Sample records for yield estimation system

  1. Estimating yield gaps at the cropping system level.

    PubMed

    Guilpart, Nicolas; Grassini, Patricio; Sadras, Victor O; Timsina, Jagadish; Cassman, Kenneth G

    2017-05-01

    Yield gap analyses of individual crops have been used to estimate opportunities for increasing crop production at local to global scales, thus providing information crucial to food security. However, increases in crop production can also be achieved by improving cropping system yield through modification of spatial and temporal arrangement of individual crops. In this paper we define the cropping system yield potential as the output from the combination of crops that gives the highest energy yield per unit of land and time, and the cropping system yield gap as the difference between actual energy yield of an existing cropping system and the cropping system yield potential. Then, we provide a framework to identify alternative cropping systems which can be evaluated against the current ones. A proof-of-concept is provided with irrigated rice-maize systems at four locations in Bangladesh that represent a range of climatic conditions in that country. The proposed framework identified (i) realistic alternative cropping systems at each location, and (ii) two locations where expected improvements in crop production from changes in cropping intensity (number of crops per year) were 43% to 64% higher than from improving the management of individual crops within the current cropping systems. The proposed framework provides a tool to help assess food production capacity of new systems ( e.g. with increased cropping intensity) arising from climate change, and assess resource requirements (water and N) and associated environmental footprint per unit of land and production of these new systems. By expanding yield gap analysis from individual crops to the cropping system level and applying it to new systems, this framework could also be helpful to bridge the gap between yield gap analysis and cropping/farming system design.

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. 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

    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.

  9. 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

  10. 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...

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. Estimating the potential intensification of global grazing systems based on climate adjusted yield gap analysis

    NASA Astrophysics Data System (ADS)

    Sheehan, J. J.

    2016-12-01

    We report here a first-of-its-kind analysis of the potential for intensification of global grazing systems. Intensification is calculated using the statistical yield gap methodology developed previously by others (Mueller et al 2012 and Licker et al 2010) for global crop systems. Yield gaps are estimated by binning global pasture land area into 100 equal area sized bins of similar climate (defined by ranges of rainfall and growing degree days). Within each bin, grid cells of pastureland are ranked from lowest to highest productivity. The global intensification potential is defined as the sum of global production across all bins at a given percentile ranking (e.g. performance at the 90th percentile) divided by the total current global production. The previous yield gap studies focused on crop systems because productivity data on these systems is readily available. Nevertheless, global crop land represents only one-third of total global agricultural land, while pasture systems account for the remaining two-thirds. Thus, it is critical to conduct the same kind of analysis on what is the largest human use of land on the planet—pasture systems. In 2013, Herrero et al announced the completion of a geospatial data set that augmented the animal census data with data and modeling about production systems and overall food productivity (Herrero et al, PNAS 2013). With this data set, it is now possible to apply yield gap analysis to global pasture systems. We used the Herrero et al data set to evaluate yield gaps for meat and milk production from pasture based systems for cattle, sheep and goats. The figure included with this abstract shows the intensification potential for kcal per hectare per year of meat and milk from global cattle, sheep and goats as a function of increasing levels of performance. Performance is measured as the productivity achieved at a given ranked percentile within each bin.We find that if all pasture land were raised to their 90th percentile of

  16. 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...

  17. 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.

  18. 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...

  19. 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

  20. 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.

  1. 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) ...

  2. 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.

  3. EarthSat spring wheat yield system test 1975

    NASA Technical Reports Server (NTRS)

    1976-01-01

    The results of an operational test of the EarthSat System during the period 1 June - 30 August 1975 over the spring wheat regions of North Dakota, South Dakota, and Minnesota are presented. The errors associated with each sub-element of the system during the operational test and the sensitivity of the complete system and each major functional sub-element of the system to the observed errors were evaluated. Evaluations and recommendations for future operational users of the system include: (1) changes in various system sub-elements, (2) changes in the yield model to affect improved accuracy, (3) changes in the number of geobased cells needed to develop an accurate aggregated yield estimate, (4) changes associated with the implementation of future operational satellites and data processing systems, and (5) detailed system documentation.

  4. 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...

  5. 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.

  6. 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.

  7. 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%.

  8. 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...

  9. Estimating national crop yield potential and the relevance of weather data sources

    NASA Astrophysics Data System (ADS)

    Van Wart, Justin

    2011-12-01

    To determine where, when, and how to increase yields, researchers often analyze the yield gap (Yg), the difference between actual current farm yields and crop yield potential. Crop yield potential (Yp) is the yield of a crop cultivar grown under specific management limited only by temperature and solar radiation and also by precipitation for water limited yield potential (Yw). Yp and Yw are critical components of Yg estimations, but are very difficult to quantify, especially at larger scales because management data and especially daily weather data are scarce. A protocol was developed to estimate Yp and Yw at national scales using site-specific weather, soils and management data. Protocol procedures and inputs were evaluated to determine how to improve accuracy of Yp, Yw and Yg estimates. The protocol was also used to evaluate raw, site-specific and gridded weather database sources for use in simulations of Yp or Yw. The protocol was applied to estimate crop Yp in US irrigated maize and Chinese irrigated rice and Yw in US rainfed maize and German rainfed wheat. These crops and countries account for >20% of global cereal production. The results have significant implications for past and future studies of Yp, Yw and Yg. Accuracy of national long-term average Yp and Yw estimates was significantly improved if (i) > 7 years of simulations were performed for irrigated and > 15 years for rainfed sites, (ii) > 40% of nationally harvested area was within 100 km of all simulation sites, (iii) observed weather data coupled with satellite derived solar radiation data were used in simulations, and (iv) planting and harvesting dates were specified within +/- 7 days of farmers actual practices. These are much higher standards than have been applied in national estimates of Yp and Yw and this protocol is a substantial step in making such estimates more transparent, robust, and straightforward. Finally, this protocol may be a useful tool for understanding yield trends and directing

  10. 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 %.

  11. 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.

  12. 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...

  13. 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 ...

  14. 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

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. Refinement and evaluation of the Massachusetts firm-yield estimator model version 2.0

    USGS Publications Warehouse

    Levin, Sara B.; Archfield, Stacey A.; Massey, Andrew J.

    2011-01-01

    The firm yield is the maximum average daily withdrawal that can be extracted from a reservoir without risk of failure during an extended drought period. Previously developed procedures for determining the firm yield of a reservoir were refined and applied to 38 reservoir systems in Massachusetts, including 25 single- and multiple-reservoir systems that were examined during previous studies and 13 additional reservoir systems. Changes to the firm-yield model include refinements to the simulation methods and input data, as well as the addition of several scenario-testing capabilities. The simulation procedure was adapted to run at a daily time step over a 44-year simulation period, and daily streamflow and meteorological data were compiled for all the reservoirs for input to the model. Another change to the model-simulation methods is the adjustment of the scaling factor used in estimating groundwater contributions to the reservoir. The scaling factor is used to convert the daily groundwater-flow rate into a volume by multiplying the rate by the length of reservoir shoreline that is hydrologically connected to the aquifer. Previous firm-yield analyses used a constant scaling factor that was estimated from the reservoir surface area at full pool. The use of a constant scaling factor caused groundwater flows during periods when the reservoir stage was very low to be overestimated. The constant groundwater scaling factor used in previous analyses was replaced with a variable scaling factor that is based on daily reservoir stage. This change reduced instability in the groundwater-flow algorithms and produced more realistic groundwater-flow contributions during periods of low storage. Uncertainty in the firm-yield model arises from many sources, including errors in input data. The sensitivity of the model to uncertainty in streamflow input data and uncertainty in the stage-storage relation was examined. A series of Monte Carlo simulations were performed on 22 reservoirs

  1. 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.

  2. 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...

  3. Exoplanet Yield Estimation for Decadal Study Concepts using EXOSIMS

    NASA Astrophysics Data System (ADS)

    Morgan, Rhonda; Lowrance, Patrick; Savransky, Dmitry; Garrett, Daniel

    2016-01-01

    The anticipated upcoming large mission study concepts for the direct imaging of exo-earths present an exciting opportunity for exoplanet discovery and characterization. While these telescope concepts would also be capable of conducting a broad range of astrophysical investigations, the most difficult technology challenges are driven by the requirements for imaging exo-earths. The exoplanet science yield for these mission concepts will drive design trades and mission concept comparisons.To assist in these trade studies, the Exoplanet Exploration Program Office (ExEP) is developing a yield estimation tool that emphasizes transparency and consistent comparison of various design concepts. The tool will provide a parametric estimate of science yield of various mission concepts using contrast curves from physics-based model codes and Monte Carlo simulations of design reference missions using realistic constraints, such as solar avoidance angles, the observatory orbit, propulsion limitations of star shades, the accessibility of candidate targets, local and background zodiacal light levels, and background confusion by stars and galaxies. The python tool utilizes Dmitry Savransky's EXOSIMS (Exoplanet Open-Source Imaging Mission Simulator) design reference mission simulator that is being developed for the WFIRST Preliminary Science program. ExEP is extending and validating the tool for future mission concepts under consideration for the upcoming 2020 decadal review. We present a validation plan and preliminary yield results for a point design.

  4. 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 ...

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. Estimating rice yield from MODIS-Landsat fusion data in Taiwan

    NASA Astrophysics Data System (ADS)

    Chen, C. R.; Chen, C. F.; Nguyen, S. T.

    2017-12-01

    Rice production monitoring with remote sensing is an important activity in Taiwan due to official initiatives. Yield estimation is a challenge in Taiwan because rice fields are small and fragmental. High spatiotemporal satellite data providing phenological information of rice crops is thus required for this monitoring purpose. This research aims to develop data fusion approaches to integrate daily Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat data for rice yield estimation in Taiwan. In this study, the low-resolution MODIS LST and emissivity data are used as reference data sources to obtain the high-resolution LST from Landsat data using the mixed-pixel analysis technique, and the time-series EVI data were derived the fusion of MODIS and Landsat spectral band data using STARFM method. The LST and EVI simulated results showed the close agreement between the LST and EVI obtained by the proposed methods with the reference data. The rice-yield model was established using EVI and LST data based on information of rice crop phenology collected from 371 ground survey sites across the country in 2014. The results achieved from the fusion datasets compared with the reference data indicated the close relationship between the two datasets with the correlation coefficient (R2) of 0.75 and root mean square error (RMSE) of 338.7 kgs, which were more accurate than those using the coarse-resolution MODIS LST data (R2 = 0.71 and RMSE = 623.82 kgs). For the comparison of total production, 64 towns located in the west part of Taiwan were used. The results also confirmed that the model using fusion datasets produced more accurate results (R2 = 0.95 and RMSE = 1,243 tons) than that using the course-resolution MODIS data (R2 = 0.91 and RMSE = 1,749 tons). This study demonstrates the application of MODIS-Landsat fusion data for rice yield estimation at the township level in Taiwan. The results obtained from the methods used in this study could be useful to policymakers

  10. 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

  11. 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

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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

    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.

  18. 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.

  19. 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

  20. 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.

  1. 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...

  2. 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.; hide

    2016-01-01

    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.

  3. 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.

  4. Image Based Mango Fruit Detection, Localisation and Yield Estimation Using Multiple View Geometry

    PubMed Central

    Stein, Madeleine; Bargoti, Suchet; Underwood, James

    2016-01-01

    This paper presents a novel multi-sensor framework to efficiently identify, track, localise and map every piece of fruit in a commercial mango orchard. A multiple viewpoint approach is used to solve the problem of occlusion, thus avoiding the need for labour-intensive field calibration to estimate actual yield. Fruit are detected in images using a state-of-the-art faster R-CNN detector, and pair-wise correspondences are established between images using trajectory data provided by a navigation system. A novel LiDAR component automatically generates image masks for each canopy, allowing each fruit to be associated with the corresponding tree. The tracked fruit are triangulated to locate them in 3D, enabling a number of spatial statistics per tree, row or orchard block. A total of 522 trees and 71,609 mangoes were scanned on a Calypso mango orchard near Bundaberg, Queensland, Australia, with 16 trees counted by hand for validation, both on the tree and after harvest. The results show that single, dual and multi-view methods can all provide precise yield estimates, but only the proposed multi-view approach can do so without calibration, with an error rate of only 1.36% for individual trees. PMID:27854271

  5. 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.

  6. Visual tree grading systems for estimating lumber yields in young and mature southern pine

    Treesearch

    Alexander Clark; Robert H. McAlister

    1998-01-01

    New visual tree grading systems for mature southern pine ? 35 years old and young pine ? 35 years old based on number and size of branches in the lower bole are described. A series of lumber grade yield studies was conducted to test the new grading rules. A total of 214 natural loblolly pine (Pinus taeda L.) and shortleaf pine (P. echinata Mill) trees 9 to 20 inches...

  7. Soil Moisture as an Estimator for Crop Yield in Germany

    NASA Astrophysics Data System (ADS)

    Peichl, Michael; Meyer, Volker; Samaniego, Luis; Thober, Stephan

    2015-04-01

    Annual crop yield depends on various factors such as soil properties, management decisions, and meteorological conditions. Unfavorable weather conditions, e.g. droughts, have the potential to drastically diminish crop yield in rain-fed agriculture. For example, the drought in 2003 caused direct losses of 1.5 billion EUR only in Germany. Predicting crop yields allows to mitigate negative effects of weather extremes which are assumed to occur more often in the future due to climate change. A standard approach in economics is to predict the impact of climate change on agriculture as a function of temperature and precipitation. This approach has been developed further using concepts like growing degree days. Other econometric models use nonlinear functions of heat or vapor pressure deficit. However, none of these approaches uses soil moisture to predict crop yield. We hypothesize that soil moisture is a better indicator to explain stress on plant growth than estimations based on precipitation and temperature. This is the case because the latter variables do not explicitly account for the available water content in the root zone, which is the primary source of water supply for plant growth. In this study, a reduced form panel approach is applied to estimate a multivariate econometric production function for the years 1999 to 2010. Annual crop yield data of various crops on the administrative district level serve as depending variables. The explanatory variable of major interest is the Soil Moisture Index (SMI), which quantifies anomalies in root zone soil moisture. The SMI is computed by the mesoscale Hydrological Model (mHM, www.ufz.de/mhm). The index represents the monthly soil water quantile at a 4 km2 grid resolution covering entire Germany. A reduced model approach is suitable because the SMI is the result of a stochastic weather process and therefore can be considered exogenous. For the ease of interpretation a linear functionality is preferred. Meteorological

  8. 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

  9. Annual Corn Yield Estimation through Multi-temporal MODIS Data

    NASA Astrophysics Data System (ADS)

    Shao, Y.; Zheng, B.; Campbell, J. B.

    2013-12-01

    This research employed 13 years of the Moderate Resolution Imaging Spectroradiometer (MODIS) to estimate annual corn yield for the Midwest of the United States. The overall objective of this study was to examine if annual corn yield could be accurately predicted using MODIS time-series NDVI (Normalized Difference Vegetation Index) and ancillary data such monthly precipitation and temperature. MODIS-NDVI 16-Day composite images were acquired from the USGS EROS Data Center for calendar years 2000 to 2012. For the same time-period, county level corn yield statistics were obtained from the National Agricultural Statistics Service (NASS). The monthly precipitation and temperature measures were derived from Precipitation-Elevation Regressions on Independent Slopes Model (PRISM) climate data. A cropland mask was derived using 2006 National Land Cover Database. For each county and within the cropland mask, the MODIS-NDVI time-series data and PRISM climate data were spatially averaged, at their respective time steps. We developed a random forest predictive model with the MODIS-NDVI and climate data as predictors and corn yield as response. To assess the model accuracy, we used twelve years of data as training and the remaining year as hold-out testing set. The training and testing procedures were repeated 13 times. The R2 ranged from 0.72 to 0.83 for testing years. It was also found that the inclusion of climate data did not improve the model predictive performance. MODIS-NDVI time-series data alone might provide sufficient information for county level corn yield prediction.

  10. 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.

  11. An evaluation of the lamb vision system as a predictor of lamb carcass red meat yield percentage.

    PubMed

    Brady, A S; Belk, K E; LeValley, S B; Dalsted, N L; Scanga, J A; Tatum, J D; Smith, G C

    2003-06-01

    An objective method for predicting red meat yield in lamb carcasses is needed to accurately assess true carcass value. This study was performed to evaluate the ability of the lamb vision system (LVS; Research Management Systems USA, Fort Collins, CO) to predict fabrication yields of lamb carcasses. Lamb carcasses (n = 246) were evaluated using LVS and hot carcass weight (HCW), as well as by USDA expert and on-line graders, before fabrication of carcass sides to either bone-in or boneless cuts. On-line whole number, expert whole-number, and expert nearest-tenth USDA yield grades and LVS + HCW estimates accounted for 53, 52, 58, and 60%, respectively, of the observed variability in boneless, saleable meat yields, and accounted for 56, 57, 62, and 62%, respectively, of the variation in bone-in, saleable meat yields. The LVS + HCW system predicted 77, 65, 70, and 87% of the variation in weights of boneless shoulders, racks, loins, and legs, respectively, and 85, 72, 75, and 86% of the variation in weights of bone-in shoulders, racks, loins, and legs, respectively. Addition of longissimus muscle area (REA), adjusted fat thickness (AFT), or both REA and AFT to LVS + HCW models resulted in improved prediction of boneless saleable meat yields by 5, 3, and 5 percentage points, respectively. Bone-in, saleable meat yield estimations were improved in predictive accuracy by 7.7, 6.6, and 10.1 percentage points, and in precision, when REA alone, AFT alone, or both REA and AFT, respectively, were added to the LVS + HCW output models. Use of LVS + HCW to predict boneless red meat yields of lamb carcasses was more accurate than use of current on-line whole-number, expert whole-number, or expert nearest-tenth USDA yield grades. Thus, LVS + HCW output, when used alone or in combination with AFT and/or REA, improved on-line estimation of boneless cut yields from lamb carcasses. The ability of LVS + HCW to predict yields of wholesale cuts suggests that LVS could be used as an objective

  12. Seismic Yield Estimates of UTTR Surface Explosions

    NASA Astrophysics Data System (ADS)

    Hayward, C.; Park, J.; Stump, B. W.

    2016-12-01

    Since 2007 the Utah Test and Training Range (UTTR) has used explosive demolition as a method to destroy excess solid rocket motors ranging in size from 19 tons to less than 2 tons. From 2007 to 2014, 20 high quality seismic stations within 180 km recorded most of the more than 200 demolitions. This provides an interesting dataset to examine seismic source scaling for surface explosions. Based upon observer records, shots were of 4 sizes, corresponding to the size of the rocket motors. Instrument corrections for the stations were quality controlled by examining the P-wave amplitudes of all magnitude 6.5-8 earthquakes from 30 to 90 degrees away. For each station recording, the instrument corrected RMS seismic amplitude in the first 10 seconds after the P-onset was calculated. Waveforms at any given station for all the observed explosions are nearly identical. The observed RMS amplitudes were fit to a model including a term for combined distance and station correction, a term for observed RMS amplitude, and an error term for the actual demolition size. The observed seismic yield relationship is RMS=k*Weight2/3 . Estimated yields for the largest shots vary by about 50% from the stated weights, with a nearly normal distribution.

  13. 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.

  14. Estimating and validating harvesting system production through computer simulation

    Treesearch

    John E. Baumgras; Curt C. Hassler; Chris B. LeDoux

    1993-01-01

    A Ground Based Harvesting System Simulation model (GB-SIM) has been developed to estimate stump-to-truck production rates and multiproduct yields for conventional ground-based timber harvesting systems in Appalachian hardwood stands. Simulation results reflect inputs that define harvest site and timber stand attributes, wood utilization options, and key attributes of...

  15. 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.

  16. 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.

  17. 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.

  18. Estimating the potential refolding yield of recombinant proteins expressed as inclusion bodies.

    PubMed

    Ho, Jason G S; Middelberg, Anton P J

    2004-09-05

    Recombinant protein production in bacteria is efficient except that insoluble inclusion bodies form when some gene sequences are expressed. Such proteins must undergo renaturation, which is an inefficient process due to protein aggregation on dilution from concentrated denaturant. In this study, the protein-protein interactions of eight distinct inclusion-body proteins are quantified, in different solution conditions, by measurement of protein second virial coefficients (SVCs). Protein solubility is shown to decrease as the SVC is reduced (i.e., as protein interactions become more attractive). Plots of SVC versus denaturant concentration demonstrate two clear groupings of proteins: a more aggregative group and a group having higher SVC and better solubility. A correlation of the measured SVC with protein molecular weight and hydropathicity, that is able to predict which group each of the eight proteins falls into, is presented. The inclusion of additives known to inhibit aggregation during renaturation improves solubility and increases the SVC of both protein groups. Furthermore, an estimate of maximum refolding yield (or solubility) using high-performance liquid chromatography was obtained for each protein tested, under different environmental conditions, enabling a relationship between "yield" and SVC to be demonstrated. Combined, the results enable an approximate estimation of the maximum refolding yield that is attainable for each of the eight proteins examined, under a selected chemical environment. Although the correlations must be tested with a far larger set of protein sequences, this work represents a significant move beyond empirical approaches for optimizing renaturation conditions. The approach moves toward the ideal of predicting maximum refolding yield using simple bioinformatic metrics that can be estimated from the gene sequence. Such a capability could potentially "screen," in silico, those sequences suitable for expression in bacteria from those

  19. 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.

  20. 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

  1. Surprising yields with no-till cropping systems

    USDA-ARS?s Scientific Manuscript database

    Producers using no-till systems have found that crop yields often exceed their expectation based on nutrient and water supply. For example, corn yields 7% higher in a no-till system in central South Dakota than in a tilled system in eastern South Dakota. This is surprising because rainfall is 5 in...

  2. 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.

  3. Satellite-based assessment of yield variation and its determinants in smallholder African systems

    PubMed Central

    Lobell, David B.

    2017-01-01

    The emergence of satellite sensors that can routinely observe millions of individual smallholder farms raises possibilities for monitoring and understanding agricultural productivity in many regions of the world. Here we demonstrate the potential to track smallholder maize yield variation in western Kenya, using a combination of 1-m Terra Bella imagery and intensive field sampling on thousands of fields over 2 y. We find that agreement between satellite-based and traditional field survey-based yield estimates depends significantly on the quality of the field-based measures, with agreement highest (R2 up to 0.4) when using precise field measures of plot area and when using larger fields for which rounding errors are smaller. We further show that satellite-based measures are able to detect positive yield responses to fertilizer and hybrid seed inputs and that the inferred responses are statistically indistinguishable from estimates based on survey-based yields. These results suggest that high-resolution satellite imagery can be used to make predictions of smallholder agricultural productivity that are roughly as accurate as the survey-based measures traditionally used in research and policy applications, and they indicate a substantial near-term potential to quickly generate useful datasets on productivity in smallholder systems, even with minimal or no field training data. Such datasets could rapidly accelerate learning about which interventions in smallholder systems have the most positive impact, thus enabling more rapid transformation of rural livelihoods. PMID:28202728

  4. Satellite-based assessment of yield variation and its determinants in smallholder African systems.

    PubMed

    Burke, Marshall; Lobell, David B

    2017-02-28

    The emergence of satellite sensors that can routinely observe millions of individual smallholder farms raises possibilities for monitoring and understanding agricultural productivity in many regions of the world. Here we demonstrate the potential to track smallholder maize yield variation in western Kenya, using a combination of 1-m Terra Bella imagery and intensive field sampling on thousands of fields over 2 y. We find that agreement between satellite-based and traditional field survey-based yield estimates depends significantly on the quality of the field-based measures, with agreement highest ([Formula: see text] up to 0.4) when using precise field measures of plot area and when using larger fields for which rounding errors are smaller. We further show that satellite-based measures are able to detect positive yield responses to fertilizer and hybrid seed inputs and that the inferred responses are statistically indistinguishable from estimates based on survey-based yields. These results suggest that high-resolution satellite imagery can be used to make predictions of smallholder agricultural productivity that are roughly as accurate as the survey-based measures traditionally used in research and policy applications, and they indicate a substantial near-term potential to quickly generate useful datasets on productivity in smallholder systems, even with minimal or no field training data. Such datasets could rapidly accelerate learning about which interventions in smallholder systems have the most positive impact, thus enabling more rapid transformation of rural livelihoods.

  5. 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.

  6. 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

  7. Control system estimation and design for aerospace vehicles with time delay

    NASA Technical Reports Server (NTRS)

    Allgaier, G. R.; Williams, T. L.

    1972-01-01

    The problems of estimation and control of discrete, linear, time-varying systems are considered. Previous solutions to these problems involved either approximate techniques, open-loop control solutions, or results which required excessive computation. The estimation problem is solved by two different methods, both of which yield the identical algorithm for determining the optimal filter. The partitioned results achieve a substantial reduction in computation time and storage requirements over the expanded solution, however. The results reduce to the Kalman filter when no delays are present in the system. The control problem is also solved by two different methods, both of which yield identical algorithms for determining the optimal control gains. The stochastic control is shown to be identical to the deterministic control, thus extending the separation principle to time delay systems. The results obtained reduce to the familiar optimal control solution when no time delays are present in the system.

  8. 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...

  9. Seismic Methods of Identifying Explosions and Estimating Their Yield

    NASA Astrophysics Data System (ADS)

    Walter, W. R.; Ford, S. R.; Pasyanos, M.; Pyle, M. L.; Myers, S. C.; Mellors, R. J.; Pitarka, A.; Rodgers, A. J.; Hauk, T. F.

    2014-12-01

    Seismology plays a key national security role in detecting, locating, identifying and determining the yield of explosions from a variety of causes, including accidents, terrorist attacks and nuclear testing treaty violations (e.g. Koper et al., 2003, 1999; Walter et al. 1995). A collection of mainly empirical forensic techniques has been successfully developed over many years to obtain source information on explosions from their seismic signatures (e.g. Bowers and Selby, 2009). However a lesson from the three DPRK declared nuclear explosions since 2006, is that our historic collection of data may not be representative of future nuclear test signatures (e.g. Selby et al., 2012). To have confidence in identifying future explosions amongst the background of other seismic signals, and accurately estimate their yield, we need to put our empirical methods on a firmer physical footing. Goals of current research are to improve our physical understanding of the mechanisms of explosion generation of S- and surface-waves, and to advance our ability to numerically model and predict them. As part of that process we are re-examining regional seismic data from a variety of nuclear test sites including the DPRK and the former Nevada Test Site (now the Nevada National Security Site (NNSS)). Newer relative location and amplitude techniques can be employed to better quantify differences between explosions and used to understand those differences in term of depth, media and other properties. We are also making use of the Source Physics Experiments (SPE) at NNSS. The SPE chemical explosions are explicitly designed to improve our understanding of emplacement and source material effects on the generation of shear and surface waves (e.g. Snelson et al., 2013). Finally we are also exploring the value of combining seismic information with other technologies including acoustic and InSAR techniques to better understand the source characteristics. Our goal is to improve our explosion models

  10. 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.

  11. 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...

  12. Estimated winter wheat yield from crop growth predicted by LANDSAT

    NASA Technical Reports Server (NTRS)

    Kanemasu, E. T.

    1977-01-01

    An evapotranspiration and growth model for winter wheat is reported. The inputs are daily solar radiation, maximum temperature, minimum temperature, precipitation/irrigation and leaf area index. The meteorological data were obtained from National Weather Service while LAI was obtained from LANDSAT multispectral scanner. The output provides daily estimates of potential evapotranspiration, transpiration, evaporation, soil moisture (50 cm depth), percentage depletion, net photosynthesis and dry matter production. Winter wheat yields are correlated with transpiration and dry matter accumulation.

  13. Exoplanet Classification and Yield Estimates for Direct Imaging Missions

    NASA Astrophysics Data System (ADS)

    Kopparapu, Ravi Kumar; Hébrard, Eric; Belikov, Rus; Batalha, Natalie M.; Mulders, Gijs D.; Stark, Chris; Teal, Dillon; Domagal-Goldman, Shawn; Mandell, Avi

    2018-04-01

    Future NASA concept missions that are currently under study, like the Habitable Exoplanet Imaging Mission (HabEx) and the Large Ultra-violet Optical Infra Red Surveyor, could discover a large diversity of exoplanets. We propose here a classification scheme that distinguishes exoplanets into different categories based on their size and incident stellar flux, for the purpose of providing the expected number of exoplanets observed (yield) with direct imaging missions. The boundaries of this classification can be computed using the known chemical behavior of gases and condensates at different pressures and temperatures in a planetary atmosphere. In this study, we initially focus on condensation curves for sphalerite ZnS, {{{H}}}2{{O}}, {CO}}2, and {CH}}4. The order in which these species condense in a planetary atmosphere define the boundaries between different classes of planets. Broadly, the planets are divided into rocky planets (0.5–1.0 R ⊕), super-Earths (1.0–1.75 R ⊕), sub-Neptunes (1.75–3.5 R ⊕), sub-Jovians (3.5–6.0 R ⊕), and Jovians (6–14.3 R ⊕) based on their planet sizes, and “hot,” “warm,” and “cold” based on the incident stellar flux. We then calculate planet occurrence rates within these boundaries for different kinds of exoplanets, η planet, using the community coordinated results of NASA’s Exoplanet Program Analysis Group’s Science Analysis Group-13 (SAG-13). These occurrence rate estimates are in turn used to estimate the expected exoplanet yields for direct imaging missions of different telescope diameters.

  14. Estimation of genetic parameters for milk yield in Murrah buffaloes by Bayesian inference.

    PubMed

    Breda, F C; Albuquerque, L G; Euclydes, R F; Bignardi, A B; Baldi, F; Torres, R A; Barbosa, L; Tonhati, H

    2010-02-01

    Random regression models were used to estimate genetic parameters for test-day milk yield in Murrah buffaloes using Bayesian inference. Data comprised 17,935 test-day milk records from 1,433 buffaloes. Twelve models were tested using different combinations of third-, fourth-, fifth-, sixth-, and seventh-order orthogonal polynomials of weeks of lactation for additive genetic and permanent environmental effects. All models included the fixed effects of contemporary group, number of daily milkings and age of cow at calving as covariate (linear and quadratic effect). In addition, residual variances were considered to be heterogeneous with 6 classes of variance. Models were selected based on the residual mean square error, weighted average of residual variance estimates, and estimates of variance components, heritabilities, correlations, eigenvalues, and eigenfunctions. Results indicated that changes in the order of fit for additive genetic and permanent environmental random effects influenced the estimation of genetic parameters. Heritability estimates ranged from 0.19 to 0.31. Genetic correlation estimates were close to unity between adjacent test-day records, but decreased gradually as the interval between test-days increased. Results from mean squared error and weighted averages of residual variance estimates suggested that a model considering sixth- and seventh-order Legendre polynomials for additive and permanent environmental effects, respectively, and 6 classes for residual variances, provided the best fit. Nevertheless, this model presented the largest degree of complexity. A more parsimonious model, with fourth- and sixth-order polynomials, respectively, for these same effects, yielded very similar genetic parameter estimates. Therefore, this last model is recommended for routine applications. Copyright 2010 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  15. Estimation efficiency of usage satellite derived and modelled biophysical products for yield forecasting

    NASA Astrophysics Data System (ADS)

    Kolotii, Andrii; Kussul, Nataliia; Skakun, Sergii; Shelestov, Andrii; Ostapenko, Vadim; Oliinyk, Tamara

    2015-04-01

    Efficient and timely crop monitoring and yield forecasting are important tasks for ensuring of stability and sustainable economic development [1]. As winter crops pay prominent role in agriculture of Ukraine - the main focus of this study is concentrated on winter wheat. In our previous research [2, 3] it was shown that usage of biophysical parameters of crops such as FAPAR (derived from Geoland-2 portal as for SPOT Vegetation data) is far more efficient for crop yield forecasting to NDVI derived from MODIS data - for available data. In our current work efficiency of usage such biophysical parameters as LAI, FAPAR, FCOVER (derived from SPOT Vegetation and PROBA-V data at resolution of 1 km and simulated within WOFOST model) and NDVI product (derived from MODIS) for winter wheat monitoring and yield forecasting is estimated. As the part of crop monitoring workflow (vegetation anomaly detection, vegetation indexes and products analysis) and yield forecasting SPIRITS tool developed by JRC is used. Statistics extraction is done for landcover maps created in SRI within FP-7 SIGMA project. Efficiency of usage satellite based and modelled with WOFOST model biophysical products is estimated. [1] N. Kussul, S. Skakun, A. Shelestov, O. Kussul, "Sensor Web approach to Flood Monitoring and Risk Assessment", in: IGARSS 2013, 21-26 July 2013, Melbourne, Australia, pp. 815-818. [2] F. Kogan, N. Kussul, T. Adamenko, S. Skakun, O. Kravchenko, O. Kryvobok, A. Shelestov, A. Kolotii, O. Kussul, and A. Lavrenyuk, "Winter wheat yield forecasting in Ukraine based on Earth observation, meteorological data and biophysical models," International Journal of Applied Earth Observation and Geoinformation, vol. 23, pp. 192-203, 2013. [3] Kussul O., Kussul N., Skakun S., Kravchenko O., Shelestov A., Kolotii A, "Assessment of relative efficiency of using MODIS data to winter wheat yield forecasting in Ukraine", in: IGARSS 2013, 21-26 July 2013, Melbourne, Australia, pp. 3235 - 3238.

  16. Simple agrometeorological models for estimating Guineagrass yield in Southeast Brazil.

    PubMed

    Pezzopane, José Ricardo Macedo; da Cruz, Pedro Gomes; Santos, Patricia Menezes; Bosi, Cristiam; de Araujo, Leandro Coelho

    2014-09-01

    The objective of this work was to develop and evaluate agrometeorological models to simulate the production of Guineagrass. For this purpose, we used forage yield from 54 growing periods between December 2004-January 2007 and April 2010-March 2012 in irrigated and non-irrigated pastures in São Carlos, São Paulo state, Brazil (latitude 21°57'42″ S, longitude 47°50'28″ W and altitude 860 m). Initially we performed linear regressions between the agrometeorological variables and the average dry matter accumulation rate for irrigated conditions. Then we determined the effect of soil water availability on the relative forage yield considering irrigated and non-irrigated pastures, by means of segmented linear regression among water balance and relative production variables (dry matter accumulation rates with and without irrigation). The models generated were evaluated with independent data related to 21 growing periods without irrigation in the same location, from eight growing periods in 2000 and 13 growing periods between December 2004-January 2007 and April 2010-March 2012. The results obtained show the satisfactory predictive capacity of the agrometeorological models under irrigated conditions based on univariate regression (mean temperature, minimum temperature and potential evapotranspiration or degreedays) or multivariate regression. The response of irrigation on production was well correlated with the climatological water balance variables (ratio between actual and potential evapotranspiration or between actual and maximum soil water storage). The models that performed best for estimating Guineagrass yield without irrigation were based on minimum temperature corrected by relative soil water storage, determined by the ratio between the actual soil water storage and the soil water holding capacity.irrigation in the same location, in 2000, 2010 and 2011. The results obtained show the satisfactory predictive capacity of the agrometeorological models under

  17. GT0 Explosion Sources for IMS Infrasound Calibration: Charge Design and Yield Estimation from Near-source Observations

    NASA Astrophysics Data System (ADS)

    Gitterman, Y.; Hofstetter, R.

    2014-03-01

    Three large-scale on-surface explosions were conducted by the Geophysical Institute of Israel (GII) at the Sayarim Military Range, Negev desert, Israel: about 82 tons of strong high explosives in August 2009, and two explosions of about 10 and 100 tons of ANFO explosives in January 2011. It was a collaborative effort between Israel, CTBTO, USA and several European countries, with the main goal to provide fully controlled ground truth (GT0) infrasound sources, monitored by extensive observations, for calibration of International Monitoring System (IMS) infrasound stations in Europe, Middle East and Asia. In all shots, the explosives were assembled like a pyramid/hemisphere on dry desert alluvium, with a complicated explosion design, different from the ideal homogenous hemisphere used in similar experiments in the past. Strong boosters and an upward charge detonation scheme were applied to provide more energy radiated to the atmosphere. Under these conditions the evaluation of the actual explosion yield, an important source parameter, is crucial for the GT0 calibration experiment. Audio-visual, air-shock and acoustic records were utilized for interpretation of observed unique blast effects, and for determination of blast wave parameters suited for yield estimation and the associated relationships. High-pressure gauges were deployed at 100-600 m to record air-blast properties, evaluate the efficiency of the charge design and energy generation, and provide a reliable estimation of the charge yield. The yield estimators, based on empirical scaled relations for well-known basic air-blast parameters—the peak pressure, impulse and positive phase duration, as well as on the crater dimensions and seismic magnitudes, were analyzed. A novel empirical scaled relationship for the little-known secondary shock delay was developed, consistent for broad ranges of ANFO charges and distances, which facilitates using this stable and reliable air-blast parameter as a new potential

  18. 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.

  19. 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

  20. Advances in regional crop yield estimation over the United States using satellite remote sensing data

    NASA Astrophysics Data System (ADS)

    Johnson, D. M.; Dorn, M. F.; Crawford, C.

    2015-12-01

    Since the dawn of earth observation imagery, particularly from systems like Landsat and the Advanced Very High Resolution Radiometer, there has been an overarching desire to regionally estimate crop production remotely. Research efforts integrating space-based imagery into yield models to achieve this need have indeed paralleled these systems through the years, yet development of a truly useful crop production monitoring system has been arguably mediocre in coming. As a result, relatively few organizations have yet to operationalize the concept, and this is most acute in regions of the globe where there are not even alternative sources of crop production data being collected. However, the National Agricultural Statistics Service (NASS) has continued to push for this type of data source as a means to complement its long-standing, traditional crop production survey efforts which are financially costly to the government and create undue respondent burden on farmers. Corn and soybeans, the two largest field crops in the United States, have been the focus of satellite-based production monitoring by NASS for the past decade. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) has been seen as the most pragmatic input source for modeling yields primarily based on its daily revisit capabilities and reasonable ground sample resolution. The research methods presented here will be broad but provides a summary of what is useful and adoptable with satellite imagery in terms of crop yield estimation. Corn and soybeans will be of particular focus but other major staple crops like wheat and rice will also be presented. NASS will demonstrate that while MODIS provides a slew of vegetation related products, the traditional normalized difference vegetation index (NDVI) is still ideal. Results using land surface temperature products, also generated from MODIS, will also be shown. Beyond the MODIS data itself, NASS research has also focused efforts on understanding a

  1. Optimizing rice yields while minimizing yield-scaled global warming potential.

    PubMed

    Pittelkow, Cameron M; Adviento-Borbe, Maria A; van Kessel, Chris; Hill, James E; Linquist, Bruce A

    2014-05-01

    To meet growing global food demand with limited land and reduced environmental impact, agricultural greenhouse gas (GHG) emissions are increasingly evaluated with respect to crop productivity, i.e., on a yield-scaled as opposed to area basis. Here, we compiled available field data on CH4 and N2 O emissions from rice production systems to test the hypothesis that in response to fertilizer nitrogen (N) addition, yield-scaled global warming potential (GWP) will be minimized at N rates that maximize yields. Within each study, yield N surplus was calculated to estimate deficit or excess N application rates with respect to the optimal N rate (defined as the N rate at which maximum yield was achieved). Relationships between yield N surplus and GHG emissions were assessed using linear and nonlinear mixed-effects models. Results indicate that yields increased in response to increasing N surplus when moving from deficit to optimal N rates. At N rates contributing to a yield N surplus, N2 O and yield-scaled N2 O emissions increased exponentially. In contrast, CH4 emissions were not impacted by N inputs. Accordingly, yield-scaled CH4 emissions decreased with N addition. Overall, yield-scaled GWP was minimized at optimal N rates, decreasing by 21% compared to treatments without N addition. These results are unique compared to aerobic cropping systems in which N2 O emissions are the primary contributor to GWP, meaning yield-scaled GWP may not necessarily decrease for aerobic crops when yields are optimized by N fertilizer addition. Balancing gains in agricultural productivity with climate change concerns, this work supports the concept that high rice yields can be achieved with minimal yield-scaled GWP through optimal N application rates. Moreover, additional improvements in N use efficiency may further reduce yield-scaled GWP, thereby strengthening the economic and environmental sustainability of rice systems. © 2013 John Wiley & Sons Ltd.

  2. A Theoretical Model for Estimation of Yield Strength of Fiber Metal Laminate

    NASA Astrophysics Data System (ADS)

    Bhat, Sunil; Nagesh, Suresh; Umesh, C. K.; Narayanan, S.

    2017-08-01

    The paper presents a theoretical model for estimation of yield strength of fiber metal laminate. Principles of elasticity and formulation of residual stress are employed to determine the stress state in metal layer of the laminate that is found to be higher than the stress applied over the laminate resulting in reduced yield strength of the laminate in comparison with that of the metal layer. The model is tested over 4A-3/2 Glare laminate comprising three thin aerospace 2014-T6 aluminum alloy layers alternately bonded adhesively with two prepregs, each prepreg built up of three uni-directional glass fiber layers laid in longitudinal and transverse directions. Laminates with prepregs of E-Glass and S-Glass fibers are investigated separately under uni-axial tension. Yield strengths of both the Glare variants are found to be less than that of aluminum alloy with use of S-Glass fiber resulting in higher laminate yield strength than with the use of E-Glass fiber. Results from finite element analysis and tensile tests conducted over the laminates substantiate the theoretical model.

  3. 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.

  4. 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.

  5. 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.

  6. OCO-2 Solar-induced Fluorescence Data Portal and Applications to Crop Yield Estimation

    NASA Astrophysics Data System (ADS)

    Zhai, A. J.; Jiang, J. H.; Frankenberg, C.; Yung, Y. L.; Choi, Y. S.

    2016-12-01

    Solar-induced fluorescence (SIF) is a direct byproduct of photosynthesis and is an index that can represent overall plant productivity level of any region around the globe. Recently, in 2014, NASA launched the Orbiting Carbon Observatory 2 (OCO-2) satellite, which collects SIF measurements at a higher spatial resolution than any previous instrument has. We have first assembled a web-based data portal, which can be easily utilized by both farmers and researchers, to allow convenient access to the SIF data from OCO-2. One possible use of SIF is to estimate agricultural status of crop fields anywhere in the world. We are using OCO-2 level 2 measurements in conjunction with the USDA's Cropland Data Layer and reported crop yield data to study how effectively SIF can estimate agricultural yield on various types of landscape and various species of crops. Results, methods, and future implications will be presented.

  7. 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.

  8. 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.

  9. 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

  10. Cancer Risk Estimates from Space Flight Estimated Using Yields of Chromosome Damage in Astronaut's Blood Lymphocytes

    NASA Technical Reports Server (NTRS)

    George, Kerry A.; Rhone, J.; Chappell, L. J.; Cucinotta, F. A.

    2011-01-01

    To date, cytogenetic damage has been assessed in blood lymphocytes from more than 30 astronauts before and after they participated in long-duration space missions of three months or more on board the International Space Station. Chromosome damage was assessed using fluorescence in situ hybridization whole chromosome analysis techniques. For all individuals, the frequency of chromosome damage measured within a month of return from space was higher than their preflight yield, and biodosimetry estimates were within the range expected from physical dosimetry. Follow up analyses have been performed on most of the astronauts at intervals ranging from around 6 months to many years after flight, and the cytogenetic effects of repeat long-duration missions have so far been assessed in four individuals. Chromosomal aberrations in peripheral blood lymphocytes have been validated as biomarkers of cancer risk and cytogenetic damage can therefore be used to characterize excess health risk incurred by individual crewmembers after their respective missions. Traditional risk assessment models are based on epidemiological data obtained on Earth in cohorts exposed predominantly to acute doses of gamma-rays, and the extrapolation to the space environment is highly problematic, involving very large uncertainties. Cytogenetic damage could play a key role in reducing uncertainty in risk estimation because it is incurred directly in the space environment, using specimens from the astronauts themselves. Relative cancer risks were estimated from the biodosimetry data using the quantitative approach derived from the European Study Group on Cytogenetic Biomarkers and Health database. Astronauts were categorized into low, medium, or high tertiles according to their yield of chromosome damage. Age adjusted tertile rankings were used to estimate cancer risk and results were compared with values obtained using traditional modeling approaches. Individual tertile rankings increased after space

  11. Vacuum transfer system increases sugar maple sap yield

    Treesearch

    Russell S. Walters

    1978-01-01

    Yields of sugar maple sap collected from three plastic pipeline systems by gravity, vacuum pump, and a vacuum pump with a transfer tank were compared during 2 years in northern Vermont. The transfer system yielded 27 percent more sap one year and 17 percent more the next year. Higher vacuum levels at the tapholes were observed in the transfer system.

  12. 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.

  13. 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; hide

    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. Multi-method 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.

  14. 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

  15. 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.

  16. Paddy crop yield estimation in Kashmir Himalayan rice bowl using remote sensing and simulation model.

    PubMed

    Muslim, Mohammad; Romshoo, Shakil Ahmad; Rather, A Q

    2015-06-01

    The Kashmir Himalayan region of India is expected to be highly prone to the change in agricultural land use because of its geo-ecological fragility, strategic location vis-à-vis the Himalayan landscape, its trans-boundary river basins, and inherent socio-economic instabilities. Food security and sustainability of the region are thus greatly challenged by these impacts. The effect of future climate change, increased competition for land and water, labor from non-agricultural sectors, and increasing population adds to this complex problem. In current study, paddy rice yield at regional level was estimated using GIS-based environment policy integrated climate (GEPIC) model. The general approach of current study involved combining regional level crop database, regional soil data base, farm management data, and climatic data outputs with GEPIC model. The simulated yield showed that estimated production to be 4305.55 kg/ha (43.05 q h(-1)). The crop varieties like Jhelum, K-39, Chenab, China 1039, China-1007, and Shalimar rice-1 grown in plains recorded average yield of 4783.3 kg/ha (47.83 q ha(-1)). Meanwhile, high altitude areas with varieties like Kohsaar, K-78 (Barkat), and K-332 recorded yield of 4102.2 kg/ha (41.02 q ha(-1)). The observed and simulated yield showed a good match with R (2) = 0.95, RMSE = 132.24 kg/ha, respectively.

  17. Number of pins in two-stage stratified sampling for estimating herbage yield

    Treesearch

    William G. O' Regan; C. Eugene Conrad

    1975-01-01

    In a two-stage stratified procedure for sampling herbage yield, plots are stratified by a pin frame in stage one, and clipped. In stage two, clippings from selected plots are sorted, dried, and weighed. Sample size and distribution of plots between the two stages are determined by equations. A way to compute the effect of number of pins on the variance of estimated...

  18. 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...

  19. 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 ...

  20. System Estimates Radius of Curvature of a Segmented Mirror

    NASA Technical Reports Server (NTRS)

    Rakoczy, John

    2008-01-01

    A system that estimates the global radius of curvature (GRoC) of a segmented telescope mirror has been developed for use as one of the subsystems of a larger system that exerts precise control over the displacements of the mirror segments. This GRoC-estimating system, when integrated into the overall control system along with a mirror-segment- actuation subsystem and edge sensors (sensors that measure displacements at selected points on the edges of the segments), makes it possible to control the GROC mirror-deformation mode, to which mode contemporary edge sensors are insufficiently sensitive. This system thus makes it possible to control the GRoC of the mirror with sufficient precision to obtain the best possible image quality and/or to impose a required wavefront correction on incoming or outgoing light. In its mathematical aspect, the system utilizes all the information available from the edge-sensor subsystem in a unique manner that yields estimates of all the states of the segmented mirror. The system does this by exploiting a special set of mirror boundary conditions and mirror influence functions in such a way as to sense displacements in degrees of freedom that would otherwise be unobservable by means of an edge-sensor subsystem, all without need to augment the edge-sensor system with additional metrological hardware. Moreover, the accuracy of the estimates increases with the number of mirror segments.

  1. High-yield positron systems for linear colliders

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

    Clendenin, J.E.

    1989-04-01

    Linear colliders, such as the SLC, are among those accelerators for which a high-yield positron source operating at the repetition rate of the accelerator is desired. The SLC, having electron energies up to 50 GeV, presents the possibility of generating positron bunches with useful charge even exceeding that of the initial electron bunch. The exact positron yield to be obtained depends on the particular capture, transport and damping system employed. Using 31 GeV electrons impinging on a W-type converter phase-space at the target to the acceptance of the capture rf section, the SLC source is capable of producing, for everymore » electron, up to two positrons within the acceptance of the positron damping ring. The design of this source and the performance of the positron system as built are described. Also, future prospects and limitations for high-yield positron systems are discussed. 11 refs., 5 figs., 3 tabs.« less

  2. Estimates of genetics and phenotypics parameters for the yield and quality of soybean seeds.

    PubMed

    Zambiazzi, E V; Bruzi, A T; Guilherme, S R; Pereira, D R; Lima, J G; Zuffo, A M; Ribeiro, F O; Mendes, A E S; Godinho, S H M; Carvalho, M L M

    2017-09-27

    Estimating genotype x environment (GxE) parameters for quality and yield in soybean seed grown in different environments in Minas Gerais State was the goal of this study, as well as to evaluate interaction effects of GxE for soybean seeds yield and quality. Seeds were produced in three locations in Minas Gerais State (Lavras, Inconfidentes, and Patos de Minas) in 2013/14 and 2014/15 seasons. Field experiments were conducted in randomized blocks in a factorial 17 x 6 (GxE), and three replications. Seed yield and quality were evaluated for germination in substrates paper and sand, seedling emergence, speed emergency index, mechanical damage by sodium hypochlorite, electrical conductivity, speed aging, vigor and viability of seeds by tetrazolium test in laboratory using completely randomized design. Quadratic component genotypic, GXE variance component, genotype determination coefficient, genetic variation coefficient and environmental variation coefficient were estimated using the Genes software. Percentage analysis of genotypes contribution, environments and genotype x environment interaction were conducted by sites combination two by two and three sites combination, using the R software. Considering genotypes selection of broad adaptation, TMG 1179 RR, CD 2737 RR, and CD 237 RR associated better yield performance at high physical and physiological potential of seed. Environmental effect was more expressive for most of the characters related to soybean seed quality. GxE interaction effects were expressive though genotypes did not present coincidental behavior in different environments.

  3. 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.

