Evaluation of the RZWQM-CERES-Maize hybrid model for maize production     

L. Ma  G. Hoogenboom  L.R. Ahuja  J.C. Ascough II  S.A. Saseendran 《Agricultural Systems》2006

The root zone water quality model (RZWQM) was developed primarily for water quality research with a generic plant growth module primarily serving as a sink for plant nitrogen and water uptake. In this study, we coupled the CERES-Maize Version 3.5 crop growth model with RZWQM to provide RZWQM users with the option for selecting a more comprehensive plant growth model. In the hybrid model, RZWQM supplied CERES with daily soil water and nitrogen contents, soil temperature, and potential evapotranspiration, in addition to daily weather data. CERES-Maize supplied RZWQM with daily water and nitrogen uptake, and other plant growth variables (e.g., root distribution and leaf area index). The RZWQM-CERES hybrid model was evaluated with two well-documented experimental datasets distributed with DSSAT (Decision Support System for Agrotechnology Transfer) Version 3.5, which had various nitrogen and irrigation treatments. Simulation results were compared to the original DSSAT-CERES-Maize model. Both models used the same plant cultivar coefficients and the same soil parameters as distributed with DSSAT Version 3.5. The hybrid model provided similar maize prediction in terms of yield, biomass and leaf area index, as the DSSAT-CERES model when the same soil and crop parameters were used. No overall differences were found between the two models based on the paired t test, suggesting successful coupling of the two models. The hybrid model offers RZWQM users access to a rigorous new plant growth model and provides CERES-Maize users with a tool to address soil and water quality issues under different cropping systems.  相似文献   

Nitrate leaching in a silage maize field under different irrigation and nitrogen fertilizer rates   总被引：4，自引：0，他引：4  

Mahdi Gheysari  Seyed Majid Mirlatifi  Mehdi Homaee  Gerrit Hoogenboom 《Agricultural Water Management》2009,96(6):946-954

Quantification of the interactive effects of nitrogen (N) and water on nitrate (NO₃) loss provides an important insight for more effective N and water management. The goal of this study was to evaluate the effect of different irrigation and nitrogen fertilizer levels on nitrate-nitrogen (NO₃-N) leaching in a silage maize field. The experiment included four irrigation levels (0.7, 0.85, 1.0, and 1.13 of soil moisture depletion, SMD) and three N fertilization levels (0, 142, and 189 kg N ha⁻¹), with three replications. Ceramic suction cups were used to extract soil solution at 30 and 60 cm soil depths for all 36 experimental plots. Soil NO₃-N content of 0-30 and 30-60-cm layers were evaluated at planting and harvest maturity. Total N uptake (NU) by the crop was also determined. Maximum NO₃-N leaching out of the 60-cm soil layer was 8.43 kg N ha⁻¹, for the 142 kg N ha⁻¹ and over irrigation (1.13 SMD) treatment. The minimum and maximum seasonal average NO₃ concentration at the 60 cm depth was 46 and 138 mg l⁻¹, respectively. Based on our findings, it is possible to control NO₃ leaching out of the root zone during the growing season with a proper combination of irrigation and fertilizer management.  相似文献   

Application of the Cropping System Model (CSM)‐CROPGRO‐Soybean for Determining Optimum Management Strategies for Soybean in Tropical Environments     

P. Banterng  G. Hoogenboom  A. Patanothai  P. Singh  S. P. Wani  P. Pathak  S. Tongpoonpol  S. Atichart  P. Srihaban  S. Buranaviriyakul  A. Jintrawet  T. C. Nguyen 《Journal of Agronomy and Crop Science》2010,196(3):231-242

