Applying the SIMPLE Crop Model to Assess Soybean (Glicine max. (L.) Merr.) Biomass and Yield in Tropical Climate Variation
2023
Quang V. Pham | Tanh T. N. Nguyen | Tuyen T. X. Vo | Phuoc H. Le | Xuan T. T. Nguyen | Nha V. Duong | Ca T. S. Le
Soybean Glicine max. (L.) Merr. is one of the most major food crops. In some areas, its responses to different climates have not been well studied, particularly in tropical countries where other crops are more dominant. Accordingly, we adopted the SIMPLE crop model to investigate the responses of soybeans to the climate. We conducted two experiments on crop growth in the Summer&ndash:Autumn season of 2020, and Winter&ndash:Spring 2021 in the Hoa Binh Commune, in the Mekong Delta, Vietnam, which is an area that is vulnerable to climate change impacts, to obtain data for our model input and assessment. The assessment was concerned with the effects of climate variables (temperature and CO2) on soybean biomass and yield. The results indicated that the SIMPLE model performed well in simulating soybean yields, with an RRMSE of 9&ndash:10% overall. The drought stress results showed a negative impact on the growth and development of soybeans, although drought stress due to less rainfall seemed more serious in Spring&ndash:Winter 2021 than in Summer&ndash:Autumn 2020. This study figured out the trend that higher temperatures can shorten biomass development and lead to yield reduction. In addition, soybeans grown under high CO2 concentrations of 600 ppm gave a higher biomass and a greater yield than in the case with 350 ppm. In conclusion, climate variance can affect the soybean yield, which can be well investigated using the SIMPLE model.
Mostrar más [+] Menos [-]Palabras clave de AGROVOC
Información bibliográfica
Este registro bibliográfico ha sido proporcionado por Multidisciplinary Digital Publishing Institute