  4. Canopy Chlorophyll Density Based Index for Estimating Nitrogen Status and Predicting Grain Yield in Rice

    PubMed Central

    Liu, Xiaojun; Zhang, Ke; Zhang, Zeyu; Cao, Qiang; Lv, Zunfu; Yuan, Zhaofeng; Tian, Yongchao; Cao, Weixing; Zhu, Yan

    2017-01-01

    Canopy chlorophyll density (Chl) has a pivotal role in diagnosing crop growth and nutrition status. The purpose of this study was to develop Chl based models for estimating N status and predicting grain yield of rice (Oryza sativa L.) with Leaf area index (LAI) and Chlorophyll concentration of the upper leaves. Six field experiments were conducted in Jiangsu Province of East China during 2007, 2008, 2009, 2013, and 2014. Different N rates were applied to generate contrasting conditions of N availability in six Japonica cultivars (9915, 27123, Wuxiangjing 14, Wuyunjing 19, Yongyou 8, and Wuyunjing 24) and two Indica cultivars (Liangyoupei 9, YLiangyou 1). The SPAD values of the four uppermost leaves and LAI were measured from tillering to flowering growth stages. Two N indicators, leaf N accumulation (LNA) and plant N accumulation (PNA) were measured. The LAI estimated by LAI-2000 and LI-3050C were compared and calibrated with a conversion equation. A linear regression analysis showed significant relationships between Chl value and N indicators, the equations were as follows: PNA = (0.092 × Chl) − 1.179 (R2 = 0.94, P < 0.001, relative root mean square error (RRMSE) = 0.196), LNA = (0.052 × Chl) − 0.269 (R2 = 0.93, P < 0.001, RRMSE = 0.185). Standardized method was used to quantity the correlation between Chl value and grain yield, normalized yield = (0.601 × normalized Chl) + 0.400 (R2 = 0.81, P < 0.001, RRMSE = 0.078). Independent experimental data also validated the use of Chl value to accurately estimate rice N status and predict grain yield. PMID:29163568

  5. 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

  6. Effects of Source RDP Models and Near-source Propagation: Implication for Seismic Yield Estimation

    NASA Astrophysics Data System (ADS)

    Saikia, C. K.; Helmberger, D. V.; Stead, R. J.; Woods, B. B.

    - It has proven difficult to uniquely untangle the source and propagation effects on the observed seismic data from underground nuclear explosions, even when large quantities of near-source, broadband data are available for analysis. This leads to uncertainties in our ability to quantify the nuclear seismic source function and, consequently the accuracy of seismic yield estimates for underground explosions. Extensive deterministic modeling analyses of the seismic data recorded from underground explosions at a variety of test sites have been conducted over the years and the results of these studies suggest that variations in the seismic source characteristics between test sites may be contributing to the observed differences in the magnitude/yield relations applicable at those sites. This contributes to our uncertainty in the determination of seismic yield estimates for explosions at previously uncalibrated test sites. In this paper we review issues involving the relationship of Nevada Test Site (NTS) source scaling laws to those at other sites. The Joint Verification Experiment (JVE) indicates that a magnitude (mb) bias (δmb) exists between the Semipalatinsk test site (STS) in the former Soviet Union (FSU) and the Nevada test site (NTS) in the United States. Generally this δmb is attributed to differential attenuation in the upper-mantle beneath the two test sites. This assumption results in rather large estimates of yield for large mb tunnel shots at Novaya Zemlya. A re-examination of the US testing experiments suggests that this δmb bias can partly be explained by anomalous NTS (Pahute) source characteristics. This interpretation is based on the modeling of US events at a number of test sites. Using a modified Haskell source description, we investigated the influence of the source Reduced Displacement Potential (RDP) parameters ψ ∞ , K and B by fitting short- and long-period data simultaneously, including the near-field body and surface waves. In general

  7. Development of estimation method for crop yield using MODIS satellite imagery data and process-based model for corn and soybean in US Corn-Belt region

    NASA Astrophysics Data System (ADS)

    Lee, J.; Kang, S.; Jang, K.; Ko, J.; Hong, S.

    2012-12-01

    Crop productivity is associated with the food security and hence, several models have been developed to estimate crop yield by combining remote sensing data with carbon cycle processes. In present study, we attempted to estimate crop GPP and NPP using algorithm based on the LUE model and a simplified respiration model. The state of Iowa and Illinois was chosen as the study site for estimating the crop yield for a period covering the 5 years (2006-2010), as it is the main Corn-Belt area in US. Present study focuses on developing crop-specific parameters for corn and soybean to estimate crop productivity and yield mapping using satellite remote sensing data. We utilized a 10 km spatial resolution daily meteorological data from WRF to provide cloudy-day meteorological variables but in clear-say days, MODIS-based meteorological data were utilized to estimate daily GPP, NPP, and biomass. County-level statistics on yield, area harvested, and productions were used to test model predicted crop yield. The estimated input meteorological variables from MODIS and WRF showed with good agreements with the ground observations from 6 Ameriflux tower sites in 2006. For examples, correlation coefficients ranged from 0.93 to 0.98 for Tmin and Tavg ; from 0.68 to 0.85 for daytime mean VPD; from 0.85 to 0.96 for daily shortwave radiation, respectively. We developed county-specific crop conversion coefficient, i.e. ratio of yield to biomass on 260 DOY and then, validated the estimated county-level crop yield with the statistical yield data. The estimated corn and soybean yields at the county level ranged from 671 gm-2 y-1 to 1393 gm-2 y-1 and from 213 gm-2 y-1 to 421 gm-2 y-1, respectively. The county-specific yield estimation mostly showed errors less than 10%. Furthermore, we estimated crop yields at the state level which were validated against the statistics data and showed errors less than 1%. Further analysis for crop conversion coefficient was conducted for 200 DOY and 280 DOY

  8. 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.

  9. Estimation of genomic breeding values for milk yield in UK dairy goats.

    PubMed

    Mucha, S; Mrode, R; MacLaren-Lee, I; Coffey, M; Conington, J

    2015-11-01

    The objective of this study was to estimate genomic breeding values for milk yield in crossbred dairy goats. The research was based on data provided by 2 commercial goat farms in the UK comprising 590,409 milk yield records on 14,453 dairy goats kidding between 1987 and 2013. The population was created by crossing 3 breeds: Alpine, Saanen, and Toggenburg. In each generation the best performing animals were selected for breeding, and as a result, a synthetic breed was created. The pedigree file contained 30,139 individuals, of which 2,799 were founders. The data set contained test-day records of milk yield, lactation number, farm, age at kidding, and year and season of kidding. Data on milk composition was unavailable. In total 1,960 animals were genotyped with the Illumina 50K caprine chip. Two methods for estimation of genomic breeding value were compared-BLUP at the single nucleotide polymorphism level (BLUP-SNP) and single-step BLUP. The highest accuracy of 0.61 was obtained with single-step BLUP, and the lowest (0.36) with BLUP-SNP. Linkage disequilibrium (r(2), the squared correlation of the alleles at 2 loci) at 50 kb (distance between 2 SNP) was 0.18. This is the first attempt to implement genomic selection in UK dairy goats. Results indicate that the single-step method provides the highest accuracy for populations with a small number of genotyped individuals, where the number of genotyped males is low and females are predominant in the reference population. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  10. Regional Detection of Decoupled Explosions, Yield Estimation from Surface Waves, Two-Dimensional Source Effects, Three-Dimensional Earthquake Modeling and Automated Magnitude Measures

    DTIC Science & Technology

    1980-07-01

    41 3.2 EXPERIMENTAL DETERMINATION OF THE DEPENDENCE OF RAYLEIGH WAVE AMPLITUDE ON PROPERTIES OF THE SOURCE MATERIAL ...Surface Wave Observations ...... ................ 48 3.3.3 Surface Wave Dependence on Source Material Properties ..... ................ .. 51 SYSTEMS...with various aspects of the problem of estimating yield from single station recordings of surface waves. The material in these four summaries has been

  11. Infrasound Propagation Modeling for Explosive Yield Estimation

    NASA Astrophysics Data System (ADS)

    Howard, J. E.; Golden, P.; Negraru, P.

    2013-12-01

    This study focuses on developing methods of estimating the size or yield of HE surface explosions from local and regional infrasound measurements in the southwestern United States. A munitions disposal facility near Mina, Nevada provides a repeating ground-truth source for this study, with charge weights ranging from 870 - 3800 lbs. Detonation logs and GPS synchronized videos were obtained for a sample of shots representing the full range of weights. These are used to calibrate a relationship between charge weight and spectral level from seismic waveforms recorded at the Nevada Seismic Array (NVAR) at a distance of 36 km. Origin times and yields for the remaining shots are inferred from the seismic recordings at NVAR. Infrasound arrivals from the detonations have been continuously recorded on three four-element, small aperture infrasound arrays since late 2009. NVIAR is collocated with NVAR at a range of approximately 36 km to the northeast. FALN and DNIAR are located at ranges of 154 km to the north, and 293 km to the southeast respectively. Travel times and amplitudes for stratospheric arrivals at DNIAR show strong seasonal variability with the largest amplitudes and celerities occurring during the winter months when the stratospheric winds are favorable. Stratospheric celerities for FNIAR to the north are more consistent as they are not strongly affected by the predominantly meridional stratospheric winds. Tropospheric arrivals at all three arrays show considerable variability that does not appear to be a seasonal effect. Naval Research Laboratory Ground to Space (NRL-G2S) Mesoscale models are used to specify the atmosphere along the propagation path for each detonation. Ray-tracing is performed for each source/receiver pair to identify events for which the models closely match the travel-time observations. This subset of events is used to establish preliminary wind correction formulas using wind values from the G2S profile for the entire propagation path. These

  12. Estimating milk yield and value losses from increased somatic cell count on US dairy farms.

    PubMed

    Hadrich, J C; Wolf, C A; Lombard, J; Dolak, T M

    2018-04-01

    Milk loss due to increased somatic cell counts (SCC) results in economic losses for dairy producers. This research uses 10 mo of consecutive dairy herd improvement data from 2013 and 2014 to estimate milk yield loss using SCC as a proxy for clinical and subclinical mastitis. A fixed effects regression was used to examine factors that affected milk yield while controlling for herd-level management. Breed, milking frequency, days in milk, seasonality, SCC, cumulative months with SCC greater than 100,000 cells/mL, lactation, and herd size were variables included in the regression analysis. The cumulative months with SCC above a threshold was included as a proxy for chronic mastitis. Milk yield loss increased as the number of test days with SCC ≥100,000 cells/mL increased. Results from the regression were used to estimate a monetary value of milk loss related to SCC as a function of cow and operation related explanatory variables for a representative dairy cow. The largest losses occurred from increased cumulative test days with a SCC ≥100,000 cells/mL, with daily losses of $1.20/cow per day in the first month to $2.06/cow per day in mo 10. Results demonstrate the importance of including the duration of months above a threshold SCC when estimating milk yield losses. Cows with chronic mastitis, measured by increased consecutive test days with SCC ≥100,000 cells/mL, resulted in higher milk losses than cows with a new infection. This provides farm managers with a method to evaluate the trade-off between treatment and culling decisions as it relates to mastitis control and early detection. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  13. 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.

  14. Estimating the impact of mineral aerosols on crop yields in food insecure regions using statistical crop models

    NASA Astrophysics Data System (ADS)

    Hoffman, A.; Forest, C. E.; Kemanian, A.

    2016-12-01

    A significant number of food-insecure nations exist in regions of the world where dust plays a large role in the climate system. While the impacts of common climate variables (e.g. temperature, precipitation, ozone, and carbon dioxide) on crop yields are relatively well understood, the impact of mineral aerosols on yields have not yet been thoroughly investigated. This research aims to develop the data and tools to progress our understanding of mineral aerosol impacts on crop yields. Suspended dust affects crop yields by altering the amount and type of radiation reaching the plant, modifying local temperature and precipitation. While dust events (i.e. dust storms) affect crop yields by depleting the soil of nutrients or by defoliation via particle abrasion. The impact of dust on yields is modeled statistically because we are uncertain which impacts will dominate the response on national and regional scales considered in this study. Multiple linear regression is used in a number of large-scale statistical crop modeling studies to estimate yield responses to various climate variables. In alignment with previous work, we develop linear crop models, but build upon this simple method of regression with machine-learning techniques (e.g. random forests) to identify important statistical predictors and isolate how dust affects yields on the scales of interest. To perform this analysis, we develop a crop-climate dataset for maize, soybean, groundnut, sorghum, rice, and wheat for the regions of West Africa, East Africa, South Africa, and the Sahel. Random forest regression models consistently model historic crop yields better than the linear models. In several instances, the random forest models accurately capture the temperature and precipitation threshold behavior in crops. Additionally, improving agricultural technology has caused a well-documented positive trend that dominates time series of global and regional yields. This trend is often removed before regression with

  15. Estimation of dew yield from radiative condensers by means of an energy balance model

    NASA Astrophysics Data System (ADS)

    Maestre-Valero, J. F.; Ragab, R.; Martínez-Alvarez, V.; Baille, A.

    2012-08-01

    SummaryThis paper presents an energy balance modelling approach to predict the nightly water yield and the surface temperature (Tf) of two passive radiative dew condensers (RDCs) tilted 30° from horizontal. One was fitted with a white hydrophilic polyethylene foil recommended for dew harvest and the other with a black polyethylene foil widely used in horticulture. The model was validated in south-eastern Spain by comparing the simulation outputs with field measurements of Tf and dew yield. The results indicate that the model is robust and accurate in reproducing the behaviour of the two RDCs, especially in what refers to Tf, whose estimates were very close to the observations. The results were somewhat less precise for dew yield, with a larger scatter around the 1:1 relationship. A sensitivity analysis showed that the simulated dew yield was highly sensitive to changes in relative humidity and downward longwave radiation. The proposed approach provides a useful tool to water managers for quantifying the amount of dew that could be harvested as a valuable water resource in arid, semiarid and water stressed regions.

  16. 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...

  17. Frost trends and their estimated impact on yield in the Australian wheatbelt

    PubMed Central

    Zheng, Bangyou; Chapman, Scott C.; Christopher, Jack T.; Frederiks, Troy M.; Chenu, Karine

    2015-01-01

    Radiant spring frosts occurring during reproductive developmental stages can result in catastrophic yield loss for wheat producers. To better understand the spatial and temporal variability of frost, the occurrence and impact of frost events on rain-fed wheat production was estimated across the Australian wheatbelt for 1957–2013 using a 0.05 ° gridded weather data set. Simulated yield outcomes at 60 key locations were compared with those for virtual genotypes with different levels of frost tolerance. Over the last six decades, more frost events, later last frost day, and a significant increase in frost impact on yield were found in certain regions of the Australian wheatbelt, in particular in the South-East and West. Increasing trends in frost-related yield losses were simulated in regions where no significant trend of frost occurrence was observed, due to higher mean temperatures accelerating crop development and causing sensitive post-heading stages to occur earlier, during the frost risk period. Simulations indicated that with frost-tolerant lines the mean national yield could be improved by up to 20% through (i) reduced frost damage (~10% improvement) and (ii) the ability to use earlier sowing dates (adding a further 10% improvement). In the simulations, genotypes with an improved frost tolerance to temperatures 1 °C lower than the current 0 °C reference provided substantial benefit in most cropping regions, while greater tolerance (to 3 °C lower temperatures) brought further benefits in the East. The results indicate that breeding for improved reproductive frost tolerance should remain a priority for the Australian wheat industry, despite warming climates. PMID:25922479

  18. Frost trends and their estimated impact on yield in the Australian wheatbelt.

    PubMed

    Zheng, Bangyou; Chapman, Scott C; Christopher, Jack T; Frederiks, Troy M; Chenu, Karine

    2015-06-01

    Radiant spring frosts occurring during reproductive developmental stages can result in catastrophic yield loss for wheat producers. To better understand the spatial and temporal variability of frost, the occurrence and impact of frost events on rain-fed wheat production was estimated across the Australian wheatbelt for 1957-2013 using a 0.05 ° gridded weather data set. Simulated yield outcomes at 60 key locations were compared with those for virtual genotypes with different levels of frost tolerance. Over the last six decades, more frost events, later last frost day, and a significant increase in frost impact on yield were found in certain regions of the Australian wheatbelt, in particular in the South-East and West. Increasing trends in frost-related yield losses were simulated in regions where no significant trend of frost occurrence was observed, due to higher mean temperatures accelerating crop development and causing sensitive post-heading stages to occur earlier, during the frost risk period. Simulations indicated that with frost-tolerant lines the mean national yield could be improved by up to 20% through (i) reduced frost damage (~10% improvement) and (ii) the ability to use earlier sowing dates (adding a further 10% improvement). In the simulations, genotypes with an improved frost tolerance to temperatures 1 °C lower than the current 0 °C reference provided substantial benefit in most cropping regions, while greater tolerance (to 3 °C lower temperatures) brought further benefits in the East. The results indicate that breeding for improved reproductive frost tolerance should remain a priority for the Australian wheat industry, despite warming climates. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology.

  19. 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

  20. 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.

  1. Quantifying Soiling Loss Directly From PV Yield

    DOE PAGES

    Deceglie, Michael G.; Micheli, Leonardo; Muller, Matthew

    2018-01-23

    Soiling of photovoltaic (PV) panels is typically quantified through the use of specialized sensors. Here, we describe and validate a method for estimating soiling loss experienced by PV systems directly from system yield without the need for precipitation data. The method, termed the stochastic rate and recovery (SRR) method, automatically detects soiling intervals in a dataset, then stochastically generates a sample of possible soiling profiles based on the observed characteristics of each interval. In this paper, we describe the method, validate it against soiling station measurements, and compare it with other PV-yield-based soiling estimation methods. The broader application of themore » SRR method will enable the fleet scale assessment of soiling loss to facilitate mitigation planning and risk assessment.« less

  2. Quantifying Soiling Loss Directly From PV Yield

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

    Deceglie, Michael G.; Micheli, Leonardo; Muller, Matthew

    Soiling of photovoltaic (PV) panels is typically quantified through the use of specialized sensors. Here, we describe and validate a method for estimating soiling loss experienced by PV systems directly from system yield without the need for precipitation data. The method, termed the stochastic rate and recovery (SRR) method, automatically detects soiling intervals in a dataset, then stochastically generates a sample of possible soiling profiles based on the observed characteristics of each interval. In this paper, we describe the method, validate it against soiling station measurements, and compare it with other PV-yield-based soiling estimation methods. The broader application of themore » SRR method will enable the fleet scale assessment of soiling loss to facilitate mitigation planning and risk assessment.« less

  3. Validation of the Unthinned Loblolly Pine Plantation Yield Model-USLYCOWG

    Treesearch

    V. Clark Baldwin; D.P. Feduccia

    1982-01-01

    Yield and stand structure predictions from an unthinned loblolly pine plantation yield prediction system (USLYCOWG computer program) were compared with observations from 80 unthinned loblolly pine plots. Overall, the predicted estimates were reasonable when compared to observed values, but predictions based on input data at or near the system's limits may be in...

  4. Forecasting overhaul or replacement intervals based on estimated system failure intensity

    NASA Astrophysics Data System (ADS)

    Gannon, James M.

    1994-12-01

    System reliability can be expressed in terms of the pattern of failure events over time. Assuming a nonhomogeneous Poisson process and Weibull intensity function for complex repairable system failures, the degree of system deterioration can be approximated. Maximum likelihood estimators (MLE's) for the system Rate of Occurrence of Failure (ROCOF) function are presented. Evaluating the integral of the ROCOF over annual usage intervals yields the expected number of annual system failures. By associating a cost of failure with the expected number of failures, budget and program policy decisions can be made based on expected future maintenance costs. Monte Carlo simulation is used to estimate the range and the distribution of the net present value and internal rate of return of alternative cash flows based on the distributions of the cost inputs and confidence intervals of the MLE's.

  5. Yield gaps and yield relationships in US soybean production systems

    USDA-ARS?s Scientific Manuscript database

    The magnitude of yield gaps (YG) (potential yield – farmer yield) provides some indication of the prospects for increasing crop yield to meet the food demands of future populations. Quantile regression analysis was applied to county soybean [Glycine max (L.) Merrill] yields (1971 – 2011) from Kentuc...

  6. 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...

  7. MODIS Data Assimilation in the CROPGRO model for improving soybean yield estimations

    NASA Astrophysics Data System (ADS)

    Richetti, J.; Monsivais-Huertero, A.; Ahmad, I.; Judge, J.

    2017-12-01

    Soybean is one of the main agricultural commodities in the world. Thus, having better estimates of its agricultural production is important. Improving the soybean crop models in Brazil is crucial for better understanding of the soybean market and enhancing decision making, because Brazil is the second largest soybean producer in the world, Parana state is responsible for almost 20% of it, and by itself would be the fourth greatest soybean producer in the world. Data assimilation techniques provide a method to improve spatio-temporal continuity of crops through integration of remotely sensed observations and crop growth models. This study aims to use MODIS EVI to improve DSSAT-CROPGRO soybean yield estimations in the Parana state, southern Brazil. The method uses the Ensemble Kalman filter which assimilates MODIS Terra and Aqua combined products (MOD13Q1 and MYD13Q1) into the CROPGRO model to improve the agricultural production estimates through update of light interception data over time. Expected results will be validated with monitored commercial farms during the period of 2013-2014.

  8. Pentopyranosyl Oligonucleotide Systems. Part 11: Systems with Shortened Backbones: D)-beta-Ribopyranosyl-(4 yields 3 )- and (L)-alpha - Lyxopyranosyl-(4 yields 3 )-oligonucleotides

    NASA Technical Reports Server (NTRS)

    Wippo, Harald; Reck, Folkert; Kudick, Rene; Ramaseshan, Mahesh; Ceulemans, Griet; Bolli, Martin; Krishnamurthy, Ramanarayanan; Eschenmoser, Albert

    2001-01-01

    The (L)-a-lyxopyranosyl-(4'yields 3')-oligonucleotide system-a member of a pentopyranosyl oligonucleotide family containing a shortened backbone-is capable of cooperative base-pairing and of cross-pairing with DNA and RNA. In contrast, corresponding (D)-beta-ribopyransoyl-(4' yields 3')-oligonucleotides do not show base-pairing under similar conditions. We conclude that oligonucleotide systems can violate the six-bonds-per-backbone-unit rule by having five bonds instead, if their vicinally bound phosphodiester bridges can assume an antiperiplanar conformation. An additional structural feature that seems relevant to the cross-pairing capability of the (L)-a-lyxopyranosyl-(4' yields 3')-oligonucleotide system is its (small) backbone/basepair axes inclination. An inclination which is similar to that in B-DNA seems to be a prerequisite for an oligonucleotide system s capability to cross-pair with DNA.

  9. An M-estimator for reduced-rank system identification.

    PubMed

    Chen, Shaojie; Liu, Kai; Yang, Yuguang; Xu, Yuting; Lee, Seonjoo; Lindquist, Martin; Caffo, Brian S; Vogelstein, Joshua T

    2017-01-15

    High-dimensional time-series data from a wide variety of domains, such as neuroscience, are being generated every day. Fitting statistical models to such data, to enable parameter estimation and time-series prediction, is an important computational primitive. Existing methods, however, are unable to cope with the high-dimensional nature of these data, due to both computational and statistical reasons. We mitigate both kinds of issues by proposing an M-estimator for Reduced-rank System IDentification ( MR. SID). A combination of low-rank approximations, ℓ 1 and ℓ 2 penalties, and some numerical linear algebra tricks, yields an estimator that is computationally efficient and numerically stable. Simulations and real data examples demonstrate the usefulness of this approach in a variety of problems. In particular, we demonstrate that MR. SID can accurately estimate spatial filters, connectivity graphs, and time-courses from native resolution functional magnetic resonance imaging data. MR. SID therefore enables big time-series data to be analyzed using standard methods, readying the field for further generalizations including non-linear and non-Gaussian state-space models.

  10. An M-estimator for reduced-rank system identification

    PubMed Central

    Chen, Shaojie; Liu, Kai; Yang, Yuguang; Xu, Yuting; Lee, Seonjoo; Lindquist, Martin; Caffo, Brian S.; Vogelstein, Joshua T.

    2018-01-01

    High-dimensional time-series data from a wide variety of domains, such as neuroscience, are being generated every day. Fitting statistical models to such data, to enable parameter estimation and time-series prediction, is an important computational primitive. Existing methods, however, are unable to cope with the high-dimensional nature of these data, due to both computational and statistical reasons. We mitigate both kinds of issues by proposing an M-estimator for Reduced-rank System IDentification ( MR. SID). A combination of low-rank approximations, ℓ1 and ℓ2 penalties, and some numerical linear algebra tricks, yields an estimator that is computationally efficient and numerically stable. Simulations and real data examples demonstrate the usefulness of this approach in a variety of problems. In particular, we demonstrate that MR. SID can accurately estimate spatial filters, connectivity graphs, and time-courses from native resolution functional magnetic resonance imaging data. MR. SID therefore enables big time-series data to be analyzed using standard methods, readying the field for further generalizations including non-linear and non-Gaussian state-space models. PMID:29391659

  11. 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.

  12. Estimating crop yields and crop evapotranspiration distributions from remote sensing and geospatial agricultural data

    NASA Astrophysics Data System (ADS)

    Smith, T.; McLaughlin, D.

    2017-12-01

    Growing more crops to provide a secure food supply to an increasing global population will further stress land and water resources that have already been significantly altered by agriculture. The connection between production and resource use depends on crop yields and unit evapotranspiration (UET) rates that vary greatly, over both time and space. For regional and global analyses of food security it is appropriate to treat yield and UET as uncertain variables conditioned on climatic and soil properties. This study describes how probability distributions of these variables can be estimated by combining remotely sensed land use and evapotranspiration data with in situ agronomic and soils data, all available at different resolutions and coverages. The results reveal the influence of water and temperature stress on crop yield at large spatial scales. They also provide a basis for stochastic modeling and optimization procedures that explicitly account for uncertainty in the environmental factors that affect food production.

  13. Estimating yields of salt- and water-stressed forages with remote sensing in the visible and near infrared.

    PubMed

    Poss, J A; Russell, W B; Grieve, C M

    2006-01-01

    In arid irrigated regions, the proportion of crop production under deficit irrigation with poorer quality water is increasing as demand for fresh water soars and efforts to prevent saline water table development occur. Remote sensing technology to quantify salinity and water stress effects on forage yield can be an important tool to address yield loss potential when deficit irrigating with poor water quality. Two important forages, alfalfa (Medicago sativa L.) and tall wheatgrass (Agropyron elongatum L.), were grown in a volumetric lysimeter facility where rootzone salinity and water content were varied and monitored. Ground-based hyperspectral canopy reflectance in the visible and near infrared (NIR) were related to forage yields from a broad range of salinity and water stress conditions. Canopy reflectance spectra were obtained in the 350- to 1000-nm region from two viewing angles (nadir view, 45 degrees from nadir). Nadir view vegetation indices (VI) were not as strongly correlated with leaf area index changes attributed to water and salinity stress treatments for both alfalfa and wheatgrass. From a list of 71 VIs, two were selected for a multiple linear-regression model that estimated yield under varying salinity and water stress conditions. With data obtained during the second harvest of a three-harvest 100-d growing period, regression coefficients for each crop were developed and then used with the model to estimate fresh weights for preceding and succeeding harvests during the same 100-d interval. The model accounted for 72% of the variation in yields in wheatgrass and 94% in yields of alfalfa within the same salinity and water stress treatment period. The model successfully predicted yield in three out of four cases when applied to the first and third harvest yields. Correlations between indices and yield increased as canopy development progressed. Growth reductions attributed to simultaneous salinity and water stress were well characterized, but the

  14. Estimating climate change, CO2 and technology development effects on wheat yield in northeast Iran

    NASA Astrophysics Data System (ADS)

    Bannayan, M.; Mansoori, H.; Rezaei, E. Eyshi

    2014-04-01

    Wheat is the main food for the majority of Iran's population. Precise estimation of wheat yield change in future is essential for any possible revision of management strategies. The main objective of this study was to evaluate the effects of climate change, CO2 concentration, technology development and their integrated effects on wheat production under future climate change. This study was performed under two scenarios of the IPCC Special Report on Emission Scenarios (SRES): regional economic (A2) and global environmental (B1). Crop production was projected for three future time periods (2020, 2050 and 2080) in comparison with a baseline year (2005) for Khorasan province located in the northeast of Iran. Four study locations in the study area included Mashhad, Birjand, Bojnourd and Sabzevar. The effect of technology development was calculated by fitting a regression equation between the observed wheat yields against historical years considering yield potential increase and yield gap reduction as technology development. Yield relative increase per unit change of CO2 concentration (1 ppm-1) was considered 0.05 % and was used to implement the effect of elevated CO2. The HadCM3 general circulation model along with the CSM-CERES-Wheat crop model were used to project climate change effects on wheat crop yield. Our results illustrate that, among all the factors considered, technology development provided the highest impact on wheat yield change. Highest wheat yield increase across all locations and time periods was obtained under the A2 scenario. Among study locations, Mashhad showed the highest change in wheat yield. Yield change compared to baseline ranged from -28 % to 56 % when the integration of all factors was considered across all locations. It seems that achieving higher yield of wheat in future may be expected in northeast Iran assuming stable improvements in production technology.

  15. Estimating climate change, CO2 and technology development effects on wheat yield in northeast Iran.

    PubMed

    Bannayan, M; Mansoori, H; Rezaei, E Eyshi

    2014-04-01

    Wheat is the main food for the majority of Iran's population. Precise estimation of wheat yield change in future is essential for any possible revision of management strategies. The main objective of this study was to evaluate the effects of climate change, CO2 concentration, technology development and their integrated effects on wheat production under future climate change. This study was performed under two scenarios of the IPCC Special Report on Emission Scenarios (SRES): regional economic (A2) and global environmental (B1). Crop production was projected for three future time periods (2020, 2050 and 2080) in comparison with a baseline year (2005) for Khorasan province located in the northeast of Iran. Four study locations in the study area included Mashhad, Birjand, Bojnourd and Sabzevar. The effect of technology development was calculated by fitting a regression equation between the observed wheat yields against historical years considering yield potential increase and yield gap reduction as technology development. Yield relative increase per unit change of CO2 concentration (1 ppm(-1)) was considered 0.05 % and was used to implement the effect of elevated CO2. The HadCM3 general circulation model along with the CSM-CERES-Wheat crop model were used to project climate change effects on wheat crop yield. Our results illustrate that, among all the factors considered, technology development provided the highest impact on wheat yield change. Highest wheat yield increase across all locations and time periods was obtained under the A2 scenario. Among study locations, Mashhad showed the highest change in wheat yield. Yield change compared to baseline ranged from -28 % to 56 % when the integration of all factors was considered across all locations. It seems that achieving higher yield of wheat in future may be expected in northeast Iran assuming stable improvements in production technology.

  16. Correlation, path analysis and heritability estimation for agronomic traits contribute to yield on soybean

    NASA Astrophysics Data System (ADS)

    Sulistyo, A.; Purwantoro; Sari, K. P.

    2018-01-01

    Selection is a routine activity in plant breeding programs that must be done by plant breeders in obtaining superior plant genotypes. The use of appropriate selection criteria will determine the effectiveness of selection activities. The purpose of this study was to analysis the inheritable agronomic traits that contribute to soybean yield. A total of 91 soybean lines were planted in Muneng Experimental Station, Probolinggo District, East Java Province, Indonesia in 2016. All soybean lines were arranged in randomized complete block design with two replicates. Correlation analysis, path analysis and heritability estimation were performed on days to flowering, days to maturing, plant height, number of branches, number of fertile nodes, number of filled pods, weight of 100 seeds, and yield to determine selection criteria on soybean breeding program. The results showed that the heritability value of almost all agronomic traits observed is high except for the number of fertile nodes with low heritability. The result of correlation analysis shows that days to flowering, plant height and number of fertile nodes have positive correlation with seed yield per plot (0.056, 0.444, and 0.100, respectively). In addition, path analysis showed that plant height and number of fertile nodes have highest positive direct effect on soybean yield. Based on this result, plant height can be selected as one of selection criteria in soybean breeding program to obtain high yielding soybean variety.

  17. 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.

  18. 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

  19. Estimating agricultural yield gap in Africa using MODIS NDVI dataset

    NASA Astrophysics Data System (ADS)

    Luan, Y.; Zhu, W.; Luo, X.; Liu, J.; Cui, X.

    2013-12-01

    Global agriculture has undergone a period of rapid intensification characterized as 'Green Revolution', except for Africa, which is the region most affected by unreliable food access and undernourishment. Increasing crop production will be one of the most challenges and most effectual way to mitigate food insecurity there, as Africa's agricultural yield is on a much lower level comparing to global average. In this study we characterize cropland vegetation phenology in Africa based on MODIS NDVI time series between 2000 and 2012. Cumulated NDVI is a proxy for net primary productivity and used as an indicator for evaluating the potential yield gap in Africa. It is achieved via translating the gap between optimum attainable productivity level in each classification of cropping systems and actual productivity level by the relationship of cumulated NDVI and cereal-equivalent production. The results show most of cropland area in Africa have decreasing trend in cumulated NDVI, distributing in the Nile Delta, Eastern Africa and central of semi-arid to arid savanna area, except significant positive cumulated NDVI trends are mainly found between Senegal and Benin. Using cumulated NDVI and statistics of cereal equivalent production, we find remarkable potential yield gap at the Horn of East Africa (especially in Somalia), Northern Africa (Morocco, Algeria and Tunisia). Meanwhile, countries locating at the savanna area near Sahel desert and South Africa also show significant potential, though they already have a relatively high level of productivity. Our results can help provide policy recommendation for local government or NGO to tackle food security problems by identifying zones with high potential of yield improvement.

  20. PROMAB-GIS: A GIS based Tool for Estimating Runoff and Sediment Yield in running Waters

    NASA Astrophysics Data System (ADS)

    Jenewein, S.; Rinderer, M.; Ploner, A.; Sönser, T.

    2003-04-01

    In recent times settlements have expanded, traffic and tourist activities have increased in most alpine regions. As a consequence, on the one hand humans and goods are affected by natural hazard processes more often, while on the other hand the demand for protection by both technical constructions and planning measures carried out by public authorities is growing. This situation results in an ever stronger need of reproducibility, comparability, transparency of all methods applied in modern natural hazard management. As a contribution to a new way of coping this situation Promab-GIS Version 1.0 has been developed. Promab-Gis has been designed as a model for time- and space-dependent determination of both runoff and bedload transport in rivers of small alpine catchment areas. The estimation of the unit hydrograph relies upon the "rational formula" and the time-area curves of the watershed. The time area diagram is a graph of cumulative drainage area contributing to discharge at the watershed outlet within a specified time of travel. The sediment yield is estimated for each cell of the channel network by determining the actual process type (erosion, transport or accumulation). Two types of transport processes are considered, sediment transport and debris flows. All functions of Promab-GIS are integrated in the graphical user interface of ArcView as pull-up menus and tool buttons. Hence the application of Promab-GIS does not rely on a sophisticated knowledge of GIS in general, respectively the ArcView software. However, despite the use of computer assistance, Promab-GIS still is an expert support system. In order to obtain plausible results, the users must be familiar with all the relevant processes controlling runoff and sediment yield in torrent catchments.

  1. EarthSat spring wheat yield system test 1975, appendix 4

    NASA Technical Reports Server (NTRS)

    1976-01-01

    A computer system is presented which processes meteorological data from both ground observations and meteorologic satellites to define plant weather aspects on a four time per day basis. Plant growth stages are calculated and soil moisture profiles are defined by the system. The EarthSat system assesses plant stress and prepares forecasts of end-of-year yields. The system was used to forecast spring wheat yields in the upper Great Plains states. Hardware and software documentation is provided.

  2. Winter wheat yield estimation of remote sensing research based on WOFOST crop model and leaf area index assimilation

    NASA Astrophysics Data System (ADS)

    Chen, Yanling; Gong, Adu; Li, Jing; Wang, Jingmei

    2017-04-01

    Accurate crop growth monitoring and yield predictive information are significant to improve the sustainable development of agriculture and ensure the security of national food. Remote sensing observation and crop growth simulation models are two new technologies, which have highly potential applications in crop growth monitoring and yield forecasting in recent years. However, both of them have limitations in mechanism or regional application respectively. Remote sensing information can not reveal crop growth and development, inner mechanism of yield formation and the affection of environmental meteorological conditions. Crop growth simulation models have difficulties in obtaining data and parameterization from single-point to regional application. In order to make good use of the advantages of these two technologies, the coupling technique of remote sensing information and crop growth simulation models has been studied. Filtering and optimizing model parameters are key to yield estimation by remote sensing and crop model based on regional crop assimilation. Winter wheat of GaoCheng was selected as the experiment object in this paper. And then the essential data was collected, such as biochemical data and farmland environmental data and meteorological data about several critical growing periods. Meanwhile, the image of environmental mitigation small satellite HJ-CCD was obtained. In this paper, research work and major conclusions are as follows. (1) Seven vegetation indexes were selected to retrieve LAI, and then linear regression model was built up between each of these indexes and the measured LAI. The result shows that the accuracy of EVI model was the highest (R2=0.964 at anthesis stage and R2=0.920 at filling stage). Thus, EVI as the most optimal vegetation index to predict LAI in this paper. (2) EFAST method was adopted in this paper to conduct the sensitive analysis to the 26 initial parameters of the WOFOST model and then a sensitivity index was constructed

  3. Yield and yield gaps in central U.S. corn production systems

    USDA-ARS?s Scientific Manuscript database

    The magnitude of yield gaps (YG) (potential yield – farmer yield) provides some indication of the prospects for increasing crop yield. Quantile regression analysis was applied to county maize (Zea mays L.) yields (1972 – 2011) from Kentucky, Iowa and Nebraska (irrigated) (total of 115 counties) to e...

  4. Assimilation of Remotely Sensed Soil Moisture Profiles into a Crop Modeling Framework for Reliable Yield Estimations

    NASA Astrophysics Data System (ADS)

    Mishra, V.; Cruise, J.; Mecikalski, J. R.

    2017-12-01

    Much effort has been expended recently on the assimilation of remotely sensed soil moisture into operational land surface models (LSM). These efforts have normally been focused on the use of data derived from the microwave bands and results have often shown that improvements to model simulations have been limited due to the fact that microwave signals only penetrate the top 2-5 cm of the soil surface. It is possible that model simulations could be further improved through the introduction of geostationary satellite thermal infrared (TIR) based root zone soil moisture in addition to the microwave deduced surface estimates. In this study, root zone soil moisture estimates from the TIR based Atmospheric Land Exchange Inverse (ALEXI) model were merged with NASA Soil Moisture Active Passive (SMAP) based surface estimates through the application of informational entropy. Entropy can be used to characterize the movement of moisture within the vadose zone and accounts for both advection and diffusion processes. The Principle of Maximum Entropy (POME) can be used to derive complete soil moisture profiles and, fortuitously, only requires a surface boundary condition as well as the overall mean moisture content of the soil column. A lower boundary can be considered a soil parameter or obtained from the LSM itself. In this study, SMAP provided the surface boundary while ALEXI supplied the mean and the entropy integral was used to tie the two together and produce the vertical profile. However, prior to the merging, the coarse resolution (9 km) SMAP data were downscaled to the finer resolution (4.7 km) ALEXI grid. The disaggregation scheme followed the Soil Evaporative Efficiency approach and again, all necessary inputs were available from the TIR model. The profiles were then assimilated into a standard agricultural crop model (Decision Support System for Agrotechnology, DSSAT) via the ensemble Kalman Filter. The study was conducted over the Southeastern United States for the

  5. Hybrid estimation of complex systems.

    PubMed

    Hofbaur, Michael W; Williams, Brian C

    2004-10-01

    Modern automated systems evolve both continuously and discretely, and hence require estimation techniques that go well beyond the capability of a typical Kalman Filter. Multiple model (MM) estimation schemes track these system evolutions by applying a bank of filters, one for each discrete system mode. Modern systems, however, are often composed of many interconnected components that exhibit rich behaviors, due to complex, system-wide interactions. Modeling these systems leads to complex stochastic hybrid models that capture the large number of operational and failure modes. This large number of modes makes a typical MM estimation approach infeasible for online estimation. This paper analyzes the shortcomings of MM estimation, and then introduces an alternative hybrid estimation scheme that can efficiently estimate complex systems with large number of modes. It utilizes search techniques from the toolkit of model-based reasoning in order to focus the estimation on the set of most likely modes, without missing symptoms that might be hidden amongst the system noise. In addition, we present a novel approach to hybrid estimation in the presence of unknown behavioral modes. This leads to an overall hybrid estimation scheme for complex systems that robustly copes with unforeseen situations in a degraded, but fail-safe manner.

  6. Estimation of genetic parameters and selection of high-yielding, upright common bean lines with slow seed-coat darkening.

    PubMed

    Alvares, R C; Silva, F C; Melo, L C; Melo, P G S; Pereira, H S

    2016-11-21

    Slow seed coat darkening is desirable in common bean cultivars and genetic parameters are important to define breeding strategies. The aims of this study were to estimate genetic parameters for plant architecture, grain yield, grain size, and seed-coat darkening in common bean; identify any genetic association among these traits; and select lines that associate desirable phenotypes for these traits. Three experiments were set up in the winter 2012 growing season, in Santo Antônio de Goiás and Brasília, Brazil, including 220 lines obtained from four segregating populations and five parents. A triple lattice 15 x 15 experimental design was used. The traits evaluated were plant architecture, grain yield, grain size, and seed-coat darkening. Analyses of variance were carried out and genetic parameters such as heritability, gain expected from selection, and correlations, were estimated. For selection of superior lines, a "weight-free and parameter-free" index was used. The estimates of genetic variance, heritability, and gain expected from selection were high, indicating good possibility for success in selection of the four traits. The genotype x environment interaction was proportionally more important for yield than for the other traits. There was no strong genetic correlation observed among the four traits, which indicates the possibility of selection of superior lines with many traits. Considering simultaneous selection, it was not possible to join high genetic gains for the four traits. Forty-four lines that combined high yield, more upright plant architecture, slow darkening grains, and commercial grade size were selected.

  7. 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.

  8. 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.

  9. Estimation of genetic parameters for heat stress, including dominance gene effects, on milk yield in Thai Holstein dairy cattle.

    PubMed

    Boonkum, Wuttigrai; Duangjinda, Monchai

    2015-03-01

    Heat stress in tropical regions is a major cause that strongly negatively affects to milk production in dairy cattle. Genetic selection for dairy heat tolerance is powerful technique to improve genetic performance. Therefore, the current study aimed to estimate genetic parameters and investigate the threshold point of heat stress for milk yield. Data included 52 701 test-day milk yield records for the first parity from 6247 Thai Holstein dairy cattle, covering the period 1990 to 2007. The random regression test day model with EM-REML was used to estimate variance components, genetic parameters and milk production loss. A decline in milk production was found when temperature and humidity index (THI) exceeded a threshold of 74, also it was associated with the high percentage of Holstein genetics. All variance component estimates increased with THI. The estimate of heritability of test-day milk yield was 0.231. Dominance variance as a proportion to additive variance (0.035) indicated that non-additive effects might not be of concern for milk genetics studies in Thai Holstein cattle. Correlations between genetic and permanent environmental effects, for regular conditions and due to heat stress, were - 0.223 and - 0.521, respectively. The heritability and genetic correlations from this study show that simultaneous selection for milk production and heat tolerance is possible. © 2014 Japanese Society of Animal Science.

  10. 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.

  11. Maximal yields from multispecies fisheries systems: rules for systems with multiple trophic levels.

    PubMed

    Matsuda, Hiroyuki; Abrams, Peter A

    2006-02-01

    Increasing centralization of the control of fisheries combined with increased knowledge of food-web relationships is likely to lead to attempts to maximize economic yield from entire food webs. With the exception of predator-prey systems, we lack any analysis of the nature of such yield-maximizing strategies. We use simple food-web models to investigate the nature of yield- or profit-maximizing exploitation of communities including two types of three-species food webs and a variety of six-species systems with as many as five trophic levels. These models show that, for most webs, relatively few species are harvested at equilibrium and that a significant fraction of the species is lost from the web. These extinctions occur for two reasons: (1) indirect effects due to harvesting of species that had positive effects on the extinct species, and (2) intentional eradication of species that are not themselves valuable, but have negative effects on more valuable species. In most cases, the yield-maximizing harvest involves taking only species from one trophic level. In no case was an unharvested top predator part of the yield-maximizing strategy. Analyses reveal that the existence of direct density dependence in consumers has a large effect on the nature of the optimal harvest policy, typically resulting in harvest of a larger number of species. A constraint that all species must be retained in the system (a "constraint of biodiversity conservation") usually increases the number of species and trophic levels harvested at the yield-maximizing policy. The reduction in total yield caused by such a constraint is modest for most food webs but can be over 90% in some cases. Independent harvesting of species within the web can also cause extinctions but is less likely to do so.

  12. On-line prediction of yield grade, longissimus muscle area, preliminary yield grade, adjusted preliminary yield grade, and marbling score using the MARC beef carcass image analysis system.

    PubMed

    Shackelford, S D; Wheeler, T L; Koohmaraie, M

    2003-01-01

    The present experiment was conducted to evaluate the ability of the U.S. Meat Animal Research Center's beef carcass image analysis system to predict calculated yield grade, longissimus muscle area, preliminary yield grade, adjusted preliminary yield grade, and marbling score under commercial beef processing conditions. In two commercial beef-processing facilities, image analysis was conducted on 800 carcasses on the beef-grading chain immediately after the conventional USDA beef quality and yield grades were applied. Carcasses were blocked by plant and observed calculated yield grade. The carcasses were then separated, with 400 carcasses assigned to a calibration data set that was used to develop regression equations, and the remaining 400 carcasses assigned to a prediction data set used to validate the regression equations. Prediction equations, which included image analysis variables and hot carcass weight, accounted for 90, 88, 90, 88, and 76% of the variation in calculated yield grade, longissimus muscle area, preliminary yield grade, adjusted preliminary yield grade, and marbling score, respectively, in the prediction data set. In comparison, the official USDA yield grade as applied by online graders accounted for 73% of the variation in calculated yield grade. The technology described herein could be used by the beef industry to more accurately determine beef yield grades; however, this system does not provide an accurate enough prediction of marbling score to be used without USDA grader interaction for USDA quality grading.

  13. The effect of flow data resolution on sediment yield estimation and channel design

    NASA Astrophysics Data System (ADS)

    Rosburg, Tyler T.; Nelson, Peter A.; Sholtes, Joel S.; Bledsoe, Brian P.

    2016-07-01

    The decision to use either daily-averaged or sub-daily streamflow records has the potential to impact the calculation of sediment transport metrics and stream channel design. Using bedload and suspended load sediment transport measurements collected at 138 sites across the United States, we calculated the effective discharge, sediment yield, and half-load discharge using sediment rating curves over long time periods (median record length = 24 years) with both daily-averaged and sub-daily streamflow records. A comparison of sediment transport metrics calculated with both daily-average and sub-daily stream flow data at each site showed that daily-averaged flow data do not adequately represent the magnitude of high stream flows at hydrologically flashy sites. Daily-average stream flow data cause an underestimation of sediment transport and sediment yield (including the half-load discharge) at flashy sites. The degree of underestimation was correlated with the level of flashiness and the exponent of the sediment rating curve. No consistent relationship between the use of either daily-average or sub-daily streamflow data and the resultant effective discharge was found. When used in channel design, computed sediment transport metrics may have errors due to flow data resolution, which can propagate into design slope calculations which, if implemented, could lead to unwanted aggradation or degradation in the design channel. This analysis illustrates the importance of using sub-daily flow data in the calculation of sediment yield in urbanizing or otherwise flashy watersheds. Furthermore, this analysis provides practical charts for estimating and correcting these types of underestimation errors commonly incurred in sediment yield calculations.

  14. Estimation of sediment yield from subsequent expanded landslides after heavy rainfalls : a case study in central Hokkaido, Japan

    NASA Astrophysics Data System (ADS)

    Koshimizu, K.; Uchida, T.

    2015-12-01

    Initial large-scale sediment yield caused by heavy rainfall or major storms have made a strong impression on us. Previous studies focusing on landslide management investigated the initial sediment movement and its mechanism. However, integrated management of catchment-scale sediment movements requires estimating the sediment yield, which is produced by the subsequent expanded landslides due to rainfall, in addition to the initial landslide movement. This study presents a quantitative analysis of expanded landslides by surveying the Shukushubetsu River basin, at the foot of the Hidaka mountain range in central Hokkaido, Japan. This area recorded heavy rainfall in 2003, reaching a maximum daily precipitation of 388 mm. We extracted the expanded landslides from 2003 to 2008 using aerial photographs taken over the river area. In particular, we calculated the probability of expansion for each landslide, the ratio of the landslide area in 2008 as compared with that in 2003, and the amount of the expanded landslide area corresponding to the initial landslide area. As a result, it is estimated 24% about probability of expansion for each landslide. In addition, each expanded landslide area is smaller than the initial landslide area. Furthermore, the amount of each expanded landslide area in 2008 is approximately 7% of their landslide area in 2003. Therefore, the sediment yield from subsequent expanded landslides is equal to or slightly greater than the sediment yield in a typical base flow. Thus, we concluded that the amount of sediment yield from subsequent expanded landslides is lower than that of initial large-scale sediment yield caused by a heavy rainfall in terms of effect on management of catchment-scale sediment movement.

  15. 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...

  16. Using operational data to estimate the reliable yields of water-supply wells

    NASA Astrophysics Data System (ADS)

    Misstear, Bruce D. R.; Beeson, Sarah

    The reliable yield of a water-supply well depends on many different factors, including the properties of the well and the aquifer; the capacities of the pumps, raw-water mains, and treatment works; the interference effects from other wells; and the constraints imposed by ion licences, water quality, and environmental issues. A relatively simple methodology for estimating reliable yields has been developed that takes into account all of these factors. The methodology is based mainly on an analysis of water-level and source-output data, where such data are available. Good operational data are especially important when dealing with wells in shallow, unconfined, fissure-flow aquifers, where actual well performance may vary considerably from that predicted using a more analytical approach. Key issues in the yield-assessment process are the identification of a deepest advisable pumping water level, and the collection of the appropriate well, aquifer, and operational data. Although developed for water-supply operators in the United Kingdom, this approach to estimating the reliable yields of water-supply wells using operational data should be applicable to a wide range of hydrogeological conditions elsewhere. Résumé La productivité d'un puits capté pour l'adduction d'eau potable dépend de différents facteurs, parmi lesquels les propriétés du puits et de l'aquifère, la puissance des pompes, le traitement des eaux brutes, les effets d'interférences avec d'autres puits et les contraintes imposées par les autorisations d'exploitation, par la qualité des eaux et par les conditions environnementales. Une méthodologie relativement simple d'estimation de la productivité qui prenne en compte tous ces facteurs a été mise au point. Cette méthodologie est basée surtout sur une analyse des données concernant le niveau piézométrique et le débit de prélèvement, quand ces données sont disponibles. De bonnes données opérationnelles sont particuli

  17. Genetic parameters for test-day yield of milk, fat and protein in buffaloes estimated by random regression models.

    PubMed

    Aspilcueta-Borquis, Rúsbel R; Araujo Neto, Francisco R; Baldi, Fernando; Santos, Daniel J A; Albuquerque, Lucia G; Tonhati, Humberto

    2012-08-01

    The test-day yields of milk, fat and protein were analysed from 1433 first lactations of buffaloes of the Murrah breed, daughters of 113 sires from 12 herds in the state of São Paulo, Brazil, born between 1985 and 2007. For the test-day yields, 10 monthly classes of lactation days were considered. The contemporary groups were defined as the herd-year-month of the test day. Random additive genetic, permanent environmental and residual effects were included in the model. The fixed effects considered were the contemporary group, number of milkings (1 or 2 milkings), linear and quadratic effects of the covariable cow age at calving and the mean lactation curve of the population (modelled by third-order Legendre orthogonal polynomials). The random additive genetic and permanent environmental effects were estimated by means of regression on third- to sixth-order Legendre orthogonal polynomials. The residual variances were modelled with a homogenous structure and various heterogeneous classes. According to the likelihood-ratio test, the best model for milk and fat production was that with four residual variance classes, while a third-order Legendre polynomial was best for the additive genetic effect for milk and fat yield, a fourth-order polynomial was best for the permanent environmental effect for milk production and a fifth-order polynomial was best for fat production. For protein yield, the best model was that with three residual variance classes and third- and fourth-order Legendre polynomials were best for the additive genetic and permanent environmental effects, respectively. The heritability estimates for the characteristics analysed were moderate, varying from 0·16±0·05 to 0·29±0·05 for milk yield, 0·20±0·05 to 0·30±0·08 for fat yield and 0·18±0·06 to 0·27±0·08 for protein yield. The estimates of the genetic correlations between the tests varied from 0·18±0·120 to 0·99±0·002; from 0·44±0·080 to 0·99±0·004; and from 0·41±0·080 to

  18. 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.

