder, and combined remaining tissues were calculated as a function of time after administration. Exposures to members of the public were considered for 131I patients with normal thyroid uptake (peak thyroid uptake of ~27% of administered 131I), differentiated thyroid cancer (DTC, 5% uptake), and hyperthyroidism (80% uptake). Results: The scenario with the patient seated behind the member of the public yielded the highest dose rate estimate of seated public transportation exposure cases. The dose rate to the adjacent room guest was highest for the exposure scenario in which the hotel guest and patient are seated by a factor of ~4 for the normal and differentiated thyroid cancer uptake cases and by a factor of ~3 for the hyperthyroid case. Conclusions: It was determined that for all modeled cases, the DTC case yielded the lowest external dose rates, whereas the hyperthyroid case yielded the highest dose rates. In estimating external dose to members of the public from patients with 131I therapy, consideration must be given to (patient- and case-specific) administered 131I activities and duration of exposure for a more complete estimate. The method implemented here included a detailed calculation model, which provides a means to determine dose rate estimates for a range of scenarios. Finally, the method was demonstrated for variations of three scenarios, showing how dose rates are expected to vary with uptake, voiding pattern, and patient location.« less

Estimating nutrient uptake requirements for soybean using QUEFTS model in China

PubMed Central

Yang, Fuqiang; Xu, Xinpeng; Wang, Wei; Ma, Jinchuan; Wei, Dan; He, Ping; Pampolino, Mirasol F.; Johnston, Adrian M.

2017-01-01

Estimating balanced nutrient requirements for soybean (Glycine max [L.] Merr) in China is essential for identifying optimal fertilizer application regimes to increase soybean yield and nutrient use efficiency. We collected datasets from field experiments in major soybean planting regions of China between 2001 and 2015 to assess the relationship between soybean seed yield and nutrient uptake, and to estimate nitrogen (N), phosphorus (P), and potassium (K) requirements for a target yield of soybean using the quantitative evaluation of the fertility of tropical soils (QUEFTS) model. The QUEFTS model predicted a linear–parabolic–plateau curve for the balanced nutrient uptake with a target yield increased from 3.0 to 6.0 t ha−1 and the linear part was continuing until the yield reached about 60–70% of the potential yield. To produce 1000 kg seed of soybean in China, 55.4 kg N, 7.9 kg P, and 20.1 kg K (N:P:K = 7:1:2.5) were required in the above-ground parts, and the corresponding internal efficiencies (IE, kg seed yield per kg nutrient uptake) were 18.1, 126.6, and 49.8 kg seed per kg N, P, and K, respectively. The QUEFTS model also simulated that a balanced N, P, and K removal by seed which were 48.3, 5.9, and 12.2 kg per 1000 kg seed, respectively, accounting for 87.1%, 74.1%, and 60.8% of the total above-ground parts, respectively. These results were conducive to make fertilizer recommendations that improve the seed yield of soybean and avoid excessive or deficient nutrient supplies. Field validation indicated that the QUEFTS model could be used to estimate nutrient requirements which help develop fertilizer recommendations for soybean. PMID:28498839

Effects of Bleaching by Nitrogen Deficiency on the Quantum Yield of Photosystem II in Synechocystis sp. PCC 6803 Revealed by Chl Fluorescence Measurements.

PubMed

Ogawa, Takako; Sonoike, Kintake

2016-03-01

Estimation of photosynthesis by Chl fluorescence measurement of cyanobacteria is always problematic due to the interference from respiratory electron transfer and from phycocyanin fluorescence. The interference from respiratory electron transfer could be avoided by the use of DCMU or background illumination by blue light, which oxidizes the plastoquinone pool that tends to be reduced by respiration. On the other hand, the precise estimation of photosynthesis in cells with a different phycobilisome content by Chl fluorescence measurement is difficult. By subtracting the basal fluorescence due to the phycobilisome and PSI, it becomes possible to estimate the precise maximum quantum yield of PSII in cyanobacteria. Estimated basal fluorescence accounted for 60% of the minimum fluorescence, resulting in a large difference between the 'apparent' yield and 'true' yield under high phycocyanin conditions. The calculated value of the 'true' maximum quantum yield of PSII was around 0.8, which was similar to the value observed in land plants. The results suggest that the cause of the apparent low yield reported in cyanobacteria is mainly ascribed to the interference from phycocyanin fluorescence. We also found that the 'true' maximum quantum yield of PSII decreased under nitrogen-deficient conditions, suggesting the impairment of the PSII reaction center, while the 'apparent' maximum quantum yield showed a marginal change under the same conditions. Due to the high contribution of phycocyanin fluorescence in cyanobacteria, it is essential to eliminate the influence of the change in phycocyanin content on Chl fluorescence measurement and to evaluate the 'true' photosynthetic condition. © The Author 2016. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Genetic evaluation of lactation persistency for five breeds of dairy cattle.

PubMed

Cole, J B; Null, D J

2009-05-01

Cows with high lactation persistency tend to produce less milk than expected at the beginning of lactation and more than expected at the end. Best prediction of lactation persistency is calculated as a function of trait-specific standard lactation curves and linear regressions of test-day deviations on days in milk. Because regression coefficients are deviations from a tipping point selected to make yield and lactation persistency phenotypically uncorrelated it should be possible to use 305-d actual yield and lactation persistency to predict yield for lactations with later endpoints. The objectives of this study were to calculate (co)variance components and breeding values for best predictions of lactation persistency of milk (PM), fat (PF), protein (PP), and somatic cell score (PSCS) in breeds other than Holstein, and to demonstrate the calculation of prediction equations for 400-d actual milk yield. Data included lactations from Ayrshire, Brown Swiss, Guernsey (GU), Jersey (JE), and Milking Shorthorn (MS) cows calving since 1997. The number of sires evaluated ranged from 86 (MS) to 3,192 (JE), and mean sire estimated breeding value for PM ranged from 0.001 (Ayrshire) to 0.10 (Brown Swiss); mean estimated breeding value for PSCS ranged from -0.01 (MS) to -0.043 (JE). Heritabilities were generally highest for PM (0.09 to 0.15) and lowest for PSCS (0.03 to 0.06), with PF and PP having intermediate values (0.07 to 0.13). Repeatabilities varied considerably between breeds, ranging from 0.08 (PSCS in GU, JE, and MS) to 0.28 (PM in GU). Genetic correlations of PM, PF, and PP with PSCS were moderate and favorable (negative), indicating that increasing lactation persistency of yield traits is associated with decreases in lactation persistency of SCS, as expected. Genetic correlations among yield and lactation persistency were low to moderate and ranged from -0.55 (PP in GU) to 0.40 (PP in MS). Prediction equations for 400-d milk yield were calculated for each breed by regression of both 305-d yield and 305-d yield and lactation persistency on 400-d yield. Goodness-of-fit was very good for both models, but the addition of lactation persistency to the model significantly improved fit in all cases. Routine genetic evaluations for lactation persistency, as well as the development of prediction equations for several lactation end-points, may provide producers with tools to better manage their herds.

Genetic correlations between the cumulative pseudo-survival rate, milk yield, and somatic cell score during lactation in Holstein cattle in Japan using a random regression model.

PubMed

Sasaki, O; Aihara, M; Nishiura, A; Takeda, H

2017-09-01

Trends in genetic correlations between longevity, milk yield, and somatic cell score (SCS) during lactation in cows are difficult to trace. In this study, changes in the genetic correlations between milk yield, SCS, and cumulative pseudo-survival rate (PSR) during lactation were examined, and the effect of milk yield and SCS information on the reliability of estimated breeding value (EBV) of PSR were determined. Test day milk yield, SCS, and PSR records were obtained for Holstein cows in Japan from 2004 to 2013. A random subset of the data was used for the analysis (825 herds, 205,383 cows). This data set was randomly divided into 5 subsets (162-168 herds, 83,389-95,854 cows), and genetic parameters were estimated in each subset independently. Data were analyzed using multiple-trait random regression animal models including either the residual effect for the whole lactation period (H0), the residual effects for 5 lactation stages (H5), or both of these residual effects (HD). Milk yield heritability increased until 310 to 351 d in milk (DIM) and SCS heritability increased until 330 to 344 DIM. Heritability estimates for PSR increased with DIM from 0.00 to 0.05. The genetic correlation between milk yield and SCS increased negatively to under -0.60 at 455 DIM. The genetic correlation between milk yield and PSR increased until 342 to 355 DIM (0.53-0.57). The genetic correlation between the SCS and PSR was -0.82 to -0.83 at around 180 DIM, and decreased to -0.65 to -0.71 at 455 DIM. The reliability of EBV of PSR for sires with 30 or more recorded daughters was 0.17 to 0.45 when the effects of correlated traits were ignored. The maximum reliability of EBV was observed at 257 (H0) or 322 (HD) DIM. When the correlations of PSR with milk yield and SCS were considered, the reliabilities of PSR estimates increased to 0.31-0.76. The genetic parameter estimates of H5 were the same as those for HD. The rank correlation coefficients of the EBV of PSR between H0 and H5 or HD were greater than 0.9. Additionally, the reliabilities of EBV of PSR of H0 were similar to those for H5 and HD. Therefore, the genetic parameter estimates in H0 were not substantially different from those in H5 and HD. When milk yield and SCS, which were genetically correlated with PSR, were used, the reliability of PSR increased. Estimates of the genetic correlations between PSR and milk yield and between PSR and SCS are useful for management and breeding decisions to extend the herd life of cows. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Modeling of an integrated fermentation/membrane extraction process for the production of 2-phenylethanol and 2-phenylethylacetate.

PubMed

Adler, Philipp; Hugen, Thorsten; Wiewiora, Marzena; Kunz, Benno

2011-03-07

An unstructured model for an integrated fermentation/membrane extraction process for the production of the aroma compounds 2-phenylethanol and 2-phenylethylacetate by Kluyveromyces marxianus CBS 600 was developed. The extent to which this model, based only on data from the conventional fermentation and separation processes, provided an estimation of the integrated process was evaluated. The effect of product inhibition on specific growth rate and on biomass yield by both aroma compounds was approximated by multivariate regression. Simulations of the respective submodels for fermentation and the separation process matched well with experimental results. With respect to the in situ product removal (ISPR) process, the effect of reduced product inhibition due to product removal on specific growth rate and biomass yield was predicted adequately by the model simulations. Overall product yields were increased considerably in this process (4.0 g/L 2-PE+2-PEA vs. 1.4 g/L in conventional fermentation) and were even higher than predicted by the model. To describe the effect of product concentration on product formation itself, the model was extended using results from the conventional and the ISPR process, thus agreement between model and experimental data improved notably. Therefore, this model can be a useful tool for the development and optimization of an efficient integrated bioprocess. Copyright © 2010 Elsevier Inc. All rights reserved.

What Is the Role of Land-Use Compositions and Spatial Configurations in Sediment Yield from Mountainous Watershed?

NASA Astrophysics Data System (ADS)

Shi, Z. H.

2014-12-01

There are strong ties between land use and sediment yield in watersheds. Many studies have used multivariate regression techniques to explore the response of sediment yield to land-use compositions and spatial configurations in watersheds. However, one issue with the use of conventional statistical methods to address relationships between land-use compositions and spatial configurations and sediment yield is multicollinearity. This paper examines the combined effects of land-use compositions and land-use spatial configurations of the watershed on the specific sediment yield of the Upper Du River watershed (8,973 km2) in China using the Soil and Water Assessment Tool (SWAT) and partial least-squares regression (PLSR). The land-use compositions and spatial configurations of the watershed were calculated at the sub-watershed scale. The sediment yields from sub-watershed were evaluated using SWAT model. The first-order factors were identified by calculating the variable importance for the projection (VIP). The results revealed that the land-use compositions exerted the largest effects on the specific sediment yield and explained 61.2% of the variation in the specific sediment yield. Land-use spatial configurations were also found to have a large effect on the specific sediment yield and explained 21.7% of the observed variation in the specific sediment yield. The following are the dominant first-order factors of the specific sediment yield at the sub-watershed scale: the areal percentages of agriculture and forest, patch density, value of the Shannon's diversity index, contagion. The VIP values suggested that the Shannon's diversity index and contagion are important factors for sediment delivery.

Alcohol intake and gastric cancer: Meta-analyses of published data versus individual participant data pooled analyses (StoP Project).

PubMed

Ferro, Ana; Morais, Samantha; Rota, Matteo; Pelucchi, Claudio; Bertuccio, Paola; Bonzi, Rossella; Galeone, Carlotta; Zhang, Zuo-Feng; Matsuo, Keitaro; Ito, Hidemi; Hu, Jinfu; Johnson, Kenneth C; Yu, Guo-Pei; Palli, Domenico; Ferraroni, Monica; Muscat, Joshua; Malekzadeh, Reza; Ye, Weimin; Song, Huan; Zaridze, David; Maximovitch, Dmitry; Fernández de Larrea, Nerea; Kogevinas, Manolis; Vioque, Jesus; Navarrete-Muñoz, Eva M; Pakseresht, Mohammadreza; Pourfarzi, Farhad; Wolk, Alicja; Orsini, Nicola; Bellavia, Andrea; Håkansson, Niclas; Mu, Lina; Pastorino, Roberta; Kurtz, Robert C; Derakhshan, Mohammad H; Lagiou, Areti; Lagiou, Pagona; Boffetta, Paolo; Boccia, Stefania; Negri, Eva; La Vecchia, Carlo; Peleteiro, Bárbara; Lunet, Nuno

2018-05-01

Individual participant data pooled analyses allow access to non-published data and statistical reanalyses based on more homogeneous criteria than meta-analyses based on systematic reviews. We quantified the impact of publication-related biases and heterogeneity in data analysis and presentation in summary estimates of the association between alcohol drinking and gastric cancer. We compared estimates obtained from conventional meta-analyses, using only data available in published reports from studies that take part in the Stomach Cancer Pooling (StoP) Project, with individual participant data pooled analyses including the same studies. A total of 22 studies from the StoP Project assessed the relation between alcohol intake and gastric cancer, 19 had specific data for levels of consumption and 18 according to cancer location; published reports addressing these associations were available from 18, 5 and 5 studies, respectively. The summary odds ratios [OR, (95%CI)] estimate obtained with published data for drinkers vs. non-drinkers was 10% higher than the one obtained with individual StoP data [18 vs. 22 studies: 1.21 (1.07-1.36) vs. 1.10 (0.99-1.23)] and more heterogeneous (I 2 : 63.6% vs 54.4%). In general, published data yielded less precise summary estimates (standard errors up to 2.6 times higher). Funnel plot analysis suggested publication bias. Meta-analyses of the association between alcohol drinking and gastric cancer tended to overestimate the magnitude of the effects, possibly due to publication bias. Additionally, individual participant data pooled analyses yielded more precise estimates for different levels of exposure or cancer subtypes. Copyright © 2018 Elsevier Ltd. All rights reserved.

A Comparison of Yield Studies of Slash Pine in Old-Field Plantations

Treesearch

F.A. Bennett; R. L. Barnes; J.L. Clutter; C.E. McGee

1970-01-01

This report compares three yield studies of slash pine in old-field plantation. Similarities and differences in yield are disccssed. Within the range of sample data common to all studies, yield estimates are similar; major difierences occur only in extrapolated values.

Satellite-based studies of maize yield spatial variations and their causes in China

NASA Astrophysics Data System (ADS)

Zhao, Y.

2013-12-01

Maize production in China has been expanding significantly in the past two decades, but yield has become relatively stagnant in the past few years, and needs to be improved to meet increasing demand. Multiple studies found that the gap between potential and actual yield of maize is as large as 40% to 60% of yield potential. Although a few major causes of yield gap have been qualitatively identified with surveys, there has not been spatial analysis aimed at quantifying relative importance of specific biophysical and socio-economic causes, information which would be useful for targeting interventions. This study analyzes the causes of yield variation at field and village level in Quzhou county of North China Plain (NCP). We combine remote sensing and crop modeling to estimate yields in 2009-2012, and identify fields that are consistently high or low yielding. To establish the relationship between yield and potential factors, we gather data on those factors through a household survey. We select targeted survey fields such that not only both extremes of yield distribution but also all soil texture categories in the county is covered. Our survey assesses management and biophysical factors as well as social factors such as farmers' access to agronomic knowledge, which is approximated by distance to the closest demonstration plot or 'Science and technology backyard'. Our survey covers 10 townships, 53 villages and 180 fields. Three to ten farmers are surveyed depending on the amount of variation present among sub pixels of each field. According to survey results, we extract the amount of variation within as well as between villages and or soil type. The higher within village or within field variation, the higher importance of management factors. Factors such as soil type and access to knowledge are more represented by between village variation. Through regression and analysis of variance, we gain more quantitative and thorough understanding of causes to yield variation at village scale, which further explains the gap between average and highest achieved yield.

A Bayesian state-space formulation of dynamic occupancy models

USGS Publications Warehouse

Royle, J. Andrew; Kery, M.

2007-01-01

Species occurrence and its dynamic components, extinction and colonization probabilities, are focal quantities in biogeography and metapopulation biology, and for species conservation assessments. It has been increasingly appreciated that these parameters must be estimated separately from detection probability to avoid the biases induced by nondetection error. Hence, there is now considerable theoretical and practical interest in dynamic occupancy models that contain explicit representations of metapopulation dynamics such as extinction, colonization, and turnover as well as growth rates. We describe a hierarchical parameterization of these models that is analogous to the state-space formulation of models in time series, where the model is represented by two components, one for the partially observable occupancy process and another for the observations conditional on that process. This parameterization naturally allows estimation of all parameters of the conventional approach to occupancy models, but in addition, yields great flexibility and extensibility, e.g., to modeling heterogeneity or latent structure in model parameters. We also highlight the important distinction between population and finite sample inference; the latter yields much more precise estimates for the particular sample at hand. Finite sample estimates can easily be obtained using the state-space representation of the model but are difficult to obtain under the conventional approach of likelihood-based estimation. We use R and Win BUGS to apply the model to two examples. In a standard analysis for the European Crossbill in a large Swiss monitoring program, we fit a model with year-specific parameters. Estimates of the dynamic parameters varied greatly among years, highlighting the irruptive population dynamics of that species. In the second example, we analyze route occupancy of Cerulean Warblers in the North American Breeding Bird Survey (BBS) using a model allowing for site-specific heterogeneity in model parameters. The results indicate relatively low turnover and a stable distribution of Cerulean Warblers which is in contrast to analyses of counts of individuals from the same survey that indicate important declines. This discrepancy illustrates the inertia in occupancy relative to actual abundance. Furthermore, the model reveals a declining patch survival probability, and increasing turnover, toward the edge of the range of the species, which is consistent with metapopulation perspectives on the genesis of range edges. Given detection/non-detection data, dynamic occupancy models as described here have considerable potential for the study of distributions and range dynamics.

Environmental and genetic factors affecting milk yield and quality in three Italian sheep breeds.

PubMed

Selvaggi, Maria; D'Alessandro, Angela Gabriella; Dario, Cataldo

2017-02-01

The aims of the study described in the Research Communication were to determine the level of influence of some environmental factors on milk yield and quality traits, including lactose, and lactation length in ewes belonging to three different Italian breeds and to estimate the heritability for the same traits. A total of 2138 lactation records obtained from 535 ewes belonging to three different Italian breeds (Comisana, Leccese, and Sarda) were used. Breed significantly affected all of the considered traits. Moreover, year of lambing affected milk yield and lactation length without influence on milk quality traits. Parity affected significantly only the milk yield, whereas type of birth showed its effect on milk yield, fat, protein, and lactose yield. On the whole, the presently reported heritability estimates are within the range of those already obtained in other dairy breeds by other authors, with values for lactation length being very low in all the investigated populations. Considering the heritability estimates for lactose content and yield, to the best of our knowledge, there is a lack of information on these parameters in ovine species and this is the first report on heritability of lactose content and yield in dairy sheep breeds. Our results suggest that genetic variability for milk traits other than lactation length is adequate for selection indicating a good response to selection in these breeds.

Soviet test yields

NASA Astrophysics Data System (ADS)

Vergino, Eileen S.

Soviet seismologists have published descriptions of 96 nuclear explosions conducted from 1961 through 1972 at the Semipalatinsk test site, in Kazakhstan, central Asia [Bocharov et al., 1989]. With the exception of releasing news about some of their peaceful nuclear explosions (PNEs) the Soviets have never before published such a body of information.To estimate the seismic yield of a nuclear explosion it is necessary to obtain a calibrated magnitude-yield relationship based on events with known yields and with a consistent set of seismic magnitudes. U.S. estimation of Soviet test yields has been done through application of relationships to the Soviet sites based on the U.S. experience at the Nevada Test Site (NTS), making some correction for differences due to attenuation and near-source coupling of seismic waves.

