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   

Multi-environment evaluation of peanut lines by model simulation with the cultivar coefficients derived from a reduced set of observed field data   总被引：1，自引：0，他引：1  

J. Anothai  A. Patanothai  K. Pannangpetch  S. Jogloy  K.J. Boote  G. Hoogenboom 《Field Crops Research》2009

A major limitation of the application of a crop simulation model is the determination of cultivar coefficients, as the recommended procedure requires extensive data sampling throughout the growing season which is very impractical when a large number of lines are involved or when critical resources are limited. Our previous study has shown that a reduced set of experimental data can be used to accurately estimate the cultivar coefficients of peanut lines as used by the CSM-CROPGRO-Peanut model. The objectives of this study were to verify our previous finding and to evaluate the derived cultivar coefficients in assisting multi-environment evaluation of peanut lines with the CSM-CROPGRO-Peanut model. Nine peanut lines in a regional yield trial (Set I) and ten peanut lines in a standard yield trial (Set II) were grown during the dry and rainy seasons of 2005. Data were collected on plant growth and development following the optimum protocol from our previous study. These data were used for model calibration to derive the cultivar coefficients of the individual peanut lines. Model calibration showed simulated values of phenology and growth characteristics of the peanut lines that were close to the corresponding observed values, with the coefficient of determination (r²) and the index of agreement (d) close to optimal values of 1, and a normalized root mean square error (RMSE_n) smaller than 35%. Genetic variation among lines in cultivar coefficients was also observed. The initial model evaluation with data collected in the 2004 rainy season confirmed that model prediction was good for independent data, i.e., giving high values of r² and d; and small RMSE_n. The derived cultivar coefficients were shown to enable the CSM-CROPGRO-Peanut model to satisfactorily mimic yield ranking and stability of peanut lines in the Set I and Set II yield trials with 10 and 8 environments, respectively. Among the top five highest yielding lines based on mean observed pod yield (upper 56% for the Set I yield trial and upper 50% for the Set II yield trial), four lines were identified by model simulation in both sets. Also, the same top yielding lines in the two sets were identified by both simulation and experimentation. The model predicted similar GGE biplot patterns as present in observed trials, and also identified the same stable lines as the observed data. It is concluded that a reduced set of field data can be used for model application in assisting the multi-environment evaluation of peanut lines.  相似文献   

Application of the CSM-CERES-Rice model for evaluation of plant density and nitrogen management of fine transplanted rice for an irrigated semiarid environment     

Shakeel Ahmad  Ashfaq Ahmad  Cecilia Manuela Tojo Soler  Hakoomat Ali  Muhammad Zia-Ul-Haq  Jakarat Anothai  Abid Hussain  Gerrit Hoogenboom  Mirza Hasanuzzaman 《Precision Agriculture》2012,13(2):200-218

The objectives of this study were to evaluate the performance of the cropping system model (CSM)-CERES-Rice to simulate growth and development of an aromatic rice variety under irrigated conditions in a semiarid environment of Pakistan and to determine the impact of various plant densities and nitrogen (N) application rates on grain yield and economic return. The crop simulation model was evaluated with experimental data collected in experiments that were conducted in 2000 and 2001 in Faisalabad, Punjab, Pakistan. The experimental design was a randomized complete block design with three replications and included three plant densities (one seedling hill⁻¹, PD₁; two seedlings hill⁻¹, PD₂; and three seedlings hill⁻¹, PD₃) and five N fertilizer regimes (control, N₀; 50 kg ha⁻¹, N₅₀; 100 kg ha⁻¹, N₁₀₀; 150 kg ha⁻¹, N₁₅₀; and 200 kg ha⁻¹, N₂₀₀). To determine the most appropriate combination of plant density and N levels, four plant densities from one seedling hill⁻¹ to four seedlings hill⁻¹ and 13 N levels ranging from 0 to 300 kg N ha⁻¹ (52 scenarios) were simulated for 35 years of historical daily weather data under irrigated conditions. The evaluation of CSM-CERES-Rice showed that the model was able to simulate growth and yield of irrigated rice in the semiarid conditions, with an average error of 11% between simulated and observed grain yield. The results of the stimulation analysis result showed that two seedlings hill⁻¹ along with 200 kg N ha⁻¹ (PD₂N₂₀₀) produced the highest yield as compared to all other scenarios. Furthermore, the economic analysis through the mean gini dominance also showed the dominance of this treatment (PD₂N₂₀₀) compared to the other treatment combinations. Thus, the management scenario that consisted of two seedlings hill⁻¹ and 200 kg N ha⁻¹ was the best for high yield and monitory return of irrigated rice in the semiarid environment. The mean monetary returns ranged from 291 US $ ha⁻¹ to 1 460 US $ ha⁻¹ to 1 460 US  ha⁻¹ among the 52 production options that were simulated. This approaching was demonstrated as effective way to optimize the density and N management for high yield and monetary return. It will help the rice production.  相似文献   

