Na Ning1, Yan-jun Yang2, Jian-ping Hong1, Xiang-yang Yuan3*, Xi-e Song3, Hong-fu Wang3, and Ping-yi Guo3
Quantifying the effects of environmental conditions on grain quality of foxtail millet (Setaria italica [L.] P. Beauv.) is critical for large-scale promotion of high-quality foxtail millet according to local conditions. We analyzed quantitative correlation between grain quality of foxtail millet and environmental factors during the growing season (May-September) using multivariate statistical analysis under different ecological conditions at five representative locations across Shanxi Province, China. Based on the results of principal component analysis, the first principal component, which explained 58.22% of total variance in grain quality, was selected to represent the comprehensive quality of foxtail millet. The results of gray relational analysis showed that the difference in grain quality across different locations was mainly affected by altitude (grey relational grade [GRG] = 0.8137), followed by precipitation (GRG = 0.7744), diurnal temperature range (GRG = 0.6816), latitude (GRG = 0.5417), sunshine hours (GRG = 0.5052), and ≥ 20 °C accumulated temperature (GRG = 0.4517). The precipitation of July and diurnal temperature range of July-September had the greatest effect on grain quality of foxtail millet. Stepwise regression and path analyses revealed that altitude, precipitation, and ≥ 20 °C accumulated temperature were the major environmental factors affecting grain quality of foxtail millet, which determined 99% of total variance in grain quality. Altitude and precipitation exhibited a significant positive effect, while ≥ 20 °C accumulated temperature showed a significant negative effect. The regression equation proposed in this study (P = 0.0048, R2 = 0.99) can be used to predict and forecast grain quality of foxtail millet.
Key words: Environmental factors, foxtail millet grain quality, gray relational analysis, path analysis, principal component analysis, stepwise regression.
1Shanxi Agricultural University, College of Resources and Environment, Taigu 030801, China.
2Jinzhong University, College of Biology and Technology, Yuci 030600, China.
3Shanxi Agricultural University, College of Agriculture, Taigu 030801, China. *Corresponding author (firstname.lastname@example.org).