Temporal Variations of Water Productivity in Irrigated Corn: An Analysis of Factors Influencing Yield and Water Use across Central Nebraska

PubMed Central

Carr, Tony; Yang, Haishun; Ray, Chittaranjan

2016-01-01

Water Productivity (WP) of a crop defines the relationship between the economic or physical yield of the crop and its water use. With this concept it is possible to identify disproportionate water use or water-limited yield gaps and thereby support improvements in agricultural water management. However, too often important qualitative and quantitative environmental factors are not part of a WP analysis and therefore neglect the aspect of maintaining a sustainable agricultural system. In this study, we examine both the physical and economic WP in perspective with temporally changing environmental conditions. The physical WP analysis was performed by comparing simulated maximum attainable corn yields per unit of water using the crop model Hybrid-Maize with observed data from 2005 through 2013 from 108 farm plots in the Central Platte and the Tri Basin Natural Resource Districts of Nebraska. In order to expand the WP analysis on external factors influencing yields, a second model, Maize-N, was used to estimate optimal nitrogen (N)–fertilizer rate for specific fields in the study area. Finally, a vadose zone flow and transport model, HYDRUS-1D for simulating vertical nutrient transport in the soil, was used to estimate locations of nitrogen pulses in the soil profile. The comparison of simulated and observed data revealed that WP was not on an optimal level, mainly due to large amounts of irrigation used in the study area. The further analysis illustrated year-to-year variations of WP during the nine consecutive years, as well as the need to improve fertilizer management to favor WP and environmental quality. In addition, we addressed the negative influence of groundwater depletion on the economic WP through increasing pumping costs. In summary, this study demonstrated that involving temporal variations of WP as well as associated environmental and economic issues can represent a bigger picture of WP that can help to create incentives to sustainably improve agricultural production. PMID:27575368

Earth's portfolio of extreme sediment transport events

NASA Astrophysics Data System (ADS)

Korup, Oliver

2012-05-01

Quantitative estimates of sediment flux and the global cycling of sediments from hillslopes to rivers, estuaries, deltas, continental shelves, and deep-sea basins have a long research tradition. In this context, extremely large and commensurately rare sediment transport events have so far eluded a systematic analysis. To start filling this knowledge gap I review some of the highest reported sediment yields in mountain rivers impacted by volcanic eruptions, earthquake- and storm-triggered landslide episodes, and catastrophic dam breaks. Extreme specific yields, defined here as those exceeding the 95th percentile of compiled data, are ~ 104 t km- 2 yr- 1 if averaged over 1 yr. These extreme yields vary by eight orders of magnitude, but systematically decay with reference intervals from minutes to millennia such that yields vary by three orders of magnitude for a given reference interval. Sediment delivery from natural dam breaks and pyroclastic eruptions dominate these yields for a given reference interval. Even if averaged over 102-103 yr, the contribution of individual disturbances may remain elevated above corresponding catchment denudation rates. I further estimate rates of sediment (re-)mobilisation by individual giant terrestrial and submarine mass movements. Less than 50 postglacial submarine mass movements have involved an equivalent of ~ 10% of the contemporary annual global flux of fluvial sediment to Earth's oceans, while mobilisation rates by individual events rival the decadal-scale sediment discharge from tectonically active orogens such as Taiwan or New Zealand. Sediment flushing associated with catastrophic natural dam breaks is non-stationary and shows a distinct kink at the last glacial-interglacial transition, owing to the drainage of very large late Pleistocene ice-marginal lakes. Besides emphasising the contribution of high-magnitude and low-frequency events to the global sediment cascade, these findings stress the importance of sediment storage for fuelling rather than buffering high sediment transport rates.

Ranking contributing areas of salt and selenium in the Lower Gunnison River Basin, Colorado, using multiple linear regression models

USGS Publications Warehouse

Linard, Joshua I.

2013-01-01

Mitigating the effects of salt and selenium on water quality in the Grand Valley and lower Gunnison River Basin in western Colorado is a major concern for land managers. Previous modeling indicated means to improve the models by including more detailed geospatial data and a more rigorous method for developing the models. After evaluating all possible combinations of geospatial variables, four multiple linear regression models resulted that could estimate irrigation-season salt yield, nonirrigation-season salt yield, irrigation-season selenium yield, and nonirrigation-season selenium yield. The adjusted r-squared and the residual standard error (in units of log-transformed yield) of the models were, respectively, 0.87 and 2.03 for the irrigation-season salt model, 0.90 and 1.25 for the nonirrigation-season salt model, 0.85 and 2.94 for the irrigation-season selenium model, and 0.93 and 1.75 for the nonirrigation-season selenium model. The four models were used to estimate yields and loads from contributing areas corresponding to 12-digit hydrologic unit codes in the lower Gunnison River Basin study area. Each of the 175 contributing areas was ranked according to its estimated mean seasonal yield of salt and selenium.

Yield gap analyses to estimate attainable bovine milk yields and evaluate options to increase production in Ethiopia and India.

PubMed

Mayberry, Dianne; Ash, Andrew; Prestwidge, Di; Godde, Cécile M; Henderson, Ben; Duncan, Alan; Blummel, Michael; Ramana Reddy, Y; Herrero, Mario

2017-07-01

Livestock provides an important source of income and nourishment for around one billion rural households worldwide. Demand for livestock food products is increasing, especially in developing countries, and there are opportunities to increase production to meet local demand and increase farm incomes. Estimating the scale of livestock yield gaps and better understanding factors limiting current production will help to define the technological and investment needs in each livestock sector. The aim of this paper is to quantify livestock yield gaps and evaluate opportunities to increase dairy production in Sub-Saharan Africa and South Asia, using case studies from Ethiopia and India. We combined three different methods in our approach. Benchmarking and a frontier analysis were used to estimate attainable milk yields based on survey data. Household modelling was then used to simulate the effects of various interventions on dairy production and income. We tested interventions based on improved livestock nutrition and genetics in the extensive lowland grazing zone and highland mixed crop-livestock zones of Ethiopia, and the intensive irrigated and rainfed zones of India. Our analyses indicate that there are considerable yield gaps for dairy production in both countries, and opportunities to increase production using the interventions tested. In some cases, combined interventions could increase production past currently attainable livestock yields.

Crop monitoring & yield forecasting system based on Synthetic Aperture Radar (SAR) and process-based crop growth model: Development and validation in South and South East Asian Countries

NASA Astrophysics Data System (ADS)

Setiyono, T. D.

2014-12-01

Accurate and timely information on rice crop growth and yield helps governments and other stakeholders adapting their economic policies and enables relief organizations to better anticipate and coordinate relief efforts in the wake of a natural catastrophe. Such delivery of rice growth and yield information is made possible by regular earth observation using space-born Synthetic Aperture Radar (SAR) technology combined with crop modeling approach to estimate yield. Radar-based remote sensing is capable of observing rice vegetation growth irrespective of cloud coverage, an important feature given that in incidences of flooding the sky is often cloud-covered. The system allows rapid damage assessment over the area of interest. Rice yield monitoring is based on a crop growth simulation and SAR-derived key information, particularly start of season and leaf growth rate. Results from pilot study sites in South and South East Asian countries suggest that incorporation of SAR data into crop model improves yield estimation for actual yields. Remote-sensing data assimilation into crop model effectively capture responses of rice crops to environmental conditions over large spatial coverage, which otherwise is practically impossible to achieve. Such improvement of actual yield estimates offers practical application such as in a crop insurance program. Process-based crop simulation model is used in the system to ensure climate information is adequately captured and to enable mid-season yield forecast.

Understanding the Changes in Global Crop Yields Through Changes in Climate and Technology

NASA Astrophysics Data System (ADS)

Najafi, Ehsan; Devineni, Naresh; Khanbilvardi, Reza M.; Kogan, Felix

2018-03-01

During the last few decades, the global agricultural production has risen and technology enhancement is still contributing to yield growth. However, population growth, water crisis, deforestation, and climate change threaten the global food security. An understanding of the variables that caused past changes in crop yields can help improve future crop prediction models. In this article, we present a comprehensive global analysis of the changes in the crop yields and how they relate to different large-scale and regional climate variables, climate change variables and technology in a unified framework. A new multilevel model for yield prediction at the country level is developed and demonstrated. The structural relationships between average yield and climate attributes as well as trends are estimated simultaneously. All countries are modeled in a single multilevel model with partial pooling to automatically group and reduce estimation uncertainties. El Niño-southern oscillation (ENSO), Palmer drought severity index (PDSI), geopotential height anomalies (GPH), historical carbon dioxide (CO2) concentration and country-based time series of GDP per capita as an approximation of technology measurement are used as predictors to estimate annual agricultural crop yields for each country from 1961 to 2013. Results indicate that these variables can explain the variability in historical crop yields for most of the countries and the model performs well under out-of-sample verifications. While some countries were not generally affected by climatic factors, PDSI and GPH acted both positively and negatively in different regions for crop yields in many countries.

Numerically accurate computational techniques for optimal estimator analyses of multi-parameter models

NASA Astrophysics Data System (ADS)

Berger, Lukas; Kleinheinz, Konstantin; Attili, Antonio; Bisetti, Fabrizio; Pitsch, Heinz; Mueller, Michael E.

2018-05-01

Modelling unclosed terms in partial differential equations typically involves two steps: First, a set of known quantities needs to be specified as input parameters for a model, and second, a specific functional form needs to be defined to model the unclosed terms by the input parameters. Both steps involve a certain modelling error, with the former known as the irreducible error and the latter referred to as the functional error. Typically, only the total modelling error, which is the sum of functional and irreducible error, is assessed, but the concept of the optimal estimator enables the separate analysis of the total and the irreducible errors, yielding a systematic modelling error decomposition. In this work, attention is paid to the techniques themselves required for the practical computation of irreducible errors. Typically, histograms are used for optimal estimator analyses, but this technique is found to add a non-negligible spurious contribution to the irreducible error if models with multiple input parameters are assessed. Thus, the error decomposition of an optimal estimator analysis becomes inaccurate, and misleading conclusions concerning modelling errors may be drawn. In this work, numerically accurate techniques for optimal estimator analyses are identified and a suitable evaluation of irreducible errors is presented. Four different computational techniques are considered: a histogram technique, artificial neural networks, multivariate adaptive regression splines, and an additive model based on a kernel method. For multiple input parameter models, only artificial neural networks and multivariate adaptive regression splines are found to yield satisfactorily accurate results. Beyond a certain number of input parameters, the assessment of models in an optimal estimator analysis even becomes practically infeasible if histograms are used. The optimal estimator analysis in this paper is applied to modelling the filtered soot intermittency in large eddy simulations using a dataset of a direct numerical simulation of a non-premixed sooting turbulent flame.

Search for supersymmetry in pp collisions at [Formula: see text] TeV in events with a single lepton, jets, and missing transverse momentum.

PubMed

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Mott, A; Newman, H B; Rogan, C; Spiropulu, M; Timciuc, V; Veverka, J; Wilkinson, R; Xie, S; Yang, Y; Zhu, R Y; Akgun, B; Azzolini, V; Calamba, A; Carroll, R; Ferguson, T; Iiyama, Y; Jang, D W; Liu, Y F; Paulini, M; Vogel, H; Vorobiev, I; Cumalat, J P; Drell, B R; Ford, W T; Gaz, A; Luiggi Lopez, E; Smith, J G; Stenson, K; Ulmer, K A; Wagner, S R; Alexander, J; Chatterjee, A; Eggert, N; Gibbons, L K; Heltsley, B; Khukhunaishvili, A; Kreis, B; Mirman, N; Nicolas Kaufman, G; Patterson, J R; Ryd, A; Salvati, E; Sun, W; Teo, W D; Thom, J; Thompson, J; Tucker, J; Vaughan, J; Weng, Y; Winstrom, L; Wittich, P; Winn, D; Abdullin, S; Albrow, M; Anderson, J; Bauerdick, L A T; Beretvas, A; Berryhill, J; Bhat, P C; Bloch, I; Burkett, K; Butler, J N; Chetluru, V; Cheung, H W K; Chlebana, F; Elvira, V D; Fisk, I; Freeman, J; Gao, Y; Green, D; Gutsche, O; Hanlon, J; Harris, R M; Hirschauer, J; Hooberman, B; Jindariani, S; Johnson, M; Joshi, U; Kilminster, B; Klima, B; Kunori, S; Kwan, S; Leonidopoulos, C; Linacre, J; Lincoln, D; Lipton, R; Lykken, J; Maeshima, K; Marraffino, J M; Maruyama, S; Mason, D; McBride, P; Mishra, K; Mrenna, S; Musienko, Y; Newman-Holmes, C; O'Dell, V; Prokofyev, O; Sexton-Kennedy, E; Sharma, S; Spalding, W J; Spiegel, L; Taylor, L; Tkaczyk, S; Tran, N V; Uplegger, L; Vaandering, E W; Vidal, R; Whitmore, J; Wu, W; Yang, F; Yumiceva, F; Yun, J C; Acosta, D; Avery, P; Bourilkov, D; Chen, M; Cheng, T; Das, S; De Gruttola, M; Di Giovanni, G P; Dobur, D; Drozdetskiy, A; Field, R D; Fisher, M; Fu, Y; Furic, I K; Gartner, J; Hugon, J; Kim, B; Konigsberg, J; Korytov, A; Kropivnitskaya, A; Kypreos, T; Low, J F; Matchev, K; Milenovic, P; Mitselmakher, G; Muniz, L; Park, M; Remington, R; Rinkevicius, A; Sellers, P; Skhirtladze, N; Snowball, M; Yelton, J; Zakaria, M; Gaultney, V; Hewamanage, S; Lebolo, L M; Linn, S; Markowitz, P; Martinez, G; Rodriguez, J L; Adams, T; Askew, A; Bochenek, J; Chen, J; Diamond, B; Gleyzer, S V; Haas, J; Hagopian, S; Hagopian, V; Jenkins, M; Johnson, K F; 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Pierro, G A; Ross, I; Savin, A; Smith, W H; Swanson, J

Results are reported from a search for new physics processes in events containing a single isolated high-transverse-momentum lepton (electron or muon), energetic jets, and large missing transverse momentum. The analysis is based on a 4.98 fb -1 sample of proton-proton collisions at a center-of-mass energy of 7 TeV, obtained with the CMS detector at the LHC. Three separate background estimation methods, each relying primarily on control samples in the data, are applied to a range of signal regions, providing complementary approaches for estimating the background yields. The observed yields are consistent with the predicted standard model backgrounds. The results are interpreted in terms of limits on the parameter space for the constrained minimal supersymmetric extension of the standard model, as well as on cross sections for simplified models, which provide a generic description of the production and decay of new particles in specific, topology based final states. The online version of this article (doi:10.1140/epjc/s10052-013-2404-z) contains supplementary material, which is available to authorized users.

Using the SPEI to Estimate Food Production in East Africa

NASA Astrophysics Data System (ADS)

Husak, G. J.; Hobbins, M.; Verdin, J. P.; Peterson, P.; Funk, C. C.

2015-12-01

The Famine Early Warning Systems Network (FEWS NET) monitors critical environmental variables that impact food production in developing countries. Due to a sparse network of observations in the developing world, many of these variables are estimated using remotely sensed data. As scientists develop new techniques to leverage available observations and remotely sensed information there are opportunities to create products that identify the environmental conditions that stress agriculture and reduce food production. FEWS NET pioneered the development of the Climate Hazards Group InfraRed Precipitation with stations (CHIRPS) dataset, to estimate precipitation and monitor growing conditions throughout the world. These data are used to drive land surface models, hydrologic models and basic crop models among others. A new dataset estimating the reference evapotranspiration (ET0) has been developed using inputs from the ERA-Interim GCM. This ET0 dataset stretches back to 1981, allowing for a long-term record, stretching many seasons and drought events. Combining the CHIRPS data to estimate water availability and the ET0 data to estimate evaporative demand, one can estimate the approximate water gap (surplus or deficit) over a specific time period. Normalizing this difference creates the Standardized Precipitation Evapotranspiration Index (SPEI), which presents these gaps in comparison to the historical record for a specific location and accumulation period. In this study we evaluate the SPEI as a tool to estimate crop yields for different regions of Kenya. Identifying the critical time of analysis for the SPEI is the first step in building a relationship between the water gap and food production. Once this critical period is identified, we look at the predictability of food production using the SPEI, and assess the utility of it for monitoring food security, with the goal of incorporating the SPEI in the standard monitoring suite of FEWS NET tools.

Evaluating accuracy of DSSAT model for soybean yield estimation using satellite weather data

NASA Astrophysics Data System (ADS)

Ovando, Gustavo; Sayago, Silvina; Bocco, Mónica

2018-04-01

Crop models allow simulating the development and yield of the crops, to represent and to evaluate the influence of multiple factors. The DSSAT cropping system model is one of the most widely used and contains CROPGRO module for soybean. This crop has a great importance for many southern countries of Latin America and for Argentina. Solar radiation and rainfall are necessary variables as inputs for crop models; however these data are not as readily available. The satellital products from Clouds and Earth's Radiant Energy System (CERES) and Tropic Rainfall Measurement Mission (TRMM) provide continuous spatial and temporal information of solar radiation and precipitation, respectively. This study evaluates and quantifies the uncertainty in estimating soybean yield using a DSSAT model, when recorded weather data are replaced with CERES and TRMM ones. Different percentages of data replacements, soybean maturity groups and planting dates are considered, for 2006-2016 period in Oliveros (Argentina). Results show that CERES and TRMM products can be used for soybean yield estimation with DSSAT considering that: percentage of data replacement, campaign, planting date and maturity group, determine the amounts and trends of yield errors. Replacements with CERES data up to 30% result in %RMSE lower than 10% in 87% of the cases; while the replacement with TRMM data presents the best statisticals in campaigns with high yields. Simulations based entirely on CERES solar radiation give better results than those with TRMM. In general, similar percentages of replacement show better performance in the estimation of soybean yield for solar radiation than the replacement of precipitation values.

Superheavy elements and r-process

NASA Astrophysics Data System (ADS)

Panov, I. V.; Korneev, I. Yu.; Thielemann, F.-K.

2009-06-01

The probability for the production of superheavy elements in the astrophysical r-process is discussed. The dependence of the estimated superheavy-element yields on input data is estimated. Preliminary calculations revealed that the superheavy-element yields at the instant of completion of the r-process may be commensurate with the uranium yield, but the former depend strongly on the models used to forecast the properties of beta-delayed, neutron-induced, and spontaneous fission. This study is dedicated to the 80th anniversary of V.S. Imshennik’s birth.

Suspended-Sediment Loads and Yields in the North Santiam River Basin, Oregon, Water Years 1999-2004

USGS Publications Warehouse

Bragg, Heather M.; Sobieszczyk, Steven; Uhrich, Mark A.; Piatt, David R.

2007-01-01

The North Santiam River provides drinking water to the residents and businesses of the city of Salem, Oregon, and many surrounding communities. Since 1998, water-quality data, including turbidity, were collected continuously at monitoring stations throughout the basin as part of the North Santiam River Basin Turbidity and Suspended Sediment Study. In addition, sediment samples have been collected over a range of turbidity and streamflow values. Regression models were developed between the instream turbidity and suspended-sediment concentration from the samples collected from each monitoring station. The models were then used to estimate the daily and annual suspended-sediment loads and yields. For water years 1999-2004, suspended-sediment loads and yields were estimated for each station. Annual suspended-sediment loads and yields were highest during water years 1999 and 2000. A drought during water year 2001 resulted in the lowest suspended-sediment loads and yields for all monitoring stations. High-turbidity events that were unrelated or disproportional to increased streamflow occurred at several of the monitoring stations during the period of study. These events highlight the advantage of estimating suspended-sediment loads and yields from instream turbidity rather than from streamflow alone.

Yield variability prediction by remote sensing sensors with different spatial resolution

NASA Astrophysics Data System (ADS)

Kumhálová, Jitka; Matějková, Štěpánka

2017-04-01

Currently, remote sensing sensors are very popular for crop monitoring and yield prediction. This paper describes how satellite images with moderate (Landsat satellite data) and very high (QuickBird and WorldView-2 satellite data) spatial resolution, together with GreenSeeker hand held crop sensor, can be used to estimate yield and crop growth variability. Winter barley (2007 and 2015) and winter wheat (2009 and 2011) were chosen because of cloud-free data availability in the same time period for experimental field from Landsat satellite images and QuickBird or WorldView-2 images. Very high spatial resolution images were resampled to worse spatial resolution. Normalised difference vegetation index was derived from each satellite image data sets and it was also measured with GreenSeeker handheld crop sensor for the year 2015 only. Results showed that each satellite image data set can be used for yield and plant variability estimation. Nevertheless, better results, in comparison with crop yield, were obtained for images acquired in later phenological phases, e.g. in 2007 - BBCH 59 - average correlation coefficient 0.856, and in 2011 - BBCH 59-0.784. GreenSeeker handheld crop sensor was not suitable for yield estimation due to different measuring method.

Global Crop Yields, Climatic Trends and Technology Enhancement

NASA Astrophysics Data System (ADS)

Najafi, E.; Devineni, N.; Khanbilvardi, R.; Kogan, F.

2016-12-01

During the last decades the global agricultural production has soared up and technology enhancement is still making positive contribution to yield growth. However, continuing population, water crisis, deforestation and climate change threaten the global food security. Attempts to predict food availability in the future around the world can be partly understood from the impact of changes to date. A new multilevel model for yield prediction at the country scale using climate covariates and technology trend is presented in this paper. The structural relationships between average yield and climate attributes as well as trends are estimated simultaneously. All countries are modeled in a single multilevel model with partial pooling and/or clustering to automatically group and reduce estimation uncertainties. El Niño Southern Oscillation (ENSO), Palmer Drought Severity Index (PDSI), Geopotential height (GPH), historical CO2 level and time-trend as a relatively reliable approximation of technology measurement are used as predictors to estimate annual agricultural crop yields for each country from 1961 to 2007. Results show that these indicators can explain the variability in historical crop yields for most of the countries and the model performs well under out-of-sample verifications.

Real-time yield estimation based on deep learning

NASA Astrophysics Data System (ADS)

Rahnemoonfar, Maryam; Sheppard, Clay

2017-05-01

Crop yield estimation is an important task in product management and marketing. Accurate yield prediction helps farmers to make better decision on cultivation practices, plant disease prevention, and the size of harvest labor force. The current practice of yield estimation based on the manual counting of fruits is very time consuming and expensive process and it is not practical for big fields. Robotic systems including Unmanned Aerial Vehicles (UAV) and Unmanned Ground Vehicles (UGV), provide an efficient, cost-effective, flexible, and scalable solution for product management and yield prediction. Recently huge data has been gathered from agricultural field, however efficient analysis of those data is still a challenging task. Computer vision approaches currently face diffident challenges in automatic counting of fruits or flowers including occlusion caused by leaves, branches or other fruits, variance in natural illumination, and scale. In this paper a novel deep convolutional network algorithm was developed to facilitate the accurate yield prediction and automatic counting of fruits and vegetables on the images. Our method is robust to occlusion, shadow, uneven illumination and scale. Experimental results in comparison to the state-of-the art show the effectiveness of our algorithm.

Early Yields of Biomass Plantations in the North-Central U.S.

Treesearch

Edward Hansen

1990-01-01

A network of hybrid poplar short-rotation plantations was established across the north-central region of the U.S. during 1986-1988. This paper documents the greater than expected early yields from these plantations and dicusses potential yields and uncertainties surrounding potential yield estimates.

Effects of sex change on the implications of marine reserves for fisheries.

