4.7 Article

Impacts of mean climate and extreme climate indices on soybean yield and yield components in Northeast China

Journal

SCIENCE OF THE TOTAL ENVIRONMENT
Volume 838, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.scitotenv.2022.156284

Keywords

Mean climate; Extreme climate indices; Soybean yield; Yield components; Northeast China

Funding

  1. National Natural Science Foundation of China [31471408]
  2. National Key Research and Development Program of China [2019YFA0607402]

Ask authors/readers for more resources

This study assessed the impacts of mean climate and extreme climate indices on soybean yield in Northeast China, using weather data from 61 counties. Results showed that changes in climate indices had significant effects on soybean yield, particularly on the number of pods and seed weight.
Soybean is an important oil crop in China, and the national focus of soybean production is in Northeast China. In order to achieve high-stable yield, it is crucial to acknowledge the impacts of mean climate and extreme climate indices on soybean yield and yield components. In this study, based on the weather data from 61 counties from 1981 to 2017 in Northeast China, we assessed the impacts ofmean climate and extreme climate indices on soybean observed yield and simulated yield. Mean climate include effective growing degree days (GDD(10)), precipitation (Pre), and solar radiation (SR); extreme climate indices include the number of cool days during seed-filling period (C-15), the number of cool days during 15 days before anthesis (C-17), the number of hot days (H-30), maximum amount of 5 Day accumulated precipitation (P-5), and consecutive dry days (CDD)). We used the DSSAT-CROPGRO-Soybean model to identify the main yield components for soybean. The results showed that observed soybean yield reduced by 3.57% due to the collective changes in the eight study climate indices. Increases in GDD(10), decreases in Pre, and decreases in SR caused a 3.96%, -3.89%, and - 0.48% change in soybean yield, respectively. Decreases in C-15 and C-17 led to a 5.36% increase in soybean yield; increases in H-30, P-5, and CDD caused a 5.75%, 0.30%, and 1.14% reduction in soybean yield, respectively. By comparing the response of observed and simulated soybean yield to climate indices (excluding P-5) in the DSSAT-CROPGRO-Soybean model, we identified the key yield components for soybean as the number of pods and seed weight. The negative impacts on the number of pods and seed weight were mainly attributed to changes in Pre and H-30 from anthesis to podding and during seed-filling period. Our results could be used to assist the local soybean community adapt to climate change.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available