  19. Greenhouse tomato limited cluster production systems: crop management practices affect yield

    NASA Technical Reports Server (NTRS)

    Logendra, L. S.; Gianfagna, T. J.; Specca, D. R.; Janes, H. W.

    2001-01-01

    Limited-cluster production systems may be a useful strategy to increase crop production and profitability for the greenhouse tomato (Lycopersicon esculentum Mill). In this study, using an ebb-and-flood hydroponics system, we modified plant architecture and spacing and determined the effects on fruit yield and harvest index at two light levels. Single-cluster plants pruned to allow two leaves above the cluster had 25% higher fruit yields than did plants pruned directly above the cluster; this was due to an increase in fruit weight, not fruit number. Both fruit yield and harvest index were greater for all single-cluster plants at the higher light level because of increases in both fruit weight and fruit number. Fruit yield for two-cluster plants was 30% to 40% higher than for single-cluster plants, and there was little difference in the dates or length of the harvest period. Fruit yield for three-cluster plants was not significantly different from that of two-cluster plants; moreover, the harvest period was delayed by 5 days. Plant density (5.5, 7.4, 9.2 plants/m2) affected fruit yield/plant, but not fruit yield/unit area. Given the higher costs for materials and labor associated with higher plant densities, a two-cluster crop at 5.5 plants/m2 with two leaves above the cluster was the best of the production system strategies tested.

  20. Semiblind channel estimation for MIMO-OFDM systems

    NASA Astrophysics Data System (ADS)

    Chen, Yi-Sheng; Song, Jyu-Han

    2012-12-01

    This article proposes a semiblind channel estimation method for multiple-input multiple-output orthogonal frequency-division multiplexing systems based on circular precoding. Relying on the precoding scheme at the transmitters, the autocorrelation matrix of the received data induces a structure relating the outer product of the channel frequency response matrix and precoding coefficients. This structure makes it possible to extract information about channel product matrices, which can be used to form a Hermitian matrix whose positive eigenvalues and corresponding eigenvectors yield the channel impulse response matrix. This article also tests the resistance of the precoding design to finite-sample estimation errors, and explores the effects of the precoding scheme on channel equalization by performing pairwise error probability analysis. The proposed method is immune to channel zero locations, and is reasonably robust to channel order overestimation. The proposed method is applicable to the scenarios in which the number of transmitters exceeds that of the receivers. Simulation results demonstrate the performance of the proposed method and compare it with some existing methods.

  1. Estimating bottomland hardwood growth and yield

    Treesearch

    1989-01-01

    Most bottomland hardwoods grow on very productive sites-site index 70 or more. A fully stocked immature stand (table 1, fig. 1) requires tending throughout its life. The goal is to attain a stand of approximately 50 high quality trees of commercial species per acre at maturity. Releasing these crop trees can result in the cumulative yield of 2,000-4,000 board feet per...

  2. Ground-Water Contributions to Reservoir Storage and the Effect on Estimates of Firm Yield for Reservoirs in Massachusetts

    USGS Publications Warehouse

    Archfield, Stacey A.; Carlson, Carl S.

    2006-01-01

    Potential ground-water contributions to reservoir storage were determined for nine reservoirs in Massachusetts that had shorelines in contact with sand and gravel aquifers. The effect of ground water on firm yield was not only substantial, but furthermore, the firm yield of a reservoir in contact with a sand and gravel aquifer was always greater when the ground-water contribution was included in the water balance. Increases in firm yield ranged from 2 to 113 percent, with a median increase in firm yield of 10 percent. Additionally, the increase in firm yield in two reservoirs was greater than 85 percent. This study identified a set of equations that are based on an analytical solution to the ground-water-flow equation for the case of one-dimensional flow in a finite-width aquifer bounded by a linear surface-water feature such as a stream. These equations, which require only five input variables, were incorporated into an existing firm-yield-estimator (FYE) model, and the potential effect of ground water on firm yield was evaluated. To apply the FYE model to a reservoir in Massachusetts, the model requires that the drainage area to the reservoir be clearly defined and that some surface water flows into the reservoir. For surface-water-body shapes having a more realistic representation of a reservoir shoreline than a stream, a comparison of ground-water-flow rates simulated by the ground-water equations with flow rates simulated by a two-dimensional, finite-difference ground-water-flow model indicate that the agreement between the simulated flow rates is within ?10 percent when the ratio of the distance from the reservoir shoreline to the aquifer boundary to the length of shoreline in contact with the aquifer is between values of 0.5 and 3.5. Idealized reservoir-aquifer systems were assumed to verify that the ground-water-flow equations were implemented correctly into the existing FYE model; however, the modified FYE model has not been validated through a comparison

  3. Conjunctive-use optimization model and sustainable-yield estimation for the Sparta aquifer of southeastern Arkansas and north-central Louisiana

    USGS Publications Warehouse

    McKee, Paul W.; Clark, Brian R.; Czarnecki, John B.

    2004-01-01

    Conjunctive-use optimization modeling was done to assist water managers and planners by estimating the maximum amount of ground water that hypothetically could be withdrawn from wells within the Sparta aquifer indefinitely without violating hydraulic-head or stream-discharge constraints. The Sparta aquifer is largely a confined aquifer of regional importance that comprises a sequence of unconsolidated sand units that are contained within the Sparta Sand. In 2000, more than 35.4 million cubic feet per day (Mft3/d) of water were withdrawn from the aquifer by more than 900 wells, primarily for industry, municipal supply, and crop irrigation in Arkansas. Continued, heavy withdrawals from the aquifer have caused several large cones of depression, lowering hydraulic heads below the top of the Sparta Sand in parts of Union and Columbia Counties and several areas in north-central Louisiana. Problems related to overdraft in the Sparta aquifer can result in increased drilling and pumping costs, reduced well yields, and degraded water quality in areas of large drawdown. A finite-difference ground-water flow model was developed for the Sparta aquifer using MODFLOW, primarily in eastern and southeastern Arkansas and north-central Louisiana. Observed aquifer conditions in 1997 supported by numerical simulations of ground-water flow show that continued pumping at withdrawal rates representative of 1990 - 1997 rates cannot be sustained indefinitely without causing hydraulic heads to drop substantially below the top of the Sparta Sand in southern Arkansas and north-central Louisiana. Areas of ground-water levels below the top of the Sparta Sand have been designated as Critical Ground-Water Areas by the State of Arkansas. A steady-state conjunctive-use optimization model was developed to simulate optimized surface-water and ground-water withdrawals while maintaining hydraulic-head and streamflow constraints, thus determining the 'sustainable yield' for the aquifer. Initial attempts

  4. Development of a telemetry and yield-mapping system of olive harvester.

    PubMed

    Castillo-Ruiz, Francisco J; Pérez-Ruiz, Manuel; Blanco-Roldán, Gregorio L; Gil-Ribes, Jesús A; Agüera, Juan

    2015-02-10

    Sensors, communication systems and geo-reference units are required to achieve an optimized management of agricultural inputs with respect to the economic and environmental aspects of olive groves. In this study, three commercial olive harvesters were tracked during two harvesting seasons in Spain and Chile using remote and autonomous equipment that was developed to determine their time efficiency and effective based on canopy shaking for fruit detachment. These harvesters work in intensive/high-density (HD) and super-high-density (SHD) olive orchards. A GNSS (Global Navigation Satellite System) and GSM (Global System for Mobile Communications) device was installed to track these harvesters. The GNSS receiver did not affect the driver's work schedule. Time elements methodology was adapted to the remote data acquisition system. The effective field capacity and field efficiency were investigated. In addition, the field shape, row length, angle between headland alley and row, and row alley width were measured to determinate the optimum orchard design parameters value. The SHD olive harvester showed significant lower effective field capacity values when alley width was less than 4 m. In addition, a yield monitor was developed and installed on a traditional olive harvester to obtain a yield map from the harvested area. The hedge straddle harvester stood out for its highly effective field capacity; nevertheless, a higher field efficiency was provided by a non-integral lateral canopy shaker. All of the measured orchard parameters have influenced machinery yields, whether effective field capacity or field efficiency. A saving of 40% in effective field capacity was achieved with a reduction from 4 m or higher to 3.5 m in alley width for SHD olive harvester. A yield map was plotted using data that were acquired by a yield monitor, reflecting the yield gradient in spite of the larger differences between tree yields.

  5. Development of a Telemetry and Yield-Mapping System of Olive Harvester

    PubMed Central

    Castillo-Ruiz, Francisco J.; Pérez-Ruiz, Manuel; Blanco-Roldán, Gregorio L.; Gil-Ribes, Jesús A.; Agüera, Juan

    2015-01-01

    Sensors, communication systems and geo-reference units are required to achieve an optimized management of agricultural inputs with respect to the economic and environmental aspects of olive groves. In this study, three commercial olive harvesters were tracked during two harvesting seasons in Spain and Chile using remote and autonomous equipment that was developed to determine their time efficiency and effective based on canopy shaking for fruit detachment. These harvesters work in intensive/high-density (HD) and super-high-density (SHD) olive orchards. A GNSS (Global Navigation Satellite System) and GSM (Global System for Mobile Communications) device was installed to track these harvesters. The GNSS receiver did not affect the driver’s work schedule. Time elements methodology was adapted to the remote data acquisition system. The effective field capacity and field efficiency were investigated. In addition, the field shape, row length, angle between headland alley and row, and row alley width were measured to determinate the optimum orchard design parameters value. The SHD olive harvester showed significant lower effective field capacity values when alley width was less than 4 m. In addition, a yield monitor was developed and installed on a traditional olive harvester to obtain a yield map from the harvested area. The hedge straddle harvester stood out for its highly effective field capacity; nevertheless, a higher field efficiency was provided by a non-integral lateral canopy shaker. All of the measured orchard parameters have influenced machinery yields, whether effective field capacity or field efficiency. A saving of 40% in effective field capacity was achieved with a reduction from 4 m or higher to 3.5 m in alley width for SHD olive harvester. A yield map was plotted using data that were acquired by a yield monitor, reflecting the yield gradient in spite of the larger differences between tree yields. PMID:25675283

  6. Explosive Yield Estimation using Fourier Amplitude Spectra of Velocity Histories

    NASA Astrophysics Data System (ADS)

    Steedman, D. W.; Bradley, C. R.

    2016-12-01

    The Source Physics Experiment (SPE) is a series of explosive shots of various size detonated at varying depths in a borehole in jointed granite. The testbed includes an extensive array of accelerometers for measuring the shock environment close-in to the explosive source. One goal of SPE is to develop greater understanding of the explosion phenomenology in all regimes: from near-source, non-linear response to the far-field linear elastic region, and connecting the analyses from the respective regimes. For example, near-field analysis typically involves review of kinematic response (i.e., acceleration, velocity and displacement) in the time domain and looks at various indicators (e.g., peaks, pulse duration) to facilitate comparison among events. Review of far-field data more often is based on study of response in the frequency domain to facilitate comparison of event magnitudes. To try to "bridge the gap" between approaches, we have developed a scaling law for Fourier amplitude spectra of near-field velocity histories that successfully collapses data from a wide range of yields (100 kg to 5000 kg) and range to sensors in jointed granite. Moreover, we show that we can apply this scaling law to data from a new event to accurately estimate the explosive yield of that event. This approach presents a new way of working with near-field data that will be more compatible with traditional methods of analysis of seismic data and should serve to facilitate end-to-end event analysis. The goal is that this new approach to data analysis will eventually result in improved methods for discrimination of event type (i.e., nuclear or chemical explosion, or earthquake) and magnitude.

  7. Source spectral variation and yield estimation for small, near-source explosions

    NASA Astrophysics Data System (ADS)

    Yoo, S.; Mayeda, K. M.

    2012-12-01

    Significant S-wave generation is always observed from explosion sources which can lead to difficulty in discriminating explosions from natural earthquakes. While there are numerous S-wave generation mechanisms that are currently the topic of significant research, the mechanisms all remain controversial and appear to be dependent upon the near-source emplacement conditions of that particular explosion. To better understand the generation and partitioning of the P and S waves from explosion sources and to enhance the identification and discrimination capability of explosions, we investigate near-source explosion data sets from the 2008 New England Damage Experiment (NEDE), the Humble-Redwood (HR) series of explosions, and a Massachusetts quarry explosion experiment. We estimate source spectra and characteristic source parameters using moment tensor inversions, direct P and S waves multi-taper analysis, and improved coda spectral analysis using high quality waveform records from explosions from a variety of emplacement conditions (e.g., slow/fast burning explosive, fully tamped, partially tamped, single/ripple-fired, and below/above ground explosions). The results from direct and coda waves are compared to theoretical explosion source model predictions. These well-instrumented experiments provide us with excellent data from which to document the characteristic spectral shape, relative partitioning between P and S-waves, and amplitude/yield dependence as a function of HOB/DOB. The final goal of this study is to populate a comprehensive seismic source reference database for small yield explosions based on the results and to improve nuclear explosion monitoring capability.

  8. Multiple-trait random regression models for the estimation of genetic parameters for milk, fat, and protein yield in buffaloes.

    PubMed

    Borquis, Rusbel Raul Aspilcueta; Neto, Francisco Ribeiro de Araujo; Baldi, Fernando; Hurtado-Lugo, Naudin; de Camargo, Gregório M F; Muñoz-Berrocal, Milthon; Tonhati, Humberto

    2013-09-01

    In this study, genetic parameters for test-day milk, fat, and protein yield were estimated for the first lactation. The data analyzed consisted of 1,433 first lactations of Murrah buffaloes, daughters of 113 sires from 12 herds in the state of São Paulo, Brazil, with calvings from 1985 to 2007. Ten-month classes of lactation days were considered for the test-day yields. The (co)variance components for the 3 traits were estimated using the regression analyses by Bayesian inference applying an animal model by Gibbs sampling. The contemporary groups were defined as herd-year-month of the test day. In the model, the random effects were additive genetic, permanent environment, and residual. The fixed effects were contemporary group and number of milkings (1 or 2), the linear and quadratic effects of the covariable age of the buffalo at calving, as well as the mean lactation curve of the population, which was modeled by orthogonal Legendre polynomials of fourth order. The random effects for the traits studied were modeled by Legendre polynomials of third and fourth order for additive genetic and permanent environment, respectively, the residual variances were modeled considering 4 residual classes. The heritability estimates for the traits were moderate (from 0.21-0.38), with higher estimates in the intermediate lactation phase. The genetic correlation estimates within and among the traits varied from 0.05 to 0.99. The results indicate that the selection for any trait test day will result in an indirect genetic gain for milk, fat, and protein yield in all periods of the lactation curve. The accuracy associated with estimated breeding values obtained using multi-trait random regression was slightly higher (around 8%) compared with single-trait random regression. This difference may be because to the greater amount of information available per animal. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  9. Assessing the likely value of gravity and drawdown measurements to constrain estimates of hydraulic conductivity and specific yield during unconfined aquifer testing

    USGS Publications Warehouse

    Blainey, Joan B.; Ferré, Ty P.A.; Cordova, Jeffrey T.

    2007-01-01

    Pumping of an unconfined aquifer can cause local desaturation detectable with high‐resolution gravimetry. A previous study showed that signal‐to‐noise ratios could be predicted for gravity measurements based on a hydrologic model. We show that although changes should be detectable with gravimeters, estimations of hydraulic conductivity and specific yield based on gravity data alone are likely to be unacceptably inaccurate and imprecise. In contrast, a transect of low‐quality drawdown data alone resulted in accurate estimates of hydraulic conductivity and inaccurate and imprecise estimates of specific yield. Combined use of drawdown and gravity data, or use of high‐quality drawdown data alone, resulted in unbiased and precise estimates of both parameters. This study is an example of the value of a staged assessment regarding the likely significance of a new measurement method or monitoring scenario before collecting field data.

  10. Random Regression Models Using Legendre Polynomials to Estimate Genetic Parameters for Test-day Milk Protein Yields in Iranian Holstein Dairy Cattle.

    PubMed

    Naserkheil, Masoumeh; Miraie-Ashtiani, Seyed Reza; Nejati-Javaremi, Ardeshir; Son, Jihyun; Lee, Deukhwan

    2016-12-01

    The objective of this study was to estimate the genetic parameters of milk protein yields in Iranian Holstein dairy cattle. A total of 1,112,082 test-day milk protein yield records of 167,269 first lactation Holstein cows, calved from 1990 to 2010, were analyzed. Estimates of the variance components, heritability, and genetic correlations for milk protein yields were obtained using a random regression test-day model. Milking times, herd, age of recording, year, and month of recording were included as fixed effects in the model. Additive genetic and permanent environmental random effects for the lactation curve were taken into account by applying orthogonal Legendre polynomials of the fourth order in the model. The lowest and highest additive genetic variances were estimated at the beginning and end of lactation, respectively. Permanent environmental variance was higher at both extremes. Residual variance was lowest at the middle of the lactation and contrarily, heritability increased during this period. Maximum heritability was found during the 12th lactation stage (0.213±0.007). Genetic, permanent, and phenotypic correlations among test-days decreased as the interval between consecutive test-days increased. A relatively large data set was used in this study; therefore, the estimated (co)variance components for random regression coefficients could be used for national genetic evaluation of dairy cattle in Iran.

  11. Random Regression Models Using Legendre Polynomials to Estimate Genetic Parameters for Test-day Milk Protein Yields in Iranian Holstein Dairy Cattle

    PubMed Central

    Naserkheil, Masoumeh; Miraie-Ashtiani, Seyed Reza; Nejati-Javaremi, Ardeshir; Son, Jihyun; Lee, Deukhwan

    2016-01-01

    The objective of this study was to estimate the genetic parameters of milk protein yields in Iranian Holstein dairy cattle. A total of 1,112,082 test-day milk protein yield records of 167,269 first lactation Holstein cows, calved from 1990 to 2010, were analyzed. Estimates of the variance components, heritability, and genetic correlations for milk protein yields were obtained using a random regression test-day model. Milking times, herd, age of recording, year, and month of recording were included as fixed effects in the model. Additive genetic and permanent environmental random effects for the lactation curve were taken into account by applying orthogonal Legendre polynomials of the fourth order in the model. The lowest and highest additive genetic variances were estimated at the beginning and end of lactation, respectively. Permanent environmental variance was higher at both extremes. Residual variance was lowest at the middle of the lactation and contrarily, heritability increased during this period. Maximum heritability was found during the 12th lactation stage (0.213±0.007). Genetic, permanent, and phenotypic correlations among test-days decreased as the interval between consecutive test-days increased. A relatively large data set was used in this study; therefore, the estimated (co)variance components for random regression coefficients could be used for national genetic evaluation of dairy cattle in Iran. PMID:26954192

  12. High-yield maize with large net energy yield and small global warming intensity

    PubMed Central

    Grassini, Patricio; Cassman, Kenneth G.

    2012-01-01

    Addressing concerns about future food supply and climate change requires management practices that maximize productivity per unit of arable land while reducing negative environmental impact. On-farm data were evaluated to assess energy balance and greenhouse gas (GHG) emissions of irrigated maize in Nebraska that received large nitrogen (N) fertilizer (183 kg of N⋅ha−1) and irrigation water inputs (272 mm or 2,720 m3 ha−1). Although energy inputs (30 GJ⋅ha−1) were larger than those reported for US maize systems in previous studies, irrigated maize in central Nebraska achieved higher grain and net energy yields (13.2 Mg⋅ha−1 and 159 GJ⋅ha−1, respectively) and lower GHG-emission intensity (231 kg of CO2e⋅Mg−1 of grain). Greater input-use efficiencies, especially for N fertilizer, were responsible for better performance of these irrigated systems, compared with much lower-yielding, mostly rainfed maize systems in previous studies. Large variation in energy inputs and GHG emissions across irrigated fields in the present study resulted from differences in applied irrigation water amount and imbalances between applied N inputs and crop N demand, indicating potential to further improve environmental performance through better management of these inputs. Observed variation in N-use efficiency, at any level of applied N inputs, suggests that an N-balance approach may be more appropriate for estimating soil N2O emissions than the Intergovernmental Panel on Climate Change approach based on a fixed proportion of applied N. Negative correlation between GHG-emission intensity and net energy yield supports the proposition that achieving high yields, large positive energy balance, and low GHG emissions in intensive cropping systems are not conflicting goals. PMID:22232684

  13. 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

  14. Genetic correlations among body condition score, yield, and fertility in first-parity cows estimated by random regression models.

    PubMed

    Veerkamp, R F; Koenen, E P; De Jong, G

    2001-10-01

    Twenty type classifiers scored body condition (BCS) of 91,738 first-parity cows from 601 sires and 5518 maternal grandsires. Fertility data during first lactation were extracted for 177,220 cows, of which 67,278 also had a BCS observation, and first-lactation 305-d milk, fat, and protein yields were added for 180,631 cows. Heritabilities and genetic correlations were estimated using a sire-maternal grandsire model. Heritability of BCS was 0.38. Heritabilities for fertility traits were low (0.01 to 0.07), but genetic standard deviations were substantial, 9 d for days to first service and calving interval, 0.25 for number of services, and 5% for first-service conception. Phenotypic correlations between fertility and yield or BCS were small (-0.15 to 0.20). Genetic correlations between yield and all fertility traits were unfavorable (0.37 to 0.74). Genetic correlations with BCS were between -0.4 and -0.6 for calving interval and days to first service. Random regression analysis (RR) showed that correlations changed with days in milk for BCS. Little agreement was found between variances and correlations from RR, and analysis including a single month (mo 1 to 10) of data for BCS, especially during early and late lactation. However, this was due to excluding data from the conventional analysis, rather than due to the polynomials used. RR and a conventional five-traits model where BCS in mo 1, 4, 7, and 10 was treated as a separate traits (plus yield or fertility) gave similar results. Thus a parsimonious random regression model gave more realistic estimates for the (co)variances than a series of bivariate analysis on subsets of the data for BCS. A higher genetic merit for yield has unfavorable effects on fertility, but the genetic correlation suggests that BCS (at some stages of lactation) might help to alleviate the unfavorable effect of selection for higher yield on fertility.

  15. Measurement and Estimation of the 99Mo Production Yield by 100Mo(n,2n)99Mo

    NASA Astrophysics Data System (ADS)

    Minato, Futoshi; Tsukada, Kazuaki; Sato, Nozomi; Watanabe, Satoshi; Saeki, Hideya; Kawabata, Masako; Hashimoto, Shintaro; Nagai, Yasuki

    2017-11-01

    We, for the first time, measured the yield of 99Mo, the mother nuclide of 99mTc used in nuclear medicine diagnostic procedures, produced by the 100Mo(n,2n)99Mo reaction with accelerator neutrons. The neutrons with a continuous energy spectrum from the thermal energy up to about 40 MeV were provided by the C(d,n) reaction with 40 MeV deuteron beams. It was proved that the 99Mo yield agrees with that estimated by using the latest data on neutrons from the C(d,n) reaction and the evaluated cross section of the 100Mo(n,2n)99Mo reaction given in the Japanese Evaluated Nuclear Data Library. On the basis of the agreement, a systematic calculation was carried out to search for an optimum condition that enables us to produce as much 99Mo as possible with a good 99Mo/100Mo value from an economical point of view. The calculated 99Mo yield from a 150 g 100MoO3 sample indicated that about 30% of the demand for 99Mo in Japan can be met with a single accelerator capable of 40 MeV, 2 mA deuteron beams. Here, by referring to an existing 18F-fluorodeoxyglucose (FDG) distribution system we assumed that 99mTc radiopharmaceuticals formed after separating 99mTc from 99Mo can be delivered to hospitals from a radiopharmaceutical company within 6 h. The elution of 99mTc from 99Mo twice a day would meet about 50% of the demand for 99Mo.

  16. The Massachusetts Sustainable-Yield Estimator: A decision-support tool to assess water availability at ungaged stream locations in Massachusetts

    USGS Publications Warehouse

    Archfield, Stacey A.; Vogel, Richard M.; Steeves, Peter A.; Brandt, Sara L.; Weiskel, Peter K.; Garabedian, Stephen P.

    2010-01-01

    Federal, State and local water-resource managers require a variety of data and modeling tools to better understand water resources. The U.S. Geological Survey, in cooperation with the Massachusetts Department of Environmental Protection, has developed a statewide, interactive decision-support tool to meet this need. The decision-support tool, referred to as the Massachusetts Sustainable-Yield Estimator (MA SYE) provides screening-level estimates of the sustainable yield of a basin, defined as the difference between the unregulated streamflow and some user-specified quantity of water that must remain in the stream to support such functions as recreational activities or aquatic habitat. The MA SYE tool was designed, in part, because the quantity of surface water available in a basin is a time-varying quantity subject to competing demands for water. To compute sustainable yield, the MA SYE tool estimates a daily time series of unregulated, daily mean streamflow for a 44-year period of record spanning October 1, 1960, through September 30, 2004. Selected streamflow quantiles from an unregulated, daily flow-duration curve are estimated by solving six regression equations that are a function of physical and climate basin characteristics at an ungaged site on a stream of interest. Streamflow is then interpolated between the estimated quantiles to obtain a continuous daily flow-duration curve. A time series of unregulated daily streamflow subsequently is created by transferring the timing of the daily streamflow at a reference streamgage to the ungaged site by equating exceedence probabilities of contemporaneous flow at the two locations. One of 66 reference streamgages is selected by kriging, a geostatistical method, which is used to map the spatial relation among correlations between the time series of the logarithm of daily streamflows at each reference streamgage and the ungaged site. Estimated unregulated, daily mean streamflows show good agreement with observed

  17. 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...

  18. Intercomparison of Soil Moisture, Evaporative Stress, and Vegetation Indices for Estimating Corn and Soybean Yields Over the U.S.

    NASA Technical Reports Server (NTRS)

    Mladenova, Iliana E.; Bolten, John D.; Crow, Wade T.; Anderson, Martha C.; Hain, C. R.; Johnson, David M.; Mueller, Rick

    2017-01-01

    This paper presents an intercomparative study of 12 operationally produced large-scale datasets describing soil moisture, evapotranspiration (ET), and or vegetation characteristics within agricultural regions of the contiguous United States (CONUS). These datasets have been developed using a variety of techniques, including, hydrologic modeling, satellite-based retrievals, data assimilation, and survey in-field data collection. The objectives are to assess the relative utility of each dataset for monitoring crop yield variability, to quantitatively assess their capacity for predicting end-of-season corn and soybean yields, and to examine the evolution of the yield-index correlations during the growing season. This analysis is unique both with regards to the number and variety of examined yield predictor datasets and the detailed assessment of the water availability timing on the end-of-season crop production during the growing season. Correlation results indicate that over CONUS, at state-level soil moisture and ET indices can provide better information for forecasting corn and soybean yields than vegetation-based indices such as normalized difference vegetation index. The strength of correlation with corn and soybean yields strongly depends on the interannual variability in yield measured at a given location. In this case study, some of the remotely derived datasets examined provide skill comparable to that of in situ field survey-based data further demonstrating the utility of these remote sensing-based approaches for estimating crop yield.

  19. 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.

  20. Genetic parameters for body condition score, body weight, milk yield, and fertility estimated using random regression models.

    PubMed

    Berry, D P; Buckley, F; Dillon, P; Evans, R D; Rath, M; Veerkamp, R F

    2003-11-01

    Genetic (co)variances between body condition score (BCS), body weight (BW), milk yield, and fertility were estimated using a random regression animal model extended to multivariate analysis. The data analyzed included 81,313 BCS observations, 91,937 BW observations, and 100,458 milk test-day yields from 8725 multiparous Holstein-Friesian cows. A cubic random regression was sufficient to model the changing genetic variances for BCS, BW, and milk across different days in milk. The genetic correlations between BCS and fertility changed little over the lactation; genetic correlations between BCS and interval to first service and between BCS and pregnancy rate to first service varied from -0.47 to -0.31, and from 0.15 to 0.38, respectively. This suggests that maximum genetic gain in fertility from indirect selection on BCS should be based on measurements taken in midlactation when the genetic variance for BCS is largest. Selection for increased BW resulted in shorter intervals to first service, but more services and poorer pregnancy rates; genetic correlations between BW and pregnancy rate to first service varied from -0.52 to -0.45. Genetic selection for higher lactation milk yield alone through selection on increased milk yield in early lactation is likely to have a more deleterious effect on genetic merit for fertility than selection on higher milk yield in late lactation.

  1. Specific yield: compilation of specific yields for various materials

    USGS Publications Warehouse

    Johnson, A.I.

    1967-01-01

    Specific yield is defined as the ratio of (1) the volume of water that a saturated rock or soil will yield by gravity to (2) the total volume of the rock or soft. Specific yield is usually expressed as a percentage. The value is not definitive, because the quantity of water that will drain by gravity depends on variables such as duration of drainage, temperature, mineral composition of the water, and various physical characteristics of the rock or soil under consideration. Values of specific yields nevertheless offer a convenient means by which hydrologists can estimate the water-yielding capacities of earth materials and, as such, are very useful in hydrologic studies. The present report consists mostly of direct or modified quotations from many selected reports that present and evaluate methods for determining specific yield, limitations of those methods, and results of the determinations made on a wide variety of rock and soil materials. Although no particular values are recommended in this report, a table summarizes values of specific yield, and their averages, determined for 10 rock textures. The following is an abstract of the table. [Table

  2. 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.

  3. Airborne and ground-based remote sensing for the estimation of evapotranspiration and yield of bean, potato, and sugar beet crops

    NASA Astrophysics Data System (ADS)

    Jayanthi, Harikishan

    The focus of this research was two-fold: (1) extend the reflectance-based crop coefficient approach to non-grain (potato and sugar beet), and vegetable crops (bean), and (2) develop vegetation index (VI)-yield statistical models for potato and sugar beet crops using high-resolution aerial multispectral imagery. Extensive crop biophysical sampling (leaf area index and aboveground dry biomass sampling) and canopy reflectance measurements formed the backbone of developing of canopy reflectance-based crop coefficients for bean, potato, and sugar beet crops in this study. Reflectance-based crop coefficient equations were developed for the study crops cultivated in Kimberly, Idaho, and subsequently used in water availability simulations in the plant root zone during 1998 and 1999 seasons. The simulated soil water profiles were compared with independent measurements of actual soil water profiles in the crop root zone in selected fields. It is concluded that the canopy reflectance-based crop coefficient technique can be successfully extended to non-grain crops as well. While the traditional basal crop coefficients generally expect uniform growth in a region the reflectance-based crop coefficients represent the actual crop growth pattern (in less than ideal water availability conditions) in individual fields. Literature on crop canopy interactions with sunlight states that there is a definite correspondence between leaf area index progression in the season and the final yield. In case of crops like potato and sugar beet, the yield is influenced not only on how early and how quickly the crop establishes its canopy but also on how long the plant stands on the ground in a healthy state. The integrated area under the crop growth curve has shown excellent correlations with hand-dug samples of potato and sugar beet crops in this research. Soil adjusted vegetation index-yield models were developed, and validated using multispectral aerial imagery. Estimated yield images were

  4. Field-scale experiments reveal persistent yield gaps in low-input and organic cropping systems

    PubMed Central

    Kravchenko, Alexandra N.; Snapp, Sieglinde S.; Robertson, G. Philip

    2017-01-01

    Knowledge of production-system performance is largely based on observations at the experimental plot scale. Although yield gaps between plot-scale and field-scale research are widely acknowledged, their extent and persistence have not been experimentally examined in a systematic manner. At a site in southwest Michigan, we conducted a 6-y experiment to test the accuracy with which plot-scale crop-yield results can inform field-scale conclusions. We compared conventional versus alternative, that is, reduced-input and biologically based–organic, management practices for a corn–soybean–wheat rotation in a randomized complete block-design experiment, using 27 commercial-size agricultural fields. Nearby plot-scale experiments (0.02-ha to 1.0-ha plots) provided a comparison of plot versus field performance. We found that plot-scale yields well matched field-scale yields for conventional management but not for alternative systems. For all three crops, at the plot scale, reduced-input and conventional managements produced similar yields; at the field scale, reduced-input yields were lower than conventional. For soybeans at the plot scale, biological and conventional managements produced similar yields; at the field scale, biological yielded less than conventional. For corn, biological management produced lower yields than conventional in both plot- and field-scale experiments. Wheat yields appeared to be less affected by the experimental scale than corn and soybean. Conventional management was more resilient to field-scale challenges than alternative practices, which were more dependent on timely management interventions; in particular, mechanical weed control. Results underscore the need for much wider adoption of field-scale experimentation when assessing new technologies and production-system performance, especially as related to closing yield gaps in organic farming and in low-resourced systems typical of much of the developing world. PMID:28096409

  5. Field-scale experiments reveal persistent yield gaps in low-input and organic cropping systems.

    PubMed

    Kravchenko, Alexandra N; Snapp, Sieglinde S; Robertson, G Philip

    2017-01-31

    Knowledge of production-system performance is largely based on observations at the experimental plot scale. Although yield gaps between plot-scale and field-scale research are widely acknowledged, their extent and persistence have not been experimentally examined in a systematic manner. At a site in southwest Michigan, we conducted a 6-y experiment to test the accuracy with which plot-scale crop-yield results can inform field-scale conclusions. We compared conventional versus alternative, that is, reduced-input and biologically based-organic, management practices for a corn-soybean-wheat rotation in a randomized complete block-design experiment, using 27 commercial-size agricultural fields. Nearby plot-scale experiments (0.02-ha to 1.0-ha plots) provided a comparison of plot versus field performance. We found that plot-scale yields well matched field-scale yields for conventional management but not for alternative systems. For all three crops, at the plot scale, reduced-input and conventional managements produced similar yields; at the field scale, reduced-input yields were lower than conventional. For soybeans at the plot scale, biological and conventional managements produced similar yields; at the field scale, biological yielded less than conventional. For corn, biological management produced lower yields than conventional in both plot- and field-scale experiments. Wheat yields appeared to be less affected by the experimental scale than corn and soybean. Conventional management was more resilient to field-scale challenges than alternative practices, which were more dependent on timely management interventions; in particular, mechanical weed control. Results underscore the need for much wider adoption of field-scale experimentation when assessing new technologies and production-system performance, especially as related to closing yield gaps in organic farming and in low-resourced systems typical of much of the developing world.

  6. Water Quality in the Upper Anacostia River, Maryland: Continuous and Discrete Monitoring with Simulations to Estimate Concentrations and Yields, 2003-05

    USGS Publications Warehouse

    Miller, Cherie V.; Gutierrez-Magness, Angelica L.; Feit Majedi, Brenda L.; Foster, Gregory D.

    2007-01-01

    concentrations of total phosphorus and total nitrogen had lower values of multiple R2 than suspended sediment, but the estimated bias for all the models was similar. The models for total nitrogen and total phosphorus tended to under-predict high concentrations and to over-predict low concentrations as compared to measured values. Annual yields (loads per square area in kilograms per year per square kilometer) were estimated for suspended sediment, total nitrogen, and total phosphorus using the U.S. Geological Survey models ESTIMATOR and LOADEST. The model LOADEST used hourly time steps and allowed the use of turbidity, which is strongly correlated to concentrations of suspended sediment, as a predictor variable. Annual yields for total nitrogen and total phosphorus were slightly higher but similar to previous estimates for other watersheds of the Chesapeake Bay, but annual yields for suspended sediment were higher by an order of magnitude for the two Anacostia River stations. Annual yields of suspended sediment at the two Anacostia River stations ranged from 131,000 to 248,000 kilograms per year per square kilometer for 2004 and 2005. LOADEST estimates were similar to those determined with ESTIMATOR, but had reduced errors associated with the estimates.

  7. Guidelines for Estimating Cone and Seed Yields of Southern Pines

    Treesearch

    James P. Barnett

    1999-01-01

    Our ability to predict cone and seed yields of southern pines (Pinus spp.) prior to collection is important when scheduling and allocating resources. Many managers have enough historical data to predict their orchards' yield; but such data are generally unavailable for some species and for collections outside of orchards. Guidelines are...

  8. Full-Waveform Envelope Templates for Low Magnitude Discrimination and Yield Estimation at Local and Regional Distances with Application to the North Korean Nuclear Tests

    NASA Astrophysics Data System (ADS)

    Yoo, S. H.

    2017-12-01

    Monitoring seismologists have successfully used seismic coda for event discrimination and yield estimation for over a decade. In practice seismologists typically analyze long-duration, S-coda signals with high signal-to-noise ratios (SNR) at regional and teleseismic distances, since the single back-scattering model reasonably predicts decay of the late coda. However, seismic monitoring requirements are shifting towards smaller, locally recorded events that exhibit low SNR and short signal lengths. To be successful at characterizing events recorded at local distances, we must utilize the direct-phase arrivals, as well as the earlier part of the coda, which is dominated by multiple forward scattering. To remedy this problem, we have developed a new hybrid method known as full-waveform envelope template matching to improve predicted envelope fits over the entire waveform and account for direct-wave and early coda complexity. We accomplish this by including a multiple forward-scattering approximation in the envelope modeling of the early coda. The new hybrid envelope templates are designed to fit local and regional full waveforms and produce low-variance amplitude estimates, which will improve yield estimation and discrimination between earthquakes and explosions. To demonstrate the new technique, we applied our full-waveform envelope template-matching method to the six known North Korean (DPRK) underground nuclear tests and four aftershock events following the September 2017 test. We successfully discriminated the event types and estimated the yield for all six nuclear tests. We also applied the same technique to the 2015 Tianjin explosions in China, and another suspected low-yield explosion at the DPRK test site on May 12, 2010. Our results show that the new full-waveform envelope template-matching method significantly improves upon longstanding single-scattering coda prediction techniques. More importantly, the new method allows monitoring seismologists to extend

  9. Asetek's Warm-Water Liquid Cooling System Yields Energy Cost Savings at

    Science.gov Websites

    NREL | Energy Systems Integration Facility | NREL Asetek Asetek's Warm-Water Liquid Cooling System Yields Energy Cost Savings at NREL Asetek's RackCDU liquid cooling system was installed and tested at the Energy Systems Integration Facility's (ESIF's) ultra-energy-efficient high-performance

  10. Estimation for bilinear stochastic systems

    NASA Technical Reports Server (NTRS)

    Willsky, A. S.; Marcus, S. I.

    1974-01-01

    Three techniques for the solution of bilinear estimation problems are presented. First, finite dimensional optimal nonlinear estimators are presented for certain bilinear systems evolving on solvable and nilpotent lie groups. Then the use of harmonic analysis for estimation problems evolving on spheres and other compact manifolds is investigated. Finally, an approximate estimation technique utilizing cumulants is discussed.

  11. Ecological intensification of cereal production systems: yield potential, soil quality, and precision agriculture.

    PubMed

    Cassman, K G

    1999-05-25

    Wheat (Triticum aestivum L.), rice (Oryza sativa L.), and maize (Zea mays L.) provide about two-thirds of all energy in human diets, and four major cropping systems in which these cereals are grown represent the foundation of human food supply. Yield per unit time and land has increased markedly during the past 30 years in these systems, a result of intensified crop management involving improved germplasm, greater inputs of fertilizer, production of two or more crops per year on the same piece of land, and irrigation. Meeting future food demand while minimizing expansion of cultivated area primarily will depend on continued intensification of these same four systems. The manner in which further intensification is achieved, however, will differ markedly from the past because the exploitable gap between average farm yields and genetic yield potential is closing. At present, the rate of increase in yield potential is much less than the expected increase in demand. Hence, average farm yields must reach 70-80% of the yield potential ceiling within 30 years in each of these major cereal systems. Achieving consistent production at these high levels without causing environmental damage requires improvements in soil quality and precise management of all production factors in time and space. The scope of the scientific challenge related to these objectives is discussed. It is concluded that major scientific breakthroughs must occur in basic plant physiology, ecophysiology, agroecology, and soil science to achieve the ecological intensification that is needed to meet the expected increase in food demand.

  12. Estimating Dynamical Systems: Derivative Estimation Hints From Sir Ronald A. Fisher.

    PubMed

    Deboeck, Pascal R

    2010-08-06

    The fitting of dynamical systems to psychological data offers the promise of addressing new and innovative questions about how people change over time. One method of fitting dynamical systems is to estimate the derivatives of a time series and then examine the relationships between derivatives using a differential equation model. One common approach for estimating derivatives, Local Linear Approximation (LLA), produces estimates with correlated errors. Depending on the specific differential equation model used, such correlated errors can lead to severely biased estimates of differential equation model parameters. This article shows that the fitting of dynamical systems can be improved by estimating derivatives in a manner similar to that used to fit orthogonal polynomials. Two applications using simulated data compare the proposed method and a generalized form of LLA when used to estimate derivatives and when used to estimate differential equation model parameters. A third application estimates the frequency of oscillation in observations of the monthly deaths from bronchitis, emphysema, and asthma in the United Kingdom. These data are publicly available in the statistical program R, and functions in R for the method presented are provided.

  13. 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...

  14. Different universality classes at the yielding transition of amorphous systems

    NASA Astrophysics Data System (ADS)

    Jagla, E. A.

    2017-08-01

    We study the yielding transition of a two-dimensional amorphous system under shear by using a mesoscopic elasto-plastic model. The model combines a full (tensorial) description of the elastic interactions in the system and the possibility of structural reaccommodations that are responsible for the plastic behavior. The possible structural reaccommodations are encoded in the form of a "plastic disorder" potential, which is chosen independently at each position of the sample to account for local heterogeneities. We observe that the stress must exceed a critical value σc in order for the system to yield. In addition, when the system yields a flow curve (relating stress σ and strain rate γ ˙) of the form γ ˙˜(σ-σc) β is obtained. Remarkably, we observe the value of β to depend on some details of the plastic disorder potential. For smooth potentials a value of β ≃2.0 is obtained, whereas for potentials obtained as a concatenation of smooth pieces a value β ≃1.5 is observed in the simulations. This indicates a dependence of critical behavior on details of the plastic behavior. In addition, by integrating out nonessential, harmonic degrees of freedom, we derive a simplified scalar version of the model that represents a collection of interacting Prandtl-Tomlinson particles. A mean-field treatment of this interaction reproduces the difference of β exponents for the two classes of plastic disorder potentials and provides values of β that compare favorably with those found in the full simulations.

  15. 48 CFR 215.407-5 - Estimating systems.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 48 Federal Acquisition Regulations System 3 2012-10-01 2012-10-01 false Estimating systems. 215.407-5 Section 215.407-5 Federal Acquisition Regulations System DEFENSE ACQUISITION REGULATIONS SYSTEM....407-5 Estimating systems. ...

  16. 48 CFR 215.407-5 - Estimating systems.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 48 Federal Acquisition Regulations System 3 2013-10-01 2013-10-01 false Estimating systems. 215.407-5 Section 215.407-5 Federal Acquisition Regulations System DEFENSE ACQUISITION REGULATIONS SYSTEM....407-5 Estimating systems. ...

  17. 48 CFR 215.407-5 - Estimating systems.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 48 Federal Acquisition Regulations System 3 2011-10-01 2011-10-01 false Estimating systems. 215.407-5 Section 215.407-5 Federal Acquisition Regulations System DEFENSE ACQUISITION REGULATIONS SYSTEM....407-5 Estimating systems. ...

  18. 48 CFR 215.407-5 - Estimating systems.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 48 Federal Acquisition Regulations System 3 2014-10-01 2014-10-01 false Estimating systems. 215.407-5 Section 215.407-5 Federal Acquisition Regulations System DEFENSE ACQUISITION REGULATIONS SYSTEM....407-5 Estimating systems. ...

  19. 48 CFR 215.407-5 - Estimating systems.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 48 Federal Acquisition Regulations System 3 2010-10-01 2010-10-01 false Estimating systems. 215.407-5 Section 215.407-5 Federal Acquisition Regulations System DEFENSE ACQUISITION REGULATIONS SYSTEM....407-5 Estimating systems. ...

  20. 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,...

  1. 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.

  2. 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

  3. 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

  4. 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.

  5. Photosensitized electron transfer processes in SiO2 colloids and sodium lauryl sulfate micellar systems: Correlation of quantum yields with interfacial surface potentials

    PubMed Central

    Laane, Colja; Willner, Itamar; Otvos, John W.; Calvin, Melvin

    1981-01-01

    The effectiveness of negatively charged colloidal SiO2 particles in controlling photosensitized electron transfer reactions has been studied and compared with that of the negatively charged sodium lauryl sulfate (NaLauSO4) micellar system. In particular, the photosensitized reduction of the zwitterionic electron acceptor propylviologen sulfonate (PVS0) with tris(2,2′-bipyridinium)ruthenium(II) [Ru(bipy)32+] as the sensitizer and triethanolamine as the electron donor is found to have a quantum yield of 0.033 for formation of the radical anion (PVS[unk]) in the SiO2 colloid compared with 0.005 in the homogeneous system and 0.0086 in a NaLauSO4 micellar solution. The higher quantum yields obtained with the SiO2 colloidal system are attributed to substantial stabilization against back reaction of the intermediate photoproducts—i.e., Ru(bipy)33+ and PVS[unk]—by electrostatic repulsion of the reduced electron acceptor from the negatively charged particle surface. The binding properties of the SiO2 particles and NaLauSO4 micelles were investigated by flow dialysis. The results show that the sensitizer binds to both interfaces and that the SiO2 interface is characterized by a much higher surface potential than the micellar interface (≈-170 mV vs. -85 mV). The effect of ionic strength on the surface potential was estimated from the Gouy-Chapman theory, and the measured quantum yields of photosensitized electron transfer were correlated with surface potential at different ionic strengths. This correlation shows that the quantum yield is not affected by surface potentials smaller than ≈-40 mV. At larger potentials, the quantum yield increases rapidly. The quantum yield obtained in the micellar system at different strengths fits nicely on the correlation curve for the colloid SiO2 system. These results indicate that the surface potential is the dominant factor in the quantum yield improvement for PVS0 reduction. PMID:16593095

  6. Yield performance and stability of CMS-based triticale hybrids.

    PubMed

    Mühleisen, Jonathan; Piepho, Hans-Peter; Maurer, Hans Peter; Reif, Jochen Christoph

    2015-02-01

    CMS-based triticale hybrids showed only marginal midparent heterosis for grain yield and lower dynamic yield stability compared to inbred lines. Hybrids of triticale (×Triticosecale Wittmack) are expected to possess outstanding yield performance and increased dynamic yield stability. The objectives of the present study were to (1) examine the optimum choice of the biometrical model to compare yield stability of hybrids versus lines, (2) investigate whether hybrids exhibit a more pronounced grain yield performance and yield stability, and (3) study optimal strategies to predict yield stability of hybrids. Thirteen female and seven male parental lines and their 91 factorial hybrids as well as 30 commercial lines were evaluated for grain yield in up to 20 environments. Hybrids were produced using a cytoplasmic male sterility (CMS)-inducing cytoplasm that originated from Triticumtimopheevii Zhuk. We found that the choice of the biometrical model can cause contrasting results and concluded that a group-by-environment interaction term should be added to the model when estimating stability variance of hybrids and lines. midparent heterosis for grain yield was on average 3 % with a range from -15.0 to 11.5 %. No hybrid outperformed the best inbred line. Hybrids had, on average, lower dynamic yield stability compared to the inbred lines. Grain yield performance of hybrids could be predicted based on midparent values and general combining ability (GCA)-predicted values. In contrast, stability variance of hybrids could be predicted only based on GCA-predicted values. We speculated that negative effects of the used CMS cytoplasm might be the reason for the low performance and yield stability of the hybrids. For this purpose a detailed study on the reasons for the drawback of the currently existing CMS system in triticale is urgently required comprising also the search of potentially alternative hybridization systems.

  7. 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

  8. 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.

  9. Systems Engineering Programmatic Estimation Using Technology Variance

    NASA Technical Reports Server (NTRS)

    Mog, Robert A.

    2000-01-01

    Unique and innovative system programmatic estimation is conducted using the variance of the packaged technologies. Covariance analysis is performed on the subsystems and components comprising the system of interest. Technological "return" and "variation" parameters are estimated. These parameters are combined with the model error to arrive at a measure of system development stability. The resulting estimates provide valuable information concerning the potential cost growth of the system under development.

  10. Managing Southeastern US Forests for Increased Water Yield

    NASA Astrophysics Data System (ADS)

    Acharya, S.; Kaplan, D. A.; Mclaughlin, D. L.; Cohen, M. J.

    2017-12-01

    Forested lands influence watershed hydrology by affecting water quantity and quality in surface and groundwater systems, making them potentially effective tools for regional water resource planning. In this study, we quantified water use and water yield by pine forests under varying silvicultural management (e.g., high density plantation, thinning, and prescribed burning). Daily forest water use (evapotranspiration, ET) was estimated using continuously monitored soil-moisture in the root-zone at six sites across Florida (USA), each with six plots ranging in forest leaf-area index (LAI). Plots included stands with different rotational ages (from clear-cut to mature pine plantations) and those restored to more historical conditions. Estimated ET relative to potential ET (PET) was strongly associated with LAI, root-zone soil-moisture status, and site hydroclimate; these factors explained 85% of the variation in the ET:PET ratio. Annual water yield (Yw) calculated from these ET estimates and a simple water balance differed significantly among sites and plots (ranging from -0.12 cm/yr to > 100 cm/yr), demonstrating substantive influence of management regimes. LAI strongly influenced Yw in all sites, and a general linear model with forest attributes (LAI and groundcover), hydroclimate, and site characteristics explained >90% of variation in observed Yw. These results can be used to predict water yield changes under different management and climate scenarios and may be useful in the development of payment for ecosystem services approaches that identify water as an important product of forest best management practices.