PubMed

Chan, Neil C S; Connolly, Sean R; Mapstone, Bruce D

2012-04-01

Marine reserves have become widely used in biodiversity conservation and are increasingly proposed as fisheries management tools. Previous modeling studies have found that reserves may increase or decrease yields, depending on local environmental conditions and on the specific life-history traits of the fishery species. Sex-changing (female-to-male) fish are targets of some of the most important commercial and recreational fisheries in the world. The potential for disproportionate removal of the larger, older sex of such species requires new theory to facilitate our understanding of how reserves will affect the yields of surrounding fisheries, relative to fishes with separate sexes. We investigated this question by modeling the effects of marine reserves on a non-sex-changing and a sex-changing population. We used demographic parameter estimates for the common coral trout as a baseline, and we conducted extensive sensitivity analyses to determine how sustainable yields of sex-changing species are likely to be affected by reserves across a broad range of life-history parameters. Our findings indicate that fisheries for sex-changing species are unlikely to receive the same yield-enhancing benefit that non-sex-changing fisheries enjoy from marine reserves, and that often reserves tend to reduce sustainable yields for a given overall population size. Specifically, the increased egg production and high fertilization success within reserves is more than offset by the reduced egg production and fertilization success in the fished areas, relative to a system in which fishing mortality is distributed more evenly over the entire system. A key reason for this appears to be that fertilization success is reduced, on average, when males are unevenly distributed among subpopulations, as is the case when reserves are present. These findings suggests that, for sex-changing populations, reserves are more suited to rebuilding overfished populations and sustaining fishery viability, rather than enhancing fishery yields. These results are robust over a range of sex-change regimes, stock-recruitment relationships, adult mortality rates, individual growth strategies, and fertilization-success functions. Our findings highlight the importance of considering the different contributions of males and females to population growth and fishery yields when evaluating the efficacy of marine reserves for enhancement of fished species.

Using multivariate generalizability theory to assess the effect of content stratification on the reliability of a performance assessment.

PubMed

Keller, Lisa A; Clauser, Brian E; Swanson, David B

2010-12-01

In recent years, demand for performance assessments has continued to grow. However, performance assessments are notorious for lower reliability, and in particular, low reliability resulting from task specificity. Since reliability analyses typically treat the performance tasks as randomly sampled from an infinite universe of tasks, these estimates of reliability may not be accurate. For tests built according to a table of specifications, tasks are randomly sampled from different strata (content domains, skill areas, etc.). If these strata remain fixed in the test construction process, ignoring this stratification in the reliability analysis results in an underestimate of "parallel forms" reliability, and an overestimate of the person-by-task component. This research explores the effect of representing and misrepresenting the stratification appropriately in estimation of reliability and the standard error of measurement. Both multivariate and univariate generalizability studies are reported. Results indicate that the proper specification of the analytic design is essential in yielding the proper information both about the generalizability of the assessment and the standard error of measurement. Further, illustrative D studies present the effect under a variety of situations and test designs. Additional benefits of multivariate generalizability theory in test design and evaluation are also discussed.

Effects of stage of pregnancy on variance components, daily milk yields and 305-day milk yield in Holstein cows, as estimated by using a test-day model.

PubMed

Yamazaki, T; Hagiya, K; Takeda, H; Osawa, T; Yamaguchi, S; Nagamine, Y

2016-08-01

Pregnancy and calving are elements indispensable for dairy production, but the daily milk yield of cows decline as pregnancy progresses, especially during the late stages. Therefore, the effect of stage of pregnancy on daily milk yield must be clarified to accurately estimate the breeding values and lifetime productivity of cows. To improve the genetic evaluation model for daily milk yield and determine the effect of the timing of pregnancy on productivity, we used a test-day model to assess the effects of stage of pregnancy on variance component estimates, daily milk yields and 305-day milk yield during the first three lactations of Holstein cows. Data were 10 646 333 test-day records for the first lactation; 8 222 661 records for the second; and 5 513 039 records for the third. The data were analyzed within each lactation by using three single-trait random regression animal models: one model that did not account for the stage of pregnancy effect and two models that did. The effect of stage of pregnancy on test-day milk yield was included in the model by applying a regression on days pregnant or fitting a separate lactation curve for each days open (days from calving to pregnancy) class (eight levels). Stage of pregnancy did not affect the heritability estimates of daily milk yield, although the additive genetic and permanent environmental variances in late lactation were decreased by accounting for the stage of pregnancy effect. The effects of days pregnant on daily milk yield during late lactation were larger in the second and third lactations than in the first lactation. The rates of reduction of the 305-day milk yield of cows that conceived fewer than 90 days after the second or third calving were significantly (P<0.05) greater than that after the first calving. Therefore, we conclude that differences between the negative effects of early pregnancy in the first, compared with later, lactations should be included when determining the optimal number of days open to maximize lifetime productivity in dairy cows.

Subglottal Impedance-Based Inverse Filtering of Voiced Sounds Using Neck Surface Acceleration

PubMed Central

Zañartu, Matías; Ho, Julio C.; Mehta, Daryush D.; Hillman, Robert E.; Wodicka, George R.

2014-01-01

A model-based inverse filtering scheme is proposed for an accurate, non-invasive estimation of the aerodynamic source of voiced sounds at the glottis. The approach, referred to as subglottal impedance-based inverse filtering (IBIF), takes as input the signal from a lightweight accelerometer placed on the skin over the extrathoracic trachea and yields estimates of glottal airflow and its time derivative, offering important advantages over traditional methods that deal with the supraglottal vocal tract. The proposed scheme is based on mechano-acoustic impedance representations from a physiologically-based transmission line model and a lumped skin surface representation. A subject-specific calibration protocol is used to account for individual adjustments of subglottal impedance parameters and mechanical properties of the skin. Preliminary results for sustained vowels with various voice qualities show that the subglottal IBIF scheme yields comparable estimates with respect to current aerodynamics-based methods of clinical vocal assessment. A mean absolute error of less than 10% was observed for two glottal airflow measures –maximum flow declination rate and amplitude of the modulation component– that have been associated with the pathophysiology of some common voice disorders caused by faulty and/or abusive patterns of vocal behavior (i.e., vocal hyperfunction). The proposed method further advances the ambulatory assessment of vocal function based on the neck acceleration signal, that previously have been limited to the estimation of phonation duration, loudness, and pitch. Subglottal IBIF is also suitable for other ambulatory applications in speech communication, in which further evaluation is underway. PMID:25400531

Estimating oak growth and yield

Treesearch

Martin E. Dale; Donald E. Hilt

1989-01-01

Yields from upland oak stands vary widely from stand to stand due to differences in age, site quality, species composition, and stand structure. Cutting history and other past disturbances such as grazing or fire also affect yields.

Minimum number of measurements for evaluating soursop (Annona muricata L.) yield.

PubMed

Sánchez, C F B; Teodoro, P E; Londoño, S; Silva, L A; Peixoto, L A; Bhering, L L

2017-05-31

Repeatability studies on fruit species are of great importance to identify the minimum number of measurements necessary to accurately select superior genotypes. This study aimed to identify the most efficient method to estimate the repeatability coefficient (r) and predict the minimum number of measurements needed for a more accurate evaluation of soursop (Annona muricata L.) genotypes based on fruit yield. Sixteen measurements of fruit yield from 71 soursop genotypes were carried out between 2000 and 2016. In order to estimate r with the best accuracy, four procedures were used: analysis of variance, principal component analysis based on the correlation matrix, principal component analysis based on the phenotypic variance and covariance matrix, and structural analysis based on the correlation matrix. The minimum number of measurements needed to predict the actual value of individuals was estimated. Principal component analysis using the phenotypic variance and covariance matrix provided the most accurate estimates of both r and the number of measurements required for accurate evaluation of fruit yield in soursop. Our results indicate that selection of soursop genotypes with high fruit yield can be performed based on the third and fourth measurements in the early years and/or based on the eighth and ninth measurements at more advanced stages.

Using NOAA/AVHRR based remote sensing data and PCR method for estimation of Aus rice yield in Bangladesh

NASA Astrophysics Data System (ADS)

Nizamuddin, Mohammad; Akhand, Kawsar; Roytman, Leonid; Kogan, Felix; Goldberg, Mitch

2015-06-01

Rice is a dominant food crop of Bangladesh accounting about 75 percent of agricultural land use for rice cultivation and currently Bangladesh is the world's fourth largest rice producing country. Rice provides about two-third of total calorie supply and about one-half of the agricultural GDP and one-sixth of the national income in Bangladesh. Aus is one of the main rice varieties in Bangladesh. Crop production, especially rice, the main food staple, is the most susceptible to climate change and variability. Any change in climate will, thus, increase uncertainty regarding rice production as climate is major cause year-to-year variability in rice productivity. This paper shows the application of remote sensing data for estimating Aus rice yield in Bangladesh using official statistics of rice yield with real time acquired satellite data from Advanced Very High Resolution Radiometer (AVHRR) sensor and Principal Component Regression (PCR) method was used to construct a model. The simulated result was compared with official agricultural statistics showing that the error of estimation of Aus rice yield was less than 10%. Remote sensing, therefore, is a valuable tool for estimating crop yields well in advance of harvest, and at a low cost.

Effect of pregnancy on the genetic evaluation of dairy cattle.

PubMed

Pereira, R J; Santana, M L; Bignardi, A B; Verneque, R S; El Faro, L; Albuquerque, L G

2011-09-26

We investigated the effect of stage of pregnancy on estimates of breeding values for milk yield and milk persistency in Gyr and Holstein dairy cattle in Brazil. Test-day milk yield records were analyzed using random regression models with or without the effect of pregnancy. Models were compared using residual variances, heritabilities, rank correlations of estimated breeding values of bulls and cows, and number of nonpregnant cows in the top 200 for milk yield and milk persistency. The estimates of residual variance and heritabilities obtained with the models with or without the effect of pregnancy were similar for the two breeds. Inclusion of the effect of pregnancy in genetic evaluation models for these populations did not affect the ranking of cows and sires based on their predicted breeding values for 305-day cumulative milk yield. In contrast, when we examined persistency of milk yield, lack of adjustment for the effect of pregnancy overestimated breeding values of nonpregnant cows and cows with a long days open period and underestimated breeding values of cows with a short days open period. We recommend that models include the effect of days of pregnancy for estimation of adjustment factors for the effect of pregnancy in genetic evaluations of Dairy Gyr and Holstein cattle.

Estimation methods and parameter assessment for ethanol yields from total soluble solids of sweet sorghum

USDA-ARS?s Scientific Manuscript database

Estimation methods and evaluation of ethanol yield from sweet sorghum (Sorghum bicolor (L.) Moench.) based on agronomic production traits and juice characteristics is important for developing parents and inbred lines of sweet sorghum that can be used by the bio-ethanol industry. The objectives of th...

Repeatability estimates for oleoresin yield measurements in three species of the southern pines

Treesearch

James H. Roberds; Brain L. Strom

2006-01-01

Repeatability was estimated for constitutive oleoresin yield measurements in 10 stands of three species of pines native to southeastern United States. Trees of these species that discharge large quantities of oleoresin upon wounding are considered to be most resistant to attack by southern pine beetle (Dendroctonus frontalis Zimmermann). Oleoresin...

A tree biomass and carbon estimation system

Treesearch

Emily B. Schultz; Thomas G. Matney; Donald L. Grebner

2013-01-01

Appropriate forest management decisions for the developing woody biofuel and carbon credit markets require inventory and growth-and-yield systems reporting component tree dry weight biomass estimates. We have developed an integrated growth-and-yield and biomass/carbon calculator. The objective was to provide Mississippi’s State inventory system with bioenergy economic...

The shared and unique values of optical, fluorescence, thermal and microwave satellite data for estimating large-scale crop yields

USDA-ARS?s Scientific Manuscript database

Large-scale crop monitoring and yield estimation are important for both scientific research and practical applications. Satellite remote sensing provides an effective means for regional and global cropland monitoring, particularly in data-sparse regions that lack reliable ground observations and rep...

Assimilating Remote Sensing Observations of Leaf Area Index and Soil Moisture for Wheat Yield Estimates: An Observing System Simulation Experiment

NASA Technical Reports Server (NTRS)

Nearing, Grey S.; Crow, Wade T.; Thorp, Kelly R.; Moran, Mary S.; Reichle, Rolf H.; Gupta, Hoshin V.

2012-01-01

Observing system simulation experiments were used to investigate ensemble Bayesian state updating data assimilation of observations of leaf area index (LAI) and soil moisture (theta) for the purpose of improving single-season wheat yield estimates with the Decision Support System for Agrotechnology Transfer (DSSAT) CropSim-Ceres model. Assimilation was conducted in an energy-limited environment and a water-limited environment. Modeling uncertainty was prescribed to weather inputs, soil parameters and initial conditions, and cultivar parameters and through perturbations to model state transition equations. The ensemble Kalman filter and the sequential importance resampling filter were tested for the ability to attenuate effects of these types of uncertainty on yield estimates. LAI and theta observations were synthesized according to characteristics of existing remote sensing data, and effects of observation error were tested. Results indicate that the potential for assimilation to improve end-of-season yield estimates is low. Limitations are due to a lack of root zone soil moisture information, error in LAI observations, and a lack of correlation between leaf and grain growth.

Efficient statistical tests to compare Youden index: accounting for contingency correlation.

PubMed

Chen, Fangyao; Xue, Yuqiang; Tan, Ming T; Chen, Pingyan

2015-04-30

Youden index is widely utilized in studies evaluating accuracy of diagnostic tests and performance of predictive, prognostic, or risk models. However, both one and two independent sample tests on Youden index have been derived ignoring the dependence (association) between sensitivity and specificity, resulting in potentially misleading findings. Besides, paired sample test on Youden index is currently unavailable. This article develops efficient statistical inference procedures for one sample, independent, and paired sample tests on Youden index by accounting for contingency correlation, namely associations between sensitivity and specificity and paired samples typically represented in contingency tables. For one and two independent sample tests, the variances are estimated by Delta method, and the statistical inference is based on the central limit theory, which are then verified by bootstrap estimates. For paired samples test, we show that the estimated covariance of the two sensitivities and specificities can be represented as a function of kappa statistic so the test can be readily carried out. We then show the remarkable accuracy of the estimated variance using a constrained optimization approach. Simulation is performed to evaluate the statistical properties of the derived tests. The proposed approaches yield more stable type I errors at the nominal level and substantially higher power (efficiency) than does the original Youden's approach. Therefore, the simple explicit large sample solution performs very well. Because we can readily implement the asymptotic and exact bootstrap computation with common software like R, the method is broadly applicable to the evaluation of diagnostic tests and model performance. Copyright © 2015 John Wiley & Sons, Ltd.

Application of remote sensing in crop growth simulation and an ensembles approach to reduce model uncertainties

NASA Astrophysics Data System (ADS)

Setiyono, T. D.; Nelson, A.; Ravis, J.; Maunahan, A.; Villano, L.; Li, T.; Bouman, B.

2012-12-01

A semi-empirical model derived from the water-cloud model was used to convert synthetic- aperture radar (SAR) backscattering data into LAI. The SAR-based LAI at early rice growth stages were in a close agreement (90%) with LAI derived from MODIS data for the same study location in Nueva Ecija, Philippines. ORYZA2000 simulated rice yield of 4.5 Mg ha-1 for the 2008 wet season in Nueva Ejica, Philippines when using LAI inputs derived from SAR data, which is closer to the observed yield of 3.9 Mg ha-1, whereas simulated yield without SAR-derived LAI inputs was 5.4 Mg ha-1. The dynamic water and nitrogen balances were accounted in these simulations based on site-specific soil properties and actual fertilizer N and water management. The use of remote sensing data was promising for model application to approximate actual growth conditions and to compensate for limitations in the model due to relevant underlining processes absent in model formulations such as detailed tillering, leaf shading effect, etc., and also limiting factors not accounted in the model such as biotic factors and abiotic factors other than water and N shortages. This study also demonstrated the use an ensembles approach for provincial level rice yield estimation in the Philippines. Such ensembles approach involved statistical classifications of agronomic management settings into 25% percentile, median, and 75% levels followed by generation of factorial combinations. For irrigated lowland system, 4 factors were considered that include transplanting date, plant density, fertilizer N rate, and amount of irrigation water. For rainfed lowland system, there were 3 agronomic management factors (transplanting date, plant density, fertilizer N) and 1 soil parameter (depth of ground water table). These 4 management/soil factors and 3 statistical levels resulted in 81 total factorial combinations representing simulation scenarios for each area of interest (province in the Philippines) and water environments (irrigated vs. rainfed). Finally a normal distribution was assumed and applied to the simulations outputs. This ensembles approach provided an efficient and yet effective method of aggregating point-based crop model results into a larger spatial level of interest. Lack of access to accurate model parameters (e.g. depth of ground water table) could be solved with this approach. The use of process-based crop growth model was critical because the ultimate aim of this study was not just to establish a reliable rice yield estimation system but also to allow yield estimation outputs explainable by the underlining agronomic practices such as transplanting date, fertilizer N application, and water management.

A meta-analysis of the effects of feeding yeast culture produced by anaerobic fermentation of Saccharomyces cerevisiae on milk production of lactating dairy cows.

PubMed

Poppy, G D; Rabiee, A R; Lean, I J; Sanchez, W K; Dorton, K L; Morley, P S

2012-10-01

The purpose of this study was to use meta-analytic methods to estimate the effect of a commercially available yeast culture product on milk production and other production measures in lactating dairy cows using a meta-analysis of randomized controlled trials. Sixty-one research publications (published journal articles, published abstracts, and technical reports) were identified through a review of literature provided by the manufacturer and a search of published literature using 6 search engines. Thirty-six separate studies with 69 comparisons met the criteria for inclusion in the meta-analysis. The fixed-effect meta-analysis showed substantial heterogeneity for milk yield, energy-corrected milk, 3.5% fat-corrected milk, milk fat yield, and milk protein yield. Sub-group analysis of the data showed much less heterogeneity in peer-reviewed studies versus non-peer-reviewed abstracts and technical reports, and tended to show higher, but not significantly different, treatment effects. A random-effects meta-analysis showed estimated raw mean differences between treated and untreated cattle reported in peer-reviewed publications of 1.18 kg/d [95% confidence interval (CI): 0.55 to 1.81], 1.61 kg/d (95% CI: 0.92 to 2.29), and 1.65 kg/d (95% CI: 0.97 to 2.34) for milk yield, 3.5% fat-corrected milk, and energy-corrected milk, respectively. Milk fat yield and milk protein yield for peer-reviewed studies showed an increase in the raw mean difference of 0.06 kg/d (95% CI: 0.01 to 0.10) and 0.03 kg/d (95% CI: 0.00 to 0.05), respectively. Estimated raw mean dry matter intake of the peer-reviewed studies during early lactation (<70 d in milk) and not-early lactation were 0.62 kg/d (95% CI: 0.21 to 1.02) and a decrease of 0.78 kg/d (95% CI: -1.36 to -0.21), respectively. These findings provide strong evidence that this commercially available yeast culture product provides significant improvement in several important milk production outcomes as evaluated in production settings typical for commercial dairies in North America. Utilizing meta-analytic methods to study the complete breadth of information relating to a specific treatment by studying multiple overcomes of all eligible studies can reduce the uncertainty often seen in small individual studies designed without sufficient power to detect differences in treatments. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

The estimation of rice paddy yield with GRAMI crop model and Geostationary Ocean Color Imager (GOCI) image over South Korea

NASA Astrophysics Data System (ADS)

Yeom, J. M.; Kim, H. O.

2014-12-01

In this study, we estimated the rice paddy yield with moderate geostationary satellite based vegetation products and GRAMI model over South Korea. Rice is the most popular staple food for Asian people. In addition, the effects of climate change are getting stronger especially in Asian region, where the most of rice are cultivated. Therefore, accurate and timely prediction of rice yield is one of the most important to accomplish food security and to prepare natural disasters such as crop defoliation, drought, and pest infestation. In the present study, GOCI, which is world first Geostationary Ocean Color Image, was used for estimating temporal vegetation indices of the rice paddy by adopting atmospheric correction BRDF modeling. For the atmospheric correction with LUT method based on Second Simulation of the Satellite Signal in the Solar Spectrum (6S), MODIS atmospheric products such as MOD04, MOD05, MOD07 from NASA's Earth Observing System Data and Information System (EOSDIS) were used. In order to correct the surface anisotropy effect, Ross-Thick Li-Sparse Reciprocal (RTLSR) BRDF model was performed at daily basis with 16day composite period. The estimated multi-temporal vegetation images was used for crop classification by using high resolution satellite images such as Rapideye, KOMPSAT-2 and KOMPSAT-3 to extract the proportional rice paddy area in corresponding a pixel of GOCI. In the case of GRAMI crop model, initial conditions are determined by performing every 2 weeks field works at Chonnam National University, Gwangju, Korea. The corrected GOCI vegetation products were incorporated with GRAMI model to predict rice yield estimation. The predicted rice yield was compared with field measurement of rice yield.

Winter bird population studies and project prairie birds for surveying grassland birds

USGS Publications Warehouse

Twedt, D.J.; Hamel, P.B.; Woodrey, M.S.

2008-01-01

We compared 2 survey methods for assessing winter bird communities in temperate grasslands: Winter Bird Population Study surveys are area-searches that have long been used in a variety of habitats whereas Project Prairie Bird surveys employ active-flushing techniques on strip-transects and are intended for use in grasslands. We used both methods to survey birds on 14 herbaceous reforested sites and 9 coastal pine savannas during winter and compared resultant estimates of species richness and relative abundance. These techniques did not yield similar estimates of avian populations. We found Winter Bird Population Studies consistently produced higher estimates of species richness, whereas Project Prairie Birds produced higher estimates of avian abundance for some species. When it is important to identify all species within the winter bird community, Winter Bird Population Studies should be the survey method of choice. If estimates of the abundance of relatively secretive grassland bird species are desired, the use of Project Prairie Birds protocols is warranted. However, we suggest that both survey techniques, as currently employed, are deficient and recommend distance- based survey methods that provide species-specific estimates of detection probabilities be incorporated into these survey methods.

Extended Hall-Petch Relationships for Yield, Cleavage and Intergranular Fracture Strengths of bcc Steel and Its Deformation and Fracture Behaviors

NASA Astrophysics Data System (ADS)

Heo, N. H.; Heo, Y.-U.; Kwon, S. K.; Kim, N. J.; Kim, S.-J.; Lee, H.-C.

