Influence Mechanisms of Dynamic Changes in Temperature, Precipitation, Sunshine Duration and Active Accumulated Temperature on Soybean Resources: A Case Study of Hulunbuir, China, from 1951 to 2019

Xuanwei Ning, Peipei Dong, Chengliang Wu, Yongliang Wang and Yang Zhang ()
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Xuanwei Ning: School of Economics and Management, Beijing Forestry University, Beijing 100083, China
Peipei Dong: School of Economics and Management, Beijing Forestry University, Beijing 100083, China
Chengliang Wu: School of Economics and Management, Beijing Forestry University, Beijing 100083, China
Yongliang Wang: School of Mechanics and Civil Engineering, China University of Mining and Technology, Beijing 100083, China
Yang Zhang: School of Economics and Management, Beijing Forestry University, Beijing 100083, China

Energies, 2022, vol. 15, issue 22, 1-19

Abstract: As a raw material for clean energy supply for the new generation, the soybean is conducive to the realization of global energy transition and sustainable development in the context of “carbon neutrality”. However, global warming has been affecting soybean yields in recent years. How to clarify the correlation between meteorological factors and soybean yields, so as to ensure the security of soybean growth and development and the stability of renewable energy development, is a key concern of the government and academia. Based on the data of temperature, precipitation, sunshine duration and active accumulated temperature during the soybean growing season in Hulunbuir, Inner Mongolia Autonomous Region from 1951 to 2019, and soybean yield data of the city from 1985 to 2019, this paper adopted statistical methods such as the Trend Analysis Method, the Rescaled Range Analysis Method and so on to analyze the trends of yield changes, characteristics of abrupt changes and periodic patterns of climate factors and soybean yields in Hulunbuir. A Pearson Correlation Analysis and a Grey Relation Analysis were used to explore the correlation between climatic factors and soybean yields, followed by a comprehensive impact model of the combined effect of temperature and precipitation on soybean yields established by the Method of Integral Regression. The results showed that temperature and active accumulated temperature are the dominant factors affecting soybean yields in Hulunbuir, while the decrease in precipitation is unfavorable to the improvement of soybean yields. Meanwhile, temperature and precipitation have different effects on the growth and development of the soybean at different stages. The conclusion of this paper is of great practical significance for Hulunbuir to promote the sustainable development of clean energy.

Keywords: clean energy; sustainable development; climate change; soybean yield (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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