  11. Concentrations, and Estimated Loads and Yields of Total Nitrogen and Total Phosphorus at Selected Stations in Kentucky, 1979-2004

    USGS Publications Warehouse

    Crain, Angela S.; Martin, Gary R.

    2009-01-01

    To evaluate the State's water quality, the Kentucky Division of Water collects data from a statewide network of primary ambient stream water-quality monitoring stations and flexible, rotating watershed-monitoring stations. This ambient stream water-quality monitoring network program is directed to assess the conditions of surface waters throughout Kentucky. Water samples were collected monthly for the majority of the stations from 1979 to 1998, which represented agricultural, undeveloped (mainly forested), and areas of mixed land use/land cover. In 1998, the number of water samples collected was reduced to a collection frequency of six times per year (every 2 months) every 4 of 5 years, because a new monitoring network was implemented involving a 5-year rotating Basin Management Unit scheme of monitoring. This report presents the results of a study conducted by the U.S. Geological Survey, in cooperation with the Kentucky Energy and Environment Cabinet-Kentucky Division of Water, to summarize concentrations of total nitrogen and total phosphorus and provide estimates of total nitrogen and total phosphorus loads and yields in 55 selected streams in Kentucky's ambient stream water-quality monitoring network, which was operated from 1979 through 2004. Streams in predominately agricultural basins had higher concentrations of total nitrogen (TN) and concentrations of total phosphorus (TP) than streams in predominately undeveloped (forested) basins. Streams in basins in intensely developed karst areas characterized by caves, springs, sinkholes, and sinking streams had a higher median concentration of TN (1.5 milligrams per liter [mg/L]) than streams in basins with limited or no karst areas (0.63 mg/L). As with TN, median concentrations of TP also were higher in areas of intense karst (0.05 mg/L) than in areas with limited or no karst (0.02 mg/L). The U.S. Environmental Protection Agency (USEPA) has recommended ecoregional nutrient water-quality criteria as a starting

  12. 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

  13. Integrated model for predicting rice yield with climate change

    NASA Astrophysics Data System (ADS)

    Park, Jin-Ki; Das, Amrita; Park, Jong-Hwa

    2018-04-01

    Rice is the chief agricultural product and one of the primary food source. For this reason, it is of pivotal importance for worldwide economy and development. Therefore, in a decision-support-system both for the farmers and in the planning and management of the country's economy, forecasting yield is vital. However, crop yield, which is a dependent of the soil-bio-atmospheric system, is difficult to represent in statistical language. This paper describes a novel approach for predicting rice yield using artificial neural network, spatial interpolation, remote sensing and GIS methods. Herein, the variation in the yield is attributed to climatic parameters and crop health, and the normalized difference vegetation index from MODIS is used as an indicator of plant health and growth. Due importance was given to scaling up the input parameters using spatial interpolation and GIS and minimising the sources of error in every step of the modelling. The low percentage error (2.91) and high correlation (0.76) signifies the robust performance of the proposed model. This simple but effective approach is then used to estimate the influence of climate change on South Korean rice production. As proposed in the RCP8.5 scenario, an upswing in temperature may increase the rice yield throughout South Korea.

  14. Effect of incomplete pedigrees on estimates of inbreeding and inbreeding depression for days to first service and summit milk yield in Holsteins and Jerseys.

    PubMed

    Cassell, B G; Adamec, V; Pearson, R E

    2003-09-01

    A method to measure completeness of pedigree information is applied to populations of Holstein (registered and grade) and Jersey (largely registered) cows. Inbreeding coefficients where missing ancestors make no contribution were compared to a method using average relationships for missing ancestors. Estimated inbreeding depression was from an animal model that simultaneously adjusted for breeding values. Inbreeding and its standard deviation increased with more information, from 0.04 +/- 0.84 to 1.65 +/- 2.05 and 2.06 +/- 2.22 for grade Holsteins with <31%, 31 to 70%, and 71 to 100% complete five-generation pedigrees. Inbreeding from the method of average relationships for missing ancestors was 2.75 +/- 1.06, 3.10 +/- 2.21, and 2.89 +/- 2.37 for the same groups. Pedigrees of registered Holsteins and Jerseys were over 97% and over 89% complete, respectively. Inbreeding depression in days to first service and summit milk yield was estimated from both methods. Inbreeding depression for days to first service was not consistently significant for grade Holsteins and ranged from -0.37 d/1% increase in inbreeding (grade Holstein pedigrees <31% complete) to 0.15 d for grade Holstein pedigrees >70% complete. Estimates were similar for both methods. Inbreeding depression for registered Holsteins and Jerseys were positive (undesirable) but not significant for days to first service. Inbreeding depressed summit milk yield significantly in all groups by both methods. Summit milk yield declined by -0.12 to -0.06 kg/d per 1% increase in inbreeding in Holsteins and by -0.08 kg/1% increase in inbreeding in Jerseys. Pedigrees of grade animals are frequently incomplete and can yield misleading estimates of inbreeding depression. This problem is not overcome by inserting average relationships for missing ancestors in calculation of inbreeding coefficients.

  15. 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.

  16. [Estimating medicinal yield of Seutellaria baicalensis in Beijing-Tianjin-Hebei region based on 3S technology].

    PubMed

    Liu, Jin-xinp; Lu, Heng; Zeng, Yan; Yue, Jian-wei; Meng, Fan-yun; Zhang, Yi-guang

    2012-09-01

    Resources survey of traditional Chinese medicine and reserves estimation are found to be the most important issues for the protection and utilization of traditional Chinese medicine resources, this paper used multi-spatial resolution remote sensing images (RS) , geographic information systems (GIS) and global positioning system (GPS) , to establish Scutellaria resources survey of 3S data platform. Combined with the traditional field survey methods, small-scale habitat types were established based on different skullcap reserve estimation model, which can estimate reserves of the wild Scutellaria in Beijing-Tianjin-Hebei region and improve the estimation accuracy. It can provide an important parameter for the fourth national survey of traditional Chinese medicine resources and traditional Chinese medicine reserves estimates based on 3S technology by multiple spatial scales model.

  17. Towards Better Simulation of US Maize Yield Responses to Climate in the Community Earth System Model

    NASA Astrophysics Data System (ADS)

    Peng, B.; Guan, K.; Chen, M.; Lawrence, D. M.; Jin, Z.; Bernacchi, C.; Ainsworth, E. A.; DeLucia, E. H.; Lombardozzi, D. L.; Lu, Y.

    2017-12-01

    Global food security is undergoing continuing pressure from increased population and climate change despites the potential advancement in breeding and management technologies. Earth system models (ESMs) are essential tools to study the impacts of historical and future climate on regional and global food production, as well as to assess the effectiveness of possible adaptations and their potential feedback to climate. Here we developed an improved maize representation within the Community Earth System Model (CESM) by combining the strengths of both the Community Land Model version 4.5 (CLM4.5) and the Agricultural Production Systems sIMulator (APSIM) models. Specifically, we modified the maize planting scheme, incorporated the phenology scheme adopted from the APSIM model, added a new carbon allocation scheme into CLM4.5, and improved the estimation of canopy structure parameters including leaf area index (LAI) and canopy height. Unique features of the new model (CLM-APSIM) include more detailed phenology stages, an explicit implementation of the impacts of various abiotic environmental stresses (including nitrogen, water, temperature and heat stresses) on maize phenology and carbon allocation, as well as an explicit simulation of grain number and grain size. We conducted a regional simulation of this new model over the US Corn Belt during 1990 to 2010. The simulated maize yield as well as its responses to climate (growing season mean temperature and precipitation) are benchmarked with data from UADA NASS statistics. Our results show that the CLM-APSIM model outperforms the CLM4.5 in simulating county-level maize yield production and reproduces more realistic yield responses to climate variations than CLM4.5. However, some critical processes (such as crop failure due to frost and inundation and suboptimal growth condition due to biotic stresses) are still missing in both CLM-APSIM and CLM4.5, making the simulated yield responses to climate slightly deviate from the

  18. 48 CFR 15.407-5 - Estimating systems.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 48 Federal Acquisition Regulations System 1 2013-10-01 2013-10-01 false Estimating systems. 15.407-5 Section 15.407-5 Federal Acquisition Regulations System FEDERAL ACQUISITION REGULATION CONTRACTING METHODS AND CONTRACT TYPES CONTRACTING BY NEGOTIATION Contract Pricing 15.407-5 Estimating systems. (a...

  19. 48 CFR 15.407-5 - Estimating systems.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 48 Federal Acquisition Regulations System 1 2011-10-01 2011-10-01 false Estimating systems. 15.407-5 Section 15.407-5 Federal Acquisition Regulations System FEDERAL ACQUISITION REGULATION CONTRACTING METHODS AND CONTRACT TYPES CONTRACTING BY NEGOTIATION Contract Pricing 15.407-5 Estimating systems. (a...

  20. 48 CFR 15.407-5 - Estimating systems.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 48 Federal Acquisition Regulations System 1 2012-10-01 2012-10-01 false Estimating systems. 15.407-5 Section 15.407-5 Federal Acquisition Regulations System FEDERAL ACQUISITION REGULATION CONTRACTING METHODS AND CONTRACT TYPES CONTRACTING BY NEGOTIATION Contract Pricing 15.407-5 Estimating systems. (a...

  1. 48 CFR 15.407-5 - Estimating systems.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 48 Federal Acquisition Regulations System 1 2010-10-01 2010-10-01 false Estimating systems. 15.407-5 Section 15.407-5 Federal Acquisition Regulations System FEDERAL ACQUISITION REGULATION CONTRACTING METHODS AND CONTRACT TYPES CONTRACTING BY NEGOTIATION Contract Pricing 15.407-5 Estimating systems. (a...

  2. Concentrations, and estimated loads and yields of nutrients and suspended sediment in the Little River basin, Kentucky, 2003-04

    USGS Publications Warehouse

    Crain, Angela S.

    2006-01-01

    Nutrients, primarily nitrogen and phosphorus compounds, naturally occur but also are applied to land in the form of commercial fertilizers and livestock waste to enhance plant growth. Concentrations, estimated loads and yields, and sources of nitrite plus nitrate, total phosphorus, and orthophosphate were evaluated in streams of the Little River Basin to assist the Commonwealth of Kentucky in developing 'total maximum daily loads' (TMDLs) for streams in the basin. The Little River Basin encompasses about 600 square miles in Christian and Trigg Counties, and a portion of Caldwell County in western Kentucky. Water samples were collected in streams in the Little River Basin during 2003-04 as part of a study conducted in cooperation with the Kentucky Department of Agriculture. A total of 92 water samples were collected at four fixed-network sites from March through November 2003 and from February through November 2004. An additional 20 samples were collected at five synoptic-network sites during the same period. Median concentrations of nitrogen, phosphorus, and suspended sediment varied spatially and seasonally. Concentrations of nitrogen were higher in the spring (March-May) after fertilizer application and runoff. The highest concentration of nitrite plus nitrate-5.7 milligrams per liter (mg/L)-was detected at the South Fork Little River site. The Sinking Fork near Cadiz site had the highest median concentration of nitrite plus nitrate (4.6 mg/L). The North Fork Little River site and the Little River near Cadiz site had higher concentrations of orthophosphate in the fall and lower concentrations in the spring. Concentrations of orthophosphate remained high during the summer (June-August) at the North Fork Little River site possibly because of the contribution of wastewater effluent to streamflow. Fifty-eight percent of the concentrations of total phosphorus at the nine sites exceeded the U.S. Environmental Protection Agency recommended maximum concentration limit of

  3. The buffer value of groundwater when well yield is limited

    NASA Astrophysics Data System (ADS)

    Foster, T.; Brozović, N.; Speir, C.

    2017-04-01

    A large proportion of the total value of groundwater in conjunctive use systems is associated with the ability to smooth out shortfalls in surface water supply during droughts. Previous research has argued that aquifer depletion in these regions will impact farmers negatively by reducing the available stock of groundwater to buffer production in future periods, and also by increasing the costs of groundwater extraction. However, existing studies have not considered how depletion may impact the productivity of groundwater stocks in conjunctive use systems through reductions in well yields. In this work, we develop a hydro-economic modeling framework to quantify the effects of changes in well yields on the buffer value of groundwater, and apply this model to an illustrative case study of tomato production in California's Central Valley. Our findings demonstrate that farmers with low well yields are forced to forgo significant production and profits because instantaneous groundwater supply is insufficient to buffer surface water shortfalls in drought years. Negative economic impacts of low well yields are an increasing function of surface water variability, and are also greatest for farmers operating less efficient irrigation systems. These results indicate that impacts of well yield reductions on the productivity of groundwater are an important economic impact of aquifer depletion, and that failure to consider this feedback may lead to significant errors in estimates of the value of groundwater management in conjunctive use systems.

  4. Reliability of reservoir firm yield determined from the historical drought of record

    USGS Publications Warehouse

    Archfield, S.A.; Vogel, R.M.

    2005-01-01

    The firm yield of a reservoir is typically defined as the maximum yield that could have been delivered without failure during the historical drought of record. In the future, reservoirs will experience droughts that are either more or less severe than the historical drought of record. The question addressed here is what the reliability of such systems will be when operated at the firm yield. To address this question, we examine the reliability of 25 hypothetical reservoirs sited across five locations in the central and western United States. These locations provided a continuous 756-month streamflow record spanning the same time interval. The firm yield of each reservoir was estimated from the historical drought of record at each location. To determine the steady-state monthly reliability of each firm-yield estimate, 12,000-month synthetic records were generated using the moving-blocks bootstrap method. Bootstrapping was repeated 100 times for each reservoir to obtain an average steady-state monthly reliability R, the number of months the reservoir did not fail divided by the total months. Values of R were greater than 0.99 for 60 percent of the study reservoirs; the other 40 percent ranged from 0.95 to 0.98. Estimates of R were highly correlated with both the level of development (ratio of firm yield to average streamflow) and average lag-1 monthly autocorrelation. Together these two predictors explained 92 percent of the variability in R, with the level of development alone explaining 85 percent of the variability. Copyright ASCE 2005.

  5. 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.

  6. 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...

  7. National Variation in Crop Yield Production Functions

    NASA Astrophysics Data System (ADS)

    Devineni, N.; Rising, J. A.

    2017-12-01

    A new multilevel model for yield prediction at the county scale using regional climate covariates is presented in this paper. A new crop specific water deficit index, growing degree days, extreme degree days, and time-trend as an approximation of technology improvements are used as predictors to estimate annual crop yields for each county from 1949 to 2009. Every county in the United States is allowed to have unique parameters describing how these weather predictors are related to yield outcomes. County-specific parameters are further modeled as varying according to climatic characteristics, allowing the prediction of parameters in regions where crops are not currently grown and into the future. The structural relationships between crop yield and regional climate as well as trends are estimated simultaneously. All counties are modeled in a single multilevel model with partial pooling to automatically group and reduce estimation uncertainties. The model captures up to 60% of the variability in crop yields after removing the effect of technology, does well in out of sample predictions and is useful in relating the climate responses to local bioclimatic factors. We apply the predicted growing models in a cost-benefit analysis to identify the most economically productive crop in each county.

  8. Yield and depth Estimation of Selected NTS Nuclear and SPE Chemical Explosions Using Source Equalization by modeling Local and Regional Seismograms (Invited)

    NASA Astrophysics Data System (ADS)

    Saikia, C. K.; Roman-nieves, J. I.; Woods, M. T.

    2013-12-01

    Source parameters of nuclear and chemical explosions are often estimated by matching either the corner frequency and spectral level of a single event or the spectral ratio when spectra from two events are available with known source parameters for one. In this study, we propose an alternative method in which waveforms from two or more events can be simultaneously equalized by setting the differential of the processed seismograms at one station from any two individual events to zero. The method involves convolving the equivalent Mueller-Murphy displacement source time function (MMDSTF) of one event with the seismogram of the second event and vice-versa, and then computing their difference seismogram. MMDSTF is computed at the elastic radius including both near and far-field terms. For this method to yield accurate source parameters, an inherent assumption is that green's functions for the any paired events from the source to a receiver are same. In the frequency limit of the seismic data, this is a reasonable assumption and is concluded based on the comparison of green's functions computed for flat-earth models at various source depths ranging from 100m to 1Km. Frequency domain analysis of the initial P wave is, however, sensitive to the depth phase interaction, and if tracked meticulously can help estimating the event depth. We applied this method to the local waveforms recorded from the three SPE shots and precisely determined their yields. These high-frequency seismograms exhibit significant lateral path effects in spectrogram analysis and 3D numerical computations, but the source equalization technique is independent of any variation as long as their instrument characteristics are well preserved. We are currently estimating the uncertainty in the derived source parameters assuming the yields of the SPE shots as unknown. We also collected regional waveforms from 95 NTS explosions at regional stations ALQ, ANMO, CMB, COR, JAS LON, PAS, PFO and RSSD. We are

  9. Brazil soybean yield covariance model

    NASA Technical Reports Server (NTRS)

    Callis, S. L.; Sakamoto, C.

    1984-01-01

    A model based on multiple regression was developed to estimate soybean yields for the seven soybean-growing states of Brazil. The meteorological data of these seven states were pooled and the years 1975 to 1980 were used to model since there was no technological trend in the yields during these years. Predictor variables were derived from monthly total precipitation and monthly average temperature.

  10. System dynamics approach for modeling of sugar beet yield considering the effects of climatic variables.

    PubMed

    Pervin, Lia; Islam, Md Saiful

    2015-02-01

    The aim of this study was to develop a system dynamics model for computation of yields and to investigate the dependency of yields on some major climatic parameters, i.e. temperature and rainfall, for Beta vulgaris subsp. (sugar beet crops) under future climate change scenarios. A system dynamics model was developed which takes account of the effects of rainfall and temperature on sugar beet yields under limited irrigation conditions. A relationship was also developed between the seasonal evapotranspiration and seasonal growing degree days for sugar beet crops. The proposed model was set to run for the present time period of 1993-2012 and for the future period 2013-2040 for Lethbridge region (Alberta, Canada). The model provides sugar beet yields on a yearly basis which are comparable to the present field data. It was found that the future average yield will be increased at about 14% with respect to the present average yield. The proposed model can help to improve the understanding of soil water conditions and irrigation water requirements of an area under certain climatic conditions and can be used for future prediction of yields for any crops in any region (with the required information to be provided). The developed system dynamics model can be used as a supporting tool for decision making, for improvement of agricultural management practice of any region. © 2014 Society of Chemical Industry.

  11. Estimating Biofuel Feedstock Water Footprints Using System Dynamics

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

    Inman, Daniel; Warner, Ethan; Stright, Dana

    Increased biofuel production has prompted concerns about the environmental tradeoffs of biofuels compared to petroleum-based fuels. Biofuel production in general, and feedstock production in particular, is under increased scrutiny. Water footprinting (measuring direct and indirect water use) has been proposed as one measure to evaluate water use in the context of concerns about depleting rural water supplies through activities such as irrigation for large-scale agriculture. Water footprinting literature has often been limited in one or more key aspects: complete assessment across multiple water stocks (e.g., vadose zone, surface, and ground water stocks), geographical resolution of data, consistent representation of manymore » feedstocks, and flexibility to perform scenario analysis. We developed a model called BioSpatial H2O using a system dynamics modeling and database framework. BioSpatial H2O could be used to consistently evaluate the complete water footprints of multiple biomass feedstocks at high geospatial resolutions. BioSpatial H2O has the flexibility to perform simultaneous scenario analysis of current and potential future crops under alternative yield and climate conditions. In this proof-of-concept paper, we modeled corn grain (Zea mays L.) and soybeans (Glycine max) under current conditions as illustrative results. BioSpatial H2O links to a unique database that houses annual spatially explicit climate, soil, and plant physiological data. Parameters from the database are used as inputs to our system dynamics model for estimating annual crop water requirements using daily time steps. Based on our review of the literature, estimated green water footprints are comparable to other modeled results, suggesting that BioSpatial H2O is computationally sound for future scenario analysis. Our modeling framework builds on previous water use analyses to provide a platform for scenario-based assessment. BioSpatial H2O's system dynamics is a flexible and user

  12. 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

  13. Assessment of uncertainties in soil erosion and sediment yield estimates at ungauged basins: an application to the Garra River basin, India

    NASA Astrophysics Data System (ADS)

    Swarnkar, Somil; Malini, Anshu; Tripathi, Shivam; Sinha, Rajiv

    2018-04-01

    High soil erosion and excessive sediment load are serious problems in several Himalayan river basins. To apply mitigation procedures, precise estimation of soil erosion and sediment yield with associated uncertainties are needed. Here, the revised universal soil loss equation (RUSLE) and the sediment delivery ratio (SDR) equations are used to estimate the spatial pattern of soil erosion (SE) and sediment yield (SY) in the Garra River basin, a small Himalayan tributary of the River Ganga. A methodology is proposed for quantifying and propagating uncertainties in SE, SDR and SY estimates. Expressions for uncertainty propagation are derived by first-order uncertainty analysis, making the method viable even for large river basins. The methodology is applied to investigate the relative importance of different RUSLE factors in estimating the magnitude and uncertainties in SE over two distinct morphoclimatic regimes of the Garra River basin, namely the upper mountainous region and the lower alluvial plains. Our results suggest that average SE in the basin is very high (23 ± 4.7 t ha-1 yr-1) with higher values in the upper mountainous region (92 ± 15.2 t ha-1 yr-1) compared to the lower alluvial plains (19.3 ± 4 t ha-1 yr-1). Furthermore, the topographic steepness (LS) and crop practice (CP) factors exhibit higher uncertainties than other RUSLE factors. The annual average SY is estimated at two locations in the basin - Nanak Sagar Dam (NSD) for the period 1962-2008 and Husepur gauging station (HGS) for 1987-2002. The SY at NSD and HGS are estimated to be 6.9 ± 1.2 × 105 t yr-1 and 6.7 ± 1.4 × 106 t yr-1, respectively, and the estimated 90 % interval contains the observed values of 6.4 × 105 t yr-1 and 7.2 × 106 t yr-1, respectively. The study demonstrated the usefulness of the proposed methodology for quantifying uncertainty in SE and SY estimates at ungauged basins.

  14. Argentina soybean yield model

    NASA Technical Reports Server (NTRS)

    Callis, S. L.; Sakamoto, C.

    1984-01-01

    A model based on multiple regression was developed to estimate soybean yields for the country of Argentina. A meteorological data set was obtained for the country by averaging data for stations within the soybean growing area. Predictor variables for the model were derived from monthly total precipitation and monthly average temperature. A trend variable was included for the years 1969 to 1978 since an increasing trend in yields due to technology was observed between these years.

  15. Yield response and economics of shallow subsurface drip irrigation systems

    USDA-ARS?s Scientific Manuscript database

    Field tests were conducted using shallow subsurface drip irrigation (S3DI) on cotton (Gossypium hirsutum, L.), corn (Zea mays, L.), and peanut (Arachis hypogeae, L.) in rotation to investigate yield potential and economic sustainability of this irrigation system technique over a six year period. Dri...

  16. System for estimating fatigue damage

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

    LeMonds, Jeffrey; Guzzo, Judith Ann; Liu, Shaopeng

    In one aspect, a system for estimating fatigue damage in a riser string is provided. The system includes a plurality of accelerometers which can be deployed along a riser string and a communications link to transmit accelerometer data from the plurality of accelerometers to one or more data processors in real time. With data from a limited number of accelerometers located at sensor locations, the system estimates an optimized current profile along the entire length of the riser including riser locations where no accelerometer is present. The optimized current profile is then used to estimate damage rates to individual risermore » components and to update a total accumulated damage to individual riser components. The number of sensor locations is small relative to the length of a deepwater riser string, and a riser string several miles long can be reliably monitored along its entire length by fewer than twenty sensor locations.« less

  17. Estimation of biogas and methane yields in an UASB treating potato starch processing wastewater with backpropagation artificial neural network.

    PubMed

    Antwi, Philip; Li, Jianzheng; Boadi, Portia Opoku; Meng, Jia; Shi, En; Deng, Kaiwen; Bondinuba, Francis Kwesi

    2017-03-01

    Three-layered feedforward backpropagation (BP) artificial neural networks (ANN) and multiple nonlinear regression (MnLR) models were developed to estimate biogas and methane yield in an upflow anaerobic sludge blanket (UASB) reactor treating potato starch processing wastewater (PSPW). Anaerobic process parameters were optimized to identify their importance on methanation. pH, total chemical oxygen demand, ammonium, alkalinity, total Kjeldahl nitrogen, total phosphorus, volatile fatty acids and hydraulic retention time selected based on principal component analysis were used as input variables, whiles biogas and methane yield were employed as target variables. Quasi-Newton method and conjugate gradient backpropagation algorithms were best among eleven training algorithms. Coefficient of determination (R 2 ) of the BP-ANN reached 98.72% and 97.93% whiles MnLR model attained 93.9% and 91.08% for biogas and methane yield, respectively. Compared with the MnLR model, BP-ANN model demonstrated significant performance, suggesting possible control of the anaerobic digestion process with the BP-ANN model. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Using groundwater levels to estimate recharge

    USGS Publications Warehouse

    Healy, R.W.; Cook, P.G.

    2002-01-01

    Accurate estimation of groundwater recharge is extremely important for proper management of groundwater systems. Many different approaches exist for estimating recharge. This paper presents a review of methods that are based on groundwater-level data. The water-table fluctuation method may be the most widely used technique for estimating recharge; it requires knowledge of specific yield and changes in water levels over time. Advantages of this approach include its simplicity and an insensitivity to the mechanism by which water moves through the unsaturated zone. Uncertainty in estimates generated by this method relate to the limited accuracy with which specific yield can be determined and to the extent to which assumptions inherent in the method are valid. Other methods that use water levels (mostly based on the Darcy equation) are also described. The theory underlying the methods is explained. Examples from the literature are used to illustrate applications of the different methods.

  19. Estimation of Dynamic Systems for Gene Regulatory Networks from Dependent Time-Course Data.

    PubMed

    Kim, Yoonji; Kim, Jaejik

    2018-06-15

    Dynamic system consisting of ordinary differential equations (ODEs) is a well-known tool for describing dynamic nature of gene regulatory networks (GRNs), and the dynamic features of GRNs are usually captured through time-course gene expression data. Owing to high-throughput technologies, time-course gene expression data have complex structures such as heteroscedasticity, correlations between genes, and time dependence. Since gene experiments typically yield highly noisy data with small sample size, for a more accurate prediction of the dynamics, the complex structures should be taken into account in ODE models. Hence, this study proposes an ODE model considering such data structures and a fast and stable estimation method for the ODE parameters based on the generalized profiling approach with data smoothing techniques. The proposed method also provides statistical inference for the ODE estimator and it is applied to a zebrafish retina cell network.

  20. Satellite-based assessment of grassland yields

    NASA Astrophysics Data System (ADS)

    Grant, K.; Siegmund, R.; Wagner, M.; Hartmann, S.

    2015-04-01

    Cutting date and frequency are important parameters determining grassland yields in addition to the effects of weather, soil conditions, plant composition and fertilisation. Because accurate and area-wide data of grassland yields are currently not available, cutting frequency can be used to estimate yields. In this project, a method to detect cutting dates via surface changes in radar images is developed. The combination of this method with a grassland yield model will result in more reliable and regional-wide numbers of grassland yields. For the test-phase of the monitoring project, a study area situated southeast of Munich, Germany, was chosen due to its high density of managed grassland. For determining grassland cutting robust amplitude change detection techniques are used evaluating radar amplitude or backscatter statistics before and after the cutting event. CosmoSkyMed and Sentinel-1A data were analysed. All detected cuts were verified according to in-situ measurements recorded in a GIS database. Although the SAR systems had various acquisition geometries, the amount of detected grassland cut was quite similar. Of 154 tested grassland plots, covering in total 436 ha, 116 and 111 cuts were detected using CosmoSkyMed and Sentinel-1A radar data, respectively. Further improvement of radar data processes as well as additional analyses with higher sample number and wider land surface coverage will follow for optimisation of the method and for validation and generalisation of the results of this feasibility study. The automation of this method will than allow for an area-wide and cost efficient cutting date detection service improving grassland yield models.

  1. Establishing a high yielding streptomyces-based cell-free protein synthesis system.

    PubMed

    Li, Jian; Wang, He; Kwon, Yong-Chan; Jewett, Michael C

    2017-06-01

    Cell-free protein synthesis (CFPS) has emerged as a powerful platform for applied biotechnology and synthetic biology, with a range of applications in synthesizing proteins, evolving proteins, and prototyping genetic circuits. To expand the current CFPS repertoire, we report here the development and optimization of a Streptomyces-based CFPS system for the expression of GC-rich genes. By developing a streamlined crude extract preparation protocol and optimizing reaction conditions, we were able to achieve active enhanced green fluorescent protein (EGFP) yields of greater than 50 μg/mL with batch reactions lasting up to 3 h. By adopting a semi-continuous reaction format, the EGFP yield could be increased to 282 ± 8 μg/mL and the reaction time was extended to 48 h. Notably, our extract preparation procedures were robust to multiple Streptomyces lividans and Streptomyces coelicolor strains, although expression yields varied. We show that our optimized Streptomyces lividans system provides benefits when compared to an Escherichia coli-based CFPS system for increasing percent soluble protein expression for four Streptomyces-originated high GC-content genes that are involved in biosynthesis of the nonribosomal peptides tambromycin and valinomycin. Looking forward, we believe that our Streptomyces-based CFPS system will contribute significantly towards efforts to express complex natural product gene clusters (e.g., nonribosomal peptides and polyketides), providing a new avenue for obtaining and studying natural product biosynthesis pathways. Biotechnol. Bioeng. 2017;114: 1343-1353. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  2. [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.

  3. State estimation for spacecraft power systems

    NASA Technical Reports Server (NTRS)

    Williamson, Susan H.; Sheble, Gerald B.

    1990-01-01

    A state estimator appropriate for spacecraft power systems is presented. Phasor voltage and current measurements are used to determine the system state. A weighted least squares algorithm with a multireference transmission cable model is used. Bad data are identified and resolved. Once the bad data have been identified, they are removed from the measurement set and the system state can be estimated from the remaining data. An observability analysis is performed on the remaining measurements to determine if the system state can be found from the reduced measurement set. An example of the algorithm for a sample spacecraft power system is presented.

  4. Estimating chlorophyll content and photochemical yield of photosystem II (ΦPSII) using solar-induced chlorophyll fluorescence measurements at different growing stages of attached leaves

    PubMed Central

    Tubuxin, Bayaer; Rahimzadeh-Bajgiran, Parinaz; Ginnan, Yusaku; Hosoi, Fumiki; Omasa, Kenji

    2015-01-01

    This paper illustrates the possibility of measuring chlorophyll (Chl) content and Chl fluorescence parameters by the solar-induced Chl fluorescence (SIF) method using the Fraunhofer line depth (FLD) principle, and compares the results with the standard measurement methods. A high-spectral resolution HR2000+ and an ordinary USB4000 spectrometer were used to measure leaf reflectance under solar and artificial light, respectively, to estimate Chl fluorescence. Using leaves of Capsicum annuum cv. ‘Sven’ (paprika), the relationships between the Chl content and the steady-state Chl fluorescence near oxygen absorption bands of O2B (686nm) and O2A (760nm), measured under artificial and solar light at different growing stages of leaves, were evaluated. The Chl fluorescence yields of ΦF 686nm/ΦF 760nm ratios obtained from both methods correlated well with the Chl content (steady-state solar light: R2 = 0.73; artificial light: R2 = 0.94). The SIF method was less accurate for Chl content estimation when Chl content was high. The steady-state solar-induced Chl fluorescence yield ratio correlated very well with the artificial-light-induced one (R2 = 0.84). A new methodology is then presented to estimate photochemical yield of photosystem II (ΦPSII) from the SIF measurements, which was verified against the standard Chl fluorescence measurement method (pulse-amplitude modulated method). The high coefficient of determination (R2 = 0.74) between the ΦPSII of the two methods shows that photosynthesis process parameters can be successfully estimated using the presented methodology. PMID:26071530

  5. Argentina wheat yield model

    NASA Technical Reports Server (NTRS)

    Callis, S. L.; Sakamoto, C.

    1984-01-01

    Five models based on multiple regression were developed to estimate wheat yields for the five wheat growing provinces of Argentina. Meteorological data sets were obtained for each province by averaging data for stations within each province. Predictor variables for the models were derived from monthly total precipitation, average monthly mean temperature, and average monthly maximum temperature. Buenos Aires was the only province for which a trend variable was included because of increasing trend in yield due to technology from 1950 to 1963.

  6. Argentina corn yield model

    NASA Technical Reports Server (NTRS)

    Callis, S. L.; Sakamoto, C.

    1984-01-01

    A model based on multiple regression was developed to estimate corn yields for the country of Argentina. A meteorological data set was obtained for the country by averaging data for stations within the corn-growing area. Predictor variables for the model were derived from monthly total precipitation, average monthly mean temperature, and average monthly maximum temperature. A trend variable was included for the years 1965 to 1980 since an increasing trend in yields due to technology was observed between these years.

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. Estimation of quantum yields of weak fluorescence from eosin Y dimers formed in aqueous solutions.

    PubMed

    Enoki, Masami; Katoh, Ryuzi

    2018-05-17

    We studied the weak fluorescence from the dimer of eosin Y (EY) in aqueous solutions. We used a newly developed ultrathin optical cell with a thickness ranging from of the order of microns to several hundreds of microns to successfully measure the fluorescence spectra of highly concentrated aqueous solutions of EY without artifacts caused by the reabsorption of fluorescence. The spectra we obtained were similar to the fluorescence spectrum of the EY monomer; almost no fluorescence was observed from the EY dimer. By a careful comparison of the spectra of solutions at low and high concentrations of EY, we succeeded in extracting the fluorescence spectrum of the EY dimer. The fluorescence quantum yield of the EY dimer was estimated to be 0.005.

  12. 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.

  13. System for Estimating Horizontal Velocity During Descent

    NASA Technical Reports Server (NTRS)

    Johnson, Andrew; Cheng, Yang; Wilson, Reg; Goguen, Jay; Martin, Alejandro San; Leger, Chris; Matthies, Larry

    2007-01-01

    The descent image motion estimation system (DIMES) is a system of hardware and software, designed for original use in estimating the horizontal velocity of a spacecraft descending toward a landing on Mars. The estimated horizontal velocity is used in generating rocket-firing commands to reduce the horizontal velocity as part of an overall control scheme to minimize the landing impact. DIMES can also be used for estimating the horizontal velocity of a remotely controlled or autonomous aircraft for purposes of navigation and control.

  14. Drogue pose estimation for unmanned aerial vehicle autonomous aerial refueling system based on infrared vision sensor

    NASA Astrophysics Data System (ADS)

    Chen, Shanjun; Duan, Haibin; Deng, Yimin; Li, Cong; Zhao, Guozhi; Xu, Yan

    2017-12-01

    Autonomous aerial refueling is a significant technology that can significantly extend the endurance of unmanned aerial vehicles. A reliable method that can accurately estimate the position and attitude of the probe relative to the drogue is the key to such a capability. A drogue pose estimation method based on infrared vision sensor is introduced with the general goal of yielding an accurate and reliable drogue state estimate. First, by employing direct least squares ellipse fitting and convex hull in OpenCV, a feature point matching and interference point elimination method is proposed. In addition, considering the conditions that some infrared LEDs are damaged or occluded, a missing point estimation method based on perspective transformation and affine transformation is designed. Finally, an accurate and robust pose estimation algorithm improved by the runner-root algorithm is proposed. The feasibility of the designed visual measurement system is demonstrated by flight test, and the results indicate that our proposed method enables precise and reliable pose estimation of the probe relative to the drogue, even in some poor conditions.

  15. 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

  16. Gene and transcript abundances of bacterial type III secretion systems from the rumen microbiome are correlated with methane yield in sheep.

    PubMed

    Kamke, Janine; Soni, Priya; Li, Yang; Ganesh, Siva; Kelly, William J; Leahy, Sinead C; Shi, Weibing; Froula, Jeff; Rubin, Edward M; Attwood, Graeme T

    2017-08-08

    Ruminants are important contributors to global methane emissions via microbial fermentation in their reticulo-rumens. This study is part of a larger program, characterising the rumen microbiomes of sheep which vary naturally in methane yield (g CH 4 /kg DM/day) and aims to define differences in microbial communities, and in gene and transcript abundances that can explain the animal methane phenotype. Rumen microbiome metagenomic and metatranscriptomic data were analysed by Gene Set Enrichment, sparse partial least squares regression and the Wilcoxon Rank Sum test to estimate correlations between specific KEGG bacterial pathways/genes and high methane yield in sheep. KEGG genes enriched in high methane yield sheep were reassembled from raw reads and existing contigs and analysed by MEGAN to predict their phylogenetic origin. Protein coding sequences from Succinivibrio dextrinosolvens strains were analysed using Effective DB to predict bacterial type III secreted proteins. The effect of S. dextrinosolvens strain H5 growth on methane formation by rumen methanogens was explored using co-cultures. Detailed analysis of the rumen microbiomes of high methane yield sheep shows that gene and transcript abundances of bacterial type III secretion system genes are positively correlated with methane yield in sheep. Most of the bacterial type III secretion system genes could not be assigned to a particular bacterial group, but several genes were affiliated with the genus Succinivibrio, and searches of bacterial genome sequences found that strains of S. dextrinosolvens were part of a small group of rumen bacteria that encode this type of secretion system. In co-culture experiments, S. dextrinosolvens strain H5 showed a growth-enhancing effect on a methanogen belonging to the order Methanomassiliicoccales, and inhibition of a representative of the Methanobrevibacter gottschalkii clade. This is the first report of bacterial type III secretion system genes being associated with high

  17. Quantitative analysis of microbial biomass yield in aerobic bioreactor.

    PubMed

    Watanabe, Osamu; Isoda, Satoru

    2013-12-01

    We have studied the integrated model of reaction rate equations with thermal energy balance in aerobic bioreactor for food waste decomposition and showed that the integrated model has the capability both of monitoring microbial activity in real time and of analyzing biodegradation kinetics and thermal-hydrodynamic properties. On the other hand, concerning microbial metabolism, it was known that balancing catabolic reactions with anabolic reactions in terms of energy and electron flow provides stoichiometric metabolic reactions and enables the estimation of microbial biomass yield (stoichiometric reaction model). We have studied a method for estimating real-time microbial biomass yield in the bioreactor during food waste decomposition by combining the integrated model with the stoichiometric reaction model. As a result, it was found that the time course of microbial biomass yield in the bioreactor during decomposition can be evaluated using the operational data of the bioreactor (weight of input food waste and bed temperature) by the combined model. The combined model can be applied to manage a food waste decomposition not only for controlling system operation to keep microbial activity stable, but also for producing value-added products such as compost on optimum condition. Copyright © 2013 The Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.

  18. 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; hide

    2016-01-01

    The aggregation of simulated gridded crop yields to national or regional scale requires information on temporal and spatial patterns of crop-specific harvested areas. This analysis estimates the uncertainty of simulated gridded yield time series related to the aggregation with four different harvested area data sets. We compare aggregated yield time series from the Global Gridded Crop Model Inter-comparison project for four crop types from 14 models at global, national, and regional scale to determine aggregation-driven differences in mean yields and temporal patterns as measures of uncertainty. The quantity and spatial patterns of harvested areas differ for individual crops among the four datasets applied for the aggregation. Also simulated spatial yield patterns differ among the 14 models. These differences in harvested areas and simulated yield patterns lead to differences in aggregated productivity estimates, both in mean yield and in the temporal dynamics. Among the four investigated crops, wheat yield (17% relative difference) is most affected by the uncertainty introduced by the aggregation at the global scale. The correlation of temporal patterns of global aggregated yield time series can be as low as for soybean (r = 0.28).For the majority of countries, mean relative differences of nationally aggregated yields account for10% or less. The spatial and temporal difference can be substantial higher for individual countries. Of the top-10 crop producers, aggregated national multi-annual mean relative difference of yields can be up to 67% (maize, South Africa), 43% (wheat, Pakistan), 51% (rice, Japan), and 427% (soybean, Bolivia).Correlations of differently aggregated yield time series can be as low as r = 0.56 (maize, India), r = 0.05*Corresponding (wheat, Russia), r = 0.13 (rice, Vietnam), and r = -0.01 (soybean, Uruguay). The aggregation to sub-national scale in comparison to country scale shows that spatial uncertainties can cancel out in countries with

  19. Light- and water-use efficiency model synergy: a revised look at crop yield estimation for agricultural decision-making

    NASA Astrophysics Data System (ADS)

    Marshall, M.; Tu, K. P.

    2015-12-01

    Large-area crop yield models (LACMs) are commonly employed to address climate-driven changes in crop yield and inform policy makers concerned with climate change adaptation. Production efficiency models (PEMs), a class of LACMs that rely on the conservative response of carbon assimilation to incoming solar radiation absorbed by a crop contingent on environmental conditions, have increasingly been used over large areas with remote sensing spectral information to improve the spatial resolution of crop yield estimates and address important data gaps. Here, we present a new PEM that combines model principles from the remote sensing-based crop yield and evapotranspiration (ET) model literature. One of the major limitations of PEMs is that they are evaluated using data restricted in both space and time. To overcome this obstacle, we first validated the model using 2009-2014 eddy covariance flux tower Gross Primary Production data in a rice field in the Central Valley of California- a critical agro-ecosystem of the United States. This evaluation yielded a Willmot's D and mean absolute error of 0.81 and 5.24 g CO2/d, respectively, using CO2, leaf area, temperature, and moisture constraints from the MOD16 ET model, Priestley-Taylor ET model, and the Global Production Efficiency Model (GLOPEM). A Monte Carlo simulation revealed that the model was most sensitive to the Enhanced Vegetation Index (EVI) input, followed by Photosynthetically Active Radiation, vapor pressure deficit, and air temperature. The model will now be evaluated using 30 x 30m (Landsat resolution) biomass transects developed in 2011 and 2012 from spectroradiometric and other non-destructive in situ metrics for several cotton, maize, and rice fields across the Central Valley. Finally, the model will be driven by Daymet and MODIS data over the entire State of California and compared with county-level crop yield statistics. It is anticipated that the new model will facilitate agro-climatic decision-making in

  20. Accounting for the decrease of photosystem photochemical efficiency with increasing irradiance to estimate quantum yield of leaf photosynthesis.

    PubMed

    Yin, Xinyou; Belay, Daniel W; van der Putten, Peter E L; Struik, Paul C

    2014-12-01

    Maximum quantum yield for leaf CO2 assimilation under limiting light conditions (Φ CO2LL) is commonly estimated as the slope of the linear regression of net photosynthetic rate against absorbed irradiance over a range of low-irradiance conditions. Methodological errors associated with this estimation have often been attributed either to light absorptance by non-photosynthetic pigments or to some data points being beyond the linear range of the irradiance response, both causing an underestimation of Φ CO2LL. We demonstrate here that a decrease in photosystem (PS) photochemical efficiency with increasing irradiance, even at very low levels, is another source of error that causes a systematic underestimation of Φ CO2LL. A model method accounting for this error was developed, and was used to estimate Φ CO2LL from simultaneous measurements of gas exchange and chlorophyll fluorescence on leaves using various combinations of species, CO2, O2, or leaf temperature levels. The conventional linear regression method under-estimated Φ CO2LL by ca. 10-15%. Differences in the estimated Φ CO2LL among measurement conditions were generally accounted for by different levels of photorespiration as described by the Farquhar-von Caemmerer-Berry model. However, our data revealed that the temperature dependence of PSII photochemical efficiency under low light was an additional factor that should be accounted for in the model.

  1. 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 ...

  2. Upper Limits for Power Yield in Thermal, Chemical, and Electrochemical Systems

    NASA Astrophysics Data System (ADS)

    Sieniutycz, Stanislaw

    2010-03-01

    We consider modeling and power optimization of energy converters, such as thermal, solar and chemical engines and fuel cells. Thermodynamic principles lead to expressions for converter's efficiency and generated power. Efficiency equations serve to solve the problems of upgrading or downgrading a resource. Power yield is a cumulative effect in a system consisting of a resource, engines, and an infinite bath. While optimization of steady state systems requires using the differential calculus and Lagrange multipliers, dynamic optimization involves variational calculus and dynamic programming. The primary result of static optimization is the upper limit of power, whereas that of dynamic optimization is a finite-rate counterpart of classical reversible work (exergy). The latter quantity depends on the end state coordinates and a dissipation index, h, which is the Hamiltonian of the problem of minimum entropy production. In reacting systems, an active part of chemical affinity constitutes a major component of the overall efficiency. The theory is also applied to fuel cells regarded as electrochemical flow engines. Enhanced bounds on power yield follow, which are stronger than those predicted by the reversible work potential.

  3. Estimates of spatial and temporal variation of energy crops biomass yields in the US

    NASA Astrophysics Data System (ADS)

    Song, Y.; Jain, A. K.; Landuyt, W.; Kheshgi, H. S.

    2013-12-01

    Perennial grasses, such as switchgrass (Panicum viragatum) and Miscanthus (Miscanthus x giganteus) have been identified for potential use as biomass feedstocks in the US. Current research on perennial grass biomass production has been evaluated on small-scale plots. However, the extent to which this potential can be realized at a landscape-scale will depend on the biophysical potential to grow these grasses with minimum possible amount of land that needs to be diverted from food to fuel production. To assess this potential three questions about the biomass yield for these grasses need to be answered: (1) how the yields for different grasses are varied spatially and temporally across the US; (2) whether the yields are temporally stable or not; and (3) how the spatial and temporal trends in yields of these perennial grasses are controlled by limiting factors, including soil type, water availability, climate, and crop varieties. To answer these questions, the growth processes of the perennial grasses are implemented into a coupled biophysical, physiological and biogeochemical model (ISAM). The model has been applied to quantitatively investigate the spatial and temporal trends in biomass yields for over the period 1980 -2010 in the US. The bioenergy grasses considered in this study include Miscanthus, Cave-in-Rock switchgrass and Alamo switchgrass. The effects of climate, soil and topography on the spatial and temporal trends of biomass yields are quantitatively analyzed using principal component analysis and GIS based geographically weighted regression. The spatial temporal trend results are evaluated further to classify each part of the US into four homogeneous potential yield zones: high and stable yield zone (HS), high but unstable yield zone (HU), low and stable yield zone (LS) and low but unstable yield zone (LU). Our preliminary results indicate that the yields for perennial grasses among different zones are strongly related to the different controlling factors

  4. Using FACE systems to screen wheat cultivars for yield increases at elevated CO2

    USDA-ARS?s Scientific Manuscript database

    Because of continuing increases in atmospheric CO2, identifying cultivars of crops with larger yield increases at elevated CO2 may provide an avenue to increase crop yield potential in future climates. Free-air CO2 enrichment (FACE) systems have most often been used with multiple replications of ea...

  5. 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.

  6. Downscaling of a global climate model for estimation of runoff, sediment yield and dam storage: A case study of Pirapama basin, Brazil

    NASA Astrophysics Data System (ADS)

    Braga, Ana Cláudia F. Medeiros; Silva, Richarde Marques da; Santos, Celso Augusto Guimarães; Galvão, Carlos de Oliveira; Nobre, Paulo

    2013-08-01

    The coastal zone of northeastern Brazil is characterized by intense human activities and by large settlements and also experiences high soil losses that can contribute to environmental damage. Therefore, it is necessary to build an integrated modeling-forecasting system for rainfall-runoff erosion that assesses plans for water availability and sediment yield that can be conceived and implemented. In this work, we present an evaluation of an integrated modeling system for a basin located in this region with a relatively low predictability of seasonal rainfall and a small area (600 km2). The National Center for Environmental Predictions - NCEP’s Regional Spectral Model (RSM) nested within the Center for Weather Forecasting and Climate Studies - CPTEC’s Atmospheric General Circulation Model (AGCM) were investigated in this study, and both are addressed in the simulation work. The rainfall analysis shows that: (1) the dynamic downscaling carried out by the regional RSM model approximates the frequency distribution of the daily observed data set although errors were detected in the magnitude and timing (anticipation of peaks, for example) at the daily scale, (2) an unbiased precipitation forecast seemed to be essential for use of the results in hydrological models, and (3) the information directly extracted from the global model may also be useful. The simulated runoff and reservoir-stored volumes are strongly linked to rainfall, and their estimation accuracy was significantly improved at the monthly scale, thus rendering the results useful for management purposes. The runoff-erosion forecasting displayed a large sediment yield that was consistent with the predicted rainfall.

  7. Development and Analysis of Global, High-Resolution Diagnostic Metrics for Vegetation Monitoring, Yield Estimation and Famine Mitigation

    NASA Astrophysics Data System (ADS)

    Anderson, B. T.; Zhang, P.; Myneni, R.

    2008-12-01

    Drought, through its impact on food scarcity and crop prices, can have significant economic, social, and environmental impacts - presently, up to 36 countries and 73 million people are facing food crises around the globe. Because of these adverse affects, there has been a drive to develop drought and vegetation- monitoring metrics that can quantify and predict human vulnerability/susceptibility to drought at high- resolution spatial scales over the entire globe. Here we introduce a new vegetation-monitoring index utilizing data derived from satellite-based instruments (the Moderate Resolution Imaging Spectroradiometer - MODIS) designed to identify the vulnerability of vegetation in a particular region to climate variability during the growing season. In addition, the index can quantify the percentage of annual grid-point vegetation production either gained or lost due to climatic variability in a given month. When integrated over the growing season, this index is shown to be better correlated with end-of-season crop yields than traditional remotely-sensed or meteorological indices. In addition, in-season estimates of the index, which are available in near real-time, provide yield forecasts comparable to concurrent in situ objective yield surveys, which are only available in limited regions of the world. Overall, the cost effectiveness and repetitive, near-global view of earth's surface provided by this satellite-based vegetation monitoring index can potentially improve our ability to mitigate human vulnerability/susceptibility to drought and its impacts upon vegetation and agriculture.

  8. Mean size estimation yields left-side bias: Role of attention on perceptual averaging.

    PubMed

    Li, Kuei-An; Yeh, Su-Ling

    2017-11-01

    The human visual system can estimate mean size of a set of items effectively; however, little is known about whether information on each visual field contributes equally to the mean size estimation. In this study, we examined whether a left-side bias (LSB)-perceptual judgment tends to depend more heavily on left visual field's inputs-affects mean size estimation. Participants were instructed to estimate the mean size of 16 spots. In half of the trials, the mean size of the spots on the left side was larger than that on the right side (the left-larger condition) and vice versa (the right-larger condition). Our results illustrated an LSB: A larger estimated mean size was found in the left-larger condition than in the right-larger condition (Experiment 1), and the LSB vanished when participants' attention was effectively cued to the right side (Experiment 2b). Furthermore, the magnitude of LSB increased with stimulus-onset asynchrony (SOA), when spots on the left side were presented earlier than the right side. In contrast, the LSB vanished and then induced a reversed effect with SOA when spots on the right side were presented earlier (Experiment 3). This study offers the first piece of evidence suggesting that LSB does have a significant influence on mean size estimation of a group of items, which is induced by a leftward attentional bias that enhances the prior entry effect on the left side.