2018-03-01

Extended Hall-Petch relationships for yield ( σy ), cleavage ( σ_{cl} ) and intergranular fracture ( σ_{ig} ) strengths of pure iron have been established through the direct calculation of the proportional constant (k) and the estimation of the friction stress (σ0 ) . The magnitude orders of k and σ0 are generally ky < k_{cl} < k_{ig} and σ_{y0} < σ_{cl0} < σ_{ig0} , respectively. Based on the Hall-Petch relationships, micro-yielding in a bcc steel occurs at the instance that the pile-up dislocations within a specific grain showing the Schmid factor of 0.5 propagate into the neighboring grain. The initial brittle crack is formed at the instance that the flow strength exceeds the brittle fracture strength. Once the brittle crack is formed, it grows catastrophically. Due to the smallest and ky and σ_{y0} , the cleavage and the intergranular fracture occur always after micro-yielding. The {100} cleavage fracture of the steel is due to the lowest theoretical {100} cleavage strength. Due to the thermal components included in cleavage and intergranular fracture strengths, they show also the temperature and strain rate dependence observed in yield strength. The increase in susceptibility to brittle fracture with decreasing temperature and increasing strain rate is due to the increase in dislocation density which causes the high work hardening rate.

Can sub-Saharan Africa feed itself?

PubMed Central

van Ittersum, Martin K.; van Bussel, Lenny G. J.; Wolf, Joost; Grassini, Patricio; van Wart, Justin; Guilpart, Nicolas; Claessens, Lieven; de Groot, Hugo; Wiebe, Keith; Yang, Haishun; Boogaard, Hendrik; van Oort, Pepijn A. J.; van Loon, Marloes P.; Saito, Kazuki; Adimo, Ochieng; Adjei-Nsiah, Samuel; Agali, Alhassane; Bala, Abdullahi; Chikowo, Regis; Kaizzi, Kayuki; Kouressy, Mamoutou; Makoi, Joachim H. J. R.; Ouattara, Korodjouma; Tesfaye, Kindie; Cassman, Kenneth G.

2016-01-01

Although global food demand is expected to increase 60% by 2050 compared with 2005/2007, the rise will be much greater in sub-Saharan Africa (SSA). Indeed, SSA is the region at greatest food security risk because by 2050 its population will increase 2.5-fold and demand for cereals approximately triple, whereas current levels of cereal consumption already depend on substantial imports. At issue is whether SSA can meet this vast increase in cereal demand without greater reliance on cereal imports or major expansion of agricultural area and associated biodiversity loss and greenhouse gas emissions. Recent studies indicate that the global increase in food demand by 2050 can be met through closing the gap between current farm yield and yield potential on existing cropland. Here, however, we estimate it will not be feasible to meet future SSA cereal demand on existing production area by yield gap closure alone. Our agronomically robust yield gap analysis for 10 countries in SSA using location-specific data and a spatial upscaling approach reveals that, in addition to yield gap closure, other more complex and uncertain components of intensification are also needed, i.e., increasing cropping intensity (the number of crops grown per 12 mo on the same field) and sustainable expansion of irrigated production area. If intensification is not successful and massive cropland land expansion is to be avoided, SSA will depend much more on imports of cereals than it does today. PMID:27956604

Can sub-Saharan Africa feed itself?

PubMed

van Ittersum, Martin K; van Bussel, Lenny G J; Wolf, Joost; Grassini, Patricio; van Wart, Justin; Guilpart, Nicolas; Claessens, Lieven; de Groot, Hugo; Wiebe, Keith; Mason-D'Croz, Daniel; Yang, Haishun; Boogaard, Hendrik; van Oort, Pepijn A J; van Loon, Marloes P; Saito, Kazuki; Adimo, Ochieng; Adjei-Nsiah, Samuel; Agali, Alhassane; Bala, Abdullahi; Chikowo, Regis; Kaizzi, Kayuki; Kouressy, Mamoutou; Makoi, Joachim H J R; Ouattara, Korodjouma; Tesfaye, Kindie; Cassman, Kenneth G

2016-12-27

Although global food demand is expected to increase 60% by 2050 compared with 2005/2007, the rise will be much greater in sub-Saharan Africa (SSA). Indeed, SSA is the region at greatest food security risk because by 2050 its population will increase 2.5-fold and demand for cereals approximately triple, whereas current levels of cereal consumption already depend on substantial imports. At issue is whether SSA can meet this vast increase in cereal demand without greater reliance on cereal imports or major expansion of agricultural area and associated biodiversity loss and greenhouse gas emissions. Recent studies indicate that the global increase in food demand by 2050 can be met through closing the gap between current farm yield and yield potential on existing cropland. Here, however, we estimate it will not be feasible to meet future SSA cereal demand on existing production area by yield gap closure alone. Our agronomically robust yield gap analysis for 10 countries in SSA using location-specific data and a spatial upscaling approach reveals that, in addition to yield gap closure, other more complex and uncertain components of intensification are also needed, i.e., increasing cropping intensity (the number of crops grown per 12 mo on the same field) and sustainable expansion of irrigated production area. If intensification is not successful and massive cropland land expansion is to be avoided, SSA will depend much more on imports of cereals than it does today.

Risk of water scarcity and water policy implications for crop production in the Ebro Basin in Spain

NASA Astrophysics Data System (ADS)

Quiroga, S.; Fernández-Haddad, Z.; Iglesias, A.

2010-08-01

The increasing pressure on water systems in the Mediterranean enhances existing water conflicts and threatens water supply for agriculture. In this context, one of the main priorities for agricultural research and public policy is the adaptation of crop yields to water pressures. This paper focuses on the evaluation of hydrological risk and water policy implications for food production. Our methodological approach includes four steps. For the first step, we estimate the impacts of rainfall and irrigation water on crop yields. However, this study is not limited to general crop production functions since it also considers the linkages between those economic and biophysical aspects which may have an important effect on crop productivity. We use statistical models of yield response to address how hydrological variables affect the yield of the main Mediterranean crops in the Ebro River Basin. In the second step, this study takes into consideration the effects of those interactions and analyzes gross value added sensitivity to crop production changes. We then use Montecarlo simulations to characterize crop yield risk to water variability. Finally we evaluate some policy scenarios with irrigated area adjustments that could cope in a context of increased water scarcity. A substantial decrease in irrigated land, of up to 30% of total, results in only moderate losses of crop productivity. The response is crop and region specific and may serve to prioritise adaptation strategies.

Selection of non-Saccharomyces yeast strains for reducing alcohol levels in wine by sugar respiration.

PubMed

Quirós, Manuel; Rojas, Virginia; Gonzalez, Ramon; Morales, Pilar

2014-07-02

Respiration of sugars by non-Saccharomyces yeasts has been recently proposed for lowering alcohol levels in wine. Development of industrial fermentation processes based on such an approach requires, amongst other steps, the identification of yeast strains which are able to grow and respire under the relatively harsh conditions found in grape must. This work describes the characterization of a collection of non-Saccharomyces yeast strains in order to identify candidate yeast strains for this specific application. It involved the estimation of respiratory quotient (RQ) values under aerated conditions, at low pH and high sugar concentrations, calculation of yields of ethanol and other relevant metabolites, and characterization of growth responses to the main stress factors found during the first stages of alcoholic fermentation. Physiological features of some strains of Metschnikowia pulcherrima or two species of Kluyveromyces, suggest they are suitable for lowering ethanol yields by respiration. The unsuitability of Saccharomyces cerevisiae strains for this purpose was not due to ethanol yields (under aerated conditions they are low enough for a significant reduction in final ethanol content), but to the high acetic acid yields under these growth conditions. According to results from controlled aeration fermentations with one strain of M. pulcherrima, design of an aeration regime allowing for lowering ethanol yields though preserving grape must components from excessive oxidation, would be conceivable. Copyright © 2014. Published by Elsevier B.V.

OP-Yield Version 1.00 user's guide

Treesearch

Martin W. Ritchie; Jianwei Zhang

2018-01-01

OP-Yield is a Microsoft Excel™ spreadsheet with 14 specified user inputs to derive custom yield estimates using the original Oliver and Powers (1978) functions as the foundation. It presents yields for ponderosa pine (Pinus ponderosa Lawson & C. Lawson) plantations in northern California. The basic model forms for dominantand...

Usability of NASA Satellite Imagery-Based Daily Solar Radiation for Crop Yield Simulation and Management Decisions

NASA Astrophysics Data System (ADS)

Yang, H.; Cassman, K. G.; Stackhouse, P. W.; Hoell, J. M.

2007-12-01

We tested the usability of NASA satellite imagery-based daily solar radiation for farm-specific crop yield simulation and management decisions using the Hybrid-Maize model (www.hybridmaize.unl.edu). Solar radiation is one of the key inputs for crop yield simulation. Farm-specific crop management decisions using simulation models require long-term (i.e., 20 years or longer) daily local weather data including solar radiation for assessing crop yield potential and its variation, optimizing crop planting date, and predicting crop yield in a real time mode. Weather stations that record daily solar radiation have sparse coverage and many of them have record shorter than 15 years. Based on satellite imagery and other remote sensed information, NASA has provided estimates of daily climatic data including solar radiation at a resolution of 1 degree grid over the earth surface from 1983 to 2005. NASA is currently continuing to update the database and has plans to provide near real-time data in the future. This database, which is free to the public at http://power.larc.nasa.gov, is a potential surrogate for ground- measured climatic data for farm-specific crop yield simulation and management decisions. In this report, we quantified (1) the similarities between NASA daily solar radiation and ground-measured data atr 20 US sites and four international sites, and (2) the accuracy and precision of simulated corn yield potential and its variability using NASA solar radiation coupled with other weather data from ground measurements. The 20 US sites are in the western Corn Belt, including Iowa, South Dakota, Nebraska, and Kansas. The four international sites are Los Banos in the Philippines, Beijing in China, Cali in Columbia, and Ibatan in Nigeria. Those sites were selected because of their high quality weather record and long duration (more than 20 years on average). We found that NASA solar radiation was highly significantly correlated (mean r2 =0.88**) with the ground measurements at the 20 US sites, while the correlation was poor (mean r2=0.55**, though significant) at the four international sites. At the 20 US sites, the mean root mean square error (RMSE) between NASA solar radiation and the ground data was 2.7 MJ/m2/d, or 19% of the mean daily ground data. At the four international sites, the mean RMSE was 4.0 MJ/m2/d, or 25% of the mean daily ground value. Large differences between NASA solar radiation and the ground data were likely associated with tropical environment or significant variation in elevation within a short distance. When using NASA solar radiation coupled with other weather data from ground measurements, the simulated corn yields were highly significantly correlated (mean r2=0.85**) with those using complete ground weather data at the 20 US sites, while the correlation (mean r2=0.48**) was poor at the four international sites. The mean RMSE between the simulated corn yields of the two batches was 0.50 Mg/ha, or 3% of the mean absolute value using the ground data. At the four international sites, the RMSE of the simulated yields was 1.5 Mg/ha, or 13% of the mean absolute value using the ground data. We conclude that the NASA satellite imagery-based daily solar radiation is a reasonably reliable surrogate for the ground observations for farm-specific crop yield simulation and management decisions, especially at locations where ground-measured solar radiation is unavailable.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Phillips, William Scott

This seminar presentation describes amplitude models and yield estimations that look at the data in order to inform legislation. The following points were brought forth in the summary: global models that will predict three-component amplitudes (R-T-Z) were produced; Q models match regional geology; corrected source spectra can be used for discrimination and yield estimation; three-component data increase coverage and reduce scatter in source spectral estimates; three-component efforts must include distance-dependent effects; a community effort on instrument calibration is needed.

Estimation of mouth level exposure to smoke constituents of cigarettes with different tar levels using filter analysis.

PubMed

Hyodo, T; Minagawa, K; Inoue, T; Fujimoto, J; Minami, N; Bito, R; Mikita, A

2013-12-01

A nicotine part-filter method can be applied to estimate smokers' mouth level exposure (MLE) to smoke constituents. The objectives of this study were (1) to generate calibration curves for 47 smoke constituents, (2) to estimate MLE to selected smoke constituents using Japanese smokers of commercially available cigarettes covering a wide range of International Organization for Standardization tar yields (1-21mg/cigarette), and (3) to investigate relationships between MLE estimates and various machine-smoking yields. Five cigarette brands were machine-smoked under 7 different smoking regimes and smoke constituents and nicotine content in part-filters were measured. Calibration curves were then generated. Spent cigarette filters were collected from a target of 50 smokers for each of the 15 brands and a total of 780 filters were obtained. Nicotine content in part-filters was then measured and MLE to each smoke constituent was estimated. Strong correlations were identified between nicotine content in part-filters and 41 out of the 47 smoke constituent yields. Estimates of MLE to acetaldehyde, acrolein, 1,3-butadiene, benzene, benzo[a]pyrene, carbon monoxide, and tar showed significant negative correlations with corresponding constituent yields per mg nicotine under the Health Canada Intense smoking regime, whereas significant positive correlations were observed for N-nitrosonornicotine and (4-methylnitrosoamino)-1-(3-pyridyl)-1-butanone. Copyright © 2013 Elsevier Inc. All rights reserved.

Targeting the right input data to improve crop modeling at global level

NASA Astrophysics Data System (ADS)

Adam, M.; Robertson, R.; Gbegbelegbe, S.; Jones, J. W.; Boote, K. J.; Asseng, S.

2012-12-01

Designed for location-specific simulations, the use of crop models at a global level raises important questions. Crop models are originally premised on small unit areas where environmental conditions and management practices are considered homogeneous. Specific information describing soils, climate, management, and crop characteristics are used in the calibration process. However, when scaling up for global application, we rely on information derived from geographical information systems and weather generators. To run crop models at broad, we use a modeling platform that assumes a uniformly generated grid cell as a unit area. Specific weather, specific soil and specific management practices for each crop are represented for each of the cell grids. Studies on the impacts of the uncertainties of weather information and climate change on crop yield at a global level have been carried out (Osborne et al, 2007, Nelson et al., 2010, van Bussel et al, 2011). Detailed information on soils and management practices at global level are very scarce but recognized to be of critical importance (Reidsma et al., 2009). Few attempts to assess the impact of their uncertainties on cropping systems performances can be found. The objectives of this study are (i) to determine sensitivities of a crop model to soil and management practices, inputs most relevant to low input rainfed cropping systems, and (ii) to define hotspots of sensitivity according to the input data. We ran DSSAT v4.5 globally (CERES-CROPSIM) to simulate wheat yields at 45arc-minute resolution. Cultivar parameters were calibrated and validated for different mega-environments (results not shown). The model was run for nitrogen-limited production systems. This setting was chosen as the most representative to simulate actual yield (especially for low-input rainfed agricultural systems) and assumes crop growth to be free of any pest and diseases damages. We conducted a sensitivity analysis on contrasting management practices, initial soil conditions, and soil characteristics information. Management practices were represented by planting date and the amount of fertilizer, initial conditions estimates for initial nitrogen, soil water, and stable soil carbon, and soil information is based on a simplified version of the WISE database, characterized by soil organic matter, texture and soil depth. We considered these factors as the most important determinants of nutrient supply to crops during their growing season. Our first global results demonstrate that the model is most sensitive to the initial conditions in terms of soil carbon and nitrogen (CN): wheat yields decreased by 45% when soil CN is null and increase by 15% when twice the soil CN content of the reference run is used. The yields did not appear to be very sensitive to initial soil water conditions, varying from 0% yield increase when initial soil water is set to wilting point to 6% yield increase when it was set to field capacity. They are slightly sensitive to nitrogen application: 8% yield decrease when no N is applied to 9% yield increase when 150 kg.ha-1 is applied. However, with closer examination of results, the model is more sensitive to nitrogen application than to initial soil CN content in Vietnam, Thailand and Japan compared to the rest of the world. More analyses per region and results on the planting dates and soil properties will be presented.

Assessment of different gridded weather data for soybean yield simulations in Brazil

NASA Astrophysics Data System (ADS)

Battisti, R.; Bender, F. D.; Sentelhas, P. C.

2018-01-01

A high-density, well-distributed, and consistent historical weather data series is of major importance for agricultural planning and climatic risk evaluation. A possible option for regions where weather station network is irregular is the use of gridded weather data (GWD), which can be downloaded online from different sources. Based on that, the aim of this study was to assess the suitability of two GWD, AgMERRA and XAVIER, by comparing them with measured weather data (MWD) for estimating soybean yield in Brazil. The GWD and MWD were obtained for 24 locations across Brazil, considering the period between 1980 and 2010. These data were used to estimate soybean yield with DSSAT-CROPGRO-Soybean model. The comparison of MWD with GWD resulted in a good agreement between climate variables, except for solar radiation. The crop simulations with GWD and MWD resulted in a good agreement for vegetative and reproductive phases. Soybean potential yield (Yp) simulated with AgMERRA and XAVIER had a high correlation (r > 0.88) when compared to the estimates with MWD, with the RMSE of about 400 kg ha-1. For attainable yield (Ya), estimates with XAVIER resulted in a RMSE of 700 kg ha-1 against 864 kg ha-1 from AgMERRA, both compared to the simulations using MWD. Even with these differences in Ya simulations, both GWD can be considered suitable for simulating soybean growth, development, and yield in Brazil; however, with XAVIER GWD presenting a better performance for weather and crop variables assessed.

Estimating hydraulic properties of the Floridan Aquifer System by analysis of earth-tide, ocean-tide, and barometric effects, Collier and Hendry Counties, Florida

USGS Publications Warehouse

Merritt, Michael L.

2004-01-01

Aquifers are subjected to mechanical stresses from natural, non-anthropogenic, processes such as pressure loading or mechanical forcing of the aquifer by ocean tides, earth tides, and pressure fluctuations in the atmosphere. The resulting head fluctuations are evident even in deep confined aquifers. The present study was conducted for the purpose of reviewing the research that has been done on the use of these phenomena for estimating the values of aquifer properties, and determining which of the analytical techniques might be useful for estimating hydraulic properties in the dissolved-carbonate hydrologic environment of southern Florida. Fifteen techniques are discussed in this report, of which four were applied.An analytical solution for head oscillations in a well near enough to the ocean to be influenced by ocean tides was applied to data from monitor zones in a well near Naples, Florida. The solution assumes a completely non-leaky confining unit of infinite extent. Resulting values of transmissivity are in general agreement with the results of aquifer performance tests performed by the South Florida Water Management District. There seems to be an inconsistency between results of the amplitude ratio analysis and independent estimates of loading efficiency. A more general analytical solution that takes leakage through the confining layer into account yielded estimates that were lower than those obtained using the non-leaky method, and closer to the South Florida Water Management District estimates. A numerical model with a cross-sectional grid design was applied to explore additional aspects of the problem.A relation between specific storage and the head oscillation observed in a well provided estimates of specific storage that were considered reasonable. Porosity estimates based on the specific storage estimates were consistent with values obtained from measurements on core samples. Methods are described for determining aquifer diffusivity by comparing the time-varying drawdown in an open well with periodic pressure-head oscillations in the aquifer, but the applicability of such methods might be limited in studies of the Floridan aquifer system.

Estimation of Rice Crop Yields Using Random Forests in Taiwan

NASA Astrophysics Data System (ADS)

Chen, C. F.; Lin, H. S.; Nguyen, S. T.; Chen, C. R.

2017-12-01

Rice is globally one of the most important food crops, directly feeding more people than any other crops. Rice is not only the most important commodity, but also plays a critical role in the economy of Taiwan because it provides employment and income for large rural populations. The rice harvested area and production are thus monitored yearly due to the government's initiatives. Agronomic planners need such information for more precise assessment of food production to tackle issues of national food security and policymaking. This study aimed to develop a machine-learning approach using physical parameters to estimate rice crop yields in Taiwan. We processed the data for 2014 cropping seasons, following three main steps: (1) data pre-processing to construct input layers, including soil types and weather parameters (e.g., maxima and minima air temperature, precipitation, and solar radiation) obtained from meteorological stations across the country; (2) crop yield estimation using the random forests owing to its merits as it can process thousands of variables, estimate missing data, maintain the accuracy level when a large proportion of the data is missing, overcome most of over-fitting problems, and run fast and efficiently when handling large datasets; and (3) error verification. To execute the model, we separated the datasets into two groups of pixels: group-1 (70% of pixels) for training the model and group-2 (30% of pixels) for testing the model. Once the model is trained to produce small and stable out-of-bag error (i.e., the mean squared error between predicted and actual values), it can be used for estimating rice yields of cropping seasons. The results obtained from the random forests-based regression were compared with the actual yield statistics indicated the values of root mean square error (RMSE) and mean absolute error (MAE) achieved for the first rice crop were respectively 6.2% and 2.7%, while those for the second rice crop were 5.3% and 2.9%, respectively. Although there are several uncertainties attributed to the data quality of input layers, our study demonstrates the promising application of random forests for estimating rice crop yields at the national level in Taiwan. This approach could be transferable to other regions of the world for improving large-scale estimation of rice crop yields.

Cross-Border Use of Food Databases: Equivalence of US and Australian Databases for Macronutrients

PubMed Central

Summer, Suzanne S.; Ollberding, Nicholas J.; Guy, Trish; Setchell, Kenneth D. R.; Brown, Nadine; Kalkwarf, Heidi J.

2013-01-01

When estimating dietary intake across multiple countries, the lack of a single comprehensive dietary database may lead researchers to modify one database to analyze intakes for all participants. This approach may yield results different from those using the country-specific database and introduce measurement error. We examined whether nutrient intakes of Australians calculated with a modified US database would be similar to those calculated with an Australian database. We analyzed 3-day food records of 68 Australian adults using the US-based Nutrition Data System for Research, modified to reflect food items consumed in Australia. Modification entailed identifying a substitute food whose energy and macronutrient content were within 10% of the Australian food or by adding a new food to the database. Paired Wilcoxon signed rank tests were used to compare differences in nutrient intakes estimated by both databases, and Pearson and intraclass correlation coefficients measured degree of association and agreement between intake estimates for individuals. Median intakes of energy, carbohydrate, protein, and fiber differed by <5% at the group level. Larger discrepancies were seen for fat (11%; P<0.0001) and most micronutrients. Despite strong correlations, nutrient intakes differed by >10% for an appreciable percentage of participants (35% for energy to 69% for total fat). Adding country-specific food items to an existing database resulted in similar overall macronutrient intake estimates but was insufficient for estimating individual intakes. When analyzing nutrient intakes in multinational studies, greater standardization and modification of databases may be required to more accurately estimate intake of individuals. PMID:23871108

3-D transient hydraulic tomography in unconfined aquifers with fast drainage response

NASA Astrophysics Data System (ADS)

Cardiff, M.; Barrash, W.

