Simulation of Maize Biomass and Yield in An Giang, Vietnam, under Climate Variabilities

Authors

  • Le Huu Phuoc Doctoral Program of Agriculture Science, Faculty of Agriculture, Andalas University, Indonesia
  • Irfan Suliansyah Faculty of Agriculture, Andalas University, Indonesia
  • Feri Arlius Faculty of Agricultural Technology, Andalas University, Indonesia
  • Irawati Chaniago Faculty of Agriculture, Andalas University, Indonesia
  • Nguyen Thi Thanh Xuan School of Agriculture and Aquacultre, Tra Vinh University, Vietnam
  • Vo Thi Huong Duong Faculty of Agriculture and Natural Resources, An Giang University, An Giang, Vietnam
  • Nguyen Phu Dung Vietnam National University, Ho Chi Minh City, Vietnam
  • Pham Van Quang Faculty of Agriculture and Natural Resources, An Giang University, An Giang, Vietnam

DOI:

https://doi.org/10.48048/tis.2024.7490

Keywords:

Climate variabilities, Elevated CO2, High temperature effect, Maize, Simulation biomass, Simulation yield

Abstract

In this study, the SIMPLECrop model was applied to simulate maize biomass and yield in 2 crop seasons, Autumn - Winter 2020 (AW) and Winter - Spring 2020 - 2021 (WS), in Cho Moi district, An Giang province, Vietnam (10°23'47''N, 105°27'41''E). The research aimed to analyze the effects of climate variabilities, particularly increased temperature, on maize growth and yield.

          The growth period for the Winter - Spring 2020 - 2021 season was 67 days, which was 1 day longer than the AW season (Autumn - Winter 2020). Four cultivar parameters, namely Tsum, HI, I50A, and I50B, were employed for the calibration process to fine-tune the model. Sensitivity analysis using Morris and FAST methods revealed that RUE and Tbase had the highest sensitivity and significant impact on the SIMPLECrop model. These 2 parameters showed strong interactions and played a crucial role in influencing model outcomes. The evaluation of the model’s performance resulted in RRMSE values ranging from 4.8 to 6.3 % and NSE values between 0.86 and 0.93, indicating good agreement between model predictions and observed data.

          Regarding the impact of temperature increase, a 5 °C temperature rise led to a reduction in stover biomass ranging from 5.2 % (Autumn - Winter 2020) to 19.3 % (Winter - Spring 2020 - 2021) and a decrease in yield by 11.3 % (Autumn - Winter 2020) and 27.0 % (Winter - Spring 2020 - 2021). Simulating an increase in CO2 concentration alone, varying from 50, 100, 150, 200 to 250 ppm, resulted in increased biomass and yield for maize. The most substantial increases were observed at 250 ppm CO2, with approximately 2.5 % higher biomass and 7.7 to 9.1 % greater yield. However, under more severe heat stress (5 °C increase), the positive effects of elevated CO2 were mitigated, resulting in a reduced increase in biomass and yield, approximately 3 - 5 %. These findings highlight the importance of considering temperature and CO2 interactions when assessing crop responses to climate variability.

HIGHLIGHTS

  • The SIMPLECrop model was rigorously validated for maize in An Giang Province, Vietnam. Validation metrics, including RRMSE and NSE, demonstrated good-fit model performance, with RRMSE values ranging from 4.8 to 6.3 % and NSE values between 0.86 and 0.93 for open field conditions.
  • Sensitivity analysis using Morris and FAST methods identified that two parameters, RUE (Radiation Use Efficiency) and Tbase (Base Temperature), consistently exhibited the highest sensitivity within the SIMPLECrop model. These parameters played a pivotal role in influencing model outcomes and understanding maize responses to climate variability.
  • The study examined the combined impact of increased temperature and elevated CO2 on maize. A 5 °C temperature rise led to significant stover biomass reductions, varying from 5.2 % (AW season) to a substantial 19.3 % (WS season), along with yield declines of 11.3 % (AW) and a significant 27.0 % (WS).
  • Elevated CO2, ranging from 50 to 250 ppm, had a positive influence on maize biomass and yield. However, under more intense heat stress (5 °C increase), the favorable CO2 effects diminished. This underscores the necessity of considering temperature and CO2 interactions when analyzing crop responses to climate variability.

GRAPHICAL ABSTRACT

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Author Biographies

Le Huu Phuoc, Doctoral Program of Agriculture Science, Faculty of Agriculture, Andalas University, Indonesia

Doctoral Program of Agriculture Science, Faculty of Agriculture, Andalas University, Indonesia
Faculty of Agriculture, Andalas University, Indonesia
Faculty of Agriculture and Natural Resources, An Giang University, An Giang, Vietnam
Vietnam National University, Ho Chi Minh City, Vietnam

Irfan Suliansyah, Faculty of Agriculture, Andalas University, Indonesia

Faculty of Agriculture, Andalas University, Indonesia

Feri Arlius, Faculty of Agricultural Technology, Andalas University, Indonesia

Faculty of Agricultural Technology, Andalas University, Indonesia

Irawati Chaniago, Faculty of Agriculture, Andalas University, Indonesia

Faculty of Agriculture, Andalas University, Indonesia

Nguyen Thi Thanh Xuan, School of Agriculture and Aquacultre, Tra Vinh University, Vietnam

Faculty of Agriculture and Natural Resources, An Giang University, An Giang, Vietnam
Vietnam National University, Ho Chi Minh City, Vietnam
School of Agriculture and Aquacultre, Tra Vinh University, Vietnam

Vo Thi Huong Duong, Faculty of Agriculture and Natural Resources, An Giang University, An Giang, Vietnam

Faculty of Agriculture and Natural Resources, An Giang University, An Giang, Vietnam
Vietnam National University, Ho Chi Minh City, Vietnam

Nguyen Phu Dung, Vietnam National University, Ho Chi Minh City, Vietnam

Faculty of Agriculture and Natural Resources, An Giang University, An Giang, Vietnam
Vietnam National University, Ho Chi Minh City, Vietnam

Pham Van Quang, Faculty of Agriculture and Natural Resources, An Giang University, An Giang, Vietnam

Faculty of Agriculture and Natural Resources, An Giang University, An Giang, Vietnam
Vietnam National University, Ho Chi Minh City, Vietnam

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Published

2024-01-30

How to Cite

Phuoc, L. H. ., Suliansyah, I. ., Arlius, F. ., Chaniago, I., Xuan, N. T. T. ., Duong, V. T. H. ., Dung, N. P. ., & Quang, P. V. (2024). Simulation of Maize Biomass and Yield in An Giang, Vietnam, under Climate Variabilities. Trends in Sciences, 21(3), 7490. https://doi.org/10.48048/tis.2024.7490

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