  9. Evaluation of sliding baseline methods for spatial estimation for cluster detection in the biosurveillance system

    PubMed Central

    Xing, Jian; Burkom, Howard; Moniz, Linda; Edgerton, James; Leuze, Michael; Tokars, Jerome

    2009-01-01

    Background The Centers for Disease Control and Prevention's (CDC's) BioSense system provides near-real time situational awareness for public health monitoring through analysis of electronic health data. Determination of anomalous spatial and temporal disease clusters is a crucial part of the daily disease monitoring task. Our study focused on finding useful anomalies at manageable alert rates according to available BioSense data history. Methods The study dataset included more than 3 years of daily counts of military outpatient clinic visits for respiratory and rash syndrome groupings. We applied four spatial estimation methods in implementations of space-time scan statistics cross-checked in Matlab and C. We compared the utility of these methods according to the resultant background cluster rate (a false alarm surrogate) and sensitivity to injected cluster signals. The comparison runs used a spatial resolution based on the facility zip code in the patient record and a finer resolution based on the residence zip code. Results Simple estimation methods that account for day-of-week (DOW) data patterns yielded a clear advantage both in background cluster rate and in signal sensitivity. A 28-day baseline gave the most robust results for this estimation; the preferred baseline is long enough to remove daily fluctuations but short enough to reflect recent disease trends and data representation. Background cluster rates were lower for the rash syndrome counts than for the respiratory counts, likely because of seasonality and the large scale of the respiratory counts. Conclusion The spatial estimation method should be chosen according to characteristics of the selected data streams. In this dataset with strong day-of-week effects, the overall best detection performance was achieved using subregion averages over a 28-day baseline stratified by weekday or weekend/holiday behavior. Changing the estimation method for particular scenarios involving different spatial resolution

  10. Effect of tillage system on yield and weed populations of soybean ( Glycin Max L.).

    PubMed

    Hosseini, Seyed Z; Firouzi, Saeed; Aminpanah, Hashem; Sadeghnejhad, Hamid R

    2016-03-01

    Field experiment was conducted at Agricultural and Natural Resources Research Center of Golestan Province, Iran, to determine the effects of tillage system and weed management regime on yield and weed populations in soybean ( Glycin max L.). The experimental design was a split plot where the whole plot portion was a randomized complete block with three replicates. Main plots were tillage system: 1- No-till row crop seeding, 2- No-till seed drilling, 3- Tillage with disc harrow and drill planting, 4- Tillage with chisel packer and drill planting. The subplots were weed management regimes: 1-Weed control with herbicide application, 2- Hand weeding, 3- Herbicide application plus hand weeding, and 4- Non-weeding. Results indicated that the main effects of tillage system and weed management regime were significant for seed yield, pod number per plant, seed number per pod, weed density and biomass, while their interaction were significant only for weed density, weed biomass, and seed number per pod. The highest grain yields (3838 kg ha-1) were recorded for No-till row crop seeding. The highest seed yield (3877 kg ha-1) also was recorded for weed control with herbicide and hand weeding treatment, followed by hand weeding (3379 kg ha-1).

  11. Statistical modeling of yield and variance instability in conventional and organic cropping systems

    USDA-ARS?s Scientific Manuscript database

    Cropping systems research was undertaken to address declining crop diversity and verify competitiveness of alternatives to the predominant conventional cropping system in the northern Corn Belt. To understand and capitalize on temporal yield variability within corn and soybean fields, we quantified ...

  12. Heavy metals effects on forage crops yields and estimation of elements accumulation in plants as affected by soil.

    PubMed

    Grytsyuk, N; Arapis, G; Perepelyatnikova, L; Ivanova, T; Vynograds'ka, V

    2006-02-01

    Heavy metals (Cu, Cd, Pb, Zn) effect on the productivity of forage crops (clover and perennial cereal grasses) and their accumulation in plants, depending on the concentration of these elements in a soil, has been studied in micro-field experiments on three types of soil. The principle objective was to determine regularities of heavy metals migration in a soil-plant system aiming the estimation of permissible levels of heavy metals content in soils with the following elaboration of methods, which regulate the toxicants transfer to plants. Methods of field experiments, agrochemical and atomic absorption analysis were used. Results were statistically treated by Statistica 6.0, S-Plus 6. Experimental results have shown that the intensity of heavy metals accumulation in plants depends on the type of the soil, the species of plants, the physicochemical properties of heavy metals and their content in the soil. Logarithmic interdependency of heavy metals concentration in soils and their accumulation in plants is suggested. However, the strong correlation between the different heavy metals concentrations in the various soils and the yield of crops was not observed. Toxicants accumulation in crops decreased in time.

  13. Surprising yields with no-till cropping systems

    USDA-ARS?s Scientific Manuscript database

    Producers using no-till practices have observed that crop yields can greatly exceed expectations based on nutrient and water supply. For example, Ralph Holzwarth, who farms near Gettysburg, SD, has averaged 150 bu/ac of corn on his farm for the past 6 years. We were surprised with this yield, as c...

  14. Genetic parameters of coagulation properties, milk yield, quality, and acidity estimated using coagulating and noncoagulating milk information in Brown Swiss and Holstein-Friesian cows.

    PubMed

    Cecchinato, A; Penasa, M; De Marchi, M; Gallo, L; Bittante, G; Carnier, P

    2011-08-01

    The aim of this study was to estimate heritabilities of rennet coagulation time (RCT) and curd firmness (a(30)) and their genetic correlations with test-day milk yield, composition (fat, protein, and casein content), somatic cell score, and acidity (pH and titratable acidity) using coagulating and noncoagulating (NC) milk information. Data were from 1,025 Holstein-Friesian (HF) and 1,234 Brown Swiss (BS) cows, which were progeny of 54 HF and 58 BS artificial insemination sires, respectively. Milk coagulation properties (MCP) of each cow were measured once using a computerized renneting meter and samples not exhibiting coagulation within 31 min after rennet addition were classified as NC milk. For NC samples, RCT was unobserved. Multivariate analyses, using Bayesian methodology, were performed to estimate the genetic relationships of RCT or a(30) with the other traits and statistical inference was based on the marginal posterior distributions of parameters of concern. For analyses involving RCT, a right-censored Gaussian linear model was used and records of NC milk samples, being censored records, were included as unknown parameters in the model implementing a data augmentation procedure. Rennet coagulation time was more heritable [heritability (h(2))=0.240 and h(2)=0.210 for HF and BS, respectively] than a(30) (h(2)=0.148 and h(2)=0.168 for HF and BS, respectively). Milk coagulation properties were more heritable than a single test-day milk yield (h(2)=0.103 and h(2)=0.097 for HF and BS, respectively) and less heritable than milk composition traits whose heritability ranged from 0.275 to 0.275, with the only exception of fat content of BS milk (h(2)=0.108). A negative genetic correlation, lower than -0.85, was estimated between RCT and a(30) for both breeds. Genetic relationships of MCP with yield and composition were low or moderate and favorable. The genetic correlation of somatic cell score with RCT in BS cows was large and positive and even more positive were

  15. 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.

  16. Maximum sustainable yield estimates of Ladypees, Sillago sihama (Forsskål), fishery in Pakistan using the ASPIC and CEDA packages

    NASA Astrophysics Data System (ADS)

    Panhwar, Sher Khan; Liu, Qun; Khan, Fozia; Siddiqui, Pirzada J. A.

    2012-03-01

    Using surplus production model packages of ASPIC (a stock-production model incorporating covariates) and CEDA (Catch effort data analysis), we analyzed the catch and effort data of Sillago sihama fishery in Pakistan. ASPIC estimates the parameters of MSY (maximum sustainable yield), F msy (fishing mortality), q (catchability coefficient), K (carrying capacity or unexploited biomass) and B1/K (maximum sustainable yield over initial biomass). The estimated non-bootstrapped value of MSY based on logistic was 598 t and that based on the Fox model was 415 t, which showed that the Fox model estimation was more conservative than that with the logistic model. The R 2 with the logistic model (0.702) is larger than that with the Fox model (0.541), which indicates a better fit. The coefficient of variation (cv) of the estimated MSY was about 0.3, except for a larger value 88.87 and a smaller value of 0.173. In contrast to the ASPIC results, the R 2 with the Fox model (0.651-0.692) was larger than that with the Schaefer model (0.435-0.567), indicating a better fit. The key parameters of CEDA are: MSY, K, q, and r (intrinsic growth), and the three error assumptions in using the models are normal, log normal and gamma. Parameter estimates from the Schaefer and Pella-Tomlinson models were similar. The MSY estimations from the above two models were 398 t, 549 t and 398 t for normal, log-normal and gamma error distributions, respectively. The MSY estimates from the Fox model were 381 t, 366 t and 366 t for the above three error assumptions, respectively. The Fox model estimates were smaller than those for the Schaefer and the Pella-Tomlinson models. In the light of the MSY estimations of 415 t from ASPIC for the Fox model and 381 t from CEDA for the Fox model, MSY for S. sihama is about 400 t. As the catch in 2003 was 401 t, we would suggest the fishery should be kept at the current level. Production models used here depend on the assumption that CPUE (catch per unit effort) data

  17. 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.

  18. 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

  19. 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

  20. Brazil wheat yield covariance model

    NASA Technical Reports Server (NTRS)

    Callis, S. L.; Sakamoto, C.

    1984-01-01

    A model based on multiple regression was developed to estimate wheat yields for the wheat growing states of Rio Grande do Sul, Parana, and Santa Catarina in Brazil. The meteorological data of these three states were pooled and the years 1972 to 1979 were used to develop the model since there was no technological trend in the yields during these years. Predictor variables were derived from monthly total precipitation, average monthly mean temperature, and average monthly maximum temperature.

  1. Effect of Damping and Yielding on the Seismic Response of 3D Steel Buildings with PMRF

    PubMed Central

    Haldar, Achintya; Rodelo-López, Ramon Eduardo; Bojórquez, Eden

    2014-01-01

    The effect of viscous damping and yielding, on the reduction of the seismic responses of steel buildings modeled as three-dimensional (3D) complex multidegree of freedom (MDOF) systems, is studied. The reduction produced by damping may be larger or smaller than that of yielding. This reduction can significantly vary from one structural idealization to another and is smaller for global than for local response parameters, which in turn depends on the particular local response parameter. The uncertainty in the estimation is significantly larger for local response parameter and decreases as damping increases. The results show the limitations of the commonly used static equivalent lateral force procedure where local and global response parameters are reduced in the same proportion. It is concluded that estimating the effect of damping and yielding on the seismic response of steel buildings by using simplified models may be a very crude approximation. Moreover, the effect of yielding should be explicitly calculated by using complex 3D MDOF models instead of estimating it in terms of equivalent viscous damping. The findings of this paper are for the particular models used in the study. Much more research is needed to reach more general conclusions. PMID:25097892

  2. Effect of damping and yielding on the seismic response of 3D steel buildings with PMRF.

    PubMed

    Reyes-Salazar, Alfredo; Haldar, Achintya; Rodelo-López, Ramon Eduardo; Bojórquez, Eden

    2014-01-01

    The effect of viscous damping and yielding, on the reduction of the seismic responses of steel buildings modeled as three-dimensional (3D) complex multidegree of freedom (MDOF) systems, is studied. The reduction produced by damping may be larger or smaller than that of yielding. This reduction can significantly vary from one structural idealization to another and is smaller for global than for local response parameters, which in turn depends on the particular local response parameter. The uncertainty in the estimation is significantly larger for local response parameter and decreases as damping increases. The results show the limitations of the commonly used static equivalent lateral force procedure where local and global response parameters are reduced in the same proportion. It is concluded that estimating the effect of damping and yielding on the seismic response of steel buildings by using simplified models may be a very crude approximation. Moreover, the effect of yielding should be explicitly calculated by using complex 3D MDOF models instead of estimating it in terms of equivalent viscous damping. The findings of this paper are for the particular models used in the study. Much more research is needed to reach more general conclusions.

  3. A-posteriori error estimation for second order mechanical systems

    NASA Astrophysics Data System (ADS)

    Ruiner, Thomas; Fehr, Jörg; Haasdonk, Bernard; Eberhard, Peter

    2012-06-01

    One important issue for the simulation of flexible multibody systems is the reduction of the flexible bodies degrees of freedom. As far as safety questions are concerned knowledge about the error introduced by the reduction of the flexible degrees of freedom is helpful and very important. In this work, an a-posteriori error estimator for linear first order systems is extended for error estimation of mechanical second order systems. Due to the special second order structure of mechanical systems, an improvement of the a-posteriori error estimator is achieved. A major advantage of the a-posteriori error estimator is that the estimator is independent of the used reduction technique. Therefore, it can be used for moment-matching based, Gramian matrices based or modal based model reduction techniques. The capability of the proposed technique is demonstrated by the a-posteriori error estimation of a mechanical system, and a sensitivity analysis of the parameters involved in the error estimation process is conducted.

  4. Estimating growth and yield of mixed stands

    Treesearch

    Stephen R. Shifley; Burnell C. Fischer

    1989-01-01

    A mixed stand is defined as one in which no single species comprises more than 80 percent of the stocking. The growth estimation methods described below can be used not only in mixed stands but in almost any stand, regardless of species composition, age structure, or size structure. The methods described are necessary to accommodate the complex species mixtures and...

  5. Erodibility of selected soils and estimates of sediment yields in the San Juan Basin, New Mexico

    USGS Publications Warehouse

    Summer, Rebecca M.

    1981-01-01

    Onsite rainfall-simulation experiments were conducted to derive field-erodibility indexes for rangeland soils and soils disturbed by mining in coal fields of northwestern New Mexico. Mean indexes on rangeland soils range from 0 grams (of detached soil) on dune soil to 121 grams on wash-transport zones. Mean field-erodibility-index values of soils disturbed by mining range from 16 to 32 grams; they can be extrapolted to nearby coal fields where future mining is expected. Because field-erodibility-index data allow differentiation of erodibilities across a variable landscape, these indexes were used to adjust values of K, the erodibility factor of the Universal Soil Loss Equation. Estimates of soil loss and sediment yield were then calculated for a small basin following mining. (USGS)

  6. Estimating Evapotranspiration with Land Data Assimilation Systems

    NASA Technical Reports Server (NTRS)

    Peters-Lidard, C. D.; Kumar, S. V.; Mocko, D. M.; Tian, Y.

    2011-01-01

    Advancements in both land surface models (LSM) and land surface data assimilation, especially over the last decade, have substantially advanced the ability of land data assimilation systems (LDAS) to estimate evapotranspiration (ET). This article provides a historical perspective on international LSM intercomparison efforts and the development of LDAS systems, both of which have improved LSM ET skill. In addition, an assessment of ET estimates for current LDAS systems is provided along with current research that demonstrates improvement in LSM ET estimates due to assimilating satellite-based soil moisture products. Using the Ensemble Kalman Filter in the Land Information System, we assimilate both NASA and Land Parameter Retrieval Model (LPRM) soil moisture products into the Noah LSM Version 3.2 with the North American LDAS phase 2 (NLDAS-2) forcing to mimic the NLDAS-2 configuration. Through comparisons with two global reference ET products, one based on interpolated flux tower data and one from a new satellite ET algorithm, over the NLDAS2 domain, we demonstrate improvement in ET estimates only when assimilating the LPRM soil moisture product.

  7. Development of a European Ensemble System for Seasonal Prediction: Application to crop yield

    NASA Astrophysics Data System (ADS)

    Terres, J. M.; Cantelaube, P.

    2003-04-01

    Western European agriculture is highly intensive and the weather is the main source of uncertainty for crop yield assessment and for crop management. In the current system, at the time when a crop yield forecast is issued, the weather conditions leading up to harvest time are unknown and are therefore a major source of uncertainty. The use of seasonal weather forecast would bring additional information for the remaining crop season and has valuable benefit for improving the management of agricultural markets and environmentally sustainable farm practices. An innovative method for supplying seasonal forecast information to crop simulation models has been developed in the frame of the EU funded research project DEMETER. It consists in running a crop model on each individual member of the seasonal hindcasts to derive a probability distribution of crop yield. Preliminary results of cumulative probability function of wheat yield provides information on both the yield anomaly and the reliability of the forecast. Based on the spread of the probability distribution, the end-user can directly quantify the benefits and risks of taking weather-sensitive decisions.

  8. Development and validation of equations utilizing lamb vision system output to predict lamb carcass fabrication yields.

    PubMed

    Cunha, B C N; Belk, K E; Scanga, J A; LeValley, S B; Tatum, J D; Smith, G C

    2004-07-01

    This study was performed to validate previous equations and to develop and evaluate new regression equations for predicting lamb carcass fabrication yields using outputs from a lamb vision system-hot carcass component (LVS-HCC) and the lamb vision system-chilled carcass LM imaging component (LVS-CCC). Lamb carcasses (n = 149) were selected after slaughter, imaged hot using the LVS-HCC, and chilled for 24 to 48 h at -3 to 1 degrees C. Chilled carcasses yield grades (YG) were assigned on-line by USDA graders and by expert USDA grading supervisors with unlimited time and access to the carcasses. Before fabrication, carcasses were ribbed between the 12th and 13th ribs and imaged using the LVS-CCC. Carcasses were fabricated into bone-in subprimal/primal cuts. Yields calculated included 1) saleable meat yield (SMY); 2) subprimal yield (SPY); and 3) fat yield (FY). On-line (whole-number) USDA YG accounted for 59, 58, and 64%; expert (whole-number) USDA YG explained 59, 59, and 65%; and expert (nearest-tenth) USDA YG accounted for 60, 60, and 67% of the observed variation in SMY, SPY, and FY, respectively. The best prediction equation developed in this trial using LVS-HCC output and hot carcass weight as independent variables explained 68, 62, and 74% of the variation in SMY, SPY, and FY, respectively. Addition of output from LVS-CCC improved predictive accuracy of the equations; the combined output equations explained 72 and 66% of the variability in SMY and SPY, respectively. Accuracy and repeatability of measurement of LM area made with the LVS-CCC also was assessed, and results suggested that use of LVS-CCC provided reasonably accurate (R2 = 0.59) and highly repeatable (repeatability = 0.98) measurements of LM area. Compared with USDA YG, use of the dual-component lamb vision system to predict cut yields of lamb carcasses improved accuracy and precision, suggesting that this system could have an application as an objective means for pricing carcasses in a value

  9. Normalized Difference Vegetation Index as a Tool for Wheat Yield Estimation: A Case Study from Faisalabad, Pakistan

    PubMed Central

    Sultana, Syeda Refat; Ali, Amjed; Ahmad, Ashfaq; Mubeen, Muhammad; Zia-Ul-Haq, M.; Ahmad, Shakeel; Ercisli, Sezai; Jaafar, Hawa Z. E.

    2014-01-01

    For estimation of grain yield in wheat, Normalized Difference Vegetation Index (NDVI) is considered as a potential screening tool. Field experiments were conducted to scrutinize the response of NDVI to yield behavior of different wheat cultivars and nitrogen fertilization at agronomic research area, University of Agriculture Faisalabad (UAF) during the two years 2008-09 and 2009-10. For recording the value of NDVI, Green seeker (Handheld-505) was used. Split plot design was used as experimental model in, keeping four nitrogen rates (N1 = 0 kg ha−1, N2 = 55 kg ha−1, N3 = 110 kg ha−1, and N4 = 220 kg ha−1) in main plots and ten wheat cultivars (Bakkhar-2001, Chakwal-50, Chakwal-97, Faisalabad-2008, GA-2002, Inqlab-91, Lasani-2008, Miraj-2008, Sahar-2006, and Shafaq-2006) in subplots with four replications. Impact of nitrogen and difference between cultivars were forecasted through NDVI. The results suggested that nitrogen treatment N4 (220 kg ha−1) and cultivar Faisalabad-2008 gave maximum NDVI value (0.85) at grain filling stage among all treatments. The correlation among NDVI at booting, grain filling, and maturity stages with grain yield was positive (R 2 = 0.90; R 2 = 0.90; R 2 = 0.95), respectively. So, booting, grain filling, and maturity can be good depictive stages during mid and later growth stages of wheat crop under agroclimatic conditions of Faisalabad and under similar other wheat growing environments in the country. PMID:25045744

  10. Flood-tolerant rice reduces yield variability and raises expected yield, differentially benefitting socially disadvantaged groups

    PubMed Central

    Dar, Manzoor H.; de Janvry, Alain; Emerick, Kyle; Raitzer, David; Sadoulet, Elisabeth

    2013-01-01

    Approximately 30% of the cultivated rice area in India is prone to crop damage from prolonged flooding. We use a randomized field experiment in 128 villages of Orissa India to show that Swarna-Sub1, a recently released submergence-tolerant rice variety, has significant positive impacts on rice yield when fields are submerged for 7 to 14 days with no yield penalty without flooding. We estimate that Swarna-Sub1 offers an approximate 45% increase in yields over the current popular variety when fields are submerged for 10 days. We show additionally that low-lying areas prone to flooding tend to be more heavily occupied by people belonging to lower caste social groups. Thus, a policy relevant implication of our findings is that flood-tolerant rice can deliver both efficiency gains, through reduced yield variability and higher expected yield, and equity gains in disproportionately benefiting the most marginal group of farmers. PMID:24263095

  11. Simultaneous state-parameter estimation supports the evaluation of data assimilation performance and measurement design for soil-water-atmosphere-plant system

    NASA Astrophysics Data System (ADS)

    Hu, Shun; Shi, Liangsheng; Zha, Yuanyuan; Williams, Mathew; Lin, Lin

    2017-12-01

    Improvements to agricultural water and crop managements require detailed information on crop and soil states, and their evolution. Data assimilation provides an attractive way of obtaining these information by integrating measurements with model in a sequential manner. However, data assimilation for soil-water-atmosphere-plant (SWAP) system is still lack of comprehensive exploration due to a large number of variables and parameters in the system. In this study, simultaneous state-parameter estimation using ensemble Kalman filter (EnKF) was employed to evaluate the data assimilation performance and provide advice on measurement design for SWAP system. The results demonstrated that a proper selection of state vector is critical to effective data assimilation. Especially, updating the development stage was able to avoid the negative effect of ;phenological shift;, which was caused by the contrasted phenological stage in different ensemble members. Simultaneous state-parameter estimation (SSPE) assimilation strategy outperformed updating-state-only (USO) assimilation strategy because of its ability to alleviate the inconsistency between model variables and parameters. However, the performance of SSPE assimilation strategy could deteriorate with an increasing number of uncertain parameters as a result of soil stratification and limited knowledge on crop parameters. In addition to the most easily available surface soil moisture (SSM) and leaf area index (LAI) measurements, deep soil moisture, grain yield or other auxiliary data were required to provide sufficient constraints on parameter estimation and to assure the data assimilation performance. This study provides an insight into the response of soil moisture and grain yield to data assimilation in SWAP system and is helpful for soil moisture movement and crop growth modeling and measurement design in practice.

  12. Empirical Estimates of 0Day Vulnerabilities in Control Systems

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

    Miles A. McQueen; Wayne F. Boyer; Sean M. McBride

    2009-01-01

    We define a 0Day vulnerability to be any vulnerability, in deployed software, which has been discovered by at least one person but has not yet been publicly announced or patched. These 0Day vulnerabilities are of particular interest when assessing the risk to well managed control systems which have already effectively mitigated the publicly known vulnerabilities. In these well managed systems the risk contribution from 0Days will have proportionally increased. To aid understanding of how great a risk 0Days may pose to control systems, an estimate of how many are in existence is needed. Consequently, using the 0Day definition given above,more » we developed and applied a method for estimating how many 0Day vulnerabilities are in existence on any given day. The estimate is made by: empirically characterizing the distribution of the lifespans, measured in days, of 0Day vulnerabilities; determining the number of vulnerabilities publicly announced each day; and applying a novel method for estimating the number of 0Day vulnerabilities in existence on any given day using the number of vulnerabilities publicly announced each day and the previously derived distribution of 0Day lifespans. The method was first applied to a general set of software applications by analyzing the 0Day lifespans of 491 software vulnerabilities and using the daily rate of vulnerability announcements in the National Vulnerability Database. This led to a conservative estimate that in the worst year there were, on average, 2500 0Day software related vulnerabilities in existence on any given day. Using a smaller but intriguing set of 15 0Day software vulnerability lifespans representing the actual time from discovery to public disclosure, we then made a more aggressive estimate. In this case, we estimated that in the worst year there were, on average, 4500 0Day software vulnerabilities in existence on any given day. We then proceeded to identify the subset of software applications likely to be used

  13. 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...

  14. Maximized exoEarth candidate yields for starshades

    NASA Astrophysics Data System (ADS)

    Stark, Christopher C.; Shaklan, Stuart; Lisman, Doug; Cady, Eric; Savransky, Dmitry; Roberge, Aki; Mandell, Avi M.

    2016-10-01

    The design and scale of a future mission to directly image and characterize potentially Earth-like planets will be impacted, to some degree, by the expected yield of such planets. Recent efforts to increase the estimated yields, by creating observation plans optimized for the detection and characterization of Earth-twins, have focused solely on coronagraphic instruments; starshade-based missions could benefit from a similar analysis. Here we explore how to prioritize observations for a starshade given the limiting resources of both fuel and time, present analytic expressions to estimate fuel use, and provide efficient numerical techniques for maximizing the yield of starshades. We implemented these techniques to create an approximate design reference mission code for starshades and used this code to investigate how exoEarth candidate yield responds to changes in mission, instrument, and astrophysical parameters for missions with a single starshade. We find that a starshade mission operates most efficiently somewhere between the fuel- and exposuretime-limited regimes and, as a result, is less sensitive to photometric noise sources as well as parameters controlling the photon collection rate in comparison to a coronagraph. We produced optimistic yield curves for starshades, assuming our optimized observation plans are schedulable and future starshades are not thrust-limited. Given these yield curves, detecting and characterizing several dozen exoEarth candidates requires either multiple starshades or an η≳0.3.

  15. Measurement of neutron spectra generated from bombardment of 4 to 24 MeV protons on a thick ⁹Be target and estimation of neutron yields.

    PubMed

    Paul, Sabyasachi; Sahoo, G S; Tripathy, S P; Sharma, S C; Ramjilal; Ninawe, N G; Sunil, C; Gupta, A K; Bandyopadhyay, T

    2014-06-01

    A systematic study on the measurement of neutron spectra emitted from the interaction of protons of various energies with a thick beryllium target has been carried out. The measurements were carried out in the forward direction (at 0° with respect to the direction of protons) using CR-39 detectors. The doses were estimated using the in-house image analyzing program autoTRAK_n, which works on the principle of luminosity variation in and around the track boundaries. A total of six different proton energies starting from 4 MeV to 24 MeV with an energy gap of 4 MeV were chosen for the study of the neutron yields and the estimation of doses. Nearly, 92% of the recoil tracks developed after chemical etching were circular in nature, but the size distributions of the recoil tracks were not found to be linearly dependent on the projectile energy. The neutron yield and dose values were found to be increasing linearly with increasing projectile energies. The response of CR-39 detector was also investigated at different beam currents at two different proton energies. A linear increase of neutron yield with beam current was observed.

  16. Identifying seedling root architectural traits associated with yield and yield components in wheat.

    PubMed

    Xie, Quan; Fernando, Kurukulasuriya M C; Mayes, Sean; Sparkes, Debbie L

    2017-05-01

    Plant roots growing underground are critical for soil resource acquisition, anchorage and plant-environment interactions. In wheat ( Triticum aestivum ), however, the target root traits to improve yield potential still remain largely unknown. This study aimed to identify traits of seedling root system architecture (RSA) associated with yield and yield components in 226 recombinant inbred lines (RILs) derived from a cross between the bread wheat Triticum aestivum 'Forno' (small, wide root system) and spelt Triticum spelta 'Oberkulmer' (large, narrow root system). A 'pouch and wick' high-throughput phenotyping pipeline was used to determine the RSA traits of 13-day-old RIL seedlings. Two field experiments and one glasshouse experiment were carried out to investigate the yield, yield components and phenology, followed by identification of quantitative trait loci (QTLs). There was substantial variation in RSA traits between genotypes. Seminal root number and total root length were both positively associated with grains m -2 , grains per spike, above-ground biomass m -2 and grain yield. More seminal roots and longer total root length were also associated with delayed maturity and extended grain filling, likely to be a consequence of more grains being defined before anthesis. Additionally, the maximum width of the root system displayed positive relationships with spikes m -2 , grains m -2 and grain yield. Ten RILs selected for the longest total roots exhibited the same effects on yield and phenology as described above, compared with the ten lines with the shortest total roots. Genetic analysis revealed 38 QTLs for the RSA, and QTL coincidence between the root and yield traits was frequently observed, indicating tightly linked genes or pleiotropy, which concurs with the results of phenotypic correlation analysis. Based on the results from the Forno × Oberkulmer population, it is proposed that vigorous early root growth, particularly more seminal roots and longer total

  17. 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.

  18. 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.

  19. Dynamics and estimates of growth and loss rates of bacterioplankton in a temperate freshwater system.

    PubMed

    Jugnia, Louis-B; Sime-Ngando, Télesphore; Gilbert, Daniel

    2006-10-01

    The growth rate and losses of bacterioplankton in the epilimnion of an oligo-mesotrophic reservoir were simultaneously estimated using three different methods for each process. Bacterial production was determined by means of the tritiated thymidine incorporation method, the dialysis bag method and the dilution method, while bacterial mortality was assessed with the dilution method, the disappearance of thymidine-labeled natural cells and ingestion of fluorescent bacterial tracers by heterotrophic flagellates. The different methods used to estimate bacterial growth rates yielded similar results. On the other hand, the mortality rates obtained with the dilution method were significantly lower than those obtained with the use of thymidine-labeled natural cells. The bacterial ingestion rate by flagellates accounted on average for 39% of total bacterial mortality estimated by the dilution method, but this value fell to 5% when the total mortality was measured by the thymidine-labeling method. Bacterial abundance and production varied in opposite phase to flagellate abundance and the various bacterial mortality rates. All this points to the critical importance of methodological aspects in the elaboration of quantitative models of matter and energy flows over the time through microbial trophic networks in aquatic systems, and highlights the role of bacterioplankton as a source of carbon for higher trophic levels in the studied system.

  20. Simulating maize yield and bomass with spatial variability of soil field capacity

    USGS Publications Warehouse

    Ma, Liwang; Ahuja, Lajpat; Trout, Thomas; Nolan, Bernard T.; Malone, Robert W.

    2015-01-01

    Spatial variability in field soil properties is a challenge for system modelers who use single representative values, such as means, for model inputs, rather than their distributions. In this study, the root zone water quality model (RZWQM2) was first calibrated for 4 yr of maize (Zea mays L.) data at six irrigation levels in northern Colorado and then used to study spatial variability of soil field capacity (FC) estimated in 96 plots on maize yield and biomass. The best results were obtained when the crop parameters were fitted along with FCs, with a root mean squared error (RMSE) of 354 kg ha–1 for yield and 1202 kg ha–1 for biomass. When running the model using each of the 96 sets of field-estimated FC values, instead of calibrating FCs, the average simulated yield and biomass from the 96 runs were close to measured values with a RMSE of 376 kg ha–1 for yield and 1504 kg ha–1 for biomass. When an average of the 96 FC values for each soil layer was used, simulated yield and biomass were also acceptable with a RMSE of 438 kg ha–1 for yield and 1627 kg ha–1 for biomass. Therefore, when there are large numbers of FC measurements, an average value might be sufficient for model inputs. However, when the ranges of FC measurements were known for each soil layer, a sampled distribution of FCs using the Latin hypercube sampling (LHS) might be used for model inputs.

  1. Sequential state estimation of nonlinear/non-Gaussian systems with stochastic input for turbine degradation estimation

    NASA Astrophysics Data System (ADS)

    Hanachi, Houman; Liu, Jie; Banerjee, Avisekh; Chen, Ying

    2016-05-01

    Health state estimation of inaccessible components in complex systems necessitates effective state estimation techniques using the observable variables of the system. The task becomes much complicated when the system is nonlinear/non-Gaussian and it receives stochastic input. In this work, a novel sequential state estimation framework is developed based on particle filtering (PF) scheme for state estimation of general class of nonlinear dynamical systems with stochastic input. Performance of the developed framework is then validated with simulation on a Bivariate Non-stationary Growth Model (BNGM) as a benchmark. In the next step, three-year operating data of an industrial gas turbine engine (GTE) are utilized to verify the effectiveness of the developed framework. A comprehensive thermodynamic model for the GTE is therefore developed to formulate the relation of the observable parameters and the dominant degradation symptoms of the turbine, namely, loss of isentropic efficiency and increase of the mass flow. The results confirm the effectiveness of the developed framework for simultaneous estimation of multiple degradation symptoms in complex systems with noisy measured inputs.

  2. Nitrous oxide in fresh water systems: An estimate for the yield of atmospheric N2O associated with disposal of human waste

    NASA Technical Reports Server (NTRS)

    Kaplan, W. A.; Elkins, J. W.; Kolb, C. E.; Mcelroy, M. B.; Wofsy, S. C.; Duran, A. P.

    1977-01-01

    The N2O content of waters in the Potomac and Merrimack Rivers was measured on a number of occasions over the period April to July 1977. The concentrations of dissolved N2O exceeded those which would apply in equilibrium with air by factors ranging from about 46 in the Potomac to 1.2 in the Merrimack. Highest concentrations of dissolved N2O were associated with sewage discharges from the vicinity of Washington, D. C., and analysis indicates a relatively high yield, 1.3 to 11%, for prompt conversion of waste nitrogen to N2O. Measurements of dissolved N2O in fresh water ponds near Boston demonstrated that aquatic systems provide both strong sources and sinks for atmospheric N2O.

  3. Enhanced Furfural Yields from Xylose Dehydration in the gamma-Valerolactone/Water Solvent System at Elevated Temperatures.

    PubMed

    Sener, Canan; Motagamwala, Ali Hussain; Alonso, David Martin; Dumesic, James

    2018-05-18

    High yields of furfural (>90%) were achieved from xylose dehydration in a sustainable solvent system composed of -valerolactone (GVL), a biomass derived solvent, and water. It is identified that high reaction temperatures (e.g., 498 K) are required to achieve high furfural yield. Additionally, it is shown that the furfural yield at these temperatures is independent of the initial xylose concentration, and high furfural yield is obtained for industrially relevant xylose concentrations (10 wt%). A reaction kinetics model is developed to describe the experimental data obtained with solvent system composed of 80 wt% GVL and 20 wt% water across the range of reaction conditions studied (473 - 523 K, 1-10 mM acid catalyst, 66 - 660 mM xylose concentration). The kinetic model demonstrates that furfural loss due to bimolecular condensation of xylose and furfural is minimized at elevated temperature, whereas carbon loss due to xylose degradation increases with increasing temperature. Accordingly, the optimal temperature range for xylose dehydration to furfural in the GVL/H2O solvent system is identified to be from 480 to 500 K. Under these reaction conditions, furfural yield of 93% is achieved at 97% xylan conversion from lignocellulosic biomass (maple wood). © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  4. Comparison of groundwater recharge estimation techniques in an alluvial aquifer system with an intermittent/ephemeral stream (Queensland, Australia)

    NASA Astrophysics Data System (ADS)

    King, Adam C.; Raiber, Matthias; Cox, Malcolm E.; Cendón, Dioni I.

    2017-09-01

    This study demonstrates the importance of the conceptual hydrogeological model for the estimation of groundwater recharge rates in an alluvial system interconnected with an ephemeral or intermittent stream in south-east Queensland, Australia. The losing/gaining condition of these streams is typically subject to temporal and spatial variability, and knowledge of these hydrological processes is critical for the interpretation of recharge estimates. Recharge rate estimates of 76-182 mm/year were determined using the water budget method. The water budget method provides useful broad approximations of recharge and discharge fluxes. The chloride mass balance (CMB) method and the tritium method were used on 17 and 13 sites respectively, yielding recharge rates of 1-43 mm/year (CMB) and 4-553 mm/year (tritium method). However, the conceptual hydrogeological model confirms that the results from the CMB method at some sites are not applicable in this setting because of overland flow and channel leakage. The tritium method was appropriate here and could be applied to other alluvial systems, provided that channel leakage and diffuse infiltration of rainfall can be accurately estimated. The water-table fluctuation (WTF) method was also applied to data from 16 bores; recharge estimates ranged from 0 to 721 mm/year. The WTF method was not suitable where bank storage processes occurred.

  5. On-line estimation of nonlinear physical systems

    USGS Publications Warehouse

    Christakos, G.

    1988-01-01

    Recursive algorithms for estimating states of nonlinear physical systems are presented. Orthogonality properties are rediscovered and the associated polynomials are used to linearize state and observation models of the underlying random processes. This requires some key hypotheses regarding the structure of these processes, which may then take account of a wide range of applications. The latter include streamflow forecasting, flood estimation, environmental protection, earthquake engineering, and mine planning. The proposed estimation algorithm may be compared favorably to Taylor series-type filters, nonlinear filters which approximate the probability density by Edgeworth or Gram-Charlier series, as well as to conventional statistical linearization-type estimators. Moreover, the method has several advantages over nonrecursive estimators like disjunctive kriging. To link theory with practice, some numerical results for a simulated system are presented, in which responses from the proposed and extended Kalman algorithms are compared. ?? 1988 International Association for Mathematical Geology.

  6. A Comparative Study of Distribution System Parameter Estimation Methods

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

    Sun, Yannan; Williams, Tess L.; Gourisetti, Sri Nikhil Gup

    2016-07-17

    In this paper, we compare two parameter estimation methods for distribution systems: residual sensitivity analysis and state-vector augmentation with a Kalman filter. These two methods were originally proposed for transmission systems, and are still the most commonly used methods for parameter estimation. Distribution systems have much lower measurement redundancy than transmission systems. Therefore, estimating parameters is much more difficult. To increase the robustness of parameter estimation, the two methods are applied with combined measurement snapshots (measurement sets taken at different points in time), so that the redundancy for computing the parameter values is increased. The advantages and disadvantages of bothmore » methods are discussed. The results of this paper show that state-vector augmentation is a better approach for parameter estimation in distribution systems. Simulation studies are done on a modified version of IEEE 13-Node Test Feeder with varying levels of measurement noise and non-zero error in the other system model parameters.« less

  7. Effects of capillarity and microtopography on wetland specific yield

    USGS Publications Warehouse

    Sumner, D.M.

    2007-01-01

    Hydrologic models aid in describing water flows and levels in wetlands. Frequently, these models use a specific yield conceptualization to relate water flows to water level changes. Traditionally, a simple conceptualization of specific yield is used, composed of two constant values for above- and below-surface water levels and neglecting the effects of soil capillarity and land surface microtopography. The effects of capiltarity and microtopography on specific yield were evaluated at three wetland sites in the Florida Everglades. The effect of capillarity on specific yield was incorporated based on the fillable pore space within a soil moisture profile at hydrostatic equilibrium with the water table. The effect of microtopography was based on areal averaging of topographically varying values of specific yield. The results indicate that a more physically-based conceptualization of specific yield incorporating capillary and microtopographic considerations can be substantially different from the traditional two-part conceptualization, and from simpler conceptualizations incorporating only capillarity or only microtopography. For the sites considered, traditional estimates of specific yield could under- or overestimate the more physically based estimates by a factor of two or more. The results suggest that consideration of both capillarity and microtopography is important to the formulation of specific yield in physically based hydrologic models of wetlands. ?? 2007, The Society of Wetland Scientists.

  8. Interpretation of quantum yields exceeding unity in photoelectrochemical systems

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

    Szklarczyk, M.; Allen, R.E.

    1986-10-20

    In photoelectrochemical systems involving light shining on a semiconductor interfaced with an electrolyte, the quantum yield as a function of photon frequency ..nu.. is observed to exhibit a peak at h..nu..roughly-equal2E/sub g/, where E/sub g/ is the band gap of the semiconductor. The maximum in this peak is sometimes found to exceed unity. We provide an interpretation involving surface states and inelastic electron-electron scattering. The theory indicates that the effect should be observable for p-type semiconductors, but not n-type.

  9. Decentralization, stabilization, and estimation of large-scale linear systems

    NASA Technical Reports Server (NTRS)

    Siljak, D. D.; Vukcevic, M. B.

    1976-01-01

    In this short paper we consider three closely related aspects of large-scale systems: decentralization, stabilization, and estimation. A method is proposed to decompose a large linear system into a number of interconnected subsystems with decentralized (scalar) inputs or outputs. The procedure is preliminary to the hierarchic stabilization and estimation of linear systems and is performed on the subsystem level. A multilevel control scheme based upon the decomposition-aggregation method is developed for stabilization of input-decentralized linear systems Local linear feedback controllers are used to stabilize each decoupled subsystem, while global linear feedback controllers are utilized to minimize the coupling effect among the subsystems. Systems stabilized by the method have a tolerance to a wide class of nonlinearities in subsystem coupling and high reliability with respect to structural perturbations. The proposed output-decentralization and stabilization schemes can be used directly to construct asymptotic state estimators for large linear systems on the subsystem level. The problem of dimensionality is resolved by constructing a number of low-order estimators, thus avoiding a design of a single estimator for the overall system.

  10. Introduction to State Estimation of High-Rate System Dynamics.

    PubMed

    Hong, Jonathan; Laflamme, Simon; Dodson, Jacob; Joyce, Bryan

    2018-01-13

    Engineering systems experiencing high-rate dynamic events, including airbags, debris detection, and active blast protection systems, could benefit from real-time observability for enhanced performance. However, the task of high-rate state estimation is challenging, in particular for real-time applications where the rate of the observer's convergence needs to be in the microsecond range. This paper identifies the challenges of state estimation of high-rate systems and discusses the fundamental characteristics of high-rate systems. A survey of applications and methods for estimators that have the potential to produce accurate estimations for a complex system experiencing highly dynamic events is presented. It is argued that adaptive observers are important to this research. In particular, adaptive data-driven observers are advantageous due to their adaptability and lack of dependence on the system model.

  11. Increased bacterial cell density and recombinant protein yield using a commercial microbial cultivation system.

    PubMed

    Peck, Grantley R; Bowden, Timothy R; Shiell, Brian J; Michalski, Wojtek P

    2014-01-01

    EnBase (BioSilta, Finland) is a microbial cultivation system that replicates fed-batch systems through sustained release of glucose by enzymatic degradation of a polymeric substrate. Achievable bacterial cell densities and recombinant capripoxvirus protein expression levels, solubility, and antigenicity using the EnBase system were assessed. BL21-AI Escherichia coli expressing capripoxvirus proteins achieved up to eightfold higher cell densities when grown in EnBase media compared with standard media. Greater yields of capripoxvirus proteins were attained using EnBase media, either through increases in the amount of expressed protein per cell in conjunction with higher cell density or through the increase in cell density alone. Addition of EnBase booster enhanced protein yield for one of the proteins tested but reduced yield for the other. However, the amount of soluble forms of the capripoxvirus proteins tested was not different from that observed from cultures grown under standard conditions. Purified capripoxvirus proteins expressed using EnBase or standard media were assessed for their performance by enzyme-linked immunosorbent assay (ELISA) and were shown to be equally capable of specifically binding capripoxvirus antibodies.

  12. Efficient SRAM yield optimization with mixture surrogate modeling

    NASA Astrophysics Data System (ADS)

    Zhongjian, Jiang; Zuochang, Ye; Yan, Wang

    2016-12-01

    Largely repeated cells such as SRAM cells usually require extremely low failure-rate to ensure a moderate chi yield. Though fast Monte Carlo methods such as importance sampling and its variants can be used for yield estimation, they are still very expensive if one needs to perform optimization based on such estimations. Typically the process of yield calculation requires a lot of SPICE simulation. The circuit SPICE simulation analysis accounted for the largest proportion of time in the process yield calculation. In the paper, a new method is proposed to address this issue. The key idea is to establish an efficient mixture surrogate model. The surrogate model is based on the design variables and process variables. This model construction method is based on the SPICE simulation to get a certain amount of sample points, these points are trained for mixture surrogate model by the lasso algorithm. Experimental results show that the proposed model is able to calculate accurate yield successfully and it brings significant speed ups to the calculation of failure rate. Based on the model, we made a further accelerated algorithm to further enhance the speed of the yield calculation. It is suitable for high-dimensional process variables and multi-performance applications.

  13. Tensile Yielding of Multi-Wall Carbon Nanotube

    NASA Technical Reports Server (NTRS)

    Wei, Chenyu; Cho, Kyeongjae; Srivastava, Deepak; Parks, John W. (Technical Monitor)

    2002-01-01

    The tensile yielding of multiwall carbon nanotubes (MWCNTs) has been studied using Molecular Dynamics simulations and a Transition State Theory based model. We find a strong dependence of the yielding on the strain rate. A critical strain rate has been predicted above/below which yielding strain of a MWCNT is larger/smaller than that of the corresponding single-wall carbon nanotubes. At experimentally feasible strain rate of 1% /hour and T = 300K, the yield strain of a MWCNT is estimated to be about 3-4 % higher than that of an equivalent SWCNT (Single Wall Carbon Nanotube), in good agreement with recent experimental observations.

  14. A Web-Based System for Bayesian Benchmark Dose Estimation.

    PubMed

    Shao, Kan; Shapiro, Andrew J

    2018-01-11

    Benchmark dose (BMD) modeling is an important step in human health risk assessment and is used as the default approach to identify the point of departure for risk assessment. A probabilistic framework for dose-response assessment has been proposed and advocated by various institutions and organizations; therefore, a reliable tool is needed to provide distributional estimates for BMD and other important quantities in dose-response assessment. We developed an online system for Bayesian BMD (BBMD) estimation and compared results from this software with U.S. Environmental Protection Agency's (EPA's) Benchmark Dose Software (BMDS). The system is built on a Bayesian framework featuring the application of Markov chain Monte Carlo (MCMC) sampling for model parameter estimation and BMD calculation, which makes the BBMD system fundamentally different from the currently prevailing BMD software packages. In addition to estimating the traditional BMDs for dichotomous and continuous data, the developed system is also capable of computing model-averaged BMD estimates. A total of 518 dichotomous and 108 continuous data sets extracted from the U.S. EPA's Integrated Risk Information System (IRIS) database (and similar databases) were used as testing data to compare the estimates from the BBMD and BMDS programs. The results suggest that the BBMD system may outperform the BMDS program in a number of aspects, including fewer failed BMD and BMDL calculations and estimates. The BBMD system is a useful alternative tool for estimating BMD with additional functionalities for BMD analysis based on most recent research. Most importantly, the BBMD has the potential to incorporate prior information to make dose-response modeling more reliable and can provide distributional estimates for important quantities in dose-response assessment, which greatly facilitates the current trend for probabilistic risk assessment. https://doi.org/10.1289/EHP1289.

  15. Atmospheric Fluorescence Yield

    NASA Technical Reports Server (NTRS)

    Adams, James H., Jr.; Christl, M. J.; Fountain, W. F.; Gregory, J. C.; Martens, K.; Sokolsky, P.; Whitaker, Ann F. (Technical Monitor)

    2001-01-01

    Several existing and planned experiments estimate the energies of ultra-high energy cosmic rays from air showers using the atmospheric fluorescence from these showers. Accurate knowledge of the conversion from atmospheric fluorescence to energy loss by ionizing particles in the atmosphere is key to this technique. In this paper we discuss a small balloon-borne instrument to make the first in situ measurements versus altitude of the atmospheric fluorescence yield. The instrument can also be used in the lab to investigate the dependence of the fluorescence yield in air on temperature, pressure and the concentrations of other gases that present in the atmosphere. The results can be used to explore environmental effects on and improve the accuracy of cosmic ray energy measurements for existing ground-based experiments and future space-based experiments.

  16. Grain yield response to poultry litter application under a wheat-soybean double cropping system

    USDA-ARS?s Scientific Manuscript database

    Poultry litter application and double cropping are management practices that could be used with conservation tillage systems to increase yields compared to conventional monocropping systems. The objective of this study was to evaluate wheat (Triticum aestivum L.) and soybean [Glycine max (L.) Merr.]...

  17. Introduction to State Estimation of High-Rate System Dynamics

    PubMed Central

    Dodson, Jacob; Joyce, Bryan

    2018-01-01

    Engineering systems experiencing high-rate dynamic events, including airbags, debris detection, and active blast protection systems, could benefit from real-time observability for enhanced performance. However, the task of high-rate state estimation is challenging, in particular for real-time applications where the rate of the observer’s convergence needs to be in the microsecond range. This paper identifies the challenges of state estimation of high-rate systems and discusses the fundamental characteristics of high-rate systems. A survey of applications and methods for estimators that have the potential to produce accurate estimations for a complex system experiencing highly dynamic events is presented. It is argued that adaptive observers are important to this research. In particular, adaptive data-driven observers are advantageous due to their adaptability and lack of dependence on the system model. PMID:29342855

  18. Estimation of Faults in DC Electrical Power System

    NASA Technical Reports Server (NTRS)

    Gorinevsky, Dimitry; Boyd, Stephen; Poll, Scott

    2009-01-01

    This paper demonstrates a novel optimization-based approach to estimating fault states in a DC power system. Potential faults changing the circuit topology are included along with faulty measurements. Our approach can be considered as a relaxation of the mixed estimation problem. We develop a linear model of the circuit and pose a convex problem for estimating the faults and other hidden states. A sparse fault vector solution is computed by using 11 regularization. The solution is computed reliably and efficiently, and gives accurate diagnostics on the faults. We demonstrate a real-time implementation of the approach for an instrumented electrical power system testbed, the ADAPT testbed at NASA ARC. The estimates are computed in milliseconds on a PC. The approach performs well despite unmodeled transients and other modeling uncertainties present in the system.

  19. 48 CFR 252.215-7002 - Cost estimating system requirements.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... Department of Defense to rely upon information produced by the system that is needed for management purposes... management systems; and (4) Is subject to applicable financial control systems. Estimating system means the... estimates of costs and other data included in proposals submitted to customers in the expectation of...

  20. Yield and economic performance of organic and conventional cotton-based farming systems--results from a field trial in India.