2011-12-01

We investigate, through numerical experiments, the viability of three-dimensional transient hydraulic tomography (3DTHT) for identifying the spatial distribution of groundwater flow parameters (primarily, hydraulic conductivity K) in permeable, unconfined aquifers. To invert the large amount of transient data collected from 3DTHT surveys, we utilize an iterative geostatistical inversion strategy in which outer iterations progressively increase the number of data points fitted and inner iterations solve the quasi-linear geostatistical formulas of Kitanidis. In order to base our numerical experiments around realistic scenarios, we utilize pumping rates, geometries, and test lengths similar to those attainable during 3DTHT field campaigns performed at the Boise Hydrogeophysical Research Site (BHRS). We also utilize hydrologic parameters that are similar to those observed at the BHRS and in other unconsolidated, unconfined fluvial aquifers. In addition to estimating K, we test the ability of 3DTHT to estimate both average storage values (specific storage Ss and specific yield Sy) as well as spatial variability in storage coefficients. The effects of model conceptualization errors during unconfined 3DTHT are investigated including: (1) assuming constant storage coefficients during inversion and (2) assuming stationary geostatistical parameter variability. Overall, our findings indicate that estimation of K is slightly degraded if storage parameters must be jointly estimated, but that this effect is quite small compared with the degradation of estimates due to violation of "structural" geostatistical assumptions. Practically, we find for our scenarios that assuming constant storage values during inversion does not appear to have a significant effect on K estimates or uncertainty bounds.

Bias in estimating accuracy of a binary screening test with differential disease verification

PubMed Central

Brinton, John T.; Ringham, Brandy M.; Glueck, Deborah H.

2011-01-01

SUMMARY Sensitivity, specificity, positive and negative predictive value are typically used to quantify the accuracy of a binary screening test. In some studies it may not be ethical or feasible to obtain definitive disease ascertainment for all subjects using a gold standard test. When a gold standard test cannot be used an imperfect reference test that is less than 100% sensitive and specific may be used instead. In breast cancer screening, for example, follow-up for cancer diagnosis is used as an imperfect reference test for women where it is not possible to obtain gold standard results. This incomplete ascertainment of true disease, or differential disease verification, can result in biased estimates of accuracy. In this paper, we derive the apparent accuracy values for studies subject to differential verification. We determine how the bias is affected by the accuracy of the imperfect reference test, the percent who receive the imperfect reference standard test not receiving the gold standard, the prevalence of the disease, and the correlation between the results for the screening test and the imperfect reference test. It is shown that designs with differential disease verification can yield biased estimates of accuracy. Estimates of sensitivity in cancer screening trials may be substantially biased. However, careful design decisions, including selection of the imperfect reference test, can help to minimize bias. A hypothetical breast cancer screening study is used to illustrate the problem. PMID:21495059

The influence of purge times on the yields of essential oil components extracted from plants by pressurized liquid extraction.

PubMed

Wianowska, Dorota

2014-01-01

The influence of different purge times on the yield of the main essential oil constituents of rosemary (Rosmarinus officinalis L.), thyme (Thymus vulgaris L.), and chamomile (Chamomilla recutita L.) was investigated. The pressurized liquid extraction process was performed by applying different extraction temperatures and solvents. The results presented in the paper show that the estimated yield of essential oil components extracted from the plants in the pressurized liquid extraction process is purge time-dependent. The differences in the estimated yields are mainly connected with the evaporation of individual essential oil components and the applied solvent during the purge; the more volatile an essential oil constituent is, the greater is its loss during purge time, and the faster the evaporation of the solvent during the purge process is, the higher the concentration of less volatile essential oil components in the pressurized liquid extraction receptacle. The effect of purge time on the estimated yield of individual essential oil constituents is additionally differentiated by the extraction temperature and the extraction ability of the applied solvent.

The direct cost of epilepsy in the United States: A systematic review of estimates.

PubMed

Begley, Charles E; Durgin, Tracy L

2015-09-01

To develop estimates of the direct cost of epilepsy in the United States for the general epilepsy population and sub-populations by systematically comparing similarities and differences in types of estimates and estimation methods from recently published studies. Papers published since 1995 were identified by systematic literature search. Information on types of estimates, study designs, data sources, types of epilepsy, and estimation methods was extracted from each study. Annual per person cost estimates from methodologically similar studies were identified, converted to 2013 U.S. dollars, and compared. From 4,104 publications discovered in the literature search, 21 were selected for review. Three were added that were published after the search. Eighteen were identified that reported estimates of average annual direct costs for the general epilepsy population in the United States. For general epilepsy populations (comprising all clinically defined subgroups), total direct healthcare costs per person ranged from $10,192 to $47,862 and epilepsy-specific costs ranged from $1,022 to $19,749. Four recent studies using claims data from large general populations yielded relatively similar epilepsy-specific annual cost estimates ranging from $8,412 to $11,354. Although more difficult to compare, studies examining direct cost differences for epilepsy sub-populations indicated a consistent pattern of markedly higher costs for those with uncontrolled or refractory epilepsy, and for those with comorbidities. This systematic review found that various approaches have been used to estimate the direct costs of epilepsy in the United States. However, recent studies using large claims databases and similar methods allow estimation of the direct cost burden of epilepsy for the general disease population, and show that it is greater for some patient subgroups. Additional research is needed to further understand the broader economic burden of epilepsy and how it varies across subpopulations. Wiley Periodicals, Inc. © 2015 International League Against Epilepsy.

Potato Production as Affected by Crop Parameters and Meteoro Logical Elements

NASA Astrophysics Data System (ADS)

Pereira, André B.; Villa Nova, Nilson A.; Pereira, Antonio R.

Meteorological elements directly influence crop potential productivity, regulating its transpiration, photosynthesis, and respiration processes in such a way as to control the growth and development of the plants throughout their physiological mechanisms at a given site. The interaction of the meteorological factors with crop responses is complex and has been the target of attention of many researchers from all over the world. There is currently a great deal of interest in estimating crop productivity as a function of climate by means of different crop weather models in order to help growers choose planting locations and timing to produce high yields with good tuber quality under site-specific atmospheric conditions. In this manuscript an agrometeorological model based on maximum carbon dioxide assimilation rates for C3 plants, fraction of photosynthetically active radiation, air temperature, photoperiod duration, and crop parameters is assessed as to its performance under tropical conditions. Crop parameters include leaf areaand harvest indexes, dry matter content of potato tubers, and crop cycles to estimate potato potential yields. Productivity obtained with the cultivar Itararé, grown with adequate soil water supply conditions at four different sites in the State of São Paulo (Itararé, Piracicaba, TatuÍ, and São Manuel), Brazil, were used to test the model. The results showed thatthe agrometeorological model tested under the climatic conditions of the State of São Paulo in general underestimated irrigated potato yield by less than 10%.This justifies the recommendation to test the performance of the model in study in other climaticregions for different crops and genotypes under optimal irrigationconditions in further scientific investigations. We reached the conclusion that the agrometeorological model taking into account information on leaf area index, photoperiod duration, photosynthetically active radiation and air temperature is feasible to estimate potential tuber yield at a commercial scale. The performance test shows that it can then be used to forecast harvest time, and also as an effective tool to predict the suitability of potential regions to the cultivation of potato crop, cultivar Itararé, at the State of São Paulo, Brazil.

Impacts of Different Assimilation Methodologies on Crop Yield Estimates Using Active and Passive Microwave Dataset at L-Band

NASA Astrophysics Data System (ADS)

Liu, P.; Bongiovanni, T. E.; Monsivais-Huertero, A.; Bindlish, R.; Judge, J.

2013-12-01

Accurate estimates of crop yield are important for managing agricultural production and food security. Although the crop growth models, such as the Decision Support System Agrotechnology Transfer (DSSAT), have been used to simulate crop growth and development, the crop yield estimates still diverge from the reality due to different sources of errors in the models and computation. Auxiliary observations may be incorporated into such dynamic models to improve predictions using data assimilation. Active and passive (AP) microwave observations at L-band (1-2 GHz) are sensitive to dielectric and geometric properties of soil and vegetation, including soil moisture (SM), vegetation water content (VWC), surface roughness, and vegetation structure. Because SM and VWC are one of the governing factors in estimating crop yield, microwave observations may be used to improve crop yield estimates. Current studies have shown that active observations are more sensitive to the surface roughness of soil and vegetation structure during the growing season, while the passive observations are more sensitive to the SM. Backscatter and emission models linked with the DSSAT model (DSSAT-A-P) allow assimilation of microwave observations of backscattering coefficient (σ0) and brightness temperature (TB) may provide biophysically realistic estimates of model states and parameters. The present ESA Soil Moisture Ocean Salinity (SMOS) mission provides passive observations at 1.41 GHz at 25 km every 2-3 days, and the NASA/CNDAE Aquarius mission provides L-band AP observations at spatial resolution of 150 km with a repeat coverage of 7 days for global SM products. In 2014, the planned NASA Soil Moisture Active Passive mission will provide AP observations at 1.26 and 1.41 GHz at the spatial resolutions of 3 and 30 km, respectively, with a repeat coverage of 2-3 days. The goal of this study is to understand the impacts of assimilation of asynchronous and synchronous AP observations on crop yield estimates. An Ensemble Kalman Filter-based methodology is implemented to incorporate σ0 and TB from Aquarius and SMOS in the DSSAT-A-P model to improve crop yield for two growing seasons of soybean -a normal and a drought affected season- in the rain-fed region of the Brazilian La Plata Basin, South America. Different scenarios of assimilation, including active only, passive only, and combined AP observations were considered. The elements of the state vector included both model states and parameters related to soil and vegetation. The number of elements included in the state vector changed depending upon different scenarios of assimilation and also upon the growth stages. Crop yield estimates were compared for different scenarios during the two seasons. A synthetic experiment conducted previously showed an improvement of crop estimates in the RMSD by 90 kg/ha using combined AP compared to the openloop and active only assimilation over the region.

Prediction of County-Level Corn Yields Using an Energy-Crop Growth Index.

NASA Astrophysics Data System (ADS)

Andresen, Jeffrey A.; Dale, Robert F.; Fletcher, Jerald J.; Preckel, Paul V.

1989-01-01

Weather conditions significantly affect corn yields. while weather remains as the major uncontrolled variable in crop production, an understanding of the influence of weather on yields can aid in early and accurate assessment of the impact of weather and climate on crop yields and allow for timely agricultural extension advisories to help reduce farm management costs and improve marketing, decisions. Based on data for four representative countries in Indiana from 1960 to 1984 (excluding 1970 because of the disastrous southern corn leaf blight), a model was developed to estimate corn (Zea mays L.) yields as a function of several composite soil-crop-weather variables and a technology-trend marker, applied nitrogen fertilizer (N). The model was tested by predicting corn yields for 15 other counties. A daily energy-crop growth (ECG) variable in which different weights were used for the three crop-weather variables which make up the daily ECG-solar radiation intercepted by the canopy, a temperature function, and the ratio of actual to potential evapotranspiration-performed better than when the ECG components were weighted equally. The summation of the weighted daily ECG over a relatively short period (36 days spanning silk) was found to provide the best index for predicting county average corn yield. Numerical estimation results indicate that the ratio of actual to potential evapotranspiration (ET/PET) is much more important than the other two ECG factors in estimating county average corn yield in Indiana.

Kansas environmental and resource study: A Great Plains model. Extraction of agricultural statistics from ERTS-1 data of Kansas. [wheat inventory and agriculture land use

NASA Technical Reports Server (NTRS)

Morain, S. A. (Principal Investigator); Williams, D. L.

1974-01-01

The author has identified the following significant results. Wheat area, yield, and production statistics as derived from satellite image analysis, combined with a weather model, are presented for a ten county area in southwest Kansas. The data (representing the 1972-73 crop year) are compared for accuracy against both the USDA August estimate and its final (official) tabulation. The area estimates from imagery for both dryland and irrigated winter wheat were within 5% of the official figures for the same area, and predated them by almost one year. Yield on dryland wheat was estimated by the Thompson weather model to within 0.1% of the observed yield. A combined irrigated and dryland wheat production estimate for the ten county area was completed in July, 1973 and was within 1% of the production reported by USDA in February, 1974.

Assimilating remote sensing observations of leaf area index and soil moisture for wheat yield estimates: An observing system simulation experiment

USDA-ARS?s Scientific Manuscript database

We develop a robust understanding of the effects of assimilating remote sensing observations of leaf area index and soil moisture (in the top 5 cm) on DSSAT-CSM CropSim-Ceres wheat yield estimates. Synthetic observing system simulation experiments compare the abilities of the Ensemble Kalman Filter...

Potential for Improved Crop Yield Prediction Through Assimilation of Satellite-Derived Soil Moisture Data

USDA-ARS?s Scientific Manuscript database

Crop yield estimates have a strong impact on dealing with food shortages and on market demand and supply; these estimates are critical for decision-making processes by the U.S. Government, policy makers, stakeholders, etc. Most of the decision making is based on forecasts provided by the U.S. Depart...

Assimilating a synthetic Kalman filter leaf area index series into the WOFOST model to improve regional winter wheat yield estimation

USDA-ARS?s Scientific Manuscript database

The scale mismatch between remotely sensed observations and crop growth models simulated state variables decreases the reliability of crop yield estimates. To overcome this problem, we used a two-step data assimilation phases: first we generated a complete leaf area index (LAI) time series by combin...

Evaluating the potential of vegetation indices for winter wheat LAI estimation under different fertilization and water conditions

NASA Astrophysics Data System (ADS)

Xie, Qiaoyun; Huang, Wenjiang; Dash, Jadunandan; Song, Xiaoyu; Huang, Linsheng; Zhao, Jinling; Wang, Renhong

2015-12-01

Leaf area index (LAI) is an important indicator for monitoring crop growth conditions and forecasting grain yield. Many algorithms have been developed for remote estimation of the leaf area index of vegetation, such as using spectral vegetation indices, inversion of radiative transfer models, and supervised learning techniques. Spectral vegetation indices, mathematical combination of reflectance bands, are widely used for LAI estimation due to their computational simplicity and their applications ranged from the leaf scale to the entire globe. However, in many cases, their applicability is limited to specific vegetation types or local conditions due to species specific nature of the relationship used to transfer the vegetation indices to LAI. The overall objective of this study is to investigate the most suitable vegetation index for estimating winter wheat LAI under eight different types of fertilizer and irrigation conditions. Regression models were used to estimate LAI using hyperspectral reflectance data from the Pushbroom Hyperspectral Imager (PHI) and in-situ measurements. Our results showed that, among six vegetation indices investigated, the modified soil-adjusted vegetation index (MSAVI) and the normalized difference vegetation index (NDVI) exhibited strong and significant relationships with LAI, and thus were sensitive across different nitrogen and water treatments. The modified triangular vegetation index (MTVI2) confirmed its potential on crop LAI estimation, although second to MSAVI and NDVI in our study. The enhanced vegetation index (EVI) showed moderate performance. However, the ratio vegetation index (RVI) and the modified simple ratio index (MSR) predicted the least accurate estimations of LAI, exposing the simple band ratio index's weakness under different treatment conditions. The results support the use of vegetation indices for a quick and effective LAI mapping procedure that is suitable for winter wheat under different management practices.

Estimating rice yield related traits and quantitative trait loci analysis under different nitrogen treatments using a simple tower-based field phenotyping system with modified single-lens reflex cameras

NASA Astrophysics Data System (ADS)

Naito, Hiroki; Ogawa, Satoshi; Valencia, Milton Orlando; Mohri, Hiroki; Urano, Yutaka; Hosoi, Fumiki; Shimizu, Yo; Chavez, Alba Lucia; Ishitani, Manabu; Selvaraj, Michael Gomez; Omasa, Kenji

2017-03-01

Application of field based high-throughput phenotyping (FB-HTP) methods for monitoring plant performance in real field conditions has a high potential to accelerate the breeding process. In this paper, we discuss the use of a simple tower based remote sensing platform using modified single-lens reflex cameras for phenotyping yield traits in rice under different nitrogen (N) treatments over three years. This tower based phenotyping platform has the advantages of simplicity, ease and stability in terms of introduction, maintenance and continual operation under field conditions. Out of six phenological stages of rice analyzed, the flowering stage was the most useful in the estimation of yield performance under field conditions. We found a high correlation between several vegetation indices (simple ratio (SR), normalized difference vegetation index (NDVI), transformed vegetation index (TVI), corrected transformed vegetation index (CTVI), soil-adjusted vegetation index (SAVI) and modified soil-adjusted vegetation index (MSAVI)) and multiple yield traits (panicle number, grain weight and shoot biomass) across a three trials. Among all of the indices studied, SR exhibited the best performance in regards to the estimation of grain weight (R2 = 0.80). Under our tower-based field phenotyping system (TBFPS), we identified quantitative trait loci (QTL) for yield related traits using a mapping population of chromosome segment substitution lines (CSSLs) and a single nucleotide polymorphism data set. Our findings suggest the TBFPS can be useful for the estimation of yield performance during early crop development. This can be a major opportunity for rice breeders whom desire high throughput phenotypic selection for yield performance traits.

The yield and decay coefficients of exoelectrogenic bacteria in bioelectrochemical systems.

PubMed

Wilson, Erica L; Kim, Younggy

2016-05-01

In conventional wastewater treatment, waste sludge management and disposal contribute the major cost for wastewater treatment. Bioelectrochemical systems, as a potential alternative for future wastewater treatment and resources recovery, are expected to produce small amounts of waste sludge because exoelectrogenic bacteria grow on anaerobic respiration and form highly populated biofilms on bioanode surfaces. While waste sludge production is governed by the yield and decay coefficient, none of previous studies have quantified these kinetic constants for exoelectrogenic bacteria. For yield coefficient estimation, we modified McCarty's free energy-based model by using the bioanode potential for the free energy of the electron acceptor reaction. The estimated true yield coefficient ranged 0.1 to 0.3 g-VSS (volatile suspended solids) g-COD(-1) (chemical oxygen demand), which is similar to that of most anaerobic microorganisms. The yield coefficient was sensitively affected by the bioanode potential and pH while the substrate and bicarbonate concentrations had relatively minor effects on the yield coefficient. In lab-scale experiments using microbial electrolysis cells, the observed yield coefficient (including the effect of cell decay) was found to be 0.020 ± 0.008 g-VSS g-COD(-1), which is an order of magnitude smaller than the theoretical estimation. Based on the difference between the theoretical and experimental results, the decay coefficient was approximated to be 0.013 ± 0.002 d(-1). These findings indicate that bioelectrochemical systems have potential for future wastewater treatment with reduced waste sludge as well as for resources recovery. Also, the found kinetic information will allow accurate estimation of wastewater treatment performance in bioelectrochemical systems. Copyright © 2016 Elsevier Ltd. All rights reserved.

Pre-treatment patient-specific stopping power by combining list-mode proton radiography and x-ray CT

NASA Astrophysics Data System (ADS)

Collins-Fekete, Charles-Antoine; Brousmiche, Sébastien; Hansen, David C.; Beaulieu, Luc; Seco, Joao

2017-09-01

The relative stopping power (RSP) uncertainty is the largest contributor to the range uncertainty in proton therapy. The purpose of this work was to develop a systematic method that yields accurate and patient-specific RSPs by combining (1) pre-treatment x-ray CT and (2) daily proton radiography of the patient. The method was formulated as a penalized least squares optimization problem (argmin(\\Vert {A}{x}-{b}\\Vert _22 )). The parameter A represents the cumulative path-length crossed by the proton in each material, separated by thresholding on the HU. The material RSPs (water equivalent thickness/physical thickness) are denoted by x. The parameter b is the list-mode proton radiography produced using Geant4 simulations. The problem was solved using a non-negative linear-solver with {x}≥slant0 . A was computed by superposing proton trajectories calculated with a cubic or linear spline approach to the CT. The material’s RSP assigned in Geant4 were used for reference while the clinical HU-RSP calibration curve was used for comparison. The Gammex RMI-467 phantom was first investigated. The standard deviation between the estimated material RSP and the calculated RSP is 0.45%. The robustness of the techniques was then assessed as a function of the number of projections and initial proton energy. Optimization with two initial projections yields precise RSP (⩽1.0%) for 330 MeV protons. 250 MeV protons have shown higher uncertainty (⩽2.0%) due to the loss of precision in the path estimate. Anthropomorphic phantoms of the head, pelvis, and lung were subsequently evaluated. Accurate RSP has been obtained for the head (μ =0.21+/-1.63% ), the lung (μ=0.06+/-0.99% ) and the pelvis (μ=0.90+/-3.87% ). The range precision has been optimized using the calibration curves obtained with the algorithm, yielding a mean R80 difference to the reference of 0.11  ±0.09%, 0.28  ±  0.34% and 0.05 +/- 0.06% in the same order. The solution’s accuracy is limited by the assumed HU/RSP bijection, neglecting inherent degeneracy. The proposed formulation of the problem with prior knowledge x-ray CT demonstrates potential to increase the accuracy of present RSP estimates.

Pre-treatment patient-specific stopping power by combining list-mode proton radiography and x-ray CT.