A sequential approach for determining the cultivar coefficients of peanut lines using end-of-season data of crop performance trials     

J. Anothai  A. Patanothai  S. Jogloy  K. Pannangpetch  K.J. Boote  G. Hoogenboom 《Field Crops Research》2008

Coefficients of crop cultivars, a required input for the application of crop simulation models, are normally derived from experiments designed specifically for their estimation. This procedure is laborious and time consuming even with a reduced data set. Recent studies have shown that cultivar coefficients for soybean lines can be derived from standard crop performance trials. However, this needs to be confirmed in other crops and be simplified for broader applications. The objective of this study was to determine the feasibility of estimating cultivar coefficients for new peanut lines using data from standard performance trials. Data from performance trials of 17 peanut lines that were conducted in farmers’ fields and research stations in the northeastern and northern regions of Thailand during 2002–2004, totaling eight environments, were used in this study. The data that were collected included dates of first flower and harvest maturity, final biomass, pod and seed yield, seed size, pod and seed harvest index, and shelling percentage. These data were used for the calculation of the cultivar coefficients using the Genotype Coefficient Calculator (GENCALC) program, which is part of the Decision Support System for Agrotechnology Transfer (DSSAT). Evaluation of the derived cultivar coefficients was conducted with time series growth data collected in three additional experiments grown during the 2002 rainy, 2003 dry, and 2004 dry seasons. The model calibration with GENCALC resulted in cultivar coefficients that produced simulated values for the development and growth characteristics that were close to their corresponding observed values, with root mean square errors (RMSE) ranging from 1.5 to 4.1 days for development traits and 0.20–1.32 t ha⁻¹ for growth traits and coefficient of determinations (r²) ranging from 0.55 to 0.97 for all traits. The evaluation of the cultivar coefficients that were derived from the performance trials data with independent data worked well for all development traits and fairly well for the plant growth characteristics, as judged by RMSE, r², normalized root mean square error (RMSEn) and index of agreement (d). The mean RMSE values for days to first flower and to harvest maturity were 1.6 and 2.4 days; and mean r² were 0.72 and 0.91, respectively. The mean RMSEn values calculated from time series growth data were 17.9, 24.6 and 11.5% with the mean d values of 0.88, 0.93 and 0.93 for the 2002 rainy, 2003 dry and 2004 dry seasons, respectively. It is concluded that the cultivar coefficients of peanut lines can be estimated from typical data that are collected in standard performance trials using either GENCALC or similar methodologies.  相似文献   

Complexity and adaptability of a traditional agricultural system: case study of a gall midge resistant rice landrace from northern Thailand     

Prateep Oupkaew  Tonapha Pusadee  Anothai Sirabanchongkran  Kanok Rerkasem  Sansanee Jamjod  Benjavan Rerkasem 《Genetic Resources and Crop Evolution》2011,58(3):361-372

Adaptability of traditional agricultural systems is suggested by their success over time, but documentation of how this happens is rare. This paper shows how genetic diversity in a rice landrace enables rice farming system of northern Thailand to adapt to a constraint of an insect pest, microenvironments of mountainous landscape and people’s different tastes in rice. Resistance to laboratory-reared gall midge varied among accessions the rice landrace Muey Nawng and gall midge populations. Higher rice yield in farmers’ fields reflected adaptation to local environment as well as resistance to gall midge. Microsatellite variation of the accessions correlated negatively with their gall midge resistance, but there was also variation in heading time and endosperm starch. Presence of non-waxy endosperm in glutinous rice provides opportunity to select for rice that is cooked into non-glutinous rice preferred by minority groups who live at higher elevations, where the gall midge is emerging as a new threat, possibly because of climate change. These data show how genetic diversity of a rice landrace coupled with seed management by farmers enabled a rice farming system to adapt to the varied microenvironment of a mountainous landscape under the constraint of an insect pest and people’s different tastes in rice.  相似文献