    PubMed

    Forster, Dionys; Andres, Christian; Verma, Rajeev; Zundel, Christine; Messmer, Monika M; Mäder, Paul

    2013-01-01

    The debate on the relative benefits of conventional and organic farming systems has in recent time gained significant interest. So far, global agricultural development has focused on increased productivity rather than on a holistic natural resource management for food security. Thus, developing more sustainable farming practices on a large scale is of utmost importance. However, information concerning the performance of farming systems under organic and conventional management in tropical and subtropical regions is scarce. This study presents agronomic and economic data from the conversion phase (2007-2010) of a farming systems comparison trial on a Vertisol soil in Madhya Pradesh, central India. A cotton-soybean-wheat crop rotation under biodynamic, organic and conventional (with and without Bt cotton) management was investigated. We observed a significant yield gap between organic and conventional farming systems in the 1(st) crop cycle (cycle 1: 2007-2008) for cotton (-29%) and wheat (-27%), whereas in the 2(nd) crop cycle (cycle 2: 2009-2010) cotton and wheat yields were similar in all farming systems due to lower yields in the conventional systems. In contrast, organic soybean (a nitrogen fixing leguminous plant) yields were marginally lower than conventional yields (-1% in cycle 1, -11% in cycle 2). Averaged across all crops, conventional farming systems achieved significantly higher gross margins in cycle 1 (+29%), whereas in cycle 2 gross margins in organic farming systems were significantly higher (+25%) due to lower variable production costs but similar yields. Soybean gross margin was significantly higher in the organic system (+11%) across the four harvest years compared to the conventional systems. Our results suggest that organic soybean production is a viable option for smallholder farmers under the prevailing semi-arid conditions in India. Future research needs to elucidate the long-term productivity and profitability, particularly of cotton and

  1. Fission yields data generation and benchmarks of decay heat estimation of a nuclear fuel

    NASA Astrophysics Data System (ADS)

    Gil, Choong-Sup; Kim, Do Heon; Yoo, Jae Kwon; Lee, Jounghwa

    2017-09-01

    Fission yields data with the ENDF-6 format of 235U, 239Pu, and several actinides dependent on incident neutron energies have been generated using the GEF code. In addition, fission yields data libraries of ORIGEN-S, -ARP modules in the SCALE code, have been generated with the new data. The decay heats by ORIGEN-S using the new fission yields data have been calculated and compared with the measured data for validation in this study. The fission yields data ORIGEN-S libraries based on ENDF/B-VII.1, JEFF-3.1.1, and JENDL/FPY-2011 have also been generated, and decay heats were calculated using the ORIGEN-S libraries for analyses and comparisons.

  2. Modeling survival, yield, volume partitioning and their response to thinning for longleaf pine plantations

    Treesearch

    Carlos A. Gonzalez-Benecke; Salvador A. Gezan; Daniel J. Leduc; Timothy A. Martin; Wendell P. Cropper Jr; Lisa J Samuelson

    2012-01-01

    Longleaf pine (Pinus palustris Mill.) is an important tree species of the southeast U.S. Currently there is no comprehensive stand-level growth and yield model for the species. The model system described here estimates site index (SI) if dominant height (Hdom) and stand age are known (inversely, the model can project H

  3. Estimating sediment yield in the southern Appalachians using WCS-SED

    Treesearch

    Paul Bolstad; Andrew Jenks; Mark Riedel; James M. Vose

    2006-01-01

    We measured and modeled sediment yield over two months on five watersheds in the southern Appalachian Mountains of North Carolina. These watersheds contained first and second-order streams and are primarily forested, but span the development gradient common in this region, with up to 10 percent in suburban and transitional development and up to 27% low-intensity...

  4. Evaluation of weather-based rice yield models in India

    NASA Astrophysics Data System (ADS)

    Sudharsan, D.; Adinarayana, J.; Reddy, D. Raji; Sreenivas, G.; Ninomiya, S.; Hirafuji, M.; Kiura, T.; Tanaka, K.; Desai, U. B.; Merchant, S. N.

    2013-01-01

    The objective of this study was to compare two different rice simulation models—standalone (Decision Support System for Agrotechnology Transfer [DSSAT]) and web based (SImulation Model for RIce-Weather relations [SIMRIW])—with agrometeorological data and agronomic parameters for estimation of rice crop production in southern semi-arid tropics of India. Studies were carried out on the BPT5204 rice variety to evaluate two crop simulation models. Long-term experiments were conducted in a research farm of Acharya N G Ranga Agricultural University (ANGRAU), Hyderabad, India. Initially, the results were obtained using 4 years (1994-1997) of data with weather parameters from a local weather station to evaluate DSSAT simulated results with observed values. Linear regression models used for the purpose showed a close relationship between DSSAT and observed yield. Subsequently, yield comparisons were also carried out with SIMRIW and DSSAT, and validated with actual observed values. Realizing the correlation coefficient values of SIMRIW simulation values in acceptable limits, further rice experiments in monsoon (Kharif) and post-monsoon (Rabi) agricultural seasons (2009, 2010 and 2011) were carried out with a location-specific distributed sensor network system. These proximal systems help to simulate dry weight, leaf area index and potential yield by the Java based SIMRIW on a daily/weekly/monthly/seasonal basis. These dynamic parameters are useful to the farming community for necessary decision making in a ubiquitous manner. However, SIMRIW requires fine tuning for better results/decision making.

  5. Evaluation of weather-based rice yield models in India.

    PubMed

    Sudharsan, D; Adinarayana, J; Reddy, D Raji; Sreenivas, G; Ninomiya, S; Hirafuji, M; Kiura, T; Tanaka, K; Desai, U B; Merchant, S N

    2013-01-01

    The objective of this study was to compare two different rice simulation models--standalone (Decision Support System for Agrotechnology Transfer [DSSAT]) and web based (SImulation Model for RIce-Weather relations [SIMRIW])--with agrometeorological data and agronomic parameters for estimation of rice crop production in southern semi-arid tropics of India. Studies were carried out on the BPT5204 rice variety to evaluate two crop simulation models. Long-term experiments were conducted in a research farm of Acharya N G Ranga Agricultural University (ANGRAU), Hyderabad, India. Initially, the results were obtained using 4 years (1994-1997) of data with weather parameters from a local weather station to evaluate DSSAT simulated results with observed values. Linear regression models used for the purpose showed a close relationship between DSSAT and observed yield. Subsequently, yield comparisons were also carried out with SIMRIW and DSSAT, and validated with actual observed values. Realizing the correlation coefficient values of SIMRIW simulation values in acceptable limits, further rice experiments in monsoon (Kharif) and post-monsoon (Rabi) agricultural seasons (2009, 2010 and 2011) were carried out with a location-specific distributed sensor network system. These proximal systems help to simulate dry weight, leaf area index and potential yield by the Java based SIMRIW on a daily/weekly/monthly/seasonal basis. These dynamic parameters are useful to the farming community for necessary decision making in a ubiquitous manner. However, SIMRIW requires fine tuning for better results/decision making.

  6. Set-theoretic estimation of hybrid system configurations.

    PubMed

    Benazera, Emmanuel; Travé-Massuyès, Louise

    2009-10-01

    Hybrid systems serve as a powerful modeling paradigm for representing complex continuous controlled systems that exhibit discrete switches in their dynamics. The system and the models of the system are nondeterministic due to operation in uncertain environment. Bayesian belief update approaches to stochastic hybrid system state estimation face a blow up in the number of state estimates. Therefore, most popular techniques try to maintain an approximation of the true belief state by either sampling or maintaining a limited number of trajectories. These limitations can be avoided by using bounded intervals to represent the state uncertainty. This alternative leads to splitting the continuous state space into a finite set of possibly overlapping geometrical regions that together with the system modes form configurations of the hybrid system. As a consequence, the true system state can be captured by a finite number of hybrid configurations. A set of dedicated algorithms that can efficiently compute these configurations is detailed. Results are presented on two systems of the hybrid system literature.

  7. Dynamic state estimation assisted power system monitoring and protection

    NASA Astrophysics Data System (ADS)

    Cui, Yinan

    The advent of phasor measurement units (PMUs) has unlocked several novel methods to monitor, control, and protect bulk electric power systems. This thesis introduces the concept of "Dynamic State Estimation" (DSE), aided by PMUs, for wide-area monitoring and protection of power systems. Unlike traditional State Estimation where algebraic variables are estimated from system measurements, DSE refers to a process to estimate the dynamic states associated with synchronous generators. This thesis first establishes the viability of using particle filtering as a technique to perform DSE in power systems. The utility of DSE for protection and wide-area monitoring are then shown as potential novel applications. The work is presented as a collection of several journal and conference papers. In the first paper, we present a particle filtering approach to dynamically estimate the states of a synchronous generator in a multi-machine setting considering the excitation and prime mover control systems. The second paper proposes an improved out-of-step detection method for generators by means of angular difference. The generator's rotor angle is estimated with a particle filter-based dynamic state estimator and the angular separation is then calculated by combining the raw local phasor measurements with this estimate. The third paper introduces a particle filter-based dual estimation method for tracking the dynamic states of a synchronous generator. It considers the situation where the field voltage measurements are not readily available. The particle filter is modified to treat the field voltage as an unknown input which is sequentially estimated along with the other dynamic states. The fourth paper proposes a novel framework for event detection based on energy functions. The key idea is that any event in the system will leave a signature in WAMS data-sets. It is shown that signatures for four broad classes of disturbance events are buried in the components that constitute the

  8. Ecosystem approach to fisheries: Exploring environmental and trophic effects on Maximum Sustainable Yield (MSY) reference point estimates

    PubMed Central

    Kumar, Rajeev; Pitcher, Tony J.; Varkey, Divya A.

    2017-01-01

    We present a comprehensive analysis of estimation of fisheries Maximum Sustainable Yield (MSY) reference points using an ecosystem model built for Mille Lacs Lake, the second largest lake within Minnesota, USA. Data from single-species modelling output, extensive annual sampling for species abundances, annual catch-survey, stomach-content analysis for predatory-prey interactions, and expert opinions were brought together within the framework of an Ecopath with Ecosim (EwE) ecosystem model. An increase in the lake water temperature was observed in the last few decades; therefore, we also incorporated a temperature forcing function in the EwE model to capture the influences of changing temperature on the species composition and food web. The EwE model was fitted to abundance and catch time-series for the period 1985 to 2006. Using the ecosystem model, we estimated reference points for most of the fished species in the lake at single-species as well as ecosystem levels with and without considering the influence of temperature change; therefore, our analysis investigated the trophic and temperature effects on the reference points. The paper concludes that reference points such as MSY are not stationary, but change when (1) environmental conditions alter species productivity and (2) fishing on predators alters the compensatory response of their prey. Thus, it is necessary for the management to re-estimate or re-evaluate the reference points when changes in environmental conditions and/or major shifts in species abundance or community structure are observed. PMID:28957387

  9. Cost Estimation and Control for Flight Systems

    NASA Technical Reports Server (NTRS)

    Hammond, Walter E.; Vanhook, Michael E. (Technical Monitor)

    2002-01-01

    Good program management practices, cost analysis, cost estimation, and cost control for aerospace flight systems are interrelated and depend upon each other. The best cost control process cannot overcome poor design or poor systems trades that lead to the wrong approach. The project needs robust Technical, Schedule, Cost, Risk, and Cost Risk practices before it can incorporate adequate Cost Control. Cost analysis both precedes and follows cost estimation -- the two are closely coupled with each other and with Risk analysis. Parametric cost estimating relationships and computerized models are most often used. NASA has learned some valuable lessons in controlling cost problems, and recommends use of a summary Project Manager's checklist as shown here.

  10. Compression of freestanding gold nanostructures: from stochastic yield to predictable flow

    NASA Astrophysics Data System (ADS)

    Mook, W. M.; Niederberger, C.; Bechelany, M.; Philippe, L.; Michler, J.

    2010-02-01

    Characterizing the mechanical response of isolated nanostructures is vitally important to fields such as microelectromechanical systems (MEMS) where the behaviour of nanoscale contacts can in large part determine system reliability and lifetime. To address this challenge directly, single crystal gold nanodots are compressed inside a high resolution scanning electron microscope (SEM) using a nanoindenter equipped with a flat punch tip. These structures load elastically, and then yield in a stochastic manner, at loads ranging from 16 to 110 µN, which is up to five times higher than the load necessary for flow after yield. Yielding is immediately followed by displacement bursts equivalent to 1-50% of the initial height, depending on the yield point. During the largest displacement bursts, strain energy within the structure is released while new surface area is created in the form of localized slip bands, which are evident in both the SEM movies and still-images. A first order estimate of the apparent energy release rate, in terms of fracture mechanics concepts, for bursts representing 5-50% of the structure's initial height is on the order of 10-100 J m-2, which is approximately two orders of magnitude lower than bulk values. Once this initial strain burst during yielding has occurred, the structures flow in a ductile way. The implications of this behaviour, which is analogous to a brittle to ductile transition, are discussed with respect to mechanical reliability at the micro- and nanoscales.

  11. Energy yields in the prebiotic synthesis of hydrogen cyanide and formaldehyde

    NASA Technical Reports Server (NTRS)

    Stribling, R.; Miller, S. L.

    1986-01-01

    Prebiotic experiments are usually reported in terms of carbon yields, i.e., the yield of product based on the total carbon in the system. These experiments usually involve a large input of energy and are designed to maximize the yields of product. However, large inputs of energy result in multiple activation of the reactants and products. A more realistic prebiotic experiment is to remove the products of the activation step so they are not exposed a second time to the energy source. This is equivalent to transporting the products synthesized in the primitive atmosphere to the ocean, and thereby protecting them from destruction by atmospheric energy sources. Experiments of this type, using lower inputs of energy, give energy yields (moles of products/joule) which can be used to estimate the relative importance of the different energy sources on the primitive earth. Simulated prebiotic atmospheres containing either CH4, CO or CO2 with N2, H2O and variable amounts of H2 were subjected to a high frequency Tesla coil. Samples of the aqueous phase were taken at various time intervals from 1 hr to 7 days, and the energy yields were obtained by extrapolation to zero time. The samples were analyzed for HCN with the cyanide electrode and for H2CO by chromotropic acid. The spark energy was estimated by calorimetry. The temperature rise in an insulated discharge flask was compared with the temperature rise from a resistance heater in the same flask. These results will be compared with calculated production rates of HCN and H2CO from lightning and a number of photochemical processes on the primitive Earth.

  12. Design of a two-level power system linear state estimator

    NASA Astrophysics Data System (ADS)

    Yang, Tao

    The availability of synchro-phasor data has raised the possibility of a linear state estimator if the inputs are only complex currents and voltages and if there are enough such measurements to meet observability and redundancy requirements. Moreover, the new digital substations can perform some of the computation at the substation itself resulting in a more accurate two-level state estimator. The objective of this research is to develop a two-level linear state estimator processing synchro-phasor data and estimating the states at both the substation level and the control center level. Both the mathematical algorithms that are different from those in the present state estimation procedure and the layered architecture of databases, communications and application programs that are required to support this two-level linear state estimator are described in this dissertation. Besides, as the availability of phasor measurements at substations will increase gradually, this research also describes how the state estimator can be enhanced to handle both the traditional state estimator and the proposed linear state estimator simultaneously. This provides a way to immediately utilize the benefits in those parts of the system where such phasor measurements become available and provides a pathway to transition to the smart grid of the future. The design procedure of the two-level state estimator is applied to two study systems. The first study system is the IEEE-14 bus system. The second one is the 179 bus Western Electricity Coordinating Council (WECC) system. The static database for the substations is constructed from the power flow data of these systems and the real-time measurement database is produced by a power system dynamic simulating tool (TSAT). Time-skew problems that may be caused by communication delays are also considered and simulated. We used the Network Simulator (NS) tool to simulate a simple communication system and analyse its time delay performance. These

  13. Estimating Dynamical Systems: Derivative Estimation Hints from Sir Ronald A. Fisher

    ERIC Educational Resources Information Center

    Deboeck, Pascal R.

    2010-01-01

    The fitting of dynamical systems to psychological data offers the promise of addressing new and innovative questions about how people change over time. One method of fitting dynamical systems is to estimate the derivatives of a time series and then examine the relationships between derivatives using a differential equation model. One common…

  14. Improving precision of forage yield trials: A case study

    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 of yield estimates in cultivar evaluation trials to make reliable selections. Experimental error in yield trials is sensitive to several facto...

  15. Adaptive estimation of hand movement trajectory in an EEG based brain-computer interface system

    NASA Astrophysics Data System (ADS)

    Robinson, Neethu; Guan, Cuntai; Vinod, A. P.

    2015-12-01

    Objective. The various parameters that define a hand movement such as its trajectory, speed, etc, are encoded in distinct brain activities. Decoding this information from neurophysiological recordings is a less explored area of brain-computer interface (BCI) research. Applying non-invasive recordings such as electroencephalography (EEG) for decoding makes the problem more challenging, as the encoding is assumed to be deep within the brain and not easily accessible by scalp recordings. Approach. EEG based BCI systems can be developed to identify the neural features underlying movement parameters that can be further utilized to provide a detailed and well defined control command set to a BCI output device. A real-time continuous control is better suited for practical BCI systems, and can be achieved by continuous adaptive reconstruction of movement trajectory than discrete brain activity classifications. In this work, we adaptively reconstruct/estimate the parameters of two-dimensional hand movement trajectory, namely movement speed and position, from multi-channel EEG recordings. The data for analysis is collected by performing an experiment that involved center-out right-hand movement tasks in four different directions at two different speeds in random order. We estimate movement trajectory using a Kalman filter that models the relation between brain activity and recorded parameters based on a set of defined predictors. We propose a method to define these predictor variables that includes spatial, spectral and temporally localized neural information and to select optimally informative variables. Main results. The proposed method yielded correlation of (0.60 ± 0.07) between recorded and estimated data. Further, incorporating the proposed predictor subset selection, the correlation achieved is (0.57 ± 0.07, p {\\lt }0.004) with significant gain in stability of the system, as well as dramatic reduction in number of predictors (76%) for the savings of computational

  16. Estimating the Impact and Spillover Effect of Climate Change on Crop Yield in Northern Ghana.

    NASA Astrophysics Data System (ADS)

    Botchway, E.

    2016-12-01

    In tropical regions of the world human-induced climate change is likely to impact negatively on crop yields. To investigate the impact of climate change and its spillover effect on mean and variance of crop yields in northern Ghana, the Just and Pope stochastic production function and the Spatial Durbin model were adopted. Surprisingly, the results suggest that both precipitation and average temperature have positive effects on mean crop yield during the wet season. Wet season average temperature has a significant spillover effect in the region, whereas precipitation during the wet season has only one significant spillover effect on maize yield. Wet season precipitation does not have a strong significant effect on crop yield despite the rainfed nature of agriculture in the region. Thus, even if there are losers and winners as a result of future climate change at the regional level, future crop yield would largely depend on future technological development in agriculture, which may improve yields over time despite the changing climate. We argue, therefore, that technical improvement in farm management such as improved seeds and fertilizers, conservation tillage and better pest control, may have a more significant role in increasing observed crop productivity levels over time. So investigating the relative importance of non-climatic factors on crop yield may shed more light on where appropriate interventions can help in improving crop yields. Climate change, also, needs to be urgently assessed at the level of the household, so that poor and vulnerable people dependent on agriculture can be appropriately targeted in research and development activities whose object is poverty alleviation.

  17. 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.

  18. 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.

  19. Ternary particle yields in 249Cf(nth,f)

    NASA Astrophysics Data System (ADS)

    Tsekhanovich, I.; Büyükmumcu, Z.; Davi, M.; Denschlag, H. O.; Gönnenwein, F.; Boulyga, S. F.

    2003-03-01

    An experiment measuring ternary particle yields in 249Cf(nth,f) was carried out at the high flux reactor of the Institut Laue-Langevin using the Lohengrin recoil mass separator. Parameters of energy distributions were determined for 27 ternary particles up to 30Mg and their yields were calculated. The yields of 17 further ternary particles were estimated on the basis of the systematics developed. The heaviest particles observed in the experiment are 37Si and 37S; their possible origin is discussed.

  20. The alfalfa yield gap: A review of the evidence

    USDA-ARS?s Scientific Manuscript database

    Knowledge of feasibly attainable crop yields is needed for many purposes, from field-scale management to national policy decisions. For alfalfa (Medicago sativa L.), the most widely used estimates of yield in the US are whole-farm reports from the National Agriculture Statistics Service, which are b...

  1. REML/BLUP and sequential path analysis in estimating genotypic values and interrelationships among simple maize grain yield-related traits.

    PubMed

    Olivoto, T; Nardino, M; Carvalho, I R; Follmann, D N; Ferrari, M; Szareski, V J; de Pelegrin, A J; de Souza, V Q

    2017-03-22

    Methodologies using restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) in combination with sequential path analysis in maize are still limited in the literature. Therefore, the aims of this study were: i) to use REML/BLUP-based procedures in order to estimate variance components, genetic parameters, and genotypic values of simple maize hybrids, and ii) to fit stepwise regressions considering genotypic values to form a path diagram with multi-order predictors and minimum multicollinearity that explains the relationships of cause and effect among grain yield-related traits. Fifteen commercial simple maize hybrids were evaluated in multi-environment trials in a randomized complete block design with four replications. The environmental variance (78.80%) and genotype-vs-environment variance (20.83%) accounted for more than 99% of the phenotypic variance of grain yield, which difficult the direct selection of breeders for this trait. The sequential path analysis model allowed the selection of traits with high explanatory power and minimum multicollinearity, resulting in models with elevated fit (R 2 > 0.9 and ε < 0.3). The number of kernels per ear (NKE) and thousand-kernel weight (TKW) are the traits with the largest direct effects on grain yield (r = 0.66 and 0.73, respectively). The high accuracy of selection (0.86 and 0.89) associated with the high heritability of the average (0.732 and 0.794) for NKE and TKW, respectively, indicated good reliability and prospects of success in the indirect selection of hybrids with high-yield potential through these traits. The negative direct effect of NKE on TKW (r = -0.856), however, must be considered. The joint use of mixed models and sequential path analysis is effective in the evaluation of maize-breeding trials.

  2. Assessment of cluster yield components by image analysis.

    PubMed

    Diago, Maria P; Tardaguila, Javier; Aleixos, Nuria; Millan, Borja; Prats-Montalban, Jose M; Cubero, Sergio; Blasco, Jose

    2015-04-01

    Berry weight, berry number and cluster weight are key parameters for yield estimation for wine and tablegrape industry. Current yield prediction methods are destructive, labour-demanding and time-consuming. In this work, a new methodology, based on image analysis was developed to determine cluster yield components in a fast and inexpensive way. Clusters of seven different red varieties of grapevine (Vitis vinifera L.) were photographed under laboratory conditions and their cluster yield components manually determined after image acquisition. Two algorithms based on the Canny and the logarithmic image processing approaches were tested to find the contours of the berries in the images prior to berry detection performed by means of the Hough Transform. Results were obtained in two ways: by analysing either a single image of the cluster or using four images per cluster from different orientations. The best results (R(2) between 69% and 95% in berry detection and between 65% and 97% in cluster weight estimation) were achieved using four images and the Canny algorithm. The model's capability based on image analysis to predict berry weight was 84%. The new and low-cost methodology presented here enabled the assessment of cluster yield components, saving time and providing inexpensive information in comparison with current manual methods. © 2014 Society of Chemical Industry.

  3. Measurements of aquifer-storage change and specific yield using gravity surveys

    USGS Publications Warehouse

    Pool, D.R.; Eychaner, J.H.

    1995-01-01

    Pinal Creek is an intermittent stream that drains a 200-square-mile alluvial basin in central Arizona. Large changes in water levels and aquifer storage occur in an alluvial aquifer near the stream in response to periodic recharge and ground-water withdrawals. Outflow components of the ground-water budget and hydraulic properties of the alluvium are well-defined by field measurements; however, data are insufficient to adequately describe recharge, aquifer-storage change, and specific-yield values. An investigation was begun to assess the utility of temporal-gravity surveys to directly measure aquifer-storage change and estimate values of specific yield.The temporal-gravity surveys measured changes in the differences in gravity between two reference stations on bedrock and six stations at wells; changes are caused by variations in aquifer storage. Specific yield was estimated by dividing storage change by water-level change. Four surveys were done between February 21, 1991, and March 31, 1993. Gravity increased as much as 158 microGal ± 1 to 6 microGal, and water levels rose as much as 58 feet. Average specific yield at wells ranged from 0.16 to 0.21, and variations in specific yield with depth correlate with lithologic variations. Results indicate that temporal-gravity surveys can be used to estimate aquifer-storage change and specific yield of water-table aquifers where significant variations in water levels occur. Direct measurement of aquifer-storage change can eliminate a major unknown from the ground-water budget of arid basins and improve residual estimates of recharge.

  4. Estimating Power System Dynamic States Using Extended Kalman Filter

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

    Huang, Zhenyu; Schneider, Kevin P.; Nieplocha, Jaroslaw

    2014-10-31

    Abstract—The state estimation tools which are currently deployed in power system control rooms are based on a steady state assumption. As a result, the suite of operational tools that rely on state estimation results as inputs do not have dynamic information available and their accuracy is compromised. This paper investigates the application of Extended Kalman Filtering techniques for estimating dynamic states in the state estimation process. The new formulated “dynamic state estimation” includes true system dynamics reflected in differential equations, not like previously proposed “dynamic state estimation” which only considers the time-variant snapshots based on steady state modeling. This newmore » dynamic state estimation using Extended Kalman Filter has been successfully tested on a multi-machine system. Sensitivity studies with respect to noise levels, sampling rates, model errors, and parameter errors are presented as well to illustrate the robust performance of the developed dynamic state estimation process.« less

  5. Climatically driven yield variability of major crops in Khakassia (South Siberia)

    NASA Astrophysics Data System (ADS)

    Babushkina, Elena A.; Belokopytova, Liliana V.; Zhirnova, Dina F.; Shah, Santosh K.; Kostyakova, Tatiana V.

    2018-06-01

    We investigated the variability of yield of the three main crop cultures in the Khakassia Republic: spring wheat, spring barley, and oats. In terms of yield values, variability characteristics, and climatic response, the agricultural territory of Khakassia can be divided into three zones: (1) the Northern Zone, where crops yield has a high positive response to the amount of precipitation, May-July, and a moderately negative one to the temperatures of the same period; (2) the Central Zone, where crops yield depends mainly on temperatures; and (3) the Southern Zone, where climate has the least expressed impact on yield. The dominant pattern in the crops yield is caused by water stress during periods of high temperatures and low moisture supply with heat stress as additional reason. Differences between zones are due to combinations of temperature latitudinal gradient, precipitation altitudinal gradient, and the presence of a well-developed hydrological network and the irrigational system as moisture sources in the Central Zone. More detailed analysis shows differences in the climatic sensitivity of crops during phases of their vegetative growth and grain development and, to a lesser extent, during harvesting period. Multifactor linear regression models were constructed to estimate climate- and autocorrelation-induced variability of the crops yield. These models allowed prediction of the possibility of yield decreasing by at least 2-11% in the next decade due to increasing of the regional summer temperatures.

  6. Climatically driven yield variability of major crops in Khakassia (South Siberia)

    NASA Astrophysics Data System (ADS)

    Babushkina, Elena A.; Belokopytova, Liliana V.; Zhirnova, Dina F.; Shah, Santosh K.; Kostyakova, Tatiana V.

    2017-12-01

    We investigated the variability of yield of the three main crop cultures in the Khakassia Republic: spring wheat, spring barley, and oats. In terms of yield values, variability characteristics, and climatic response, the agricultural territory of Khakassia can be divided into three zones: (1) the Northern Zone, where crops yield has a high positive response to the amount of precipitation, May-July, and a moderately negative one to the temperatures of the same period; (2) the Central Zone, where crops yield depends mainly on temperatures; and (3) the Southern Zone, where climate has the least expressed impact on yield. The dominant pattern in the crops yield is caused by water stress during periods of high temperatures and low moisture supply with heat stress as additional reason. Differences between zones are due to combinations of temperature latitudinal gradient, precipitation altitudinal gradient, and the presence of a well-developed hydrological network and the irrigational system as moisture sources in the Central Zone. More detailed analysis shows differences in the climatic sensitivity of crops during phases of their vegetative growth and grain development and, to a lesser extent, during harvesting period. Multifactor linear regression models were constructed to estimate climate- and autocorrelation-induced variability of the crops yield. These models allowed prediction of the possibility of yield decreasing by at least 2-11% in the next decade due to increasing of the regional summer temperatures.

  7. 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.

  8. The Z {yields} cc-bar {yields} {gamma}{gamma}*, Z {yields} bb-bar {yields} {gamma}{gamma}* triangle diagrams and the Z {yields} {gamma}{psi}, Z {yields} {gamma}Y decays

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

    Achasov, N. N., E-mail: achasov@math.nsc.ru

    2011-03-15

    The approach to the Z {yields} {gamma}{psi} and Z {yields} {gamma}Y decay study is presented in detail, based on the sum rules for the Z {yields} cc-bar {yields} {gamma}{gamma}* and Z {yields} bb-bar {yields} {gamma}{gamma}* amplitudes and their derivatives. The branching ratios of the Z {yields} {gamma}{psi} and Z {yields} {gamma}Y decays are calculated for different hypotheses on saturation of the sum rules. The lower bounds of {Sigma}{sub {psi}} BR(Z {yields} {gamma}{psi}) = 1.95 Multiplication-Sign 10{sup -7} and {Sigma}{sub {upsilon}} BR(Z {yields} {gamma}Y) = 7.23 Multiplication-Sign 10{sup -7} are found. Deviations from the lower bounds are discussed, including the possibilitymore » of BR(Z {yields} {gamma}J/{psi}(1S)) {approx} BR(Z {yields} {gamma}Y(1S)) {approx} 10{sup -6}, that could be probably measured in LHC. The angular distributions in the Z {yields} {gamma}{psi} and Z {yields} {gamma}Y decays are also calculated.« less

  9. Spatial discretization of large watersheds and its influence on the estimation of hillslope sediment yield

    USDA-ARS?s Scientific Manuscript database

    The combined use of water erosion models and geographic information systems (GIS) has facilitated soil loss estimation at the watershed scale. Tools such as the Geo-spatial interface for the Water Erosion Prediction Project (GeoWEPP) model provide a convenient spatially distributed soil loss estimat...

  10. Applied estimation for hybrid dynamical systems using perceptional information

    NASA Astrophysics Data System (ADS)

    Plotnik, Aaron M.

    This dissertation uses the motivating example of robotic tracking of mobile deep ocean animals to present innovations in robotic perception and estimation for hybrid dynamical systems. An approach to estimation for hybrid systems is presented that utilizes uncertain perceptional information about the system's mode to improve tracking of its mode and continuous states. This results in significant improvements in situations where previously reported methods of estimation for hybrid systems perform poorly due to poor distinguishability of the modes. The specific application that motivates this research is an automatic underwater robotic observation system that follows and films individual deep ocean animals. A first version of such a system has been developed jointly by the Stanford Aerospace Robotics Laboratory and Monterey Bay Aquarium Research Institute (MBARI). This robotic observation system is successfully fielded on MBARI's ROVs, but agile specimens often evade the system. When a human ROV pilot performs this task, one advantage that he has over the robotic observation system in these situations is the ability to use visual perceptional information about the target, immediately recognizing any changes in the specimen's behavior mode. With the approach of the human pilot in mind, a new version of the robotic observation system is proposed which is extended to (a) derive perceptional information (visual cues) about the behavior mode of the tracked specimen, and (b) merge this dissimilar, discrete and uncertain information with more traditional continuous noisy sensor data by extending existing algorithms for hybrid estimation. These performance enhancements are enabled by integrating techniques in hybrid estimation, computer vision and machine learning. First, real-time computer vision and classification algorithms extract a visual observation of the target's behavior mode. Existing hybrid estimation algorithms are extended to admit this uncertain but discrete

  11. 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.

  12. Using Satellite Data to Unpack Causes of Yield Gaps in India's Wheat Belt

    NASA Astrophysics Data System (ADS)

    Jain, M.; Singh, B.; Srivastava, A.; Malik, R. K.; McDonald, A.; Lobell, D. B.

    2016-12-01

    India will face significant food security challenges in the coming decades due to climate change, natural resource degradation, and population growth. Yields of wheat, one of India's staple crops, are already stagnating and will be significantly impacted by warming temperatures. Despite these challenges, wheat yields can be enhanced by implementing improved management in regions with existing yield gaps. To identify the magnitude and causes of current yield gaps, we produced 30 m resolution yield maps across India's main wheat belt, the Indo-Gangetic Plains (IGP), from 2000 to 2015. Yield maps were derived using a new method that translates satellite vegetation indices to yield estimates using crop model simulations, bypassing the need for ground calibration data that rarely exist in smallholder systems. We find that yields can be increased by 5% on average and up to 16% in the eastern IGP by improving management to current best practices within a given district. However, if policies and technologies are put in place to improve management to current best practices in Punjab, the highest yielding state, yields can be increased by 29% in the eastern IGP. Considering which factors most influence wheat yields, we find that later sow dates and warmer temperatures are most associated with low yields across the IGP. This suggests that strategies that reduce the negative effects of heat stress, like earlier sowing and planting heat-tolerant wheat varieties, are critical to India's current and future food security.

  13. Estimation and Analysis of Nonlinear Stochastic Systems. Ph.D. Thesis

    NASA Technical Reports Server (NTRS)

    Marcus, S. I.

    1975-01-01

    The algebraic and geometric structures of certain classes of nonlinear stochastic systems were exploited in order to obtain useful stability and estimation results. The class of bilinear stochastic systems (or linear systems with multiplicative noise) was discussed. The stochastic stability of bilinear systems driven by colored noise was considered. Approximate methods for obtaining sufficient conditions for the stochastic stability of bilinear systems evolving on general Lie groups were discussed. Two classes of estimation problems involving bilinear systems were considered. It was proved that, for systems described by certain types of Volterra series expansions or by certain bilinear equations evolving on nilpotent or solvable Lie groups, the optimal conditional mean estimator consists of a finite dimensional nonlinear set of equations. The theory of harmonic analysis was used to derive suboptimal estimators for bilinear systems driven by white noise which evolve on compact Lie groups or homogeneous spaces.

  14. 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.

  15. Calibration-induced uncertainty of the EPIC model to estimate climate change impact on global maize yield

    NASA Astrophysics Data System (ADS)

    Xiong, Wei; Skalský, Rastislav; Porter, Cheryl H.; Balkovič, Juraj; Jones, James W.; Yang, Di

    2016-09-01

    Understanding the interactions between agricultural production and climate is necessary for sound decision-making in climate policy. Gridded and high-resolution crop simulation has emerged as a useful tool for building this understanding. Large uncertainty exists in this utilization, obstructing its capacity as a tool to devise adaptation strategies. Increasing focus has been given to sources of uncertainties for climate scenarios, input-data, and model, but uncertainties due to model parameter or calibration are still unknown. Here, we use publicly available geographical data sets as input to the Environmental Policy Integrated Climate model (EPIC) for simulating global-gridded maize yield. Impacts of climate change are assessed up to the year 2099 under a climate scenario generated by HadEM2-ES under RCP 8.5. We apply five strategies by shifting one specific parameter in each simulation to calibrate the model and understand the effects of calibration. Regionalizing crop phenology or harvest index appears effective to calibrate the model for the globe, but using various values of phenology generates pronounced difference in estimated climate impact. However, projected impacts of climate change on global maize production are consistently negative regardless of the parameter being adjusted. Different values of model parameter result in a modest uncertainty at global level, with difference of the global yield change less than 30% by the 2080s. The uncertainty subjects to decrease if applying model calibration or input data quality control. Calibration has a larger effect at local scales, implying the possible types and locations for adaptation.

  16. Systemic Operational Design: An Alternative to Estimate Planning

    DTIC Science & Technology

    2009-05-04

    relationships found in the COE. Framing and campaign design, with emphasis on systems theory , have therefore made their way to the forefront of doctrinal...short explanation of the systems theory behind SOD, examines how the SOD process happens, and compares SOD with the time proven “Commander’s Estimate... Theory , Campaign planning, Contemporary Operating Environment, Commander’s Estimate Process, Operational design 16. SECURITY CLASSIFICATION OF

  17. 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.

  18. Subplots facilitate assessment of corn yield losses from weed competition in a long-term systems experiment

    USDA-ARS?s Scientific Manuscript database

    Weeds can potentially limit crop yield, particularly in organic systems where herbicide technologies are unavailable. Weedy and weed-free subplots were established within full plots of a long-term cropping systems experiment, the Farming Systems Project, at Beltsville, Maryland, USA, to determine t...

  19. 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.

  20. Maximum sustainable yield and species extinction in a prey-predator system: some new results.

    PubMed

    Ghosh, Bapan; Kar, T K

    2013-06-01

    Though the maximum sustainable yield (MSY) approach has been legally adopted for the management of world fisheries, it does not provide any guarantee against from species extinction in multispecies communities. In the present article, we describe the appropriateness of the MSY policy in a Holling-Tanner prey-predator system with different types of functional responses. It is observed that for both type I and type II functional responses, harvesting of either prey or predator species at the MSY level is a sustainable fishing policy. In the case of combined harvesting, both the species coexist at the maximum sustainable total yield (MSTY) level if the biotic potential of the prey species is greater than a threshold value. Further, increase of the biotic potential beyond the threshold value affects the persistence of the system.

  1. On decentralized estimation. [for large linear systems

    NASA Technical Reports Server (NTRS)

    Siljak, D. D.; Vukcevic, M. B.

    1978-01-01

    A multilevel scheme is proposed to construct decentralized estimators for large linear systems. The scheme is numerically attractive since only observability tests of low-order subsystems are required. Equally important is the fact that the constructed estimators are reliable under structural perturbations and can tolerate a wide range of nonlinearities in coupling among the subsystems.

  2. Recent results of nonlinear estimators applied to hereditary systems.

    NASA Technical Reports Server (NTRS)

    Schiess, J. R.; Roland, V. R.; Wells, W. R.

    1972-01-01

    An application of the extended Kalman filter to delayed systems to estimate the state and time delay is presented. Two nonlinear estimators are discussed and the results compared with those of the Kalman filter. For all the filters considered, the hereditary system was treated with the delay in the pure form and by using Pade approximations of the delay. A summary of the convergence properties of the filters studied is given. The results indicate that the linear filter applied to the delayed system performs inadequately while the nonlinear filters provide reasonable estimates of both the state and the parameters.

  3. Cost estimating methods for advanced space systems

    NASA Technical Reports Server (NTRS)

    Cyr, Kelley

    1994-01-01

    NASA is responsible for developing much of the nation's future space technology. Cost estimates for new programs are required early in the planning process so that decisions can be made accurately. Because of the long lead times required to develop space hardware, the cost estimates are frequently required 10 to 15 years before the program delivers hardware. The system design in conceptual phases of a program is usually only vaguely defined and the technology used is so often state-of-the-art or beyond. These factors combine to make cost estimating for conceptual programs very challenging. This paper describes an effort to develop parametric cost estimating methods for space systems in the conceptual design phase. The approach is to identify variables that drive cost such as weight, quantity, development culture, design inheritance and time. The nature of the relationships between the driver variables and cost will be discussed. In particular, the relationship between weight and cost will be examined in detail. A theoretical model of cost will be developed and tested statistically against a historical database of major research and development projects.

  4. Destiny-yield relationship for channel catfish reared in a biofloc technology production system

    USDA-ARS?s Scientific Manuscript database

    The effect of stocking density on yield of stocker channel catfish and water quality in a biofloc technology production system was studied in this completely randomized design experiment. Fingerling channel catfish (Ictalurus punctatus; 48.0 g/fish, 17.8 cm/fish) were stocked into nine continuously ...

  5. The separation distance distribution in electron-donor-acceptor systems and the wavelength dependence of free ion yields

    NASA Astrophysics Data System (ADS)

    Zhou, Jinwei; Findley, Bret R.; Braun, Charles L.; Sutin, Norman

    2001-06-01

    We recently reported that free radical ion quantum yields for electron-donor-acceptor (EDA) systems of alkylbenzenes-tetracyanoethylene (TCNE) exhibit a remarkable wavelength dependence in dichloromethane, a medium polarity solvent. We proposed that weak absorption by long-distance, unassociated or "random" D⋯A pairs is mainly responsible for the free radical ion yield. Here a model for the wavelength dependence of the free ion yield is developed for four systems in which differing degrees of EDA complex formation are present: 1,3,5-tri-tert-butylbenzene-TCNE in which only random pairs exist due to the bulky groups on the electron donor, and toluene—TCNE, 1,3,5-triethylbenzene-TCNE and 1,3,5-trimethylbenzene-TCNE. Mulliken-Hush theory is used to determine the excitation distance distribution of unassociated, random pairs at different wavelengths. For each absorption distribution, free radical ion yields at different wavelengths are then calculated using Onsager's result for the ion separation probability. Encouraging agreement between the calculated yields and our experimental results is obtained. As far as we are aware, this is the first time that photoexcitation of unassociated donor/acceptor pairs has been invoked as the source of separated radical ion pairs.

  6. 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.

  7. Parameter estimation for chaotic systems using improved bird swarm algorithm

    NASA Astrophysics Data System (ADS)

    Xu, Chuangbiao; Yang, Renhuan

    2017-12-01

    Parameter estimation of chaotic systems is an important problem in nonlinear science and has aroused increasing interest of many research fields, which can be basically reduced to a multidimensional optimization problem. In this paper, an improved boundary bird swarm algorithm is used to estimate the parameters of chaotic systems. This algorithm can combine the good global convergence and robustness of the bird swarm algorithm and the exploitation capability of improved boundary learning strategy. Experiments are conducted on the Lorenz system and the coupling motor system. Numerical simulation results reveal the effectiveness and with desirable performance of IBBSA for parameter estimation of chaotic systems.

  8. Commercial Crop Yields Reveal Strengths and Weaknesses for Organic Agriculture in the United States.

    PubMed

    Kniss, Andrew R; Savage, Steven D; Jabbour, Randa

    2016-01-01

    Land area devoted to organic agriculture has increased steadily over the last 20 years in the United States, and elsewhere around the world. A primary criticism of organic agriculture is lower yield compared to non-organic systems. Previous analyses documenting the yield deficiency in organic production have relied mostly on data generated under experimental conditions, but these studies do not necessarily reflect the full range of innovation or practical limitations that are part of commercial agriculture. The analysis we present here offers a new perspective, based on organic yield data collected from over 10,000 organic farmers representing nearly 800,000 hectares of organic farmland. We used publicly available data from the United States Department of Agriculture to estimate yield differences between organic and conventional production methods for the 2014 production year. Similar to previous work, organic crop yields in our analysis were lower than conventional crop yields for most crops. Averaged across all crops, organic yield averaged 67% of conventional yield [corrected]. However, several crops had no significant difference in yields between organic and conventional production, and organic yields surpassed conventional yields for some hay crops. The organic to conventional yield ratio varied widely among crops, and in some cases, among locations within a crop. For soybean (Glycine max) and potato (Solanum tuberosum), organic yield was more similar to conventional yield in states where conventional yield was greatest. The opposite trend was observed for barley (Hordeum vulgare), wheat (Triticum aestevum), and hay crops, however, suggesting the geographical yield potential has an inconsistent effect on the organic yield gap.

  9. Commercial Crop Yields Reveal Strengths and Weaknesses for Organic Agriculture in the United States

    PubMed Central

    Savage, Steven D.; Jabbour, Randa

    2016-01-01

    Land area devoted to organic agriculture has increased steadily over the last 20 years in the United States, and elsewhere around the world. A primary criticism of organic agriculture is lower yield compared to non-organic systems. Previous analyses documenting the yield deficiency in organic production have relied mostly on data generated under experimental conditions, but these studies do not necessarily reflect the full range of innovation or practical limitations that are part of commercial agriculture. The analysis we present here offers a new perspective, based on organic yield data collected from over 10,000 organic farmers representing nearly 800,000 hectares of organic farmland. We used publicly available data from the United States Department of Agriculture to estimate yield differences between organic and conventional production methods for the 2014 production year. Similar to previous work, organic crop yields in our analysis were lower than conventional crop yields for most crops. Averaged across all crops, organic yield averaged 80% of conventional yield. However, several crops had no significant difference in yields between organic and conventional production, and organic yields surpassed conventional yields for some hay crops. The organic to conventional yield ratio varied widely among crops, and in some cases, among locations within a crop. For soybean (Glycine max) and potato (Solanum tuberosum), organic yield was more similar to conventional yield in states where conventional yield was greatest. The opposite trend was observed for barley (Hordeum vulgare), wheat (Triticum aestevum), and hay crops, however, suggesting the geographical yield potential has an inconsistent effect on the organic yield gap. PMID:27552217

  10. 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.

  11. Study of B{yields}{lambda}{sub c}{lambda}{sub c} and B{yields}{lambda}{sub c}{lambda}{sub c}K

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

    Cheng, H.-Y.; Hsiao, Y.-K.; Chua, C.-K.

    2009-06-01

    We study the doubly charmful two-body and three-body baryonic B decays B{yields}{lambda}{sub c}{sup +}{lambda}{sub c}{sup -} and B{yields}{lambda}{sub c}{sup +}{lambda}{sub c}{sup -}K. As pointed out before, a naive estimate of the branching ratio O(10{sup -8}) for the latter decay is too small by 3 to 4 orders of magnitude compared to experiment. Previously, it has been shown that a large enhancement for the {lambda}{sub c}{sup +}{lambda}{sub c}{sup -}K production can occur due to a charmoniumlike resonance (e.g. X(4630) discovered by Belle) with a mass near the {lambda}{sub c}{lambda}{sub c} threshold. Motivated by the BABAR's observation of a resonance in themore » {lambda}{sub c}K system with a mass of order 2930 MeV, we study in this work the contribution to B{yields}{lambda}{sub c}{sup +}{lambda}{sub c}{sup -}K from the intermediate state {xi}{sub c}(2980) which is postulated to be a first positive-parity excited D-wave charmed baryon state. Assuming that a soft qq quark pair is produced through the {sigma} and {pi} meson exchanges in the configuration for B{yields}{xi}{sub c}(2980){lambda}{sub c} and {lambda}{sub c}{lambda}{sub c}, it is found that branching ratios of B{yields}{lambda}{sub c}{sup +}{lambda}{sub c}{sup -}K and B{yields}{lambda}{sub c}{sup +}{lambda}{sub c}{sup -} are of order 3.5x10{sup -4} and 5x10{sup -5}, respectively, in agreement with experiment except that the prediction for the {lambda}{sub c}{lambda}{sub c}K{sup -} is slightly smaller. In conjunction with our previous analysis, we conclude that the enormously large rate of B{yields}{lambda}{sub c}{sup +}{lambda}{sub c}{sup -}K arises from the resonances {xi}{sub c}(2980) and X(4630)« less

  12. A quality assessment of the MARS crop yield forecasting system for the European Union

    NASA Astrophysics Data System (ADS)

    van der Velde, Marijn; Bareuth, Bettina

    2015-04-01

    Timely information on crop production forecasts can become of increasing importance as commodity markets are more and more interconnected. Impacts across large crop production areas due to (e.g.) extreme weather and pest outbreaks can create ripple effects that may affect food prices and availability elsewhere. The MARS Unit (Monitoring Agricultural ResourceS), DG Joint Research Centre, European Commission, has been providing forecasts of European crop production levels since 1993. The operational crop production forecasting is carried out with the MARS Crop Yield Forecasting System (M-CYFS). The M-CYFS is used to monitor crop growth development, evaluate short-term effects of anomalous meteorological events, and provide monthly forecasts of crop yield at national and European Union level. The crop production forecasts are published in the so-called MARS bulletins. Forecasting crop yield over large areas in the operational context requires quality benchmarks. Here we present an analysis of the accuracy and skill of past crop yield forecasts of the main crops (e.g. soft wheat, grain maize), throughout the growing season, and specifically for the final forecast before harvest. Two simple benchmarks to assess the skill of the forecasts were defined as comparing the forecasts to 1) a forecast equal to the average yield and 2) a forecast using a linear trend established through the crop yield time-series. These reveal a variability in performance as a function of crop and Member State. In terms of production, the yield forecasts of 67% of the EU-28 soft wheat production and 80% of the EU-28 maize production have been forecast superior to both benchmarks during the 1993-2013 period. In a changing and increasingly variable climate crop yield forecasts can become increasingly valuable - provided they are used wisely. We end our presentation by discussing research activities that could contribute to this goal.

  13. A switched systems approach to image-based estimation

    NASA Astrophysics Data System (ADS)

    Parikh, Anup

    With the advent of technological improvements in imaging systems and computational resources, as well as the development of image-based reconstruction techniques, it is necessary to understand algorithm performance when subject to real world conditions. Specifically, this dissertation focuses on the stability and performance of a class of image-based observers in the presence of intermittent measurements, caused by e.g., occlusions, limited FOV, feature tracking losses, communication losses, or finite frame rates. Observers or filters that are exponentially stable under persistent observability may have unbounded error growth during intermittent sensing, even while providing seemingly accurate state estimates. In Chapter 3, dwell time conditions are developed to guarantee state estimation error convergence to an ultimate bound for a class of observers while undergoing measurement loss. Bounds are developed on the unstable growth of the estimation errors during the periods when the object being tracked is not visible. A Lyapunov-based analysis for the switched system is performed to develop an inequality in terms of the duration of time the observer can view the moving object and the duration of time the object is out of the field of view. In Chapter 4, a motion model is used to predict the evolution of the states of the system while the object is not visible. This reduces the growth rate of the bounding function to an exponential and enables the use of traditional switched systems Lyapunov analysis techniques. The stability analysis results in an average dwell time condition to guarantee state error convergence with a known decay rate. In comparison with the results in Chapter 3, the estimation errors converge to zero rather than a ball, with relaxed switching conditions, at the cost of requiring additional information about the motion of the feature. In some applications, a motion model of the object may not be available. Numerous adaptive techniques have been

  14. Real-time estimation system for seismic-intensity exposed-population

    NASA Astrophysics Data System (ADS)

    Aoi, S.; Nakamura, H.; Kunugi, T.; Suzuki, W.; Fujiwara, H.

    2013-12-01

    For an appropriate first-action to an earthquake, risk (damage) information evaluated in real-time are important as well as hazard (ground motion) information. To meet this need, we are developing real-time estimation system (J-RISQ) for exposed population and earthquake damage on buildings. We plan to open the web page of estimated exposed population to the public from autumn. When an earthquake occurs, seismic intensities are calculated at each observation station and sent to the DMC (Data Management Center) in different timing. For rapid estimation, the system does not wait for the data from all the stations but begins the first estimation when the number of the stations observing the seismic intensity of 2.5 or larger exceeds the threshold amount. Estimations are updated several times using all the available data at that moment. Spatial distribution of seismic intensity in 250 m meshes is estimated by the site amplification factor of surface layers and the observed data. By using this intensity distribution, the exposed population is estimated using population data of each mesh. The exposed populations for municipalities and prefectures are estimated by summing-up the exposures of included meshes for the area and are appropriately rounded taking estimation precision into consideration. The estimated intensities for major cities are shown by the histograms, which indicate the variation of the estimated values in the city together with the observed maximum intensity. The variation is mainly caused by the difference of the site amplification factors. The intensities estimated for meshes with large amplification factor are sometimes larger than the maximum value observed in the city. The estimated results are seen on the web site just after the earthquake. The results of the past earthquakes can be easily searched by keywords such as date, magnitudes, seismic intensities and source areas. The summary of the results in the one-page report of Portable Document Format

  15. Practical Methods for Estimating Software Systems Fault Content and Location

    NASA Technical Reports Server (NTRS)

    Nikora, A.; Schneidewind, N.; Munson, J.