PubMed

Collins-Fekete, Charles-Antoine; Brousmiche, Sébastien; Hansen, David C; Beaulieu, Luc; Seco, Joao

2017-08-03

The relative stopping power (RSP) uncertainty is the largest contributor to the range uncertainty in proton therapy. The purpose of this work was to develop a systematic method that yields accurate and patient-specific RSPs by combining (1) pre-treatment x-ray CT and (2) daily proton radiography of the patient. The method was formulated as a penalized least squares optimization problem (argmin([Formula: see text])). The parameter A represents the cumulative path-length crossed by the proton in each material, separated by thresholding on the HU. The material RSPs (water equivalent thickness/physical thickness) are denoted by x. The parameter b is the list-mode proton radiography produced using Geant4 simulations. The problem was solved using a non-negative linear-solver with [Formula: see text]. A was computed by superposing proton trajectories calculated with a cubic or linear spline approach to the CT. The material's RSP assigned in Geant4 were used for reference while the clinical HU-RSP calibration curve was used for comparison. The Gammex RMI-467 phantom was first investigated. The standard deviation between the estimated material RSP and the calculated RSP is 0.45%. The robustness of the techniques was then assessed as a function of the number of projections and initial proton energy. Optimization with two initial projections yields precise RSP (⩽1.0%) for 330 MeV protons. 250 MeV protons have shown higher uncertainty (⩽2.0%) due to the loss of precision in the path estimate. Anthropomorphic phantoms of the head, pelvis, and lung were subsequently evaluated. Accurate RSP has been obtained for the head ([Formula: see text]), the lung ([Formula: see text]) and the pelvis ([Formula: see text]). The range precision has been optimized using the calibration curves obtained with the algorithm, yielding a mean [Formula: see text] difference to the reference of 0.11  ±0.09%, 0.28  ±  0.34% and [Formula: see text] in the same order. The solution's accuracy is limited by the assumed HU/RSP bijection, neglecting inherent degeneracy. The proposed formulation of the problem with prior knowledge x-ray CT demonstrates potential to increase the accuracy of present RSP estimates.

Linkages among climate change, crop yields and Mexico–US cross-border migration

PubMed Central

Feng, Shuaizhang; Krueger, Alan B.; Oppenheimer, Michael

2010-01-01

Climate change is expected to cause mass human migration, including immigration across international borders. This study quantitatively examines the linkages among variations in climate, agricultural yields, and people's migration responses by using an instrumental variables approach. Our method allows us to identify the relationship between crop yields and migration without explicitly controlling for all other confounding factors. Using state-level data from Mexico, we find a significant effect of climate-driven changes in crop yields on the rate of emigration to the United States. The estimated semielasticity of emigration with respect to crop yields is approximately −0.2, i.e., a 10% reduction in crop yields would lead an additional 2% of the population to emigrate. We then use the estimated semielasticity to explore the potential magnitude of future emigration. Depending on the warming scenarios used and adaptation levels assumed, with other factors held constant, by approximately the year 2080, climate change is estimated to induce 1.4 to 6.7 million adult Mexicans (or 2% to 10% of the current population aged 15–65 y) to emigrate as a result of declines in agricultural productivity alone. Although the results cannot be mechanically extrapolated to other areas and time periods, our findings are significant from a global perspective given that many regions, especially developing countries, are expected to experience significant declines in agricultural yields as a result of projected warming. PMID:20660749

Linkages among climate change, crop yields and Mexico-US cross-border migration.

PubMed

Feng, Shuaizhang; Krueger, Alan B; Oppenheimer, Michael

2010-08-10

Climate change is expected to cause mass human migration, including immigration across international borders. This study quantitatively examines the linkages among variations in climate, agricultural yields, and people's migration responses by using an instrumental variables approach. Our method allows us to identify the relationship between crop yields and migration without explicitly controlling for all other confounding factors. Using state-level data from Mexico, we find a significant effect of climate-driven changes in crop yields on the rate of emigration to the United States. The estimated semielasticity of emigration with respect to crop yields is approximately -0.2, i.e., a 10% reduction in crop yields would lead an additional 2% of the population to emigrate. We then use the estimated semielasticity to explore the potential magnitude of future emigration. Depending on the warming scenarios used and adaptation levels assumed, with other factors held constant, by approximately the year 2080, climate change is estimated to induce 1.4 to 6.7 million adult Mexicans (or 2% to 10% of the current population aged 15-65 y) to emigrate as a result of declines in agricultural productivity alone. Although the results cannot be mechanically extrapolated to other areas and time periods, our findings are significant from a global perspective given that many regions, especially developing countries, are expected to experience significant declines in agricultural yields as a result of projected warming.

Radar Investigations of Asteroids

NASA Technical Reports Server (NTRS)

Ostro, S. J.

1984-01-01

Radar investigations of asteroids, including observations during 1984 to 1985 of at least 8 potential targets and continued analyses of radar data obtained during 1980 to 1984 for 30 other asteroids is proposed. The primary scientific objectives include estimation of echo strength, polarization, spectral shape, spectral bandwidth, and Doppler shift. These measurements yield estimates of target size, shape, and spin vector; place constraints on topography, morphology, density, and composition of the planetary surface; yield refined estimates of target orbital parameters; and reveals the presence of asteroidal satellites.

Why is it so difficult to determine the yield of indoor cannabis plantations? A case study from the Netherlands.

PubMed

Vanhove, Wouter; Maalsté, Nicole; Van Damme, Patrick

2017-07-01

Together, the Netherlands and Belgium are the largest indoor cannabis producing countries in Europe. In both countries, legal prosecution procedure of convicted illicit cannabis growers usually includes recovery of the profits gained. However, it is not easy to make a reliable estimation of the latter profits, due to the wide range of factors that determine indoor cannabis yields and eventual selling prices. In the Netherlands, since 2005, a reference model is used that assumes a constant yield (g) per plant for a given indoor cannabis plant density. Later, in 2011, a new model was developed in Belgium for yield estimation of Belgian indoor cannabis plantations that assumes a constant yield per m 2 of growth surface, provided that a number of growth conditions are met. Indoor cannabis plantations in the Netherlands and Belgium share similar technical characteristics. As a result, for indoor cannabis plantations in both countries, both aforementioned yield estimation models should yield similar yield estimations. By means of a real-case study from the Netherlands, we show that the reliability of both models is hampered by a number of flaws and unmet preconditions. The Dutch model is based on a regression equation that makes use of ill-defined plant development stages, assumes a linear plant growth, does not discriminate between different plantation size categories and does not include other important yield determining factors (such as fertilization). The Belgian model addresses some of the latter shortcomings, but its applicability is constrained by a number of pre-conditions including plantation size between 50 and 1000 plants; cultivation in individual pots with peat soil; 600W (electrical power) assimilation lamps; constant temperature between 20°C and 30°C; adequate fertilizer application and plants unaffected by pests and diseases. Judiciary in both the Netherlands and Belgium require robust indoor cannabis yield models for adequate legal prosecution of illicit indoor cannabis growth operations. To that aim, the current models should be optimized whereas the validity of their application should be examined case by case. Copyright © 2017 Elsevier B.V. All rights reserved.

The Safe Yield and Climatic Variability: Implications for Groundwater Management.

PubMed

Loáiciga, Hugo A

2017-05-01

Methods for calculating the safe yield are evaluated in this paper using a high-quality and long historical data set of groundwater recharge, discharge, extraction, and precipitation in a karst aquifer. Consideration is given to the role that climatic variability has on the determination of a climatically representative period with which to evaluate the safe yield. The methods employed to estimate the safe yield are consistent with its definition as a long-term average extraction rate that avoids adverse impacts on groundwater. The safe yield is a useful baseline for groundwater planning; yet, it is herein shown that it is not an operational rule that works well under all climatic conditions. This paper shows that due to the nature of dynamic groundwater processes it may be most appropriate to use an adaptive groundwater management strategy that links groundwater extraction rates to groundwater discharge rates, thus achieving a safe yield that represents an estimated long-term sustainable yield. An example of the calculation of the safe yield of the Edwards Aquifer (Texas) demonstrates that it is about one-half of the average annual recharge. © 2016, National Ground Water Association.

Use of vegetation health data for estimation of aus rice yield in bangladesh.

PubMed

Rahman, Atiqur; Roytman, Leonid; Krakauer, Nir Y; Nizamuddin, Mohammad; Goldberg, Mitch

2009-01-01

Rice is a vital staple crop for Bangladesh and surrounding countries, with interannual variation in yields depending on climatic conditions. We compared Bangladesh yield of aus rice, one of the main varieties grown, from official agricultural statistics with Vegetation Health (VH) Indices [Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and Vegetation Health Index (VHI)] computed from Advanced Very High Resolution Radiometer (AVHRR) data covering a period of 15 years (1991-2005). A strong correlation was found between aus rice yield and VCI and VHI during the critical period of aus rice development that occurs during March-April (weeks 8-13 of the year), several months in advance of the rice harvest. Stepwise principal component regression (PCR) was used to construct a model to predict yield as a function of critical-period VHI. The model reduced the yield prediction error variance by 62% compared with a prediction of average yield for each year. Remote sensing is a valuable tool for estimating rice yields well in advance of harvest and at a low cost.

Use of Vegetation Health Data for Estimation of Aus Rice Yield in Bangladesh

PubMed Central

Rahman, Atiqur; Roytman, Leonid; Krakauer, Nir Y.; Nizamuddin, Mohammad; Goldberg, Mitch

2009-01-01

Rice is a vital staple crop for Bangladesh and surrounding countries, with interannual variation in yields depending on climatic conditions. We compared Bangladesh yield of aus rice, one of the main varieties grown, from official agricultural statistics with Vegetation Health (VH) Indices [Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and Vegetation Health Index (VHI)] computed from Advanced Very High Resolution Radiometer (AVHRR) data covering a period of 15 years (1991–2005). A strong correlation was found between aus rice yield and VCI and VHI during the critical period of aus rice development that occurs during March–April (weeks 8–13 of the year), several months in advance of the rice harvest. Stepwise principal component regression (PCR) was used to construct a model to predict yield as a function of critical-period VHI. The model reduced the yield prediction error variance by 62% compared with a prediction of average yield for each year. Remote sensing is a valuable tool for estimating rice yields well in advance of harvest and at a low cost. PMID:22574057

Estimating the impact of seawater on the production of soil water-extractable organic carbon during coastal erosion.

PubMed

Dou, Fugen; Ping, Chien-Lu; Guo, Laodong; Jorgenson, Torre

2008-01-01

The production of water-extractable organic carbon (WEOC) during arctic coastal erosion and permafrost degradation may contribute significantly to C fluxes under warming conditions, but it remains difficult to quantify. A tundra soil collected near Barrow, AK, was selected to evaluate the effects of soil pretreatments (oven drying vs. freeze drying) as well as extraction solutions (pure water vs. seawater) on WEOC yields. Both oven drying and freeze drying significantly increased WEOC release compared with the original moist soil samples; dried samples released, on average, 18% more WEOC than did original moist samples. Similar results were observed for the production of low-molecular-weight dissolved organic C. However, extractable OC released from different soil horizons exhibited differences in specific UV absorption, suggesting differences in WEOC quality. Furthermore, extractable OC yields were significantly less in samples extracted with seawater compared with those extracted with pure water, likely due to the effects of major ions on extractable OC flocculation. Compared with samples from the active horizons, upper permafrost samples released more WEOC, suggesting that continuously frozen samples were more sensitive than samples that had experienced more drying-wetting cycles in nature. Specific UV absorption of seawater-extracted OC was significantly lower than that of OC extracted using pure water, suggesting more aromatic or humic substances were flocculated during seawater extraction. Our results suggest that overestimation of total terrestrial WEOC input to the Arctic Ocean during coastal erosion could occur if estimations were based on WEOC extracted from dried soil samples using pure water.

Using the Center for Epidemiologic Studies Depression Scale to Screen for Depression in Systemic Lupus Erythematosus

PubMed Central

Julian, Laura J.; Gregorich, Steven E.; Tonner, Chris; Yazdany, Jinoos; Trupin, Laura; Criswell, Lindsey A.; Yelin, ED; Katz, Patricia P.

2013-01-01

Objective Identifying persons with systemic lupus erythematosus (SLE) at risk for depression would facilitate the identification and treatment of an important comorbidity conferring additional risk for poor outcomes. The purpose of this study was to determine the utility of a brief screening measure, the Center for Epidemiologic Studies Depression Scale (CES-D), in detecting mood disorders in persons with SLE. Methods This cross-sectional study examined 150 persons with SLE. Screening cut points were empirically derived using threshold selection methods, and receiver operating characteristic curves were estimated. The empirically derived cut points of the CES-D were used as the screening measures and were compared to other commonly used CES-D cut points in addition to other commonly used methods to screen for depression. Diagnoses of major depressive disorder or other mood disorders were determined using a “gold standard” structured clinical interview. Results Of the 150 persons with SLE, 26% of subjects met criteria for any mood disorder and 17% met criteria for major depressive disorder. Optimal threshold estimations suggested a CES-D cut score of 24 and above, which yielded adequate sensitivity and specificity in detecting major depressive disorder (88% and 93%, respectively) and correctly classified 92% of participants. To detect the presence of any mood disorder, a cut score of 20 and above was suggested, yielding sensitivity and specificity of 87% and correctly classifying 87%. Conclusion These results suggest the CES-D may be a useful screening measure to identify patients at risk for depression. PMID:21312347

Whole Genome Sequencing Increases Molecular Diagnostic Yield Compared with Current Diagnostic Testing for Inherited Retinal Disease.

PubMed

Ellingford, Jamie M; Barton, Stephanie; Bhaskar, Sanjeev; Williams, Simon G; Sergouniotis, Panagiotis I; O'Sullivan, James; Lamb, Janine A; Perveen, Rahat; Hall, Georgina; Newman, William G; Bishop, Paul N; Roberts, Stephen A; Leach, Rick; Tearle, Rick; Bayliss, Stuart; Ramsden, Simon C; Nemeth, Andrea H; Black, Graeme C M

2016-05-01

To compare the efficacy of whole genome sequencing (WGS) with targeted next-generation sequencing (NGS) in the diagnosis of inherited retinal disease (IRD). Case series. A total of 562 patients diagnosed with IRD. We performed a direct comparative analysis of current molecular diagnostics with WGS. We retrospectively reviewed the findings from a diagnostic NGS DNA test for 562 patients with IRD. A subset of 46 of 562 patients (encompassing potential clinical outcomes of diagnostic analysis) also underwent WGS, and we compared mutation detection rates and molecular diagnostic yields. In addition, we compared the sensitivity and specificity of the 2 techniques to identify known single nucleotide variants (SNVs) using 6 control samples with publically available genotype data. Diagnostic yield of genomic testing. Across known disease-causing genes, targeted NGS and WGS achieved similar levels of sensitivity and specificity for SNV detection. However, WGS also identified 14 clinically relevant genetic variants through WGS that had not been identified by NGS diagnostic testing for the 46 individuals with IRD. These variants included large deletions and variants in noncoding regions of the genome. Identification of these variants confirmed a molecular diagnosis of IRD for 11 of the 33 individuals referred for WGS who had not obtained a molecular diagnosis through targeted NGS testing. Weighted estimates, accounting for population structure, suggest that WGS methods could result in an overall 29% (95% confidence interval, 15-45) uplift in diagnostic yield. We show that WGS methods can detect disease-causing genetic variants missed by current NGS diagnostic methodologies for IRD and thereby demonstrate the clinical utility and additional value of WGS. Copyright © 2016 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Using thermal units for estimating critical period of weed competition in off-season maize crop.

PubMed

López-Ovejero, Ramiro Fernando; y Garcia, Axel Garcia; de Carvalho, Saul Jorge P; Christoffoleti, Pedro J; Neto, Durval Dourado; Martins, Fernando; Nicolai, Marcelo

2005-01-01

Brazilian off-season maize production is characterized by low yield due to several factors, such as climate variability and inadequate management practices, specifically weed management. Thus, the goal of this study was to determinate the critical period of weed competition in off-season maize (Zea mays L.) crop using thermal units or growing degree days (GDD) approach to characterize crop growth and development. The study was carried out in experimental area of the University of São Paulo, Brazil, with weed control (C), as well as seven coexistence periods, 2, 4, 6, 8, and 12 leaves, flowering, and all crop cycle; fourteen treatments were done. Climate data were obtained from a weather station located close to the experimental area. To determine the critical period for weed control (CPWC) logistic models were fitted to yield data obtained in both W and C, as a function of GDD. For an arbitrary maximum yield loss fixed in 2.5%, the CPWC was found between 301 and 484 GDD (7-8 leaves). Also, when the arbitrary loss yield was fixed in 5 and 10%, the period before interference (PBI) was higher than the critical weed-free period (CWFP), suggesting that the weeds control can be done with only one application, between 144 and 410 GDD and 131 and 444 GDD (3-8 leaves), respectively. The GDD approach to characterize crop growth and development was successfully used to determine the critical period of weeds control in maize sown off-season. Further works will be necessary to better characterize the interaction and complexity of maize sown off-season with weeds. However, these results are encouraging because the possibility of the results to be extrapolated and because the potential of the method on providing important results to researchers, specifically crop modelers.

Steady-state and transient models of groundwater flow and advective transport, Eastern Snake River Plain aquifer, Idaho National Laboratory and vicinity, Idaho

USGS Publications Warehouse

Ackerman, Daniel J.; Rousseau, Joseph P.; Rattray, Gordon W.; Fisher, Jason C.

2010-01-01

Three-dimensional steady-state and transient models of groundwater flow and advective transport in the eastern Snake River Plain aquifer were developed by the U.S. Geological Survey in cooperation with the U.S. Department of Energy. The steady-state and transient flow models cover an area of 1,940 square miles that includes most of the 890 square miles of the Idaho National Laboratory (INL). A 50-year history of waste disposal at the INL has resulted in measurable concentrations of waste contaminants in the eastern Snake River Plain aquifer. Model results can be used in numerical simulations to evaluate the movement of contaminants in the aquifer. Saturated flow in the eastern Snake River Plain aquifer was simulated using the MODFLOW-2000 groundwater flow model. Steady-state flow was simulated to represent conditions in 1980 with average streamflow infiltration from 1966-80 for the Big Lost River, the major variable inflow to the system. The transient flow model simulates groundwater flow between 1980 and 1995, a period that included a 5-year wet cycle (1982-86) followed by an 8-year dry cycle (1987-94). Specified flows into or out of the active model grid define the conditions on all boundaries except the southwest (outflow) boundary, which is simulated with head-dependent flow. In the transient flow model, streamflow infiltration was the major stress, and was variable in time and location. The models were calibrated by adjusting aquifer hydraulic properties to match simulated and observed heads or head differences using the parameter-estimation program incorporated in MODFLOW-2000. Various summary, regression, and inferential statistics, in addition to comparisons of model properties and simulated head to measured properties and head, were used to evaluate the model calibration. Model parameters estimated for the steady-state calibration included hydraulic conductivity for seven of nine hydrogeologic zones and a global value of vertical anisotropy. Parameters estimated for the transient calibration included specific yield for five of the seven hydrogeologic zones. The zones represent five rock units and parts of four rock units with abundant interbedded sediment. All estimates of hydraulic conductivity were nearly within 2 orders of magnitude of the maximum expected value in a range that exceeds 6 orders of magnitude. The estimate of vertical anisotropy was larger than the maximum expected value. All estimates of specific yield and their confidence intervals were within the ranges of values expected for aquifers, the range of values for porosity of basalt, and other estimates of specific yield for basalt. The steady-state model reasonably simulated the observed water-table altitude, orientation, and gradients. Simulation of transient flow conditions accurately reproduced observed changes in the flow system resulting from episodic infiltration from the Big Lost River and facilitated understanding and visualization of the relative importance of historical differences in infiltration in time and space. As described in a conceptual model, the numerical model simulations demonstrate flow that is (1) dominantly horizontal through interflow zones in basalt and vertical anisotropy resulting from contrasts in hydraulic conductivity of various types of basalt and the interbedded sediments, (2) temporally variable due to streamflow infiltration from the Big Lost River, and (3) moving downward downgradient of the INL. The numerical models were reparameterized, recalibrated, and analyzed to evaluate alternative conceptualizations or implementations of the conceptual model. The analysis of the reparameterized models revealed that little improvement in the model could come from alternative descriptions of sediment content, simulated aquifer thickness, streamflow infiltration, and vertical head distribution on the downgradient boundary. Of the alternative estimates of flow to or from the aquifer, only a 20 percent decrease in

Quantitative Generalizations for Catchment Sediment Yield Following Plantation Logging

NASA Astrophysics Data System (ADS)

Bathurst, James; Iroume, Andres

2014-05-01

While there is a reasonably clear qualitative understanding of the impact of forest plantations on sediment yield, there is a lack of quantitative generalizations. Such generalizations would be helpful for estimating the impacts of proposed forestry operations and would aid the spread of knowledge amongst both relevant professionals and new students. This study therefore analyzed data from the literature to determine the extent to which quantitative statements can be established. The research was restricted to the impact of plantation logging on catchment sediment yield as a function of ground disturbance in the years immediately following logging, in temperate countries, and does not consider landslides consequent upon tree root decay. Twelve paired catchment studies incorporating pre- and post-logging measurements of sediment yield were identified, resulting in forty-three test catchments (including 14 control catchments). Analysis yielded the following principal conclusions: 1) Logging generally provokes maximum annual sediment yields of less than a few hundred t km-2 yr-1; best management practice can reduce this below 100 t km-2 yr-1. 2) At both the annual and event scales, the sediment yield excess of a logged catchment over a control catchment is within one order of magnitude, except with severe ground disturbance. 3) There is no apparent relationship between sediment yield impact and the proportion of catchment logged. The effect depends on which part of the catchment is altered and on its connectivity to the stream network. 4) The majority of catchments delivered their maximum sediment yield in the first two years after logging. The logging impacts were classified in terms of the absolute values of specific sediment yield, the values relative to those in the control catchments for the same period and the values relative both to the control catchment and the pre-logging period. Most studies have been for small catchments (< 10 km2) and temperate regions; the impact at large catchment scales and in tropical regions requires further research.

Estimating mean long-term hydrologic budget components for watersheds and counties: An application to the commonwealth of Virginia, USA

USGS Publications Warehouse

Sanford, Ward E.; Nelms, David L.; Pope, Jason P.; Selnick, David L.

