Simulation and production of soybean plant growth (Glycine max (L) Merrill) using the DSSAT model with different scenarios of water supply and compost

Yassi, Abdul Hakim; Syaiful, S. A.; Ruslan, Achmad; Ridwan, Ifayanti; Andari, Gardis

doi:10.1088/1755-1315/343/1/012014

Cited by 2 publications

(1 citation statement)

References 4 publications

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“…Currently, the commonly used crop growth models include the FAO Crop Model to Simulate Yield Response to Water (AquaCrop) [27,28], Agricultural Production Systems Simulator (APSIM) [29], Environmental Policy-Integrated Climate (EPIC) [30][31][32] and Decision Support System for Agrotechnology Transfer (DSSAT) [33,34] models. Scholars use appropriate crop growth models to evaluate agricultural drought vulnerability according to the major crops in the region.…”

Section: Introductionmentioning

confidence: 99%

Winter Wheat Drought Risk Assessment by Coupling Improved Moisture-Sensitive Crop Model and Gridded Vulnerability Curve

Yang

et al. 2023

Remote Sensing

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The crop drought risk assessment is an important basis for mitigating the effects of drought on crops. The study of drought using crop growth models is an integral part of agricultural drought risk research. The current Decision Support System for Agrotechnology Transfer (DSSAT) model is not sufficiently sensitive to moisture parameters when performing simulations, and most studies that conduct different scenario simulations to assess crop drought vulnerability are based on the site-scale. In this paper, we improved the moisture sensitivity of the Crop Environment Resource Synthesis System (CERES)-Wheat to improve the simulation accuracy of winter wheat under water stress, and then we assessed the drought intensity in the Beijing-Tianjin-Hebei region and constructed a gridded vulnerability curve. The grid vulnerability curves (1 km × 1 km) were quantitatively characterized using key points, and the drought risk distribution and zoning of winter wheat were evaluated under different return periods. The results show that the stress mechanism of coupled water and photosynthetic behavior improved the CERES-Wheat model. The accuracy of the modified model improved in terms of the above-ground biomass and yield compared with that before the modification, with increases of 20.39% and 11.45% in accuracy, respectively. The drought hazard intensity index of winter wheat in the study area from 1970 to 2019 exhibited a trend of high in the southwest and low in the southeast. The range of the multi-year average drought hazard intensity across the region was 0.29–0.61. There were some differences in the shape and characteristic covariates of the drought vulnerability curves among the different sub-zones. In terms of the cumulative loss rates, almost the entire region had a cumulative drought loss rate of 49.00–54.00%. Overall, the drought risk index decreased from west to east and from north to south under different return periods. This quantitative evaluation of the drought hazard intensity index provides a reference for agricultural drought risk evaluation.

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Section: Introductionmentioning

confidence: 99%

Winter Wheat Drought Risk Assessment by Coupling Improved Moisture-Sensitive Crop Model and Gridded Vulnerability Curve

Yang

et al. 2023

Remote Sensing

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Evaluation of soybean (Glycine max L.) adaptation to northern European regions under different agro-climatic scenarios

Boulch¹,

Elmerich²,

Djemel³

et al. 2021

In Silico Plants

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Soybean is a candidate crop to increase the independency of Europe in leguminous protein crops. However, its adaptation to northern European regions is not yet well defined due to lack of long-term references. Herein, we simulated soybean yield potential in northern France and identified the main yield limiting factors under rainfed vs irrigated conditions. Two cultivars representing maturity groups 000 and 00 were planted within three different trials. Leaf area index, shoot and pod biomass, main phenological stages and yield were recorded to evaluate CROPGRO-soybean model predictability. Adjustment of genetic coefficients was performed prior to simulate yield on 21-years weather database (1999-2018) at Beauvais (France, N 49.46°, E 2.07°) and Estrées-Mons (France, N 49.88°, E 3.01°) under different water regimes and planting dates. Predictions showed that adding irrigation at grain filling period would increase yield potential to the level of non-water limited scenarios. Although simulated yield variability is reduced with irrigation, the remaining variability suggests that water is not the only yield-limiting factor. A tentative explanation is proposed by deriving environmental covariates from the model. The analysis confirmed the importance of precipitation amount (optimum around 200 mm) and duration (optimum around 60 days) of the flowering to physiological maturity period under rainfed conditions. Under irrigated conditions, increasing evapotranspiration and average minimum temperature affected simulated yield positively while increasing the number of days below 10°C had a negative impact. These results give insights for soybean crop management and bring indications to breeders for adapting the existing genetic material to northern Europe.

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Simulation and production of soybean plant growth (Glycine max (L) Merrill) using the DSSAT model with different scenarios of water supply and compost

Cited by 2 publications

References 4 publications

Winter Wheat Drought Risk Assessment by Coupling Improved Moisture-Sensitive Crop Model and Gridded Vulnerability Curve

Winter Wheat Drought Risk Assessment by Coupling Improved Moisture-Sensitive Crop Model and Gridded Vulnerability Curve

Evaluation of soybean (Glycine max L.) adaptation to northern European regions under different agro-climatic scenarios

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