The determination of optimum crop management practices for increasing soybean production can provide valuable information for strategic planning in the tropics. However, this process is time consuming and expensive. The use of a dynamic crop simulation model can be an alternative option to help estimate yield levels under various growing conditions. The objectives of this study were to evaluate the performance of the Cropping System Model (CSM)‐CROPGRO‐Soybean and to determine optimum management practices for soybean for growing conditions in the Phu Pha Man district, Thailand. Data from two soybean experiments that were conducted in 1991 at Chiang Mai University and in 2003 at Khon Kaen University were used to determine the cultivar coefficients for the cultivars CM 60 and SJ 5. The CSM‐CROPGRO‐Soybean model was evaluated with data from two experiments that were conducted at Chiang Mai University. The observed data sets from farmers’ fields located in the Phu Pha Man district were also used for model evaluation. Simulations for different management scenarios were conducted with soil property information for seven different soil series and historical weather data for the period 1972–2003 to predict the optimum crop management practices for soybean production in the Phu Pha Man district. The results of this study indicated that the cultivar coefficients of the two soybean cultivars resulted in simulated growth and development parameters that were in good agreement with almost all observed parameters. Model evaluation showed a good agreement between simulated and observed data for phenology and growth of soybean, and demonstrated the potential of the CSM‐CROPGRO‐Soybean model to simulate growth and yield for local environments, including farmers’ fields, in Thailand. The CSM‐CROPGRO‐Soybean simulations indicated that the optimum planting dates from June 15 to July 15 produced maximum soybean yield in a rainfed environment. However, the planting date December 15 produced the highest yield under quality irrigation. Soybean yield was slightly improved by applying nitrogen at a rate of 30 kg N ha^?1 at planting. Soybean yield also improved when the plant density was increased from 20 to 40 plants m^?2. The results from this study suggest that the CSM‐CROPGRO‐Soybean model can be a valuable tool in assisting with determining optimum management practices for soybean cropping systems in the Phu Pha Man district and might be applicable to other agricultural production areas in Thailand and southeast Asia.  相似文献   

Impact of Water Stress on Maize Grown Off-Season in a Subtropical Environment     

C. M. T. Soler  G. Hoogenboom  P. C. Sentelhas  A. P. Duarte 《Journal of Agronomy and Crop Science》2007,193(4):247-261

During the last decade, the production of off‐season maize has increased in several regions of Brazil. Growing maize during this season, with sowing from January through April, imposes several climatic risks that can impact crop yield. This is mainly caused by the high variability of precipitation and the probability of frost during the reproduction phases. High production risks are also partially due to the use of cultivars that are not adapted to the local environmental conditions. The goal of this study was to evaluate crop growth and development and associated yield, yield components and water use efficiency (WUE) for maize hybrids with different maturity ratings grown off‐season in a subtropical environment under both rainfed and irrigated conditions. Three experiments were conducted in 2001 and 2002 in Piracicaba, state of São Paulo, Brazil with four hybrids of different maturity duration, AG9010 (very short season), DAS CO32 and Exceler (short season) and DKB 333B (normal season). Leaf area index (LAI), plant height and dry matter were measured approximately every 18 days. Under rainfed conditions, the soil water content in the deeper layers was reduced, suggesting that the extension of the roots into these layers was a response to soil water limitations. On average, WUE varied from 1.45 kg m⁻³ under rainfed conditions to 1.69 kg m⁻³ under irrigated conditions during 2001. The average yield varied from 4209 kg ha⁻¹ for the hybrids grown under rainfed conditions to 5594 kg ha⁻¹ under irrigated conditions during 2001. Yield reductions under rainfed conditions were affected by the genotype. For the hybrid DKB 333B with a normal maturity, yield was reduced by 25.6 % while the short maturity hybrid Exceler was the least impacted by soil water limitations with a yield reduction of only 8.4 %. To decrease the risk of yield loss, the application of supplemental irrigation should be considered by local farmers, provided that this practice is not restricted by either economic considerations or the availability of sufficient water resources.  相似文献   

Spatial suitability assessment for vineyard site selection based on fuzzy logic     

Golnaz Badr  Gerrit Hoogenboom  Michelle Moyer  Markus Keller  Richard Rupp  Joan Davenport 《Precision Agriculture》2018,19(6):1027-1048