    1999-01-01

    Over the past several years, we have developed techniques to discriminate between fault-prone software modules and those that are not, to estimate a software system's residual fault content, to identify those portions of a software system having the highest estimated number of faults, and to estimate the effects of requirements changes on software quality.

  16. Power system frequency estimation based on an orthogonal decomposition method

    NASA Astrophysics Data System (ADS)

    Lee, Chih-Hung; Tsai, Men-Shen

    2018-06-01

    In recent years, several frequency estimation techniques have been proposed by which to estimate the frequency variations in power systems. In order to properly identify power quality issues under asynchronously-sampled signals that are contaminated with noise, flicker, and harmonic and inter-harmonic components, a good frequency estimator that is able to estimate the frequency as well as the rate of frequency changes precisely is needed. However, accurately estimating the fundamental frequency becomes a very difficult task without a priori information about the sampling frequency. In this paper, a better frequency evaluation scheme for power systems is proposed. This method employs a reconstruction technique in combination with orthogonal filters, which may maintain the required frequency characteristics of the orthogonal filters and improve the overall efficiency of power system monitoring through two-stage sliding discrete Fourier transforms. The results showed that this method can accurately estimate the power system frequency under different conditions, including asynchronously sampled signals contaminated by noise, flicker, and harmonic and inter-harmonic components. The proposed approach also provides high computational efficiency.

  17. Decentralized state estimation for a large-scale spatially interconnected system.

    PubMed

    Liu, Huabo; Yu, Haisheng

    2018-03-01

    A decentralized state estimator is derived for the spatially interconnected systems composed of many subsystems with arbitrary connection relations. An optimization problem on the basis of linear matrix inequality (LMI) is constructed for the computations of improved subsystem parameter matrices. Several computationally effective approaches are derived which efficiently utilize the block-diagonal characteristic of system parameter matrices and the sparseness of subsystem connection matrix. Moreover, this decentralized state estimator is proved to converge to a stable system and obtain a bounded covariance matrix of estimation errors under certain conditions. Numerical simulations show that the obtained decentralized state estimator is attractive in the synthesis of a large-scale networked system. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  18. Yield and Economic Performance of Organic and Conventional Cotton-Based Farming Systems – Results from a Field Trial in India

    PubMed Central

    Forster, Dionys; Andres, Christian; Verma, Rajeev; Zundel, Christine; Messmer, Monika M.; Mäder, Paul

    2013-01-01

    The debate on the relative benefits of conventional and organic farming systems has in recent time gained significant interest. So far, global agricultural development has focused on increased productivity rather than on a holistic natural resource management for food security. Thus, developing more sustainable farming practices on a large scale is of utmost importance. However, information concerning the performance of farming systems under organic and conventional management in tropical and subtropical regions is scarce. This study presents agronomic and economic data from the conversion phase (2007–2010) of a farming systems comparison trial on a Vertisol soil in Madhya Pradesh, central India. A cotton-soybean-wheat crop rotation under biodynamic, organic and conventional (with and without Bt cotton) management was investigated. We observed a significant yield gap between organic and conventional farming systems in the 1st crop cycle (cycle 1: 2007–2008) for cotton (−29%) and wheat (−27%), whereas in the 2nd crop cycle (cycle 2: 2009–2010) cotton and wheat yields were similar in all farming systems due to lower yields in the conventional systems. In contrast, organic soybean (a nitrogen fixing leguminous plant) yields were marginally lower than conventional yields (−1% in cycle 1, −11% in cycle 2). Averaged across all crops, conventional farming systems achieved significantly higher gross margins in cycle 1 (+29%), whereas in cycle 2 gross margins in organic farming systems were significantly higher (+25%) due to lower variable production costs but similar yields. Soybean gross margin was significantly higher in the organic system (+11%) across the four harvest years compared to the conventional systems. Our results suggest that organic soybean production is a viable option for smallholder farmers under the prevailing semi-arid conditions in India. Future research needs to elucidate the long-term productivity and profitability, particularly of

  19. Some methods of computing platform transmitter terminal location estimates. [ARGOS system; whale tracking

    NASA Technical Reports Server (NTRS)

    Hoisington, C. M.

    1984-01-01

    A position estimation algorithm was developed to track a humpback whale tagged with an ARGOS platform after a transmitter deployment failure and the whale's diving behavior precluded standard methods. The algorithm is especially useful where a transmitter location program exists; it determines the classical keplarian elements from the ARGOS spacecraft position vectors included with the probationary file messages. A minimum of three distinct messages are required. Once the spacecraft orbit is determined, the whale is located using standard least squares regression techniques. Experience suggests that in instances where circumstances inherent in the experiment yield message data unsuitable for the standard ARGOS reduction, (message data may be too sparse, span an insufficient period, or include variable-length messages). System ARGOS can still provide much valuable location information if the user is willing to accept the increased location uncertainties.

  20. A comparison of linear respiratory system models based on parameter estimates from PRN forced oscillation data.

    PubMed

    Diong, B; Grainger, J; Goldman, M; Nazeran, H

    2009-01-01

    The forced oscillation technique offers some advantages over spirometry for assessing pulmonary function. It requires only passive patient cooperation; it also provides data in a form, frequency-dependent impedance, which is very amenable to engineering analysis. In particular, the data can be used to obtain parameter estimates for electric circuit-based models of the respiratory system, which can in turn aid the detection and diagnosis of various diseases/pathologies. In this study, we compare the least-squares error performance of the RIC, extended RIC, augmented RIC, augmented RIC+I(p), DuBois, Nagels and Mead models in fitting 3 sets of impedance data. These data were obtained by pseudorandom noise forced oscillation of healthy subjects, mild asthmatics and more severe asthmatics. We found that the aRIC+I(p) and DuBois models yielded the lowest fitting errors (for the healthy subjects group and the 2 asthmatic patient groups, respectively) without also producing unphysiologically large component estimates.

  1. Fatality Analysis Reporting System, General Estimates System: 2001 Data Summary.

    ERIC Educational Resources Information Center

    2003

    The Fatality Analysis Reporting System (FARS), which became operational in 1975, contains data on a census of fatal traffic crashes within the 50 states, the District of Columbia, and Puerto Rico. The General Estimates System (GES), which began in 1988, provides data from a nationally representative probability sample selected from all…

  2. Time-to-impact estimation in passive missile warning systems

    NASA Astrophysics Data System (ADS)

    Şahıngıl, Mehmet Cihan

    2017-05-01

    A missile warning system can detect the incoming missile threat(s) and automatically cue the other Electronic Attack (EA) systems in the suit, such as Directed Infrared Counter Measure (DIRCM) system and/or Counter Measure Dispensing System (CMDS). Most missile warning systems are currently based on passive sensor technology operating in either Solar Blind Ultraviolet (SBUV) or Midwave Infrared (MWIR) bands on which there is an intensive emission from the exhaust plume of the threatening missile. Although passive missile warning systems have some clear advantages over pulse-Doppler radar (PDR) based active missile warning systems, they show poorer performance in terms of time-to-impact (TTI) estimation which is critical for optimizing the countermeasures and also "passive kill assessment". In this paper, we consider this problem, namely, TTI estimation from passive measurements and present a TTI estimation scheme which can be used in passive missile warning systems. Our problem formulation is based on Extended Kalman Filter (EKF). The algorithm uses the area parameter of the threat plume which is derived from the used image frame.

  3. Combining satellite remote sensing and surveys to understand persistent yield variation--- a case study in North China Plain

    NASA Astrophysics Data System (ADS)

    Zhao, Y.; Lobell, D. B.; Chen, X.

    2015-12-01

    A large gap between maize yields on average farmers' fields and the highest yields achieved by either experiment or farmers is typical throughout the developing world, including in the North China Plain (NCP). This maize yield gap as identified by previous studies indicates large opportunities for raising yield by improving agronomy. Quzhou county is typical of the winter-wheat summer-maize system in NCP where the average plot size is as small as 0.25 hectares. To analyze this cropping system amidst the challenge of substantial heterogeneity, we identified fields that were either persistently higher or lower yielding according to the remote sensing yield estimates, and then conducted detailed field surveys. We found irrigation facility to be a major constraint to yield both in terms of irrigation water quality and farmers' access to wells. In total, improving the access to unsalty water would be associated with a 0.32t/ha (4.2%) increase in multi-year average yield. In addition, farmers' method of choosing cultivar, which likely relates to their overall knowledge level, significantly explained yield variation. In particular, those choosing cultivars according to technician advice, personal experiences and high yielding neighbors' advice had on average higher yield than farmers that either followed seed sellers' advice or collectively purchased seeds. Overall, the study presents a generalizable methodology of assessing yield gap as well as its persistent factors using a combination of satellite and survey data.

  4. View Estimation Based on Value System

    NASA Astrophysics Data System (ADS)

    Takahashi, Yasutake; Shimada, Kouki; Asada, Minoru

    Estimation of a caregiver's view is one of the most important capabilities for a child to understand the behavior demonstrated by the caregiver, that is, to infer the intention of behavior and/or to learn the observed behavior efficiently. We hypothesize that the child develops this ability in the same way as behavior learning motivated by an intrinsic reward, that is, he/she updates the model of the estimated view of his/her own during the behavior imitated from the observation of the behavior demonstrated by the caregiver based on minimizing the estimation error of the reward during the behavior. From this view, this paper shows a method for acquiring such a capability based on a value system from which values can be obtained by reinforcement learning. The parameters of the view estimation are updated based on the temporal difference error (hereafter TD error: estimation error of the state value), analogous to the way such that the parameters of the state value of the behavior are updated based on the TD error. Experiments with simple humanoid robots show the validity of the method, and the developmental process parallel to young children's estimation of its own view during the imitation of the observed behavior of the caregiver is discussed.

  5. Short communication: Estimation of yield stress/viscosity of molten octol

    DOE PAGES

    Davis, S. M.; Zerkle, D. K.

    2018-05-04

    Explosive HMX particles are similar in morphology and chemistry to RDX particles, the main constituent of Composition B-3 (Comp B-3). This suggests molten HMX-TNT formulations may show Bingham plasticity, much like recent studies have shown for Comp B-3. Here a Bingham plastic viscosity model, including yield stress and shear thinning, is presented for octol (70/30wt% HMX/TNT) as a function of HMX particle volume fraction. The effect of HMX dissolution into molten TNT is included in this analysis.

  6. Short communication: Estimation of yield stress/viscosity of molten octol

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

    Davis, S. M.; Zerkle, D. K.

    Explosive HMX particles are similar in morphology and chemistry to RDX particles, the main constituent of Composition B-3 (Comp B-3). This suggests molten HMX-TNT formulations may show Bingham plasticity, much like recent studies have shown for Comp B-3. Here a Bingham plastic viscosity model, including yield stress and shear thinning, is presented for octol (70/30wt% HMX/TNT) as a function of HMX particle volume fraction. The effect of HMX dissolution into molten TNT is included in this analysis.

  7. Short communication: Estimation of yield stress/viscosity of molten octol

    NASA Astrophysics Data System (ADS)

    Davis, S. M.; Zerkle, D. K.

    2018-05-01

    Explosive HMX particles are similar in morphology and chemistry to RDX particles, the main constituent of Composition B-3 (Comp B-3). This suggests molten HMX-TNT formulations may show Bingham plasticity, much like recent studies have shown for Comp B-3. Here a Bingham plastic viscosity model, including yield stress and shear thinning, is presented for octol (70/30wt% HMX/TNT) as a function of HMX particle volume fraction. The effect of HMX dissolution into molten TNT is included in this analysis.

  8. 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.

  9. The Flight Optimization System Weights Estimation Method

    NASA Technical Reports Server (NTRS)

    Wells, Douglas P.; Horvath, Bryce L.; McCullers, Linwood A.

    2017-01-01

    FLOPS has been the primary aircraft synthesis software used by the Aeronautics Systems Analysis Branch at NASA Langley Research Center. It was created for rapid conceptual aircraft design and advanced technology impact assessments. FLOPS is a single computer program that includes weights estimation, aerodynamics estimation, engine cycle analysis, propulsion data scaling and interpolation, detailed mission performance analysis, takeoff and landing performance analysis, noise footprint estimation, and cost analysis. It is well known as a baseline and common denominator for aircraft design studies. FLOPS is capable of calibrating a model to known aircraft data, making it useful for new aircraft and modifications to existing aircraft. The weight estimation method in FLOPS is known to be of high fidelity for conventional tube with wing aircraft and a substantial amount of effort went into its development. This report serves as a comprehensive documentation of the FLOPS weight estimation method. The development process is presented with the weight estimation process.

  10. A direct comparison of exoEarth yields for starshades and coronagraphs

    NASA Astrophysics Data System (ADS)

    Stark, Christopher C.; Cady, Eric J.; Clampin, Mark; Domagal-Goldman, Shawn; Lisman, Doug; Mandell, Avi M.; McElwain, Michael W.; Roberge, Aki; Robinson, Tyler D.; Savransky, Dmitry; Shaklan, Stuart B.; Stapelfeldt, Karl R.

    2016-07-01

    The scale and design of a future mission capable of directly imaging extrasolar planets will be influenced by the detectable number (yield) of potentially Earth-like planets. Currently, coronagraphs and starshades are being considered as instruments for such a mission. We will use a novel code to estimate and compare the yields for starshade- and coronagraph-based missions. We will show yield scaling relationships for each instrument and discuss the impact of astrophysical and instrumental noise on yields. Although the absolute yields are dependent on several yet-unknown parameters, we will present several limiting cases allowing us to bound the yield comparison.

  11. 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.

  12. Effect of chemical and mechanical weed control on cassava yield, soil quality and erosion under cassava cropping system

    NASA Astrophysics Data System (ADS)

    Islami, Titiek; Wisnubroto, Erwin; Utomo, Wani

    2016-04-01

    Three years field experiments were conducted to study the effect of chemical and mechanical weed control on soil quality and erosion under cassava cropping system. The experiment were conducted at University Brawijaya field experimental station, Jatikerto, Malang, Indonesia. The experiments were carried out from 2011 - 2014. The treatments consist of three cropping system (cassava mono culture; cassava + maize intercropping and cassava + peanut intercropping), and two weed control method (chemical and mechanical methods). The experimental result showed that the yield of cassava first year and second year did not influenced by weed control method and cropping system. However, the third year yield of cassava was influence by weed control method and cropping system. The cassava yield planted in cassava + maize intercropping system with chemical weed control methods was only 24 t/ha, which lower compared to other treatments, even with that of the same cropping system used mechanical weed control. The highest cassava yield in third year was obtained by cassava + peanuts cropping system with mechanical weed control method. After three years experiment, the soil of cassava monoculture system with chemical weed control method possessed the lowest soil organic matter, and soil aggregate stability. During three years of cropping soil erosion in chemical weed control method, especially on cassava monoculture, was higher compared to mechanical weed control method. The soil loss from chemical control method were 40 t/ha, 44 t/ha and 54 t/ha for the first, second and third year crop. The soil loss from mechanical weed control method for the same years was: 36 t/ha, 36 t/ha and 38 t/ha. Key words: herbicide, intercropping, soil organic matter, aggregate stability.

  13. Estimation and detection information trade-off for x-ray system optimization

    NASA Astrophysics Data System (ADS)

    Cushing, Johnathan B.; Clarkson, Eric W.; Mandava, Sagar; Bilgin, Ali

    2016-05-01

    X-ray Computed Tomography (CT) systems perform complex imaging tasks to detect and estimate system parameters, such as a baggage imaging system performing threat detection and generating reconstructions. This leads to a desire to optimize both the detection and estimation performance of a system, but most metrics only focus on one of these aspects. When making design choices there is a need for a concise metric which considers both detection and estimation information parameters, and then provides the user with the collection of possible optimal outcomes. In this paper a graphical analysis of Estimation and Detection Information Trade-off (EDIT) will be explored. EDIT produces curves which allow for a decision to be made for system optimization based on design constraints and costs associated with estimation and detection. EDIT analyzes the system in the estimation information and detection information space where the user is free to pick their own method of calculating these measures. The user of EDIT can choose any desired figure of merit for detection information and estimation information then the EDIT curves will provide the collection of optimal outcomes. The paper will first look at two methods of creating EDIT curves. These curves can be calculated using a wide variety of systems and finding the optimal system by maximizing a figure of merit. EDIT could also be found as an upper bound of the information from a collection of system. These two methods allow for the user to choose a method of calculation which best fits the constraints of their actual system.

  14. 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.

  15. Attitude Estimation in Fractionated Spacecraft Cluster Systems

    NASA Technical Reports Server (NTRS)

    Hadaegh, Fred Y.; Blackmore, James C.

    2011-01-01

    An attitude estimation was examined in fractioned free-flying spacecraft. Instead of a single, monolithic spacecraft, a fractionated free-flying spacecraft uses multiple spacecraft modules. These modules are connected only through wireless communication links and, potentially, wireless power links. The key advantage of this concept is the ability to respond to uncertainty. For example, if a single spacecraft module in the cluster fails, a new one can be launched at a lower cost and risk than would be incurred with onorbit servicing or replacement of the monolithic spacecraft. In order to create such a system, however, it is essential to know what the navigation capabilities of the fractionated system are as a function of the capabilities of the individual modules, and to have an algorithm that can perform estimation of the attitudes and relative positions of the modules with fractionated sensing capabilities. Looking specifically at fractionated attitude estimation with startrackers and optical relative attitude sensors, a set of mathematical tools has been developed that specify the set of sensors necessary to ensure that the attitude of the entire cluster ( cluster attitude ) can be observed. Also developed was a navigation filter that can estimate the cluster attitude if these conditions are satisfied. Each module in the cluster may have either a startracker, a relative attitude sensor, or both. An extended Kalman filter can be used to estimate the attitude of all modules. A range of estimation performances can be achieved depending on the sensors used and the topology of the sensing network.

  16. Covariance generation and uncertainty propagation for thermal and fast neutron induced fission yields

    NASA Astrophysics Data System (ADS)

    Terranova, Nicholas; Serot, Olivier; Archier, Pascal; De Saint Jean, Cyrille; Sumini, Marco

    2017-09-01

    Fission product yields (FY) are fundamental nuclear data for several applications, including decay heat, shielding, dosimetry, burn-up calculations. To be safe and sustainable, modern and future nuclear systems require accurate knowledge on reactor parameters, with reduced margins of uncertainty. Present nuclear data libraries for FY do not provide consistent and complete uncertainty information which are limited, in many cases, to only variances. In the present work we propose a methodology to evaluate covariance matrices for thermal and fast neutron induced fission yields. The semi-empirical models adopted to evaluate the JEFF-3.1.1 FY library have been used in the Generalized Least Square Method available in CONRAD (COde for Nuclear Reaction Analysis and Data assimilation) to generate covariance matrices for several fissioning systems such as the thermal fission of U235, Pu239 and Pu241 and the fast fission of U238, Pu239 and Pu240. The impact of such covariances on nuclear applications has been estimated using deterministic and Monte Carlo uncertainty propagation techniques. We studied the effects on decay heat and reactivity loss uncertainty estimation for simplified test case geometries, such as PWR and SFR pin-cells. The impact on existing nuclear reactors, such as the Jules Horowitz Reactor under construction at CEA-Cadarache, has also been considered.

  17. A cohort study of a general surgery electronic consultation system: safety implications and impact on surgical yield.

    PubMed

    Ulloa, Jesus G; Russell, Marika D; Chen, Alice Hm; Tuot, Delphine S

    2017-06-23

    Electronic consultation (eConsult) systems have enhanced access to specialty expertise and enhanced care coordination among primary care and specialty care providers, while maintaining high primary care provider (PCP), specialist and patient satisfaction. Little is known about their impact on the efficiency of specialty care delivery, in particular surgical yield (percent of ambulatory visits resulting in a scheduled surgical case). Retrospective cohort of a random selection of 150 electronic consults from PCPs to a safety-net general surgery clinic for the three most common general surgery procedures (herniorrhaphy, cholecystectomy, anorectal procedures) in 2014. Electronic consultation requests were reviewed for the presence/absence of consult domains: symptom acuity/severity, diagnostic evaluation, concurrent medical conditions, and attempted diagnosis. Logic regression was used to examine the association between completeness of consult requests and scheduling an ambulatory clinic visit. Surgical yield was also calculated, as was the percentage of patients requiring unanticipated healthcare visits. In 2014, 1743 electronic consultations were submitted to general surgery. Among the 150 abstracted, the presence of consult domains ranged from 49% to 99%. Consult completeness was not associated with greater likelihood of scheduling an ambulatory visit. Seventy-six percent of consult requests (114/150) were scheduled for a clinic appointment and surgical yield was 46%; without an eConsult system, surgical yield would have been 35% (p=0.07). Among patients not scheduled for a clinic visit (n=36), 4 had related unanticipated emergency department visits. Econsult systems can be used to safely optimize the surgical yield of a safety-net general surgery service.

  18. Sleep Estimates Using Microelectromechanical Systems (MEMS)

    PubMed Central

    te Lindert, Bart H. W.; Van Someren, Eus J. W.

    2013-01-01

    Study Objectives: Although currently more affordable than polysomnography, actigraphic sleep estimates have disadvantages. Brand-specific differences in data reduction impede pooling of data in large-scale cohorts and may not fully exploit movement information. Sleep estimate reliability might improve by advanced analyses of three-axial, linear accelerometry data sampled at a high rate, which is now feasible using microelectromechanical systems (MEMS). However, it might take some time before these analyses become available. To provide ongoing studies with backward compatibility while already switching from actigraphy to MEMS accelerometry, we designed and validated a method to transform accelerometry data into the traditional actigraphic movement counts, thus allowing for the use of validated algorithms to estimate sleep parameters. Design: Simultaneous actigraphy and MEMS-accelerometry recording. Setting: Home, unrestrained. Participants: Fifteen healthy adults (23-36 y, 10 males, 5 females). Interventions: None. Measurements: Actigraphic movement counts/15-sec and 50-Hz digitized MEMS-accelerometry. Analyses: Passing-Bablok regression optimized transformation of MEMS-accelerometry signals to movement counts. Kappa statistics calculated agreement between individual epochs scored as wake or sleep. Bland-Altman plots evaluated reliability of common sleep variables both between and within actigraphs and MEMS-accelerometers. Results: Agreement between epochs was almost perfect at the low, medium, and high threshold (kappa = 0.87 ± 0.05, 0.85 ± 0.06, and 0.83 ± 0.07). Sleep parameter agreement was better between two MEMS-accelerometers or a MEMS-accelerometer and an actigraph than between two actigraphs. Conclusions: The algorithm allows for continuity of outcome parameters in ongoing actigraphy studies that consider switching to MEMS-accelerometers. Its implementation makes backward compatibility feasible, while collecting raw data that, in time, could provide

  19. Projecting crop yield in northern high latitude area.

    PubMed

    Matsumura, Kanichiro

    2014-01-01

    validation periods is used. To show the reproducing projection between observed and calculated values, the root mean squared error for skill score (RMSE SS) with the persistence model serving as the reference model is used. The persistence model is used as a benchmark. The results show that SADs near USA border show better RMSE SS values and mode 3's time coefficients can be a useful predictor especially for inland province such as Manitoba. Among 27 Canadian Prairie's SADs with perfect yield data, 67% of Alberta's SADs, 86% of Manitoba's SADs, and 77% of Saskatchewan's SADs can get positive skill scores. In each SAD, future yield projection is calculated applying predictors in 2013 for the obtained eight sets of models and eight sets of forecasted values in 2013 are averaged and a near future projection result is obtained. Series of outputs including calculated forecasted yield value in each SAD is provided by smart phone application. A system for providing climatic condition for a point with a permission of Climatic Research Unit - University of East Anglia and for obtaining patent is proposed. There are several patented systems similar to the system proposed in this paper. However, these patents are different in essence. The system proposed in this paper consists of two parts. First part is to estimate equations using time series data. The second part is to acquire and apply latest climatic conditions for obtained equations and calculate future projection. If the procedure is refined and devices are originally developed, series of idea can be patented. For future work, crop index, Hokkaido is also introduced.

  20. A simple approach to nonlinear estimation of physical systems

    USGS Publications Warehouse

    Christakos, G.

    1988-01-01

    Recursive algorithms for estimating the states of nonlinear physical systems are developed. This requires some key hypotheses regarding the structure of the underlying processes. Members of this class of random processes have several desirable properties for the nonlinear estimation of random signals. An assumption is made about the form of the estimator, which may then take account of a wide range of applications. Under the above assumption, the estimation algorithm is mathematically suboptimal but effective and computationally attractive. It may be compared favorably to Taylor series-type filters, nonlinear filters which approximate the probability density by Edgeworth or Gram-Charlier series, as well as to conventional statistical linearization-type estimators. To link theory with practice, some numerical results for a simulated system are presented, in which the responses from the proposed and the extended Kalman algorithms are compared. ?? 1988.

  1. Fast skin dose estimation system for interventional radiology

    PubMed Central

    Takata, Takeshi; Kotoku, Jun’ichi; Maejima, Hideyuki; Kumagai, Shinobu; Arai, Norikazu; Kobayashi, Takenori; Shiraishi, Kenshiro; Yamamoto, Masayoshi; Kondo, Hiroshi; Furui, Shigeru

    2018-01-01

    Abstract To minimise the radiation dermatitis related to interventional radiology (IR), rapid and accurate dose estimation has been sought for all procedures. We propose a technique for estimating the patient skin dose rapidly and accurately using Monte Carlo (MC) simulation with a graphical processing unit (GPU, GTX 1080; Nvidia Corp.). The skin dose distribution is simulated based on an individual patient’s computed tomography (CT) dataset for fluoroscopic conditions after the CT dataset has been segmented into air, water and bone based on pixel values. The skin is assumed to be one layer at the outer surface of the body. Fluoroscopic conditions are obtained from a log file of a fluoroscopic examination. Estimating the absorbed skin dose distribution requires calibration of the dose simulated by our system. For this purpose, a linear function was used to approximate the relation between the simulated dose and the measured dose using radiophotoluminescence (RPL) glass dosimeters in a water-equivalent phantom. Differences of maximum skin dose between our system and the Particle and Heavy Ion Transport code System (PHITS) were as high as 6.1%. The relative statistical error (2 σ) for the simulated dose obtained using our system was ≤3.5%. Using a GPU, the simulation on the chest CT dataset aiming at the heart was within 3.49 s on average: the GPU is 122 times faster than a CPU (Core i7–7700K; Intel Corp.). Our system (using the GPU, the log file, and the CT dataset) estimated the skin dose more rapidly and more accurately than conventional methods. PMID:29136194

  2. Fast skin dose estimation system for interventional radiology.

    PubMed

    Takata, Takeshi; Kotoku, Jun'ichi; Maejima, Hideyuki; Kumagai, Shinobu; Arai, Norikazu; Kobayashi, Takenori; Shiraishi, Kenshiro; Yamamoto, Masayoshi; Kondo, Hiroshi; Furui, Shigeru

    2018-03-01

    To minimise the radiation dermatitis related to interventional radiology (IR), rapid and accurate dose estimation has been sought for all procedures. We propose a technique for estimating the patient skin dose rapidly and accurately using Monte Carlo (MC) simulation with a graphical processing unit (GPU, GTX 1080; Nvidia Corp.). The skin dose distribution is simulated based on an individual patient's computed tomography (CT) dataset for fluoroscopic conditions after the CT dataset has been segmented into air, water and bone based on pixel values. The skin is assumed to be one layer at the outer surface of the body. Fluoroscopic conditions are obtained from a log file of a fluoroscopic examination. Estimating the absorbed skin dose distribution requires calibration of the dose simulated by our system. For this purpose, a linear function was used to approximate the relation between the simulated dose and the measured dose using radiophotoluminescence (RPL) glass dosimeters in a water-equivalent phantom. Differences of maximum skin dose between our system and the Particle and Heavy Ion Transport code System (PHITS) were as high as 6.1%. The relative statistical error (2 σ) for the simulated dose obtained using our system was ≤3.5%. Using a GPU, the simulation on the chest CT dataset aiming at the heart was within 3.49 s on average: the GPU is 122 times faster than a CPU (Core i7-7700K; Intel Corp.). Our system (using the GPU, the log file, and the CT dataset) estimated the skin dose more rapidly and more accurately than conventional methods.

  3. 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.

  4. Model error estimation for distributed systems described by elliptic equations

    NASA Technical Reports Server (NTRS)

    Rodriguez, G.

    1983-01-01

    A function space approach is used to develop a theory for estimation of the errors inherent in an elliptic partial differential equation model for a distributed parameter system. By establishing knowledge of the inevitable deficiencies in the model, the error estimates provide a foundation for updating the model. The function space solution leads to a specification of a method for computation of the model error estimates and development of model error analysis techniques for comparison between actual and estimated errors. The paper summarizes the model error estimation approach as well as an application arising in the area of modeling for static shape determination of large flexible systems.

  5. Channel estimation in few mode fiber mode division multiplexing transmission system

    NASA Astrophysics Data System (ADS)

    Hei, Yongqiang; Li, Li; Li, Wentao; Li, Xiaohui; Shi, Guangming

    2018-03-01

    It is abundantly clear that obtaining the channel state information (CSI) is of great importance for the equalization and detection in coherence receivers. However, to the best of the authors' knowledge, in most of the existing literatures, CSI is assumed to be perfectly known at the receiver. So far, few literature discusses the effects of imperfect CSI on MDM system performance caused by channel estimation. Motivated by that, in this paper, the channel estimation in few mode fiber (FMF) mode division multiplexing (MDM) system is investigated, in which two classical channel estimation methods, i.e., least square (LS) method and minimum mean square error (MMSE) method, are discussed with the assumption of the spatially white noise lumped at the receiver side of MDM system. Both the capacity and BER performance of MDM system affected by mode-dependent gain or loss (MDL) with different channel estimation errors have been studied. Simulation results show that the capacity and BER performance can be further deteriorated in MDM system by the channel estimation, and an 1e-3 variance of channel estimation error is acceptable in MDM system with 0-6 dB MDL values.

  6. ROI on yield data analysis systems through a business process management strategy

    NASA Astrophysics Data System (ADS)

    Rehani, Manu; Strader, Nathan; Hanson, Jeff

    2005-05-01

    The overriding motivation for yield engineering is profitability. This is achieved through application of yield management. The first application is to continually reduce waste in the form of yield loss. New products, new technologies and the dynamic state of the process and equipment keep introducing new ways to cause yield loss. In response, the yield management efforts have to continually come up with new solutions to minimize it. The second application of yield engineering is to aid in accurate product pricing. This is achieved through predicting future results of the yield engineering effort. The more accurate the yield prediction, the more accurate the wafer start volume, the more accurate the wafer pricing. Another aspect of yield prediction pertains to gauging the impact of a yield problem and predicting how long that will last. The ability to predict such impacts again feeds into wafer start calculations and wafer pricing. The question then is that if the stakes on yield management are so high why is it that most yield management efforts are run like science and engineering projects and less like manufacturing? In the eighties manufacturing put the theory of constraints1 into practice and put a premium on stability and predictability in manufacturing activities, why can't the same be done for yield management activities? This line of introspection led us to define and implement a business process to manage the yield engineering activities. We analyzed the best known methods (BKM) and deployed a workflow tool to make them the standard operating procedure (SOP) for yield managment. We present a case study in deploying a Business Process Management solution for Semiconductor Yield Engineering in a high-mix ASIC environment. We will present a description of the situation prior to deployment, a window into the development process and a valuation of the benefits.

  7. Identification of linear system models and state estimators for controls

    NASA Technical Reports Server (NTRS)

    Chen, Chung-Wen

    1992-01-01

    The following paper is presented in viewgraph format and covers topics including: (1) linear state feedback control system; (2) Kalman filter state estimation; (3) relation between residual and stochastic part of output; (4) obtaining Kalman filter gain; (5) state estimation under unknown system model and unknown noises; and (6) relationship between filter Markov parameters and system Markov parameters.

  8. The estimation method on diffusion spot energy concentration of the detection system

    NASA Astrophysics Data System (ADS)

    Gao, Wei; Song, Zongxi; Liu, Feng; Dan, Lijun; Sun, Zhonghan; Du, Yunfei

    2016-09-01

    We propose a method to estimate the diffusion spot energy of the detection system. We do outdoor observation experiments in Xinglong Observatory, by using a detection system which diffusion spot energy concentration is estimated (the correlation coefficient is approximate 0.9926).The aperture of system is 300mm and limiting magnitude of system is 14.15Mv. Observation experiments show that the highest detecting magnitude of estimated system is 13.96Mv, and the average detecting magnitude of estimated system is about 13.5Mv. The results indicate that this method can be used to evaluate the energy diffusion spot concentration level of detection system efficiently.

  9. Comparison of estimated and measured sediment yield in the Gualala River

    Treesearch

    Matthew O’Connor; Jack Lewis; Robert Pennington

    2012-01-01

    This study compares quantitative erosion rate estimates developed at different spatial and temporal scales. It is motivated by the need to assess potential water quality impacts of a proposed vineyard development project in the Gualala River watershed. Previous erosion rate estimates were developed using sediment source assessment techniques by the North Coast Regional...

  10. Regional yield predictions of malting barley by remote sensing and ancillary data

    NASA Astrophysics Data System (ADS)

    Weissteiner, Christof J.; Braun, Matthias; Kuehbauch, Walter

    2004-02-01

    Yield forecasts are of high interest to the malting and brewing industry in order to allow the most convenient purchasing policy of raw materials. Within this investigation, malting barley yield forecasts (Hordeum vulgare L.) were performed for typical growing regions in South-Western Germany. Multisensoral and multitemporal Remote Sensing data on one hand and ancillary meteorological, agrostatistical, topographical and pedological data on the other hand were used as input data for prediction models, which were based on an empirical-statistical modeling approach. Since spring barley production is depending on acreage and on the yield per area, classification is needed, which was performed by a supervised multitemporal classification algorithm, utilizing optical Remote Sensing data (LANDSAT TM/ETM+). Comparison between a pixel-based and an object-oriented classification algorithm was carried out. The basic version of the yield estimation model was conducted by means of linear correlation of Remote Sensing data (NOAA-AVHRR NDVI), CORINE land cover data and agrostatistical data. In an extended version meteorological data (temperature, precipitation, etc.) and soil data was incorporated. Both, basic and extended prediction systems, led to feasible results, depending on the selection of the time span for NDVI accumulation.

  11. 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

  12. An Overdetermined System for Improved Autocorrelation Based Spectral Moment Estimator Performance

    NASA Technical Reports Server (NTRS)

    Keel, Byron M.

    1996-01-01

    Autocorrelation based spectral moment estimators are typically derived using the Fourier transform relationship between the power spectrum and the autocorrelation function along with using either an assumed form of the autocorrelation function, e.g., Gaussian, or a generic complex form and applying properties of the characteristic function. Passarelli has used a series expansion of the general complex autocorrelation function and has expressed the coefficients in terms of central moments of the power spectrum. A truncation of this series will produce a closed system of equations which can be solved for the central moments of interest. The autocorrelation function at various lags is estimated from samples of the random process under observation. These estimates themselves are random variables and exhibit a bias and variance that is a function of the number of samples used in the estimates and the operational signal-to-noise ratio. This contributes to a degradation in performance of the moment estimators. This dissertation investigates the use autocorrelation function estimates at higher order lags to reduce the bias and standard deviation in spectral moment estimates. In particular, Passarelli's series expansion is cast in terms of an overdetermined system to form a framework under which the application of additional autocorrelation function estimates at higher order lags can be defined and assessed. The solution of the overdetermined system is the least squares solution. Furthermore, an overdetermined system can be solved for any moment or moments of interest and is not tied to a particular form of the power spectrum or corresponding autocorrelation function. As an application of this approach, autocorrelation based variance estimators are defined by a truncation of Passarelli's series expansion and applied to simulated Doppler weather radar returns which are characterized by a Gaussian shaped power spectrum. The performance of the variance estimators determined

  13. Selected yield tables for plantations and natural stands in Inland Northwest Forests

    Treesearch

    Albert R. Stage; David L. Renner; Roger C. Chapman

    1988-01-01

    Yields arrayed by site index and age have been tabulated for plantations of 500 trees per acre, with five thinning regimes, for Douglas-fir, grand fir, and western larch. Yields were also tabulated for naturally regenerated stands of the grand fir-cedar-hemlock ecosystem of the Inland Empire. All yields were estimated with the Prognosis Model for Stand Development,...

  14. Application of a rising plate meter to estimate forage yield on dairy farms in Pennsylvania

    USDA-ARS?s Scientific Manuscript database

    Accurately assessing pasture forage yield is necessary for producers who want to budget feed expenses and make informed pasture management decisions. Clipping and weighing forage from a known area is a direct method to measure pasture forage yield, however it is time consuming. The rising plate mete...

  15. 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...

  16. Foraminiferal faunal estimates of paleotemperature: Circumventing the no-analog problem yields cool ice age tropics

    USGS Publications Warehouse

    Mix, A.C.; Morey, A.E.; Pisias, N.G.; Hostetler, S.W.

    1999-01-01

    The sensitivity of the tropics to climate change, particularly the amplitude of glacial-to-interglacial changes in sea surface temperature (SST), is one of the great controversies in paleoclimatology. Here we reassess faunal estimates of ice age SSTs, focusing on the problem of no-analog planktonic foraminiferal assemblages in the equatorial oceans that confounds both classical transfer function and modern analog methods. A new calibration strategy developed here, which uses past variability of species to define robust faunal assemblages, solves the no-analog problem and reveals ice age cooling of 5??to 6??C in the equatorial current systems of the Atlantic and eastern Pacific Oceans. Classical transfer functions underestimated temperature changes in some areas of the tropical oceans because core-top assemblages misrepresented the ice age faunal assemblages. Our finding is consistent with some geochemical estimates and model predictions of greater ice age cooling in the tropics than was inferred by Climate: Long-Range Investigation, Mapping, and Prediction (CLIMAP) [1981] and thus may help to resolve a long-standing controversy. Our new foraminiferal transfer function suggests that such cooling was limited to the equatorial current systems, however, and supports CLIMAP's inference of stability of the subtropical gyre centers.

  17. Holographic lens spectrum splitting photovoltaic system for increased diffuse collection and annual energy yield

    NASA Astrophysics Data System (ADS)

    Vorndran, Shelby D.; Wu, Yuechen; Ayala, Silvana; Kostuk, Raymond K.

    2015-09-01

    Concentrating and spectrum splitting photovoltaic (PV) modules have a limited acceptance angle and thus suffer from optical loss under off-axis illumination. This loss manifests itself as a substantial reduction in energy yield in locations where a significant portion of insulation is diffuse. In this work, a spectrum splitting PV system is designed to efficiently collect and convert light in a range of illumination conditions. The system uses a holographic lens to concentrate shortwavelength light onto a smaller, more expensive indium gallium phosphide (InGaP) PV cell. The high efficiency PV cell near the axis is surrounded with silicon (Si), a less expensive material that collects a broader portion of the solar spectrum. Under direct illumination, the device achieves increased conversion efficiency from spectrum splitting. Under diffuse illumination, the device collects light with efficiency comparable to a flat-panel Si module. Design of the holographic lens is discussed. Optical efficiency and power output of the module under a range of illumination conditions from direct to diffuse are simulated with non-sequential raytracing software. Using direct and diffuse Typical Metrological Year (TMY3) irradiance measurements, annual energy yield of the module is calculated for several installation sites. Energy yield of the spectrum splitting module is compared to that of a full flat-panel Si reference module.

  18. Virtual Estimator for Piecewise Linear Systems Based on Observability Analysis

    PubMed Central

    Morales-Morales, Cornelio; Adam-Medina, Manuel; Cervantes, Ilse; Vela-Valdés and, Luis G.; García Beltrán, Carlos Daniel

    2013-01-01

    This article proposes a virtual sensor for piecewise linear systems based on observability analysis that is in function of a commutation law related with the system's outpu. This virtual sensor is also known as a state estimator. Besides, it presents a detector of active mode when the commutation sequences of each linear subsystem are arbitrary and unknown. For the previous, this article proposes a set of virtual estimators that discern the commutation paths of the system and allow estimating their output. In this work a methodology in order to test the observability for piecewise linear systems with discrete time is proposed. An academic example is presented to show the obtained results. PMID:23447007

  19. Genotype x environment interactions in milk yield and quality in Angus, Brahman, and reciprocal-cross cows on different forage systems.

    PubMed

    Brown, M A; Brown, A H; Jackson, W G; Miesner, J R

    2001-07-01

    Milk yield and quality were observed on 93 Angus, Brahman, and reciprocal-cross cows over 3 yr to evaluate the interactions of direct and maternal breed effects and heterosis with forage environment. Forage environments were common bermudagrass (BG), endophyte-infected tall fescue (E+), and a rotational system (ROT) of both forages, in which each forage (BG or E+) was grazed during its appropriate season, usually June through October for BG and November through May for E+. Milk yield was estimated each of 6 mo (April through September) via milking machine and converted to a 24-h basis. Milk fat, milk protein, and somatic cell count were analyzed by a commercial laboratory. Heterosis for milk yield was similar among forages, averaging 2.4 kg (P < 0.01). Expressed as percentages of purebred means, heterosis for milk yield was largest on E+ (52.8%), intermediate on ROT (39.3%), and smallest on BG (23.7%). Direct breed effects for milk yield favored Brahman, and they were similar among forages but tended to be larger for E+ (2.5 kg) and ROT (2.8 kg) than for BG (1.3 kg). Direct breed effects for milk fat favored Brahman and were similar among forages but tended to be larger for E+ (1.0%) and ROT (1.0%) than for BG (0.6%). Purebred cows exceeded crossbreds in milk protein by 0.1% on ROT (P < 0.10). Crossbred cows had lower somatic cell counts than purebreds on BG (P < 0.05), E+ (P < 0.01), or ROT (P > 0.30). Heterosis for somatic cell counts as percentages of purebred means was similar for BG (-68.3%) and E+ (-68.9%) and less favorable for ROT (-31.6%). Maternal breed effects for somatic cell count favored Angus on ROT (P < 0.10) with a similar nonsignificant trend on BG and E+. Direct breed effects for somatic cell count favored Brahman on ROT (P < 0.10) with similar nonsignificant trends on BG and E+. These results suggested that a rotation of cows from E+ to BG in the summer can partially alleviate negative effects of E+ on milk yield. Conclusions also indicated an

  20. 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

  1. 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.

  2. 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.

  3. Unmanned aircraft system-derived crop height and normalized difference vegetation index metrics for sorghum yield and aphid stress assessment

    NASA Astrophysics Data System (ADS)

    Stanton, Carly; Starek, Michael J.; Elliott, Norman; Brewer, Michael; Maeda, Murilo M.; Chu, Tianxing

    2017-04-01

    A small, fixed-wing unmanned aircraft system (UAS) was used to survey a replicated small plot field experiment designed to estimate sorghum damage caused by an invasive aphid. Plant stress varied among 40 plots through manipulation of aphid densities. Equipped with a consumer-grade near-infrared camera, the UAS was flown on a recurring basis over the growing season. The raw imagery was processed using structure-from-motion to generate normalized difference vegetation index (NDVI) maps of the fields and three-dimensional point clouds. NDVI and plant height metrics were averaged on a per plot basis and evaluated for their ability to identify aphid-induced plant stress. Experimental soil signal filtering was performed on both metrics, and a method filtering low near-infrared values before NDVI calculation was found to be the most effective. UAS NDVI was compared with NDVI from sensors onboard a manned aircraft and a tractor. The correlation results showed dependence on the growth stage. Plot averages of NDVI and canopy height values were compared with per-plot yield at 14% moisture and aphid density. The UAS measures of plant height and NDVI were correlated to plot averages of yield and insect density. Negative correlations between aphid density and NDVI were seen near the end of the season in the most damaged crops.

  4. 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.

  5. Optimal post-experiment estimation of poorly modeled dynamic systems

    NASA Technical Reports Server (NTRS)

    Mook, D. Joseph

    1988-01-01

    Recently, a novel strategy for post-experiment state estimation of discretely-measured dynamic systems has been developed. The method accounts for errors in the system dynamic model equations in a more general and rigorous manner than do filter-smoother algorithms. The dynamic model error terms do not require the usual process noise assumptions of zero-mean, symmetrically distributed random disturbances. Instead, the model error terms require no prior assumptions other than piecewise continuity. The resulting state estimates are more accurate than filters for applications in which the dynamic model error clearly violates the typical process noise assumptions, and the available measurements are sparse and/or noisy. Estimates of the dynamic model error, in addition to the states, are obtained as part of the solution of a two-point boundary value problem, and may be exploited for numerous reasons. In this paper, the basic technique is explained, and several example applications are given. Included among the examples are both state estimation and exploitation of the model error estimates.

  6. On-orbit point spread function estimation for THEOS imaging system

    NASA Astrophysics Data System (ADS)

    Khetkeeree, Suphongsa; Liangrocapart, Sompong

    2018-03-01

    In this paper, we present two approaches for net Point Spread Function (net-PSF) estimation of Thailand Earth Observation System (THEOS) imaging system. In the first approach, we estimate the net- PSF by employing the specification information of the satellite. The analytic model of the net- PSF based on the simple model of push-broom imaging system. This model consists of a scanner, optical system, detector and electronics system. The mathematical PSF model of each component is demonstrated in spatial domain. In the second approach, the specific target images from THEOS imaging system are analyzed to determine the net-PSF. For panchromatic imaging system, the images of the checkerboard target at Salon de Provence airport are used to analysis the net-PSF by slant-edge method. For multispectral imaging system, the new man-made targets are proposed. It is a pier bridge in Lamchabang, Chonburi, Thailand. This place has had a lot of bridges which have several width sizes and orientation. The pulse method is used to analysis the images of this bridge for estimating the net-PSF. Finally, the Full Width at Half Maximums (FWHMs) of the net-PSF of both approaches is compared. The results show that both approaches coincide and all Modulation Transfer Functions (MTFs) at Nyquist of both approaches are better than the requirement. However, the FWHM of multispectral system more deviate than panchromatic system, because the targets are not specially constructed for estimating the characteristics of the satellite imaging system.

  7. 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...

  8. Impacts of aerosol pollutant mitigation on lowland rice yields in China

    NASA Astrophysics Data System (ADS)

    Zhang, Tianyi; Li, Tao; Yue, Xu; Yang, Xiaoguang

    2017-10-01

    Aerosol pollution in China is significantly altering radiative transfer processes and is thereby potentially affecting rice photosynthesis and yields. However, the response of rice photosynthesis to aerosol-induced radiative perturbations is still not well understood. Here, we employ a process-based modelling approach to simulate changes in incoming radiation (RAD) and the diffuse radiation fraction (DF) with aerosol mitigation in China and their associated impacts on rice yields. Aerosol reduction has the positive effect of increasing RAD and the negative effect of decreasing DF on rice photosynthesis and yields. In rice production areas where the average RAD during the growing season is lower than 250 W m-2, aerosol reduction is beneficial for higher rice yields, whereas in areas with RAD>250 W m-2, aerosol mitigation causes yield declines due to the associated reduction in the DF, which decreases the light use efficiency. As a net effect, rice yields were estimated to significantly increase by 0.8%-2.6% with aerosol concentrations reductions from 20 to 100%, which is lower than the estimates obtained in earlier studies that only considered the effects of RAD. This finding suggests that both RAD and DF are important processes influencing rice yields and should be incorporated into future assessments of agricultural responses to variations in aerosol-induced radiation under climate change.

  9. Estimating Local Child Abuse.

    ERIC Educational Resources Information Center

    Ards, Sheila

    1989-01-01

    Three conceptual approaches to estimating local child abuse rates using the National Incidence Study of Child Abuse and Neglect data set are evaluated. All three approaches yield estimates of actual abuse cases that exceed the number of reported cases. (SLD)

  10. Periodic orbits of hybrid systems and parameter estimation via AD.

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

    Guckenheimer, John.; Phipps, Eric Todd; Casey, Richard

    Rhythmic, periodic processes are ubiquitous in biological systems; for example, the heart beat, walking, circadian rhythms and the menstrual cycle. Modeling these processes with high fidelity as periodic orbits of dynamical systems is challenging because: (1) (most) nonlinear differential equations can only be solved numerically; (2) accurate computation requires solving boundary value problems; (3) many problems and solutions are only piecewise smooth; (4) many problems require solving differential-algebraic equations; (5) sensitivity information for parameter dependence of solutions requires solving variational equations; and (6) truncation errors in numerical integration degrade performance of optimization methods for parameter estimation. In addition, mathematical modelsmore » of biological processes frequently contain many poorly-known parameters, and the problems associated with this impedes the construction of detailed, high-fidelity models. Modelers are often faced with the difficult problem of using simulations of a nonlinear model, with complex dynamics and many parameters, to match experimental data. Improved computational tools for exploring parameter space and fitting models to data are clearly needed. This paper describes techniques for computing periodic orbits in systems of hybrid differential-algebraic equations and parameter estimation methods for fitting these orbits to data. These techniques make extensive use of automatic differentiation to accurately and efficiently evaluate derivatives for time integration, parameter sensitivities, root finding and optimization. The boundary value problem representing a periodic orbit in a hybrid system of differential algebraic equations is discretized via multiple-shooting using a high-degree Taylor series integration method [GM00, Phi03]. Numerical solutions to the shooting equations are then estimated by a Newton process yielding an approximate periodic orbit. A metric is defined for computing the

  11. Probabilistic estimates of drought impacts on agricultural production

    NASA Astrophysics Data System (ADS)

    Madadgar, Shahrbanou; AghaKouchak, Amir; Farahmand, Alireza; Davis, Steven J.

    2017-08-01

    Increases in the severity and frequency of drought in a warming climate may negatively impact agricultural production and food security. Unlike previous studies that have estimated agricultural impacts of climate condition using single-crop yield distributions, we develop a multivariate probabilistic model that uses projected climatic conditions (e.g., precipitation amount or soil moisture) throughout a growing season to estimate the probability distribution of crop yields. We demonstrate the model by an analysis of the historical period 1980-2012, including the Millennium Drought in Australia (2001-2009). We find that precipitation and soil moisture deficit in dry growing seasons reduced the average annual yield of the five largest crops in Australia (wheat, broad beans, canola, lupine, and barley) by 25-45% relative to the wet growing seasons. Our model can thus produce region- and crop-specific agricultural sensitivities to climate conditions and variability. Probabilistic estimates of yield may help decision-makers in government and business to quantitatively assess the vulnerability of agriculture to climate variations. We develop a multivariate probabilistic model that uses precipitation to estimate the probability distribution of crop yields. The proposed model shows how the probability distribution of crop yield changes in response to droughts. During Australia's Millennium Drought precipitation and soil moisture deficit reduced the average annual yield of the five largest crops.

