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Evaluation of Cold Resistance at Seedling Stage for 70 Peanut Genotypes Based on Photosynthetic Fluorescence Characteristics

文献类型： 外文期刊

作者： Ye, Linmei 1 ; Wang, Tao 1 ; Wu, Renye 2 ; Zheng, Conghui 1 ; Zhan, Liuqi 3 ; Chen, Jianhong 3 ; Guo, Shengyao 3 ; Chen, Yongkuai 1 ;

作者机构： 1.Fujian Acad Agr Sci, Inst Digital Agr, Fuzhou 350003, Peoples R China

2.Fujian Agr & Forestry Univ, Fac Agr, Fuzhou 350100, Peoples R China

3.Quanzhou Inst Agr Sci, Quanzhou 362212, Peoples R China

关键词： peanut; low temperature; germplasm resources; seedling stage

期刊名称：AGRONOMY-BASEL （ 影响因子：3.4； 五年影响因子：3.8 ）

ISSN：

年卷期： 2024 年 14 卷 8 期

页码：

收录情况： SCI

摘要： Low-temperature stress is one of the factors affecting the growth and development of peanuts. Currently, biochemical detection technologies for crop freeze damage are well established. In the context of rapid development in optical sensing technology and smart agriculture, non-destructive crop freeze damage detection based on such technologies has gained increasing attention. The accurate detection, early warning, and targeted control of crop cold damage are particularly important. In this study, 70 peanut germplasm resources were collected and used for the research objectives. Indoor low-temperature seedling identification was conducted at 25 degrees C (the control group) and 5 degrees C (low-temperature stress group) for 7 days. Photosynthetic fluorescence values in leaves, as well as 13 indicators (Fo, Fm, Fv, Fv/Fm, Fv'/Fm', Phi PSII, NPQ, qP, Rfd, Pn, Gs, Ci, and Tr), were analyzed for their responses to low-temperature stress. The results showed that under low-temperature stress, the Pn and Ci of peanut seedlings exhibited an ascending trend, while Tr and other indicators showed a decreasing trend compared to the control group. Based on the relative coefficients of resistance to low temperature for each individual indicator, a comprehensive non-destructive evaluation of cold resistance was conducted using methods such as principal component analysis, cluster analysis, and stepwise regression. Through principal component analysis, the 13 individual physiological indicators were transformed into 3 comprehensive indicators. The 70 peanut varieties were divided into 4 categories based on their resistance to low temperature: sensitive materials, moderately sensitive materials, moderately cold-tolerant materials, and cold-tolerant materials. Additionally, a mathematical model for evaluating cold resistance in peanuts was established.

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