Developing a sustainable agricultural production system requires knowledge of the climate, soil, and topography of the area of interest. This is especially relevant for wine grape (Vitis vinefera L.) production. The main objective of this study was the development of a comprehensive system to aid in the selection of suitable areas for grapevine cultivation. Included in this system were several bioclimatic indices, such as Growing Degree Days (GDD), Frost Free Days (FFD), and the Huglin Index (HI) calculated over a period of 30 years using daily weather data obtained from the University of Idaho’s Gridded Surface Meteorological (UI GSM) dataset. Soil data and topographical data were also included in the system. The bioclimatic indices, soil, and topographic data were then transformed using fuzzy logic, and suitability maps with scores ranging from 0 to 1 were developed. The final vineyard-potential scores were obtained by combining the soil, weather, and topographic potential scores with a range from 0 to 1, where 0 pertained to non-suitable areas and 1 referred to optimal sites. The maps were evaluated by comparing the range of suitability scores of existing vineyards in Washington State. The evaluation indicated that 97% of the established vineyards have a vineyard-potential score that ranges from 0.8 to 1. The results of this study revealed that 11% of the total study area had a high potential for wine grape production. This study was able to successfully employ fuzzy logic to help decision-makers, growers, and others with conducting a precise land assessment for wine grape production.  相似文献   

The effect of dietary nitrite and nitrate on the metabolism of sulphadimidine administered orally to pigs     

L A Hoogenboom  A Pijpers  P W van de Steeg  M M Aerts  J H Verheijden  H A Kuiper 《The Veterinary quarterly》1988,10(2):136-139

The in vivo interaction of sulphadimidine (SDM) with nitrite and nitrate has been investigated in pigs. It was shown that the combined oral treatment with SDM and nitrite but not nitrate leads to the formation of a deaminated compound, which becomes the major metabolite in plasma soon after cessation of the treatment. The major in vitro reaction product, 1,3-di(4-[N(4,6-dimethyl-2-pyrimidinyl)]-sulphamoylphenyl)-triazen e, DDPSPT as has been reported previously, could not be detected in blood, urine or faeces of the exposed animals. No effect of nitrite or nitrate could be observed on the acetylation of SDM.  相似文献   

Predicting Crop Yields with the Agricultural Reference Index for Drought     

P. Woli  J. W. Jones  K. T. Ingram  G. Hoogenboom 《Journal of Agronomy and Crop Science》2014,200(3):163-171

A generic agricultural drought index, called Agricultural Reference Index for Drought (ARID), was designed recently to quantify water stress for use in predicting crop yield loss from drought. This study evaluated ARID in terms of its ability to predict crop yields. Daily historical weather data and yields of cotton, maize, peanut and soybean were obtained for several locations and years in the south‐eastern USA. Daily values of ARID were computed for each location and converted to monthly average values. Using regression analyses of crop yields vs. monthly ARID values during the crop growing season, ARID‐yield relationships were developed for each crop. The ability of ARID to predict yield loss from drought was evaluated using the root mean square error (RMSE), the Willmott index and the modelling efficiency (ME). The ARID‐based yield models predicted relative yields with the RMSE values of 0.144, 0.087, 0.089 and 0.142 (kg ha^?1 yield per kg ha^?1 potential yield); the Willmott index values of 0.70, 0.92, 0.86 and 0.79; and the ME values of 0.33, 0.73, 0.60 and 0.49 for cotton, maize, peanut and soybean, respectively. These values indicated that the ARID‐based yield models can predict the yield loss from drought for these crops with reasonable accuracy.  相似文献   

应用DSSAT模型对吉林省黑土玉米最佳栽培技术的模拟和校验研究I.模型品种参数校验和产量的敏感性分析   总被引：1，自引：0，他引：1  

杨靖民  刘金华  窦森  杨靖一 《土壤学报》2011,48(2)