  12. Effects of geoengineering on crop yields

    NASA Astrophysics Data System (ADS)

    Pongratz, J.; Lobell, D. B.; Cao, L.; Caldeira, K.

    2011-12-01

    The potential of "solar radiation management" (SRM) to reduce future climate change and associated risks has been receiving significant attention in scientific and policy circles. SRM schemes aim to reduce global warming despite increasing atmospheric CO2 concentrations by diminishing the amount of solar insolation absorbed by the Earth, for example, by injecting scattering aerosols into the atmosphere. Climate models predict that SRM could fully compensate warming at the global mean in a high-CO2 world. While reduction of global warming may offset a part of the predicted negative effects of future climate change on crop yields, SRM schemes are expected to alter regional climate and to have substantial effects on climate variables other than temperature, such as precipitation. It has therefore been warned that, overall, SRM may pose a risk to food security. Assessments of benefits and risks of geoengineering are imperative, yet such assessments are only beginning to emerge; in particular, effects on global food security have not previously been assessed. Here, for the first time, we combine climate model simulations with models of crop yield responses to climate to assess large-scale changes in yields and food production under SRM. In most crop-growing regions, we find that yield losses caused by climate changes are substantially reduced under SRM as compared with a non-geoengineered doubling of atmospheric CO2. Substantial yield losses with SRM are only found for rice in high latitudes, where the limits of low temperatures are no longer alleviated. At the same time, the beneficial effect of CO2-fertilization on plant productivity remains active. Overall therefore, SRM in our models causes global crop yields to increase. We estimate the direct effects of climate and CO2 changes on crop production, and do not quantify effects of market dynamics and management changes. We note, however, that an SRM deployment would be unlikely to maintain the economic status quo, as

  13. 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.

  14. Rapid measurement of the yield stress of anaerobically-digested solid waste using slump tests.

    PubMed

    Garcia-Bernet, D; Loisel, D; Guizard, G; Buffière, P; Steyer, J P; Escudié, R

    2011-04-01

    The anaerobic digestion of solid waste is usually performed using dry or semi-dry technology. Incoming waste and fermenting digestate are pasty media and thus, at the industrial scale, their suitability for pumping and mixing is a prerequisite at the industrial scale. However, their rheology has been poorly characterised in the literature because there is no suitable experimental system for analysing heterogeneous media composed of coarse particles. We have developed a practical rheometrical test, a "slump test", for the analysis of actual digested solid waste. It makes it possible to estimate yield stress from the final slump height. From the slump behavior, we conclude that digestates behave as visco-elastic materials. The yield stress of different digested waste was measured between 200 and 800Pa. We show that the media containing smaller particles or with higher moisture content are characterised by smaller yield stresses. This study thus demonstrates the impact of the origin of the digestate on the yield stress. Copyright © 2010 Elsevier Ltd. All rights reserved.

  15. 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.

  16. A nonlinear dynamical system approach for the yielding behaviour of a viscoplastic material.

    PubMed

    Burghelea, Teodor; Moyers-Gonzalez, Miguel; Sainudiin, Raazesh

    2017-03-08

    A nonlinear dynamical system model that approximates a microscopic Gibbs field model for the yielding of a viscoplastic material subjected to varying external stresses recently reported in R. Sainudiin, M. Moyers-Gonzalez and T. Burghelea, Soft Matter, 2015, 11(27), 5531-5545 is presented. The predictions of the model are in fair agreement with microscopic simulations and are in very good agreement with the micro-structural semi-empirical model reported in A. M. V. Putz and T. I. Burghelea, Rheol. Acta, 2009, 48, 673-689. With only two internal parameters, the nonlinear dynamical system model captures several key features of the solid-fluid transition observed in experiments: the effect of the interactions between microscopic constituents on the yield point, the abruptness of solid-fluid transition and the emergence of a hysteresis of the micro-structural states upon increasing/decreasing external forces. The scaling behaviour of the magnitude of the hysteresis with the degree of the steadiness of the flow is consistent with previous experimental observations. Finally, the practical usefulness of the approach is demonstrated by fitting a rheological data set measured with an elasto-viscoplastic material.

  17. Modeling Speed-Accuracy Tradeoff in Adaptive System for Practicing Estimation

    ERIC Educational Resources Information Center

    Nižnan, Juraj

    2015-01-01

    Estimation is useful in situations where an exact answer is not as important as a quick answer that is good enough. A web-based adaptive system for practicing estimates is currently being developed. We propose a simple model for estimating student's latent skill of estimation. This model combines a continuous measure of correctness and response…

  18. High yield neutron generator based on a high-current gasdynamic electron cyclotron resonance ion source

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

    Skalyga, V.; Sidorov, A.; Lobachevsky State University of Nizhny Novgorod

    2015-09-07

    In present paper, an approach for high yield compact D-D neutron generator based on a high current gasdynamic electron cyclotron resonance ion source is suggested. Results on dense pulsed deuteron beam production with current up to 500 mA and current density up to 750 mA/cm{sup 2} are demonstrated. Neutron yield from D{sub 2}O and TiD{sub 2} targets was measured in case of its bombardment by pulsed 300 mA D{sup +} beam with 45 keV energy. Neutron yield density at target surface of 10{sup 9} s{sup −1} cm{sup −2} was detected with a system of two {sup 3}He proportional counters. Estimations based on obtained experimental resultsmore » show that neutron yield from a high quality TiD{sub 2} target bombarded by D{sup +} beam demonstrated in present work accelerated to 100 keV could reach 6 × 10{sup 10} s{sup −1} cm{sup −2}. It is discussed that compact neutron generator with such characteristics could be perspective for a number of applications like boron neutron capture therapy, security systems based on neutron scanning, and neutronography.« less

  19. Factors determining yield and quality of illicit indoor cannabis (Cannabis spp.) production.

    PubMed

    Vanhove, Wouter; Van Damme, Patrick; Meert, Natalie

    2011-10-10

    Judiciary currently faces difficulties in adequately estimating the yield of illicit indoor cannabis plantations. The latter data is required in penalization which is based on the profits gained. A full factorial experiment in which two overhead light intensities, two plant densities and four varieties were combined in the indoor cultivation of cannabis (Cannabis spp.) was used to reveal cannabis drug yield and quality under each of the factor combinations. Highest yield was found for the Super Skunk and Big Bud varieties which also exhibited the highest concentrations of Δ(9)-tetrahydrocannabinol (THC). Results show that plant density and light intensity are additive factors whereas the variety factor significantly interacts with both plant density and light intensity factors. Adequate estimations of yield of illicit, indoor cannabis plantations can only be made if upon seizure all factors considered in this study are accounted for. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  20. 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...

  1. Estimation of temperature in micromaser-type systems

    NASA Astrophysics Data System (ADS)

    Farajollahi, B.; Jafarzadeh, M.; Rangani Jahromi, H.; Amniat-Talab, M.

    2018-06-01

    We address the estimation of the number of photons and temperature in a micromaser-type system with Fock state and thermal fields. We analyze the behavior of the quantum Fisher information (QFI) for both fields. In particular, we show that in the Fock state field model, the QFI for non-entangled initial state of the atoms increases monotonously with time, while for entangled initial state of the atoms, it shows oscillatory behavior, leading to non-Markovian dynamics. Moreover, it is observed that the QFI, entropy of entanglement and fidelity have collapse and revival behavior. Focusing on each period that the collapses and revivals occur, we see that the optimal points of the QFI and entanglement coincide. In addition, when one of the subsystems evolved state fidelity becomes maximum, the QFI also achieves its maximum. We also address the evolved fidelity versus the initial state as a good witness of non-Markovianity. Moreover, we interestingly find that the entropy of the composite system can be used as a witness of non-Markovian evolution of the subsystems. For the thermal field model, we similarly investigate the relation among the QFI associated with the temperature, von Neumann entropy, and fidelity. In particular, it is found that at the instants when the maximum values of the QFI are achieved, the entanglement between the two-qubit system and the environment is maximized while the entanglement between the probe and its environment is minimized. Moreover, we show that the thermometry may lead to optimal estimation of practical temperatures. Besides, extending our computation to the two-qubit system, we find that using a two-qubit probe generally leads to more effective estimation than the one-qubit scenario. Finally, we show that initial state entanglement plays a key role in the advent of non-Markovianity and determination of its strength in the composite system and its subsystems.

  2. Estimating the Life Cycle Cost of Space Systems

    NASA Technical Reports Server (NTRS)

    Jones, Harry W.

    2015-01-01

    A space system's Life Cycle Cost (LCC) includes design and development, launch and emplacement, and operations and maintenance. Each of these cost factors is usually estimated separately. NASA uses three different parametric models for the design and development cost of crewed space systems; the commercial PRICE-H space hardware cost model, the NASA-Air Force Cost Model (NAFCOM), and the Advanced Missions Cost Model (AMCM). System mass is an important parameter in all three models. System mass also determines the launch and emplacement cost, which directly depends on the cost per kilogram to launch mass to Low Earth Orbit (LEO). The launch and emplacement cost is the cost to launch to LEO the system itself and also the rockets, propellant, and lander needed to emplace it. The ratio of the total launch mass to payload mass depends on the mission scenario and destination. The operations and maintenance costs include any material and spares provided, the ground control crew, and sustaining engineering. The Mission Operations Cost Model (MOCM) estimates these costs as a percentage of the system development cost per year.

  3. 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.

  4. 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

  5. Estimating the Effects of Module Area on Thin-Film Photovoltaic System Costs: Preprint

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

    Horowitz, Kelsey A; Fu, Ran; Silverman, Timothy J

    We investigate the potential effects of module area on the cost and performance of photovoltaic systems. Applying a bottom-up methodology, we analyzed the costs associated with thin-film modules and systems as a function of module area. We calculate a potential for savings of up to 0.10 dollars/W and 0.13 dollars/W in module manufacturing costs for CdTe and CIGS respectively, with large area modules. We also find that an additional 0.04 dollars/W savings in balance-of-systems costs may be achieved. Sensitivity of the dollar/W cost savings to module efficiency, manufacturing yield, and other parameters is presented. Lifetime energy yield must also bemore » maintained to realize reductions in the levelized cost of energy; the effects of module size on energy yield for monolithic thin-film modules are not yet well understood. Finally, we discuss possible non-cost barriers to adoption of large area modules.« less

  6. System health monitoring using multiple-model adaptive estimation techniques

    NASA Astrophysics Data System (ADS)

    Sifford, Stanley Ryan

    Monitoring system health for fault detection and diagnosis by tracking system parameters concurrently with state estimates is approached using a new multiple-model adaptive estimation (MMAE) method. This novel method is called GRid-based Adaptive Parameter Estimation (GRAPE). GRAPE expands existing MMAE methods by using new techniques to sample the parameter space. GRAPE expands on MMAE with the hypothesis that sample models can be applied and resampled without relying on a predefined set of models. GRAPE is initially implemented in a linear framework using Kalman filter models. A more generalized GRAPE formulation is presented using extended Kalman filter (EKF) models to represent nonlinear systems. GRAPE can handle both time invariant and time varying systems as it is designed to track parameter changes. Two techniques are presented to generate parameter samples for the parallel filter models. The first approach is called selected grid-based stratification (SGBS). SGBS divides the parameter space into equally spaced strata. The second approach uses Latin Hypercube Sampling (LHS) to determine the parameter locations and minimize the total number of required models. LHS is particularly useful when the parameter dimensions grow. Adding more parameters does not require the model count to increase for LHS. Each resample is independent of the prior sample set other than the location of the parameter estimate. SGBS and LHS can be used for both the initial sample and subsequent resamples. Furthermore, resamples are not required to use the same technique. Both techniques are demonstrated for both linear and nonlinear frameworks. The GRAPE framework further formalizes the parameter tracking process through a general approach for nonlinear systems. These additional methods allow GRAPE to either narrow the focus to converged values within a parameter range or expand the range in the appropriate direction to track the parameters outside the current parameter range boundary

  7. Constituent concentrations, loads, and yields to Beaver Lake, Arkansas, water years 1999-2008

    USGS Publications Warehouse

    Bolyard, Susan E.; De Lanois, Jeanne L.; Green, W. Reed

    2010-01-01

    Beaver Lake is a large, deep-storage reservoir used as a drinking-water supply and considered a primary watershed of concern in the State of Arkansas. As such, information is needed to assess water quality, especially nutrient enrichment, nutrient-algal relations, turbidity, and sediment issues within the reservoir system. Water-quality samples were collected at three main inflows to Beaver Lake: the White River near Fayetteville, Richland Creek at Goshen, and War Eagle Creek near Hindsville. Water-quality samples collected over the period represented different flow conditions (from low to high). Constituent concentrations, flow-weighted concentrations, loads, and yields from White River, Richland Creek, and War Eagle Creek to Beaver Lake for water years 1999-2008 were documented for this report. Constituents include total ammonia plus organic nitrogen, dissolved nitrite plus nitrate nitrogen, dissolved orthophosphorus (soluble reactive phosphorus), total phosphorus, total nitrogen, dissolved organic carbon, total organic carbon, and suspended sediment. Linear regression models developed by computer program S-LOADEST were used to estimate loads for each constituent for the 10-year period at each station. Constituent yields and flow-weighted concentrations for each of the three stations were calculated for the study. Constituent concentrations and loads and yields varied with time and varied among the three tributaries contributing to Beaver Lake. These differences can result from differences in precipitation, land use, contributions of nutrients from point sources, and variations in basin size. Load and yield estimates varied yearly during the study period, water years 1999-2008, with the least nutrient and sediment load and yields generally occurring in water year 2006, and the greatest occurring in water year 2008, during a year with record amounts of precipitation. Flow-weighted concentrations of most constituents were greatest at War Eagle Creek near Hindsville

  8. Estimation of single plane unbalance parameters of a rotor-bearing system using Kalman filtering based force estimation technique

    NASA Astrophysics Data System (ADS)

    Shrivastava, Akash; Mohanty, A. R.

    2018-03-01

    This paper proposes a model-based method to estimate single plane unbalance parameters (amplitude and phase angle) in a rotor using Kalman filter and recursive least square based input force estimation technique. Kalman filter based input force estimation technique requires state-space model and response measurements. A modified system equivalent reduction expansion process (SEREP) technique is employed to obtain a reduced-order model of the rotor system so that limited response measurements can be used. The method is demonstrated using numerical simulations on a rotor-disk-bearing system. Results are presented for different measurement sets including displacement, velocity, and rotational response. Effects of measurement noise level, filter parameters (process noise covariance and forgetting factor), and modeling error are also presented and it is observed that the unbalance parameter estimation is robust with respect to measurement noise.

  9. Reduced-rank technique for joint channel estimation in TD-SCDMA systems

    NASA Astrophysics Data System (ADS)

    Kamil Marzook, Ali; Ismail, Alyani; Mohd Ali, Borhanuddin; Sali, Adawati; Khatun, Sabira

    2013-02-01

    In time division-synchronous code division multiple access systems, increasing the system capacity by exploiting the inserting of the largest number of users in one time slot (TS) requires adding more estimation processes to estimate the joint channel matrix for the whole system. The increase in the number of channel parameters due the increase in the number of users in one TS directly affects the precision of the estimator's performance. This article presents a novel channel estimation with low complexity, which relies on reducing the rank order of the total channel matrix H. The proposed method exploits the rank deficiency of H to reduce the number of parameters that characterise this matrix. The adopted reduced-rank technique is based on truncated singular value decomposition algorithm. The algorithms for reduced-rank joint channel estimation (JCE) are derived and compared against traditional full-rank JCEs: least squares (LS) or Steiner and enhanced (LS or MMSE) algorithms. Simulation results of the normalised mean square error showed the superiority of reduced-rank estimators. In addition, the channel impulse responses founded by reduced-rank estimator for all active users offers considerable performance improvement over the conventional estimator along the channel window length.

  10. 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

  11. Cost estimating methods for advanced space systems

    NASA Technical Reports Server (NTRS)

    Cyr, Kelley

    1988-01-01

    Parametric cost estimating methods for space systems in the conceptual design phase are developed. The approach is to identify variables that drive cost such as weight, quantity, development culture, design inheritance, and time. The relationship between weight and cost is examined in detail. A theoretical model of cost is developed and tested statistically against a historical data base of major research and development programs. It is concluded that the technique presented is sound, but that it must be refined in order to produce acceptable cost estimates.

  12. Crop biomass and evapotranspiration estimation using SPOT and Formosat-2 Data

    NASA Astrophysics Data System (ADS)

    Veloso, Amanda; Demarez, Valérie; Ceschia, Eric; Claverie, Martin

    2013-04-01

    The use of crop models allows simulating plant development, growth and yield under different environmental and management conditions. When combined with high spatial and temporal resolution remote sensing data, these models provide new perspectives for crop monitoring at regional scale. We propose here an approach to estimate time courses of dry aboveground biomass, yield and evapotranspiration (ETR) for summer (maize, sunflower) and winter crops (wheat) by assimilating Green Area Index (GAI) data, obtained from satellite observations, into a simple crop model. Only high spatial resolution and gap-free satellite time series can provide enough information for efficient crop monitoring applications. The potential of remote sensing data is often limited by cloud cover and/or gaps in observation. Data from different sensor systems need then to be combined. For this work, we employed a unique set of Formosat-2 and SPOT images (164 images) and in-situ measurements, acquired from 2006 to 2010 in southwest France. Among the several land surface biophysical variables accessible from satellite observations, the GAI is the one that has a key role in soil-plant-atmosphere interactions and in biomass accumulation process. Many methods have been developed to relate GAI to optical remote sensing signal. Here, seasonal dynamics of remotely sensed GAI were estimated by applying a method based on the inversion of a radiative transfer model using artificial neural networks. The modelling approach is based on the Simple Algorithm for Yield and Evapotranspiration estimate (SAFYE) model, which couples the FAO-56 model with an agro-meteorological model, based on Monteith's light-use efficiency theory. The SAFYE model is a daily time step crop model that simulates time series of GAI, dry aboveground biomass, grain yield and ETR. Crop and soil model parameters were determined using both in-situ measurements and values found in the literature. Phenological parameters were calibrated by the

  13. Global Agriculture Yields and Conflict under Future Climate

    NASA Astrophysics Data System (ADS)

    Rising, J.; Cane, M. A.

    2013-12-01

    Aspects of climate have been shown to correlate significantly with conflict. We investigate a possible pathway for these effects through changes in agriculture yields, as predicted by field crop models (FAO's AquaCrop and DSSAT). Using satellite and station weather data, and surveyed data for soil and management, we simulate major crop yields across all countries between 1961 and 2008, and compare these to FAO and USDA reported yields. Correlations vary by country and by crop, from approximately .8 to -.5. Some of this range in crop model performance is explained by crop varieties, data quality, and other natural, economic, and political features. We also quantify the ability of AquaCrop and DSSAT to simulate yields under past cycles of ENSO as a proxy for their performance under changes in climate. We then describe two statistical models which relate crop yields to conflict events from the UCDP/PRIO Armed Conflict dataset. The first relates several preceding years of predicted yields of the major grain in each country to any conflict involving that country. The second uses the GREG ethnic group maps to identify differences in predicted yields between neighboring regions. By using variation in predicted yields to explain conflict, rather than actual yields, we can identify the exogenous effects of weather on conflict. Finally, we apply precipitation and temperature time-series under IPCC's A1B scenario to the statistical models. This allows us to estimate the scale of the impact of future yields on future conflict. Centroids of the major growing regions for each country's primary crop, based on USDA FAS consumption. Correlations between simulated yields and reported yields, for AquaCrop and DSSAT, under the assumption that no irrigation, fertilization, or pest control is used. Reported yields are the average of FAO yields and USDA FAS yields, where both are available.

  14. Winter wheat stand density determination and yield estimates from handheld and airborne scanners. [Montana

    NASA Technical Reports Server (NTRS)

    Aase, J. K.; Millard, J. P.; Siddoway, F. H. (Principal Investigator)

    1982-01-01

    Radiance measurements from handheld (Exotech 100-A) and air-borne (Daedalus DEI 1260) radiometers were related to wheat (Triticum aestivum L.) stand densities (simulated winter wheat winterkill) and to grain yield for a field located 11 km northwest of Sidney, Montana, on a Williams loam soil (fine-loamy, mixed Typic Argiborolls) where a semidwarf hard red spring wheat cultivar was needed to stand. Radiances were measured with the handheld radiometer on clear mornings throughout the growing season. Aircraft overflight measurements were made at the end of tillering and during the early stem extension period, and the mid-heading period. The IR/red ratio and normalized difference vegetation index were used in the analysis. The aircraft measurements corroborated the ground measurements inasmuch as wheat stand densities were detected and could be evaluated at an early enough growth stage to make management decision. The aircraft measurements also corroborated handheld measurements when related to yield prediction. The IR/red ratio, although there was some growth stage dependency, related well to yield when measured from just past tillering until about the watery-ripe stage.

  15. Monte Carlo simulation of the neutron monitor yield function

    NASA Astrophysics Data System (ADS)

    Mangeard, P.-S.; Ruffolo, D.; Sáiz, A.; Madlee, S.; Nutaro, T.

    2016-08-01

    Neutron monitors (NMs) are ground-based detectors that measure variations of the Galactic cosmic ray flux at GV range rigidities. Differences in configuration, electronics, surroundings, and location induce systematic effects on the calculation of the yield functions of NMs worldwide. Different estimates of NM yield functions can differ by a factor of 2 or more. In this work, we present new Monte Carlo simulations to calculate NM yield functions and perform an absolute (not relative) comparison with the count rate of the Princess Sirindhorn Neutron Monitor (PSNM) at Doi Inthanon, Thailand, both for the entire monitor and for individual counter tubes. We model the atmosphere using profiles from the Global Data Assimilation System database and the Naval Research Laboratory Mass Spectrometer, Incoherent Scatter Radar Extended model. Using FLUKA software and the detailed geometry of PSNM, we calculated the PSNM yield functions for protons and alpha particles. An agreement better than 9% was achieved between the PSNM observations and the simulated count rate during the solar minimum of December 2009. The systematic effect from the electronic dead time was studied as a function of primary cosmic ray rigidity at the top of the atmosphere up to 1 TV. We show that the effect is not negligible and can reach 35% at high rigidity for a dead time >1 ms. We analyzed the response function of each counter tube at PSNM using its actual dead time, and we provide normalization coefficients between count rates for various tube configurations in the standard NM64 design that are valid to within ˜1% for such stations worldwide.

  16. A robust motion estimation system for minimal invasive laparoscopy

    NASA Astrophysics Data System (ADS)

    Marcinczak, Jan Marek; von Öhsen, Udo; Grigat, Rolf-Rainer

    2012-02-01

    Laparoscopy is a reliable imaging method to examine the liver. However, due to the limited field of view, a lot of experience is required from the surgeon to interpret the observed anatomy. Reconstruction of organ surfaces provide valuable additional information to the surgeon for a reliable diagnosis. Without an additional external tracking system the structure can be recovered from feature correspondences between different frames. In laparoscopic images blurred frames, specular reflections and inhomogeneous illumination make feature tracking a challenging task. We propose an ego-motion estimation system for minimal invasive laparoscopy that can cope with specular reflection, inhomogeneous illumination and blurred frames. To obtain robust feature correspondence, the approach combines SIFT and specular reflection segmentation with a multi-frame tracking scheme. The calibrated five-point algorithm is used with the MSAC robust estimator to compute the motion of the endoscope from multi-frame correspondence. The algorithm is evaluated using endoscopic videos of a phantom. The small incisions and the rigid endoscope limit the motion in minimal invasive laparoscopy. These limitations are considered in our evaluation and are used to analyze the accuracy of pose estimation that can be achieved by our approach. The endoscope is moved by a robotic system and the ground truth motion is recorded. The evaluation on typical endoscopic motion gives precise results and demonstrates the practicability of the proposed pose estimation system.

  17. Effect of genetic European taurine ancestry on milk yield of Ankole-Holstein crossbred dairy cattle in mixed smallholders system of Burundi highlands.

    PubMed

    Manirakiza, J; Hatungumukama, G; Thévenon, S; Gautier, M; Besbes, B; Flori, L; Detilleux, J

    2017-10-01

    Different breeding systems associated with specific bovine genetic resources have coexisted in Burundi. To prepare for the development of a national action plan for the improvement of bovine genetic resources in Burundi, we aimed at performing genetic characterization of Ankole and Ankole × European crossbred individuals and assessing the effect of European ancestry on milk productivity of cows kept under the mixed crops livestock system. To that end, we genotyped 37 Ankole and 138 crossbred individuals on 42 636 SNPs and combined these genotypes with those from 21 cattle breeds, representative of the bovine genetic diversity. We also measured milk yield not suckled and estimated suckled milk. Given the results, we confirmed the indicine × African taurine admixed origin of the Ankole in Burundi and showed that crossbred individuals present a high proportion of European ancestry (i.e. 57% on average). As the proportion of European ancestry increased, milk yield increased by 0.03 ± 0.01 l/day, at a lower extent than expected. We also observed that breeders were unable to correctly evaluate the European proportion in their livestock. Our results may provide useful information for objective dairy breeding in Burundi. As an example, an ex-situ conservation program of Ankole within the framework of value chains is proposed as an accompanying strategy to improve the sustainability of the crossbreeding program. © 2017 Stichting International Foundation for Animal Genetics.

  18. Adaptive optimisation-offline cyber attack on remote state estimator

    NASA Astrophysics Data System (ADS)

    Huang, Xin; Dong, Jiuxiang

    2017-10-01

    Security issues of cyber-physical systems have received increasing attentions in recent years. In this paper, deception attacks on the remote state estimator equipped with the chi-squared failure detector are considered, and it is assumed that the attacker can monitor and modify all the sensor data. A novel adaptive optimisation-offline cyber attack strategy is proposed, where using the current and previous sensor data, the attack can yield the largest estimation error covariance while ensuring to be undetected by the chi-squared monitor. From the attacker's perspective, the attack is better than the existing linear deception attacks to degrade the system performance. Finally, some numerical examples are provided to demonstrate theoretical results.

  19. 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.

  20. Production yield of rare-earth ions implanted into an optical crystal

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

    Kornher, Thomas, E-mail: t.kornher@physik.uni-stuttgart.de; Xia, Kangwei; Kolesov, Roman

    2016-02-01

    Rare-earth (RE) ions doped into desired locations of optical crystals might enable a range of novel integrated photonic devices for quantum applications. With this aim, we have investigated the production yield of cerium and praseodymium by means of ion implantation. As a measure, the collected fluorescence intensity from both implanted samples and single centers was used. With a tailored annealing procedure for cerium, a yield up to 53% was estimated. Praseodymium yield amounts up to 91%. Such high implantation yield indicates a feasibility of creation of nanopatterned rare-earth doping and suggests strong potential of RE species for on-chip photonic devices.

  1. Geology, Ground-Water Occurrence, and Estimated Well Yields from the Mariana Limestone, Kagman Area, Saipan, Commonwealth of the Northern Mariana Islands

    USGS Publications Warehouse

    Hoffmann, John P.; Carruth, Rob; Meyer, William

    1998-01-01

    A study of the geology, ground-water occurrence, and estimated well yields from the Mariana Limestone was done to investigate ground-water availability in the Kagman area, Saipan. The Mariana and Tagpochau Limestone formations form the major aquifer in the Kagman drainage basin. The Mariana Limestone, which is the major water-bearing unit in the Kagman area, ranges in thickness from 300 to 500 feet and contains intermittent, thin clay stringers. The calcareous rocks of the Tagpochau Limestone range in thickness from 500 to 1,000 feet and are more sandy than those of the Mariana Limestone. Ground water is unconfined in the Mariana Limestone and ranges from unconfined to confined in the Tagpochau Limestone. The fresh ground-water lens (that part of the lens with less than 2-percent of the chloride-ion concentration in seawater) in the Mariana Limestone is relatively thin, ranging from about 15 to 21 feet. Altitude of the water table ranges from about 1.5 to 2.5 feet above mean sea level. Freshwater in the Mariana Limestone is underlain by seawater and is separated by a transition zone about 8 to 25 feet thick. Hydraulic conductivity and transmissivity of the Mariana Limestone were calculated from data collected at six test wells. Using the Newman method, estimated hydraulic conductivity and transmissivity range from 290 to 2,500 feet per day and 7,600 to 62,000 feet squared per day, respectively. The higher values probably are indicative of average conditions in the Mariana Limestone. The estimated storage coefficient of the Mariana Limestone is about 0.1. The availability of water from the Mariana Limestone is restricted by the thinness of the freshwater lens. Results of the study indicate that fresh ground water can be obtained from the Mariana Limestone when wells are designed for minimum drawdown, effectively skimming freshwater from the top of the lens. Wells that are shallow, widely spaced, and pumped at low uniform rates can prevent saltwater intrusion

  2. Application of Multilayer Feedforward Neural Networks to Precipitation Cell-Top Altitude Estimation

    NASA Technical Reports Server (NTRS)

    Spina, Michelle S.; Schwartz, Michael J.; Staelin, David H.; Gasiewski, Albin J.

    1998-01-01

    The use of passive 118-GHz O2 observations of rain cells for precipitation cell-top altitude estimation is demonstrated by using a multilayer feed forward neural network retrieval system. Rain cell observations at 118 GHz were compared with estimates of the cell-top altitude obtained by optical stereoscopy. The observations were made with 2 4 km horizontal spatial resolution by using the Millimeter-wave Temperature Sounder (MTS) scanning spectrometer aboard the NASA ER-2 research aircraft during the Genesis of Atlantic Lows Experiment (GALE) and the COoperative Huntsville Meteorological EXperiment (COHMEX) in 1986. The neural network estimator applied to MTS spectral differences between clouds, and nearby clear air yielded an rms discrepancy of 1.76 km for a combined cumulus, mature, and dissipating cell set and 1.44 km for the cumulus-only set. An improvement in rms discrepancy to 1.36 km was achieved by including additional MTS information on the absolute atmospheric temperature profile. An incremental method for training neural networks was developed that yielded robust results, despite the use of as few as 56 training spectra. Comparison of these results with a nonlinear statistical estimator shows that superior results can be obtained with a neural network retrieval system. Imagery of estimated cell-top altitudes was created from 118-GHz spectral imagery gathered from CAMEX, September through October 1993, and from cyclone Oliver, February 7, 1993.

  3. Monitoring Crop Yield in USA Using a Satellite-Based Climate-Variability Impact Index

    NASA Technical Reports Server (NTRS)

    Zhang, Ping; Anderson, Bruce; Tan, Bin; Barlow, Mathew; Myneni, Ranga

    2011-01-01

    A quantitative index is applied to monitor crop growth and predict agricultural yield in continental USA. The Climate-Variability Impact Index (CVII), defined as the monthly contribution to overall anomalies in growth during a given year, is derived from 1-km MODIS Leaf Area Index. The growing-season integrated CVII can provide an estimate of the fractional change in overall growth during a given year. In turn these estimates can provide fine-scale and aggregated information on yield for various crops. Trained from historical records of crop production, a statistical model is used to produce crop yield during the growing season based upon the strong positive relationship between crop yield and the CVII. By examining the model prediction as a function of time, it is possible to determine when the in-season predictive capability plateaus and which months provide the greatest predictive capacity.

  4. Smooth empirical Bayes estimation of observation error variances in linear systems

    NASA Technical Reports Server (NTRS)

    Martz, H. F., Jr.; Lian, M. W.

    1972-01-01

    A smooth empirical Bayes estimator was developed for estimating the unknown random scale component of each of a set of observation error variances. It is shown that the estimator possesses a smaller average squared error loss than other estimators for a discrete time linear system.

  5. SBML-PET: a Systems Biology Markup Language-based parameter estimation tool.

    PubMed

    Zi, Zhike; Klipp, Edda

    2006-11-01

    The estimation of model parameters from experimental data remains a bottleneck for a major breakthrough in systems biology. We present a Systems Biology Markup Language (SBML) based Parameter Estimation Tool (SBML-PET). The tool is designed to enable parameter estimation for biological models including signaling pathways, gene regulation networks and metabolic pathways. SBML-PET supports import and export of the models in the SBML format. It can estimate the parameters by fitting a variety of experimental data from different experimental conditions. SBML-PET has a unique feature of supporting event definition in the SMBL model. SBML models can also be simulated in SBML-PET. Stochastic Ranking Evolution Strategy (SRES) is incorporated in SBML-PET for parameter estimation jobs. A classic ODE Solver called ODEPACK is used to solve the Ordinary Differential Equation (ODE) system. http://sysbio.molgen.mpg.de/SBML-PET/. The website also contains detailed documentation for SBML-PET.

  6. Evaluating high temporal and spatial resolution vegetation index for crop yield prediction

    USDA-ARS?s Scientific Manuscript database

    Remote sensing data have been widely used in estimating crop yield. Remote sensing derived parameters such as Vegetation Index (VI) were used either directly in building empirical models or by assimilating with crop growth models to predict crop yield. The abilities of remote sensing VI in crop yiel...

  7. Simulation of reservoir storage and firm yields of three surface-water supplies, Ipswich River Basin, Massachusetts

    USGS Publications Warehouse

    Zarriello, Phillip J.

    2002-01-01

    A Hydrologic Simulation Program FORTRAN (HSPF) model previously developed for the Ipswich River Basin was modified to simulate the hydrologic response and firm yields of the water-supply systems of Lynn, Peabody, and Salem-Beverly. The updated model, expanded to include a portion of the Saugus River Basin that supplies water to Lynn, simulated reservoir system storage over a 35-year period (1961-95) under permitted withdrawals and hypothetical restrictions designed to maintain seasonally varied streamflow for aquatic habitat. A firm yield was calculated for each system and each withdrawal restriction by altering demands until the system failed. This is considered the maximum withdrawal rate that satisfies demands, but depletes reservoir storage. Simulations indicate that, under the permitted withdrawals, Lynn and Salem-Beverly were able to meet demands and generally have their reservoir system recover to full capacity during most years; reservoir storage averaged 83 and 82 percent of capacity, respectively. The firm yields for the Lynn and Salem-Beverly systems were 11.4 and 12.2 million gallons per day (Mgal/d), respectively, or 8 and 21 percent more than average 1998-2000 demands, respectively. Under permitted withdrawals and average 1998-2000 demands, the Peabody system failed in all years; thus Peabody purchased water to meet demands. The firm yield for the Peabody system is 3.70 Mgal/d, or 37 percent less than the average 1998-2000 demand. Simulations that limit withdrawals to levels recommended by the Ipswich River Fisheries Restoration Task Group (IRFRTG) indicate that under average 1998-2000 demands, reservoir storage was depleted in each of the three systems. Reservoir storage under average 1998-2000 demands and IRFRTG-recommended streamflow requirements averaged 15, 22, and 71 percent of capacity for the Lynn, Peabody, Salem-Beverly systems, respectively. The firm-yield estimates under the IRFRTG-recommended streamflow requirements were 6.02, 1.94, and 7

  8. Adaptive optimal input design and parametric estimation of nonlinear dynamical systems: application to neuronal modeling.

    PubMed

    Madi, Mahmoud K; Karameh, Fadi N

    2018-05-11

    Many physical models of biological processes including neural systems are characterized by parametric nonlinear dynamical relations between driving inputs, internal states, and measured outputs of the process. Fitting such models using experimental data (data assimilation) is a challenging task since the physical process often operates in a noisy, possibly non-stationary environment; moreover, conducting multiple experiments under controlled and repeatable conditions can be impractical, time consuming or costly. The accuracy of model identification, therefore, is dictated principally by the quality and dynamic richness of collected data over single or few experimental sessions. Accordingly, it is highly desirable to design efficient experiments that, by exciting the physical process with smart inputs, yields fast convergence and increased accuracy of the model. We herein introduce an adaptive framework in which optimal input design is integrated with Square root Cubature Kalman Filters (OID-SCKF) to develop an online estimation procedure that first, converges significantly quicker, thereby permitting model fitting over shorter time windows, and second, enhances model accuracy when only few process outputs are accessible. The methodology is demonstrated on common nonlinear models and on a four-area neural mass model with noisy and limited measurements. Estimation quality (speed and accuracy) is benchmarked against high-performance SCKF-based methods that commonly employ dynamically rich informed inputs for accurate model identification. For all the tested models, simulated single-trial and ensemble averages showed that OID-SCKF exhibited (i) faster convergence of parameter estimates and (ii) lower dependence on inter-trial noise variability with gains up to around 1000 msec in speed and 81% increase in variability for the neural mass models. In terms of accuracy, OID-SCKF estimation was superior, and exhibited considerably less variability across experiments, in

  9. Spectrally-Based Assessment of Crop Seasonal Performance and Yield

    NASA Astrophysics Data System (ADS)

    Kancheva, Rumiana; Borisova, Denitsa; Georgiev, Georgy

    The rapid advances of space technologies concern almost all scientific areas from aeronautics to medicine, and a wide range of application fields from communications to crop yield predictions. Agricultural monitoring is among the priorities of remote sensing observations for getting timely information on crop development. Monitoring agricultural fields during the growing season plays an important role in crop health assessment and stress detection provided that reliable data is obtained. Successfully spreading is the implementation of hyperspectral data to precision farming associated with plant growth and phenology monitoring, physiological state assessment, and yield prediction. In this paper, we investigated various spectral-biophysical relationships derived from in-situ reflectance measurements. The performance of spectral data for the assessment of agricultural crops condition and yield prediction was examined. The approach comprisesd development of regression models between plant spectral and state-indicative variables such as biomass, vegetation cover fraction, leaf area index, etc., and development of yield forecasting models from single-date (growth stage) and multitemporal (seasonal) reflectance data. Verification of spectral predictions was performed through comparison with estimations from biophysical relationships between crop growth variables. The study was carried out for spring barley and winter wheat. Visible and near-infrared reflectance data was acquired through the whole growing season accompanied by detailed datasets on plant phenology and canopy structural and biochemical attributes. Empirical relationships were derived relating crop agronomic variables and yield to various spectral predictors. The study findings were tested using airborne remote sensing inputs. A good correspondence was found between predicted and actual (ground-truth) estimates

  10. Satellite Angular Rate Estimation From Vector Measurements

    NASA Technical Reports Server (NTRS)

    Azor, Ruth; Bar-Itzhack, Itzhack Y.; Harman, Richard R.

    1996-01-01

    This paper presents an algorithm for estimating the angular rate vector of a satellite which is based on the time derivatives of vector measurements expressed in a reference and body coordinate. The computed derivatives are fed into a spacial Kalman filter which yields an estimate of the spacecraft angular velocity. The filter, named Extended Interlaced Kalman Filter (EIKF), is an extension of the Kalman filter which, although being linear, estimates the state of a nonlinear dynamic system. It consists of two or three parallel Kalman filters whose individual estimates are fed to one another and are considered as known inputs by the other parallel filter(s). The nonlinear dynamics stem from the nonlinear differential equation that describes the rotation of a three dimensional body. Initial results, using simulated data, and real Rossi X ray Timing Explorer (RXTE) data indicate that the algorithm is efficient and robust.

  11. Diverse rotations and poultry litter improves soybean yield

    USDA-ARS?s Scientific Manuscript database

    Continuous cropping systems without rotations or cover crops are perceived as unsustainable for long-term yield and soil health. Continuous systems, defined as continually producing a crop on the same parcel of land for more than three years, is thought to reduce yields. Given that crop rotations a...

  12. Alternatives to estimate statewide changes in aspen cover type volumes

    Treesearch

    Curtis L. VanderSchaaf

    2015-01-01

    For Minnesota, the only data available to conduct regional or state-wide level assessments across all ownerships is the Forest Inventory and Analysis Program (FIA). Some of the many alternatives available to estimate regional changes in standing volume are referred to here as 1.) FIA alternative, 2.) a commonly applied growth and yield system referred to as Walters and...

  13. Developing a diagnostic model for estimating terrestrial vegetation gross primary productivity using the photosynthetic quantum yield and Earth Observation data.

    PubMed

    Ogutu, Booker O; Dash, Jadunandan; Dawson, Terence P

    2013-09-01

    This article develops a new carbon exchange diagnostic model [i.e. Southampton CARbon Flux (SCARF) model] for estimating daily gross primary productivity (GPP). The model exploits the maximum quantum yields of two key photosynthetic pathways (i.e. C3 and C4 ) to estimate the conversion of absorbed photosynthetically active radiation into GPP. Furthermore, this is the first model to use only the fraction of photosynthetically active radiation absorbed by photosynthetic elements of the canopy (i.e. FAPARps ) rather than total canopy, to predict GPP. The GPP predicted by the SCARF model was comparable to in situ GPP measurements (R(2)  > 0.7) in most of the evaluated biomes. Overall, the SCARF model predicted high GPP in regions dominated by forests and croplands, and low GPP in shrublands and dry-grasslands across USA and Europe. The spatial distribution of GPP from the SCARF model over Europe and conterminous USA was comparable to those from the MOD17 GPP product except in regions dominated by croplands. The SCARF model GPP predictions were positively correlated (R(2)  > 0.5) to climatic and biophysical input variables indicating its sensitivity to factors controlling vegetation productivity. The new model has three advantages, first, it prescribes only two quantum yield terms rather than species specific light use efficiency terms; second, it uses only the fraction of PAR absorbed by photosynthetic elements of the canopy (FAPARps ) hence capturing the actual PAR used in photosynthesis; and third, it does not need a detailed land cover map that is a major source of uncertainty in most remote sensing based GPP models. The Sentinel satellites planned for launch in 2014 by the European Space Agency have adequate spectral channels to derive FAPARps at relatively high spatial resolution (20 m). This provides a unique opportunity to produce global GPP operationally using the Southampton CARbon Flux (SCARF) model at high spatial resolution. © 2013 John Wiley & Sons

  14. Estimating system parameters for solvent-water and plant cuticle-water using quantum chemically estimated Abraham solute parameters.

    PubMed

    Liang, Yuzhen; Torralba-Sanchez, Tifany L; Di Toro, Dominic M

    2018-04-18

    Polyparameter Linear Free Energy Relationships (pp-LFERs) using Abraham system parameters have many useful applications. However, developing the Abraham system parameters depends on the availability and quality of the Abraham solute parameters. Using Quantum Chemically estimated Abraham solute Parameters (QCAP) is shown to produce pp-LFERs that have lower root mean square errors (RMSEs) of predictions for solvent-water partition coefficients than parameters that are estimated using other presently available methods. pp-LFERs system parameters are estimated for solvent-water, plant cuticle-water systems, and for novel compounds using QCAP solute parameters and experimental partition coefficients. Refitting the system parameter improves the calculation accuracy and eliminates the bias. Refitted models for solvent-water partition coefficients using QCAP solute parameters give better results (RMSE = 0.278 to 0.506 log units for 24 systems) than those based on ABSOLV (0.326 to 0.618) and QSPR (0.294 to 0.700) solute parameters. For munition constituents and munition-like compounds not included in the calibration of the refitted model, QCAP solute parameters produce pp-LFER models with much lower RMSEs for solvent-water partition coefficients (RMSE = 0.734 and 0.664 for original and refitted model, respectively) than ABSOLV (4.46 and 5.98) and QSPR (2.838 and 2.723). Refitting plant cuticle-water pp-LFER including munition constituents using QCAP solute parameters also results in lower RMSE (RMSE = 0.386) than that using ABSOLV (0.778) and QSPR (0.512) solute parameters. Therefore, for fitting a model in situations for which experimental data exist and system parameters can be re-estimated, or for which system parameters do not exist and need to be developed, QCAP is the quantum chemical method of choice.

  15. Fission yield covariances for JEFF: A Bayesian Monte Carlo method

    NASA Astrophysics Data System (ADS)

    Leray, Olivier; Rochman, Dimitri; Fleming, Michael; Sublet, Jean-Christophe; Koning, Arjan; Vasiliev, Alexander; Ferroukhi, Hakim

    2017-09-01

    The JEFF library does not contain fission yield covariances, but simply best estimates and uncertainties. This situation is not unique as all libraries are facing this deficiency, firstly due to the lack of a defined format. An alternative approach is to provide a set of random fission yields, themselves reflecting covariance information. In this work, these random files are obtained combining the information from the JEFF library (fission yields and uncertainties) and the theoretical knowledge from the GEF code. Examples of this method are presented for the main actinides together with their impacts on simple burn-up and decay heat calculations.

  16. A weight modification sequential method for VSC-MTDC power system state estimation

    NASA Astrophysics Data System (ADS)

    Yang, Xiaonan; Zhang, Hao; Li, Qiang; Guo, Ziming; Zhao, Kun; Li, Xinpeng; Han, Feng

    2017-06-01

    This paper presents an effective sequential approach based on weight modification for VSC-MTDC power system state estimation, called weight modification sequential method. The proposed approach simplifies the AC/DC system state estimation algorithm through modifying the weight of state quantity to keep the matrix dimension constant. The weight modification sequential method can also make the VSC-MTDC system state estimation calculation results more ccurate and increase the speed of calculation. The effectiveness of the proposed weight modification sequential method is demonstrated and validated in modified IEEE 14 bus system.

  17. Development and characterization of a high yield transportable pulsed neutron source with efficient and compact pulsed power system

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

    Verma, Rishi, E-mail: rishiv9@gmail.com, E-mail: rishiv@barc.gov.in; Mishra, Ekansh; Dhang, Prosenjit

    2016-09-15

    The results of characterization experiments carried out on a newly developed dense plasma focus device based intense pulsed neutron source with efficient and compact pulsed power system are reported. Its high current sealed pseudospark switch based low inductance capacitor bank with maximum stored energy of ∼10 kJ is segregated into four modules of ∼2.5 kJ each and it cumulatively delivers peak current in the range of 400 kA–600 kA (corresponding to charging voltage range of 14 kV–18 kV) in a quarter time period of ∼2 μs. The neutron yield performance of this device has been optimized by discretely varying deuteriummore » filling gas pressure in the range of 6 mbar–11 mbar at ∼17 kV/550 kA discharge. At ∼7 kJ/8.5 mbar operation, the average neutron yield has been measured to be in the order of ∼4 × 10{sup 9} neutrons/pulse which is the highest ever reported neutron yield from a plasma focus device with the same stored energy. The average forward to radial anisotropy in neutron yield is found to be ∼2. The entire system is contained on a moveable trolley having dimensions 1.5 m × 1 m × 0.7 m and its operation and control (up to the distance of 25 m) are facilitated through optically isolated handheld remote console. The overall compactness of this system provides minimum proximity to small as well as large samples for irradiation. The major intended application objective of this high neutron yield dense plasma focus device development is to explore the feasibility of active neutron interrogation experiments by utilization of intense pulsed neutron sources.« less

  18. Development and characterization of a high yield transportable pulsed neutron source with efficient and compact pulsed power system.

    PubMed

    Verma, Rishi; Mishra, Ekansh; Dhang, Prosenjit; Sagar, Karuna; Meena, Manraj; Shyam, Anurag

    2016-09-01

    The results of characterization experiments carried out on a newly developed dense plasma focus device based intense pulsed neutron source with efficient and compact pulsed power system are reported. Its high current sealed pseudospark switch based low inductance capacitor bank with maximum stored energy of ∼10 kJ is segregated into four modules of ∼2.5 kJ each and it cumulatively delivers peak current in the range of 400 kA-600 kA (corresponding to charging voltage range of 14 kV-18 kV) in a quarter time period of ∼2 μs. The neutron yield performance of this device has been optimized by discretely varying deuterium filling gas pressure in the range of 6 mbar-11 mbar at ∼17 kV/550 kA discharge. At ∼7 kJ/8.5 mbar operation, the average neutron yield has been measured to be in the order of ∼4 × 10 9 neutrons/pulse which is the highest ever reported neutron yield from a plasma focus device with the same stored energy. The average forward to radial anisotropy in neutron yield is found to be ∼2. The entire system is contained on a moveable trolley having dimensions 1.5 m × 1 m × 0.7 m and its operation and control (up to the distance of 25 m) are facilitated through optically isolated handheld remote console. The overall compactness of this system provides minimum proximity to small as well as large samples for irradiation. The major intended application objective of this high neutron yield dense plasma focus device development is to explore the feasibility of active neutron interrogation experiments by utilization of intense pulsed neutron sources.

  19. Regional crop yield forecasting: a probabilistic approach

    NASA Astrophysics Data System (ADS)

    de Wit, A.; van Diepen, K.; Boogaard, H.

    2009-04-01

    Information on the outlook on yield and production of crops over large regions is essential for government services dealing with import and export of food crops, for agencies with a role in food relief, for international organizations with a mandate in monitoring the world food production and trade, and for commodity traders. Process-based mechanistic crop models are an important tool for providing such information, because they can integrate the effect of crop management, weather and soil on crop growth. When properly integrated in a yield forecasting system, the aggregated model output can be used to predict crop yield and production at regional, national and continental scales. Nevertheless, given the scales at which these models operate, the results are subject to large uncertainties due to poorly known weather conditions and crop management. Current yield forecasting systems are generally deterministic in nature and provide no information about the uncertainty bounds on their output. To improve on this situation we present an ensemble-based approach where uncertainty bounds can be derived from the dispersion of results in the ensemble. The probabilistic information provided by this ensemble-based system can be used to quantify uncertainties (risk) on regional crop yield forecasts and can therefore be an important support to quantitative risk analysis in a decision making process.

  20. An error-based micro-sensor capture system for real-time motion estimation

    NASA Astrophysics Data System (ADS)

    Yang, Lin; Ye, Shiwei; Wang, Zhibo; Huang, Zhipei; Wu, Jiankang; Kong, Yongmei; Zhang, Li

    2017-10-01

    A wearable micro-sensor motion capture system with 16 IMUs and an error-compensatory complementary filter algorithm for real-time motion estimation has been developed to acquire accurate 3D orientation and displacement in real life activities. In the proposed filter algorithm, the gyroscope bias error, orientation error and magnetic disturbance error are estimated and compensated, significantly reducing the orientation estimation error due to sensor noise and drift. Displacement estimation, especially for activities such as jumping, has been the challenge in micro-sensor motion capture. An adaptive gait phase detection algorithm has been developed to accommodate accurate displacement estimation in different types of activities. The performance of this system is benchmarked with respect to the results of VICON optical capture system. The experimental results have demonstrated effectiveness of the system in daily activities tracking, with estimation error 0.16 ± 0.06 m for normal walking and 0.13 ± 0.11 m for jumping motions. Research supported by the National Natural Science Foundation of China (Nos. 61431017, 81272166).