2015-01-01

Mean long-term hydrologic budget components, such as recharge and base flow, are often difficult to estimate because they can vary substantially in space and time. Mean long-term fluxes were calculated in this study for precipitation, surface runoff, infiltration, total evapotranspiration (ET), riparian ET, recharge, base flow (or groundwater discharge) and net total outflow using long-term estimates of mean ET and precipitation and the assumption that the relative change in storage over that 30-year period is small compared to the total ET or precipitation. Fluxes of these components were first estimated on a number of real-time-gaged watersheds across Virginia. Specific conductance was used to distinguish and separate surface runoff from base flow. Specific-conductance (SC) data were collected every 15 minutes at 75 real-time gages for approximately 18 months between March 2007 and August 2008. Precipitation was estimated for 1971-2000 using PRISM climate data. Precipitation and temperature from the PRISM data were used to develop a regression-based relation to estimate total ET. The proportion of watershed precipitation that becomes surface runoff was related to physiographic province and rock type in a runoff regression equation. A new approach to estimate riparian ET using seasonal SC data gave results consistent with those from other methods. Component flux estimates from the watersheds were transferred to flux estimates for counties and independent cities using the ET and runoff regression equations. Only 48 of the 75 watersheds yielded sufficient data, and data from these 48 were used in the final runoff regression equation. Final results for the study are presented as component flux estimates for all counties and independent cities in Virginia. The method has the potential to be applied in many other states in the U.S. or in other regions or countries of the world where climate and stream flow data are plentiful.

On the use and misuse of scalar scores of confounders in design and analysis of observational studies.

PubMed

Pfeiffer, R M; Riedl, R

2015-08-15

We assess the asymptotic bias of estimates of exposure effects conditional on covariates when summary scores of confounders, instead of the confounders themselves, are used to analyze observational data. First, we study regression models for cohort data that are adjusted for summary scores. Second, we derive the asymptotic bias for case-control studies when cases and controls are matched on a summary score, and then analyzed either using conditional logistic regression or by unconditional logistic regression adjusted for the summary score. Two scores, the propensity score (PS) and the disease risk score (DRS) are studied in detail. For cohort analysis, when regression models are adjusted for the PS, the estimated conditional treatment effect is unbiased only for linear models, or at the null for non-linear models. Adjustment of cohort data for DRS yields unbiased estimates only for linear regression; all other estimates of exposure effects are biased. Matching cases and controls on DRS and analyzing them using conditional logistic regression yields unbiased estimates of exposure effect, whereas adjusting for the DRS in unconditional logistic regression yields biased estimates, even under the null hypothesis of no association. Matching cases and controls on the PS yield unbiased estimates only under the null for both conditional and unconditional logistic regression, adjusted for the PS. We study the bias for various confounding scenarios and compare our asymptotic results with those from simulations with limited sample sizes. To create realistic correlations among multiple confounders, we also based simulations on a real dataset. Copyright © 2015 John Wiley & Sons, Ltd.

Covariance Matrix Evaluations for Independent Mass Fission Yields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Terranova, N., E-mail: nicholas.terranova@unibo.it; Serot, O.; Archier, P.

2015-01-15

Recent needs for more accurate fission product yields include covariance information to allow improved uncertainty estimations of the parameters used by design codes. The aim of this work is to investigate the possibility to generate more reliable and complete uncertainty information on independent mass fission yields. Mass yields covariances are estimated through a convolution between the multi-Gaussian empirical model based on Brosa's fission modes, which describe the pre-neutron mass yields, and the average prompt neutron multiplicity curve. The covariance generation task has been approached using the Bayesian generalized least squared method through the CONRAD code. Preliminary results on mass yieldsmore » variance-covariance matrix will be presented and discussed from physical grounds in the case of {sup 235}U(n{sub th}, f) and {sup 239}Pu(n{sub th}, f) reactions.« less

[Regional scale remote sensing-based yield estimation of winter wheat by using MODIS-NDVI data: a case study of Jining City in Shandong Province].

PubMed

Ren, Jianqiang; Chen, Zhongxin; Tang, Huajun

2006-12-01

Taking Jining City of Shandong Province, one of the most important winter wheat production regions in Huanghuaihai Plain as an example, the winter wheat yield was estimated by using the 250 m MODIS-NDVI data smoothed by Savitzky-Golay filter. The NDVI values between 0. 20 and 0. 80 were selected, and the sum of NDVI value for each county was calculated to build its relation with winter wheat yield. By using stepwise regression method, the linear regression model between NDVI and winter wheat yield was established, with the precision validated by the ground survey data. The results showed that the relative error of predicted yield was between -3.6% and 3.9%, suggesting that the method was relatively accurate and feasible.

Assessing the Generalizability of Randomized Trial Results to Target Populations

PubMed Central

Stuart, Elizabeth A.; Bradshaw, Catherine P.; Leaf, Philip J.

2014-01-01

Recent years have seen increasing interest in and attention to evidence-based practices, where the “evidence” generally comes from well-conducted randomized trials. However, while those trials yield accurate estimates of the effect of the intervention for the participants in the trial (known as “internal validity”), they do not always yield relevant information about the effects in a particular target population (known as “external validity”). This may be due to a lack of specification of a target population when designing the trial, difficulties recruiting a sample that is representative of a pre-specified target population, or to interest in considering a target population somewhat different from the population directly targeted by the trial. This paper first provides an overview of existing design and analysis methods for assessing and enhancing the ability of a randomized trial to estimate treatment effects in a target population. It then provides a case study using one particular method, which weights the subjects in a randomized trial to match the population on a set of observed characteristics. The case study uses data from a randomized trial of School-wide Positive Behavioral Interventions and Supports (PBIS); our interest is in generalizing the results to the state of Maryland. In the case of PBIS, after weighting, estimated effects in the target population were similar to those observed in the randomized trial. The paper illustrates that statistical methods can be used to assess and enhance the external validity of randomized trials, making the results more applicable to policy and clinical questions. However, there are also many open research questions; future research should focus on questions of treatment effect heterogeneity and further developing these methods for enhancing external validity. Researchers should think carefully about the external validity of randomized trials and be cautious about extrapolating results to specific populations unless they are confident of the similarity between the trial sample and that target population. PMID:25307417

Assessing the generalizability of randomized trial results to target populations.

PubMed

Stuart, Elizabeth A; Bradshaw, Catherine P; Leaf, Philip J

2015-04-01

Recent years have seen increasing interest in and attention to evidence-based practices, where the "evidence" generally comes from well-conducted randomized trials. However, while those trials yield accurate estimates of the effect of the intervention for the participants in the trial (known as "internal validity"), they do not always yield relevant information about the effects in a particular target population (known as "external validity"). This may be due to a lack of specification of a target population when designing the trial, difficulties recruiting a sample that is representative of a prespecified target population, or to interest in considering a target population somewhat different from the population directly targeted by the trial. This paper first provides an overview of existing design and analysis methods for assessing and enhancing the ability of a randomized trial to estimate treatment effects in a target population. It then provides a case study using one particular method, which weights the subjects in a randomized trial to match the population on a set of observed characteristics. The case study uses data from a randomized trial of school-wide positive behavioral interventions and supports (PBIS); our interest is in generalizing the results to the state of Maryland. In the case of PBIS, after weighting, estimated effects in the target population were similar to those observed in the randomized trial. The paper illustrates that statistical methods can be used to assess and enhance the external validity of randomized trials, making the results more applicable to policy and clinical questions. However, there are also many open research questions; future research should focus on questions of treatment effect heterogeneity and further developing these methods for enhancing external validity. Researchers should think carefully about the external validity of randomized trials and be cautious about extrapolating results to specific populations unless they are confident of the similarity between the trial sample and that target population.

Photoresponsive peptide azobenzene conjugates that specifically interact with platinum surfaces

NASA Astrophysics Data System (ADS)

Dinçer, S.; Tamerler, C.; Sarıkaya, M.; Pişkin, E.

2008-05-01

The aim of this study is to prepare photoresponsive peptide-azobenzene compounds which interacts with platinum surfaces specifically, in order to create smart surfaces for further novel applications in design of smart biosensors and array platforms. Here, a water-soluble azobenzene molecule, 4-hydroxyazo benzene,4-sulfonic acid was synthesized by diazo coupling reaction. A platinum-specific peptide, originally selected by a phage display technique was chemically synthesized/purchased, and conjugated with the azobenzene compound activated with carbonyldiimidazole. Both azobenzene and its conjugate were characterized (including photoresponsive properties) by FTIR, NMR, and UV-spectrophotometer. The yield of conjugation reaction estimated by ninhydrin assay was about 65%. Peptide incorporation did not restrict the light-sensitivity of azobenzene. Adsorption of both the peptide and its azobenzene conjugate was followed by Quartz Crystal Microbalance (QCM) system. The kinetic evaluations exhibited that both molecules interact platinum surfaces, quite rapidly and strongly.

Estimating daily fat yield from a single milking on test day for herds with a robotic milking system.

PubMed

Peeters, R; Galesloot, P J B

2002-03-01

The objective of this study was to estimate the daily fat yield and fat percentage from one sampled milking per cow per test day in an automatic milking system herd, when the milking times and milk yields of all individual milkings are recorded by the automatic milking system. Multiple regression models were used to estimate the 24-h fat percentage when only one milking is sampled for components and milk yields and milking times are known for all milkings in the 24-h period before the sampled milking. In total, 10,697 cow test day records, from 595 herd tests at 91 Dutch herds milked with an automatic milking system, were used. The best model to predict 24-h fat percentage included fat percentage, protein percentage, milk yield and milking interval of the sampled milking, milk yield, and milking interval of the preceding milking, and the interaction between milking interval and the ratio of fat and protein percentage of the sampled milking. This model gave a standard deviation of the prediction error (SE) for 24-h fat percentage of 0.321 and a correlation between the predicted and actual 24-h fat percentage of 0.910. For the 24-h fat yield, we found SE = 90 g and correlation = 0.967. This precision is slightly better than that of present a.m.-p.m. testing schemes. Extra attention must be paid to correctly matching the sample jars and the milkings. Furthermore, milkings with an interval of less than 4 h must be excluded from sampling as well as milkings that are interrupted or that follow an interrupted milking. Under these restrictions (correct matching, interval of at least 4 h, and no interrupted milking), one sampled milking suffices to get a satisfactory estimate for the test-day fat yield.

Estimation of rice yield affected by drought and relation between rice yield and TVDI

NASA Astrophysics Data System (ADS)

Hongo, C.; Tamura, E.; Sigit, G.

2016-12-01

Impact of climate change is not only seen on food production but also on food security and sustainable development of society. Adaptation to climate change is a pressing issue throughout the world to reduce the risks along with the plans and strategies for food security and sustainable development. As a key adaptation to the climate change, agricultural insurance is expected to play an important role in stabilizing agricultural production through compensating the losses caused by the climate change. As the adaptation, the Government of Indonesia has launched agricultural insurance program for damage of rice by drought, flood and pest and disease. The Government started a pilot project in 2013 and this year the pilot project has been extended to 22 provinces. Having the above as background, we conducted research on development of new damage assessment method for rice using remote sensing data which could be used for evaluation of damage ratio caused by drought in West Java, Indonesia. For assessment of the damage ratio, estimation of rice yield is a key. As the result of our study, rice yield affected by drought in dry season could be estimated at level of 1 % significance using SPOT 7 data taken in 2015, and the validation result was 0.8t/ha. Then, the decrease ratio in rice yield about each individual paddy field was calculated using data of the estimated result and the average yield of the past 10 years. In addition, TVDI (Temperature Vegetation Dryness Index) which was calculated from Landsat8 data in heading season indicated the dryness in low yield area. The result suggests that rice yield was affected by irrigation water shortage around heading season as a result of the decreased precipitation by El Nino. Through our study, it becomes clear that the utilization of remote sensing data can be promising for assessment of the damage ratio of rice production precisely, quickly and quantitatively, and also it can be incorporated into the insurance procedures.

Recharge rates and aquifer hydraulic characteristics for selected drainage basins in middle and east Tennessee

USGS Publications Warehouse

Hoos, A.B.

1990-01-01

Quantitative information concerning aquifer hydrologic and hydraulic characteristics is needed to manage the development of ground-water resources. These characteristics are poorly defined for the bedrock aquifers in Middle and East Tennessee where demand for water is increasing. This report presents estimates of recharge rate, storage coefficient, diffusivity, and transmissivity for representative drainage basins in Middle and East Tennessee, as determined from analyses of stream-aquifer interactions. The drainage basins have been grouped according to the underlying major aquifer, then statistical descriptions applied to each group, in order to define area1 distribution of these characteristics. Aquifer recharge rates are estimated for representative low, average, and high flow years for 63 drainage basins using hydrograph analysis techniques. Net annual recharge during average flow years for all basins ranges from 4.1 to 16.8 in/yr (inches per year), with a mean value of 7.3 in. In general, recharge rates are highest for basins underlain by the Blue Ridge aquifer (mean value11.7 in/yr) and lowest for basins underlain by the Central Basin aquifer (mean value 5.6 in/yr). Mean recharge values for the Cumberland Plateau, Highland Rim, and Valley and Ridge aquifers are 6.5, 7.4, and 6.6 in/yr, respectively. Gravity drainage characterizes ground-water flow in most surficial bedrock aquifer in Tennessee. Accordingly, a gravity yield analysis, which compares concurrent water-level and streamflow hydrographs, was used to estimate aquifer storage coefficient for nine study basins. The basin estimates range from 0.002 to 0.140; however, most estimates are within a narrow range of values, from 0.01 to 0.025. Accordingly, storage coefficient is estimated to be 0.01 for all aquifers in Middle and East Tennessee, with the exception of the aquifer in the inner part of the Central Basin, for which storage coefficient is estimated to be 0.002. Estimates of aquifer hydraulic diffusivity are derived from estimates of the streamflow recession index and drainage density for 75 drainage basins; values range from 3,300 to 130,000 ft^2/d (feet squared per day). Basin-specific and site-specific estimates of transmissivity are computed from estimates of hydraulic diffusivity and specific-capacity test data, respectively. Basin-specific, or areal, estimates of transmissivity range from 22 to 1,300 ft^2/d, with a mean of 240 ft^2/d In general, areal transmissivity is highest for basins underlain by the Cumberland Plateau aquifer (mean value 480 ft^2/d) and lowest for basins underlain by the Central Basin aquifer (mean value 79 ft^2/d). Mean transmissivity values for the Highland Rim, Valley and Ridge, and Blue Ridge aquifer are 320,140, and 120 ft^2/d respectively. Site-specific estimates of transmissivity, computed from specific-capacity data from 118 test wells in Middle and East Tennessee range from 2 to 93,000 ft^2/d with a mean of 2,600 ft^2/d Mean transmissivity values for the Cumberland Plateau, Highland Rim, Central Basin, Valley and Ridge, and Blue Ridge aquifers are 2,800,1,200, 7,800, 390, and 65Oft Id, respectively.

RNA-Seq Alignment to Individualized Genomes Improves Transcript Abundance Estimates in Multiparent Populations

PubMed Central

Munger, Steven C.; Raghupathy, Narayanan; Choi, Kwangbom; Simons, Allen K.; Gatti, Daniel M.; Hinerfeld, Douglas A.; Svenson, Karen L.; Keller, Mark P.; Attie, Alan D.; Hibbs, Matthew A.; Graber, Joel H.; Chesler, Elissa J.; Churchill, Gary A.

2014-01-01

Massively parallel RNA sequencing (RNA-seq) has yielded a wealth of new insights into transcriptional regulation. A first step in the analysis of RNA-seq data is the alignment of short sequence reads to a common reference genome or transcriptome. Genetic variants that distinguish individual genomes from the reference sequence can cause reads to be misaligned, resulting in biased estimates of transcript abundance. Fine-tuning of read alignment algorithms does not correct this problem. We have developed Seqnature software to construct individualized diploid genomes and transcriptomes for multiparent populations and have implemented a complete analysis pipeline that incorporates other existing software tools. We demonstrate in simulated and real data sets that alignment to individualized transcriptomes increases read mapping accuracy, improves estimation of transcript abundance, and enables the direct estimation of allele-specific expression. Moreover, when applied to expression QTL mapping we find that our individualized alignment strategy corrects false-positive linkage signals and unmasks hidden associations. We recommend the use of individualized diploid genomes over reference sequence alignment for all applications of high-throughput sequencing technology in genetically diverse populations. PMID:25236449

Probability judgments under ambiguity and conflict

PubMed Central

Smithson, Michael

2015-01-01

Whether conflict and ambiguity are distinct kinds of uncertainty remains an open question, as does their joint impact on judgments of overall uncertainty. This paper reviews recent advances in our understanding of human judgment and decision making when both ambiguity and conflict are present, and presents two types of testable models of judgments under conflict and ambiguity. The first type concerns estimate-pooling to arrive at “best” probability estimates. The second type is models of subjective assessments of conflict and ambiguity. These models are developed for dealing with both described and experienced information. A framework for testing these models in the described-information setting is presented, including a reanalysis of a multi-nation data-set to test best-estimate models, and a study of participants' assessments of conflict, ambiguity, and overall uncertainty reported by Smithson (2013). A framework for research in the experienced-information setting is then developed, that differs substantially from extant paradigms in the literature. This framework yields new models of “best” estimates and perceived conflict. The paper concludes with specific suggestions for future research on judgment and decision making under conflict and ambiguity. PMID:26042081

Probability judgments under ambiguity and conflict.

PubMed

Smithson, Michael

2015-01-01

Whether conflict and ambiguity are distinct kinds of uncertainty remains an open question, as does their joint impact on judgments of overall uncertainty. This paper reviews recent advances in our understanding of human judgment and decision making when both ambiguity and conflict are present, and presents two types of testable models of judgments under conflict and ambiguity. The first type concerns estimate-pooling to arrive at "best" probability estimates. The second type is models of subjective assessments of conflict and ambiguity. These models are developed for dealing with both described and experienced information. A framework for testing these models in the described-information setting is presented, including a reanalysis of a multi-nation data-set to test best-estimate models, and a study of participants' assessments of conflict, ambiguity, and overall uncertainty reported by Smithson (2013). A framework for research in the experienced-information setting is then developed, that differs substantially from extant paradigms in the literature. This framework yields new models of "best" estimates and perceived conflict. The paper concludes with specific suggestions for future research on judgment and decision making under conflict and ambiguity.

Eigenspace perturbations for uncertainty estimation of single-point turbulence closures

NASA Astrophysics Data System (ADS)

Iaccarino, Gianluca; Mishra, Aashwin Ananda; Ghili, Saman

2017-02-01

Reynolds-averaged Navier-Stokes (RANS) models represent the workhorse for predicting turbulent flows in complex industrial applications. However, RANS closures introduce a significant degree of epistemic uncertainty in predictions due to the potential lack of validity of the assumptions utilized in model formulation. Estimating this uncertainty is a fundamental requirement for building confidence in such predictions. We outline a methodology to estimate this structural uncertainty, incorporating perturbations to the eigenvalues and the eigenvectors of the modeled Reynolds stress tensor. The mathematical foundations of this framework are derived and explicated. Thence, this framework is applied to a set of separated turbulent flows, while compared to numerical and experimental data and contrasted against the predictions of the eigenvalue-only perturbation methodology. It is exhibited that for separated flows, this framework is able to yield significant enhancement over the established eigenvalue perturbation methodology in explaining the discrepancy against experimental observations and high-fidelity simulations. Furthermore, uncertainty bounds of potential engineering utility can be estimated by performing five specific RANS simulations, reducing the computational expenditure on such an exercise.

Sensor Data Fusion for Body State Estimation in a Bipedal Robot and Its Feedback Control Application for Stable Walking

PubMed Central

Chen, Ching-Pei; Chen, Jing-Yi; Huang, Chun-Kai; Lu, Jau-Ching; Lin, Pei-Chun

2015-01-01

We report on a sensor data fusion algorithm via an extended Kalman filter for estimating the spatial motion of a bipedal robot. Through fusing the sensory information from joint encoders, a 6-axis inertial measurement unit and a 2-axis inclinometer, the robot’s body state at a specific fixed position can be yielded. This position is also equal to the CoM when the robot is in the standing posture suggested by the detailed CAD model of the robot. In addition, this body state is further utilized to provide sensory information for feedback control on a bipedal robot with walking gait. The overall control strategy includes the proposed body state estimator as well as the damping controller, which regulates the body position state of the robot in real-time based on instant and historical position tracking errors. Moreover, a posture corrector for reducing unwanted torque during motion is addressed. The body state estimator and the feedback control structure are implemented in a child-size bipedal robot and the performance is experimentally evaluated. PMID:25734644

Compartmental analysis of [11C]flumazenil kinetics for the estimation of ligand transport rate and receptor distribution using positron emission tomography.

PubMed

Koeppe, R A; Holthoff, V A; Frey, K A; Kilbourn, M R; Kuhl, D E

1991-09-01

The in vivo kinetic behavior of [11C]flumazenil ([11C]FMZ), a non-subtype-specific central benzodiazepine antagonist, is characterized using compartmental analysis with the aim of producing an optimized data acquisition protocol and tracer kinetic model configuration for the assessment of [11C]FMZ binding to benzodiazepine receptors (BZRs) in human brain. The approach presented is simple, requiring only a single radioligand injection. Dynamic positron emission tomography data were acquired on 18 normal volunteers using a 60- to 90-min sequence of scans and were analyzed with model configurations that included a three-compartment, four-parameter model, a three-compartment, three-parameter model, with a fixed value for free plus nonspecific binding; and a two-compartment, two-parameter model. Statistical analysis indicated that a four-parameter model did not yield significantly better fits than a three-parameter model. Goodness of fit was improved for three- versus two-parameter configurations in regions with low receptor density, but not in regions with moderate to high receptor density. Thus, a two-compartment, two-parameter configuration was found to adequately describe the kinetic behavior of [11C]FMZ in human brain, with stable estimates of the model parameters obtainable from as little as 20-30 min of data. Pixel-by-pixel analysis yields functional images of transport rate (K1) and ligand distribution volume (DV"), and thus provides independent estimates of ligand delivery and BZR binding.

Adoption of an unmanned helicopter for low-altitude remote sensing to estimate yield and total biomass of a rice crop

USDA-ARS?s Scientific Manuscript database

A radio-controlled unmanned helicopter-based LARS (Low-Altitude Remote Sensing) platform was used to acquire quality images of high spatial and temporal resolution, in order to estimate yield and total biomass of a rice crop (Oriza Sativa, L.). Fifteen rice field plots with five N-treatments (0, 33,...

Flumes, historic water yield and climatological data for Tenderfoot Creek Experimental Forest, Montana

Treesearch

Phillip E. Farnes; Ward W. McCaughey; Katherine J. Hansen

1999-01-01

The objectives of this Research Joint Venture Agreement (RJVA) were to install and calibrate three flumes on Tenderfoot Creek Experimental Forest (TCEF) in central Montana; check calibration of the existing seven flumes on TCEF; estimate the influence of fire on water yields over the 400-year fire history period; and estimate back records of monthly temperature,...