目前,应用农业模型去寻找改进农业生态系统的最佳农艺措施被认为是比单一的田间试验更为有效的途径之一.在应用和引进模型当中,一个很关键的环节是确定模型的输入参数对产量和土壤养分的敏感性,因为在一个地区的敏感性并不能保证在其他地区具有同样的影响.正因为如此,本文对农业技术转化决策系统(DSSAT)模型的农业管理参数进行敏感性分析.在吉林省黑土(ollisols)地区,于2008年田间试验条件下进行玉米(Zea mays L.)生长模拟(叶面积指数,地上于物质,籽粒重量),应用当地平均产量和生长期对玉米品种参数进行校验.模拟结果的综合分析表明:玉米提前播种8～10d比正常播种减产大约10%;玉米产量随播种密度呈现抛物线趋势,既当低密度下,产量曲线递增,但是当密度大于5株m-2时,产量增加平缓;产量和氮肥施用量呈典型的效应递减曲线,最佳施氮量为200～240 kg hm-2;最佳追肥时间为6月15日至6月28日.本研究证明DSSAT模型能够用于中国其他地区的玉米生长模拟,并且,本研究建立的敏感性分析方法能够用于其他作物,如水稻和小麦.进一步的研究需要包括测试土壤有机碳氮对作物生长管理参数的敏感性.  相似文献   

Report from the conference, ‘identifying obstacles to applying big data in agriculture’     

White  Emma L.  Thomasson  J. Alex  Auvermann  Brent  Kitchen  Newell R.  Pierson  Leland Sandy  Porter  Dana  Baillie  Craig  Hamann  Hendrik  Hoogenboom  Gerrit  Janzen  Todd  Khosla  Rajiv  Lowenberg-DeBoer  James  McIntosh  Matt  Murray  Seth  Osborn  Dave  Shetty  Ashoo  Stevenson  Craig  Tevis  Joe  Werner  Fletcher 《Precision Agriculture》2021,22(1):306-315

Precision Agriculture - Data-centric technology has not undergone widespread adoption in production agriculture but could address global needs for food security and farm profitability. Participants...  相似文献   

Scheduling irrigation with a dynamic crop growth model and determining the relation between simulated drought stress and yield for peanut     

Cecilia M. Tojo Soler  Ayman Suleiman  Jakarat Anothai  Ian Flitcroft  Gerrit Hoogenboom 《Irrigation Science》2013,31(5):889-901

A computer simulation model can be used as a tool to help explain the impact of drought stress on plant growth and development because it integrates the complex soil–plant-atmosphere system through a set of mathematical equations. The objectives of this study were to determine the impact of different irrigation scheduling regimes on peanut growth and development, to determine the capability of the CSM-CROPGRO-Peanut model to simulate growth and development of peanut, and to determine the relationship between yield and the two cumulative drought stress indices simulated by the peanut model. The CSM-CROPGRO-Peanut model was evaluated with experimental data collected during two field experiments that were conducted in four automated rainout shelters located at The University of Georgia, USA, in 2006 and 2007. Irrigation was applied when the simulated soil water content in the effective root zone dropped below a specific threshold value for the available soil water capacity (AWC). The irrigation treatments corresponded to irrigation thresholds (IT) of 30, 40, 60, and 90 % of AWC. The results showed that growth and development was reduced for the 30 and 40 % IT treatments which resulted in yield reductions that were 92 and 45 %, respectively, of the 90 % IT treatment. The Cropping System Model (CSM)-CROPGRO-Peanut model was able to accurately simulate growth and development of peanut grown under different irrigation treatments when compared to the observed data. We found an inverse relationship between the two simulated total cumulative drought stress indices for leaf growth (expansion) and photosynthesis and simulated pod yield. Knowing the cumulative drought stress value prior to harvest maturity could help with the prediction of potential harvestable yield.  相似文献