Estimating yellow-poplar growth and yield

Treesearch

Donald E. Beck

1989-01-01

Yellow-poplar grows in essentially pure, even-aged stands, so you can make growth and yield estimates from relatively few stand characteristics. The tables and models described here require only measures of stand age, stand basal area in trees 4.5 inches and larger, and site index. They were developed by remeasuring (at 5-year intervals over a 20-year period) many...

Estimates of Sputter Yields of Solar-Wind Heavy Ions of Lunar Regolith Materials

NASA Technical Reports Server (NTRS)

Barghouty, Abdulmasser F.; Adams, James H., Jr.

2008-01-01

At energies of approximately 1 keV/amu, solar-wind protons and heavy ions interact with the lunar surface materials via a number of microscopic interactions that include sputtering. Solar-wind induced sputtering is a main mechanism by which the composition of the topmost layers of the lunar surface can change, dynamically and preferentially. This work concentrates on sputtering induced by solar-wind heavy ions. Sputtering associated with slow (speeds the electrons speed in its first Bohr orbit) and highly charged ions are known to include both kinetic and potential sputtering. Potential sputtering enjoys some unique characteristics that makes it of special interest to lunar science and exploration. Unlike the yield from kinetic sputtering where simulation and approximation schemes exist, the yield from potential sputtering is not as easy to estimate. This work will present a preliminary numerical scheme designed to estimate potential sputtering yields from reactions relevant to this aspect of solar-wind lunar-surface coupling.

Modeling an alkaline electrolysis cell through reduced-order and loss-estimate approaches

NASA Astrophysics Data System (ADS)

Milewski, Jaroslaw; Guandalini, Giulio; Campanari, Stefano

2014-12-01

The paper presents two approaches to the mathematical modeling of an Alkaline Electrolyzer Cell. The presented models were compared and validated against available experimental results taken from a laboratory test and against literature data. The first modeling approach is based on the analysis of estimated losses due to the different phenomena occurring inside the electrolytic cell, and requires careful calibration of several specific parameters (e.g. those related to the electrochemical behavior of the electrodes) some of which could be hard to define. An alternative approach is based on a reduced-order equivalent circuit, resulting in only two fitting parameters (electrodes specific resistance and parasitic losses) and calculation of the internal electric resistance of the electrolyte. Both models yield satisfactory results with an average error limited below 3% vs. the considered experimental data and show the capability to describe with sufficient accuracy the different operating conditions of the electrolyzer; the reduced-order model could be preferred thanks to its simplicity for implementation within plant simulation tools dealing with complex systems, such as electrolyzers coupled with storage facilities and intermittent renewable energy sources.

Quantifying variety-specific heat resistance and the potential for adaptation to climate change.

PubMed

Tack, Jesse; Barkley, Andrew; Rife, Trevor W; Poland, Jesse A; Nalley, Lawton Lanier

2016-08-01

The impact of climate change on crop yields has become widely measured; however, the linkages for winter wheat are less studied due to dramatic weather changes during the long growing season that are difficult to model. Recent research suggests significant reductions under warming. A potential adaptation strategy involves the development of heat resistant varieties by breeders, combined with alternative variety selection by producers. However, the impact of heat on specific wheat varieties remains relatively unstudied due to limited data and the complex genetic basis of heat tolerance. Here, we provide a novel econometric approach that combines field-trial data with a genetic cluster mapping to group wheat varieties and estimate a separate extreme heat impact (temperatures over 34 °C) across 24 clusters spanning 197 varieties. We find a wide range of heterogeneous heat resistance and a trade-off between average yield and resistance. Results suggest that recently released varieties are less heat resistant than older varieties, a pattern that also holds for on-farm varieties. Currently released - but not yet adopted - varieties do not offer improved resistance relative to varieties currently grown on farm. Our findings suggest that warming impacts could be significantly reduced through advances in wheat breeding and/or adoption decisions by producers. However, current adaptation-through-adoption potential is limited under a 1 °C warming scenario as increased heat resistance cannot be achieved without a reduction in average yields. © 2015 John Wiley & Sons Ltd.

Spectral considerations for modeling yield of canola

USDA-ARS?s Scientific Manuscript database

Conspicuous yellow flowers that are present in a Brassica oilseed crop such as canola require careful consideration when selecting a spectral index for yield estimation. This study evaluated spectral indices for multispectral sensors that correlate with the seed yield of Brassica oilseed crops. A ...

Growth models for ponderosa pine: I. Yield of unthinned plantations in northern California.

Treesearch

William W. Oliver; Robert F. Powers

1978-01-01

Yields for high-survival, unthinned ponderosa pine (Pinus ponderosa Laws.) plantations in northern California are estimated. Stems of 367 trees in 12 plantations were analyzed to produce a growth model simulating stand yields. Diameter, basal area, and net cubic volume yields by Site Indices50 40 through 120 are tabulated for...

Estimating tar and nicotine exposure: human smoking versus machine generated smoke yields.

PubMed

St Charles, F K; Kabbani, A A; Borgerding, M F

2010-02-01

Determine human smoked (HS) cigarette yields of tar and nicotine for smokers using their own brand in their everyday environment. A robust, filter analysis method was used to estimate the tar and nicotine yields for 784 subjects. Seventeen brands were chosen to represent a wide range of styles: 85 and 100 mm lengths; menthol and non-menthol; 17, 23, and 25 mm circumference; with tar yields [Federal Trade Commission (FTC) method] ranging from 1 to 18 mg. Tar bands chosen corresponded to yields of 1-3 mg, 4-6 mg, 7-12 mg, and 13+ mg. A significant difference (p<0.0001) in HS yields of tar and nicotine between tar bands was found. Machine-smoked yields were reasonable predictors of the HS yields for groups of subjects, but the relationship was neither exact nor linear. Neither the FTC, the Massachusetts (MA) nor the Canadian Intensive (CI) machine-smoking methods accurately reflect the HS yields across all brands. The FTC method was closest for the 7-12 mg and 13+ mg products and the MA method was closest for the 1-3mg products. The HS yields for the 4-6 mg products were approximately midway between the FTC and the MA yields. HS nicotine yields corresponded well with published urinary and plasma nicotine biomarker studies. 2009 Elsevier Inc. All rights reserved.

A Quantitative Method to Identify Lithology Beneath Cover

NASA Astrophysics Data System (ADS)

Gettings, M. E.

2008-12-01

Geophysical terranes (map areas of similar potential field data response) can be used in the estimation of geological map units beneath cover (bedrock, alluvium, or tectonic block). Potential field data over nearby bedrock terranes defines "candidate terranes". Geophysical anomaly dimensions, shapes, amplitudes, trends/structural grain, and fractal measures yield a vector of measures characterizing the terrane. To compare candidate terranes fields with those for covered areas, the effect of depth of cover must be taken into account. Gravity anomaly data yields depth estimates by which the aeromagnetic data of candidate terranes are then upward continued. Comparison of characteristics of the upward continued fields from the candidate terranes to those of covered areas rank the candidates. Because of signal loss in upward continuation and overlap of physical properties, the vectors of measures for the candidate terranes are usually not unique. Possibility theory offers a relatively objective and robust method that can be used to rank terrane types that includes uncertainty. The strategy is to prepare membership functions for each measure of each candidate terrane and the covered area, based on observed values and degree of knowledge, and then form the fuzzy-logical combination of these to estimate the possibility and its uncertainty for each candidate terrane. Membership functions include uncertainty by the degree of membership for various possibility values. With no other information, uncertainty is based on information content from survey specifications and geologic features dimensions. Geologic data can also be included, such as structural trends, proximity, and tectonic history. Little knowledge implies wide membership functions; perfect knowledge, a delta function. This and the combination rules in fuzzy logic yield a robust estimation method. An uncertain membership function of a characteristic contributes much less to the possibility than a precise one. The final result for each covered area is a ranked possibility function for each candidate terrane as the underlying bedrock of the covered area that honors the aeromagnetic field and the geologic constraints that have been included. An example of the application of this method is presented for an area in south central Arizona.

Economic Cost and Burden of Dengue in the Philippines

PubMed Central

Edillo, Frances E.; Halasa, Yara A.; Largo, Francisco M.; Erasmo, Jonathan Neil V.; Amoin, Naomi B.; Alera, Maria Theresa P.; Yoon, In-Kyu; Alcantara, Arturo C.; Shepard, Donald S.

2015-01-01

Dengue, the world's most important mosquito-borne viral disease, is endemic in the Philippines. During 2008–2012, the country's Department of Health reported an annual average of 117,065 dengue cases, placing the country fourth in dengue burden in southeast Asia. This study estimates the country's annual number of dengue episodes and their economic cost. Our comparison of cases between active and passive surveillance in Punta Princesa, Cebu City yielded an expansion factor of 7.2, close to the predicted value (7.0) based on the country's health system. We estimated an annual average of 842,867 clinically diagnosed dengue cases, with direct medical costs (in 2012 US dollars) of $345 million ($3.26 per capita). This is 54% higher than an earlier estimate without Philippines-specific costs. Ambulatory settings treated 35% of cases (representing 10% of direct costs), whereas inpatient hospitals served 65% of cases (representing 90% of direct costs). The economic burden of dengue in the Philippines is substantial. PMID:25510723

Economic cost and burden of dengue in the Philippines.

PubMed

Edillo, Frances E; Halasa, Yara A; Largo, Francisco M; Erasmo, Jonathan Neil V; Amoin, Naomi B; Alera, Maria Theresa P; Yoon, In-Kyu; Alcantara, Arturo C; Shepard, Donald S

2015-02-01

Dengue, the world's most important mosquito-borne viral disease, is endemic in the Philippines. During 2008-2012, the country's Department of Health reported an annual average of 117,065 dengue cases, placing the country fourth in dengue burden in southeast Asia. This study estimates the country's annual number of dengue episodes and their economic cost. Our comparison of cases between active and passive surveillance in Punta Princesa, Cebu City yielded an expansion factor of 7.2, close to the predicted value (7.0) based on the country's health system. We estimated an annual average of 842,867 clinically diagnosed dengue cases, with direct medical costs (in 2012 US dollars) of $345 million ($3.26 per capita). This is 54% higher than an earlier estimate without Philippines-specific costs. Ambulatory settings treated 35% of cases (representing 10% of direct costs), whereas inpatient hospitals served 65% of cases (representing 90% of direct costs). The economic burden of dengue in the Philippines is substantial. © The American Society of Tropical Medicine and Hygiene.

Improvements in aircraft extraction programs

NASA Technical Reports Server (NTRS)

Balakrishnan, A. V.; Maine, R. E.

1976-01-01

Flight data from an F-8 Corsair and a Cessna 172 was analyzed to demonstrate specific improvements in the LRC parameter extraction computer program. The Cramer-Rao bounds were shown to provide a satisfactory relative measure of goodness of parameter estimates. It was not used as an absolute measure due to an inherent uncertainty within a multiplicative factor, traced in turn to the uncertainty in the noise bandwidth in the statistical theory of parameter estimation. The measure was also derived on an entirely nonstatistical basis, yielding thereby also an interpretation of the significance of off-diagonal terms in the dispersion matrix. The distinction between coefficients as linear and non-linear was shown to be important in its implication to a recommended order of parameter iteration. Techniques of improving convergence generally, were developed, and tested out on flight data. In particular, an easily implemented modification incorporating a gradient search was shown to improve initial estimates and thus remove a common cause for lack of convergence.

Fine-Scale Population Estimation by 3D Reconstruction of Urban Residential Buildings

PubMed Central

Wang, Shixin; Tian, Ye; Zhou, Yi; Liu, Wenliang; Lin, Chenxi

2016-01-01

Fine-scale population estimation is essential in emergency response and epidemiological applications as well as urban planning and management. However, representing populations in heterogeneous urban regions with a finer resolution is a challenge. This study aims to obtain fine-scale population distribution based on 3D reconstruction of urban residential buildings with morphological operations using optical high-resolution (HR) images from the Chinese No. 3 Resources Satellite (ZY-3). Specifically, the research area was first divided into three categories when dasymetric mapping was taken into consideration. The results demonstrate that the morphological building index (MBI) yielded better results than built-up presence index (PanTex) in building detection, and the morphological shadow index (MSI) outperformed color invariant indices (CIIT) in shadow extraction and height retrieval. Building extraction and height retrieval were then combined to reconstruct 3D models and to estimate population. Final results show that this approach is effective in fine-scale population estimation, with a mean relative error of 16.46% and an overall Relative Total Absolute Error (RATE) of 0.158. This study gives significant insights into fine-scale population estimation in complicated urban landscapes, when detailed 3D information of buildings is unavailable. PMID:27775670

Model-data integration for developing the Cropland Carbon Monitoring System (CCMS)

NASA Astrophysics Data System (ADS)

Jones, C. D.; Bandaru, V.; Pnvr, K.; Jin, H.; Reddy, A.; Sahajpal, R.; Sedano, F.; Skakun, S.; Wagle, P.; Gowda, P. H.; Hurtt, G. C.; Izaurralde, R. C.

2017-12-01

The Cropland Carbon Monitoring System (CCMS) has been initiated to improve regional estimates of carbon fluxes from croplands in the conterminous United States through integration of terrestrial ecosystem modeling, use of remote-sensing products and publically available datasets, and development of improved landscape and management databases. In order to develop these improved carbon flux estimates, experimental datasets are essential for evaluating the skill of estimates, characterizing the uncertainty of these estimates, characterizing parameter sensitivities, and calibrating specific modeling components. Experiments were sought that included flux tower measurement of CO2 fluxes under production of major agronomic crops. Currently data has been collected from 17 experiments comprising 117 site-years from 12 unique locations. Calibration of terrestrial ecosystem model parameters using available crop productivity and net ecosystem exchange (NEE) measurements resulted in improvements in RMSE of NEE predictions of between 3.78% to 7.67%, while improvements in RMSE for yield ranged from -1.85% to 14.79%. Model sensitivities were dominated by parameters related to leaf area index (LAI) and spring growth, demonstrating considerable capacity for model improvement through development and integration of remote-sensing products. Subsequent analyses will assess the impact of such integrated approaches on skill of cropland carbon flux estimates.

Pit-1 gene polymorphism, milk yield, and conformation traits for Italian Holstein-Friesian bulls.

PubMed

Renaville, R; Gengler, N; Vrech, E; Prandi, A; Massart, S; Corradini, C; Bertozzi, C; Mortiaux, F; Burny, A; Portetelle, D

1997-12-01

The growth hormone factor-1/pituitary-specific transcription factor Pit-1 is responsible for the expression of growth hormone in mammals. Mutations in Pit-1 have been found in growth hormone disorders of mice and humans. We studied the eventual association between Pit-1 polymorphism using the HinfI enzyme and the milk yield and conformation traits of 89 Italian Holstein-Friesian bulls. A strategy employing polymerase chain reaction was used to amplify a 451-bp fragment from semen DNA. Digestion of polymerase chain reaction products with HinfI revealed two alleles: allele A was not digested (451-bp fragment), and allele B was cut at one restriction site, generating two fragments of 244 and 207 bp. Three patterns were observed; frequencies were 2.2, 31.5, and 66.3% for AA, AB, and BB, respectively. Fixed and mixed linear models were fitted on daughter yield deviations for milk yields and on deregressed proofs for conformation traits. Predictions were weighted using the inverse of the estimated variance of records. The models used contained mean and gene substitution effects for Pit-1 A allele as fixed effects and random sire effect for the mixed model. The A allele was found to be superior for milk and protein yields, inferior for fat percentage, and superior for body depth, angularity, and rear leg set, which is difficult to explain. A canonical transformation revealed that Pit-1 had three actions, one linked to milk yield traits and angularity, a second linked to body depth and rear leg set, and a third linked to lower fat yields and to higher angularity.

Estimation of total nitrogen and total phosphorus in streams of the Middle Columbia River Basin (Oregon, Washington, and Idaho) using SPARROW models, with emphasis on the Yakima River Basin, Washington

USGS Publications Warehouse

Johnson, Henry M.; Black, Robert W.; Wise, Daniel R.

2013-01-01

The watershed model SPARROW (Spatially Related Regressions on Watershed attributes) was used to predict total nitrogen (TN) and total phosphorus (TP) loads and yields for the Middle Columbia River Basin in Idaho, Oregon, and Washington. The new models build on recently published models for the entire Pacific Northwest, and provide revised load predictions for the arid interior of the region by restricting the modeling domain and recalibrating the models. Results from the new TN and TP models are provided for the entire region, and discussed with special emphasis on the Yakima River Basin, Washington. In most catchments of the Yakima River Basin, the TN and TP in streams is from natural sources, specifically nitrogen fixation in forests (TN) and weathering and erosion of geologic materials (TP). The natural nutrient sources are overshadowed by anthropogenic sources of TN and TP in highly agricultural and urbanized catchments; downstream of the city of Yakima, most of the load in the Yakima River is derived from anthropogenic sources. Yields of TN and TP from catchments with nearly uniform land use were compared with other yield values and export coefficients published in the scientific literature, and generally were in agreement. The median yield of TN was greatest in catchments dominated by agricultural land and smallest in catchments dominated by grass and scrub land. The median yield of TP was greatest in catchments dominated by forest land, but the largest yields (90th percentile) of TP were from agricultural catchments. As with TN, the smallest TP yields were from catchments dominated by grass and scrub land.

The effects of climate change on instream nitrogen transport in the contiguous United States

NASA Astrophysics Data System (ADS)

Alam, M. J.; Goodall, J. L.

2011-12-01

Excessive nitrogen loading has caused significant environmental impacts such as eutrophication and hypoxia in waterbodies around the world. Nitrogen loading is largely dependent on nonpoint source pollution and nitrogen transport from nonpoint source pollution is greatly impacted by climate conditions. For example, increased precipitation leads to more runoff and a higher nitrogen yield. However, higher temperatures also impact nitrogen transport in that higher temperatures increase denitrification and therefore reduce nitrogen yield. The purpose of this research is to quantify potential changes in nitrogen yield for the contiguous United States under predicted climate change scenarios, specifically changes in precipitation and air temperature. The analysis was performed for high (A2) and low (B1) emission scenarios and for the year 2030, 2050 and 2090. We used 11 different IPCC (The Intergovernmental Panel on Climate Change) models predicted precipitation and temperature estimates to capture uncertainty. The SPARROW model was calibrated using historical nitrogen loading data and used to predict nitrogen yields for future climate conditions. We held nitrogen source data constant in order to isolate the impact of predicted precipitation and temperature changes for each model scenario. Preliminary results suggest an overall decrease in nitrogen yield if climate change impacts are considered in isolation. For the A2 scenario, the model results indicated an overall incremental nitrogen yield decrease of 2-17% by the year 2030, 4-26% by the year 2050, and 11-45% by the year 2090. The B1 emission scenario also indicated an incremental yield decrease, but at lesser amounts of 2-18%, 5-21% and 10-38% by the years 2030, 2050, and 2090, respectively. This decrease is mainly due to higher predicted temperatures that result in increased denitrification rates.

High Temperature Chemistry in the Columbia Accident Investigation

NASA Technical Reports Server (NTRS)

Jacobson, Nathan; Opila, Elizabeth; Tallant, David; Simpson, Regina

2004-01-01

Initial estimates on the temperature and conditions of the breach in Columbia's wing focused on analyses of the slag deposits. These deposits are complex mixtures of the reinforced carbon/carbon (RCC) constituents, insulation material, and wing structural materials. However it was possible to clearly discern melted/solidified Cerachrome(R) insulation, indicating the temperatures had exceeded 1760 C. Current research focuses on the carbon/carbon in the path from the breach. Carbon morphology indicates heavy oxidation and erosion. Raman spectroscopy yielded further temperature estimates. A technique developed at Sandia National Laboratories is based on crystallite size in carbon chars. Lower temperatures yield nanocrystalline graphite; whereas higher temperatures yield larger graphite crystals. By comparison to standards the temperatures on the recovered RCC fragments were estimated to have been greater than 2700 C.

A photometric method for the estimation of the oil yield of oil shale

USGS Publications Warehouse

Cuttitta, Frank

1951-01-01

A method is presented for the distillation and photometric estimation of the oil yield of oil-bearing shales. The oil shale is distilled in a closed test tube and the oil extracted with toluene. The optical density of the toluene extract is used in the estimation of oil content and is converted to percentage of oil by reference to a standard curve. This curve is obtained by relating the oil yields determined by the Fischer assay method to the optical density of the toluene extract of the oil evolved by the new procedure. The new method gives results similar to those obtained by the Fischer assay method in a much shorter time. The applicability of the new method to oil-bearing shale and phosphatic shale has been tested.

EnviroAtlas - Cultivated biological nitrogen fixation in agricultural lands by 12-digit HUC in the Conterminous United States, 2006

EPA Pesticide Factsheets

This EnviroAtlas dataset contains data on the mean cultivated biological nitrogen fixation (C-BNF) in cultivated crop and hay/pasture lands per 12-digit Hydrologic Unit (HUC) in 2006. Nitrogen (N) inputs from the cultivation of legumes, which possess a symbiotic relationship with N-fixing bacteria, were calculated with a recently developed model relating county-level yields of various leguminous crops with BNF rates. We accessed county-level data on annual crop yields for soybeans (Glycine max L.), alfalfa (Medicago sativa L.), peanuts (Arachis hypogaea L.), various dry beans (Phaseolus, Cicer, and Lens spp.), and dry peas (Pisum spp.) for 2006 from the USDA Census of Agriculture (http://www.agcensus.usda.gov/index.php). We estimated the yield of the non-alfalfa leguminous component of hay as 32% of the yield of total non-alfalfa hay (http://www.agcensus.usda.gov/index.php). Annual rates of C-BNF by crop type were calculated using a model that relates yield to C-BNF. We assume yield data reflect differences in soil properties, water availability, temperature, and other local and regional factors that can influence root nodulation and rate of N fixation. We distributed county-specific, C-BNF rates to cultivated crop and hay/pasture lands delineated in the 2006 National Land Cover Database (30 x 30 m pixels) within the corresponding county. C-BNF data described here represent an average input to a typical agricultural land type within a county, i.e., they are not