基于多元统计分析的小麦低温冻害评价及水分效应差异研究

[目的]明确不同水分条件下低温胁迫引起的小麦冻害程度,筛选冻害鉴定指标并建立冻害定量评估模型,为小麦生产科学防控低温冻害提供理论支撑.[方法]以弱春性品种偃展4110、兰考198和半冬性品种郑麦366、丰德存麦21为试验材料,在模拟冻害发生前一周进行灌水(W)和不灌水(D)处理,于雌雄蕊分化期将盆栽小麦移到低温模拟室进...

Evaluation of Low Temperature Freezing Injury in Winter Wheat and Difference Analysis of Water Effect Based on Multivariate Statistical Analysis

【Objective】In order to clarify the freezing injury degree of wheat under different water conditions caused by low temperature stress, the identification indexes and quantitative evaluation model of freezing injury were screened and established, which provided the theoretical support for prevention and control of freezing injury in wheat production. 【Method】 Weak spring cultivars of Yanzhan 4110 and Lankao 198, semi-winter cultivars of Zhengmai 366 and Fengdecunmai 21 were used as experimental materials. They were treated with irrigation (W) or no irrigation (D) one week before the freezing injury, respectively. Pot experiments were moved to a low-temperature simulation room during the female and male ear differentiation stages. The temperatures were set as -2℃ (T1), -4℃ (T2), -6℃ (T3), -8℃ (T4), -10℃ (T5) and control (CK is the field temperature on the same day). Physiological and biochemical indexes of wheat were measured on the second day after low temperature stress. The standardized physiological indexes were analyzed by multivariate statistical analysis, such as principal component, membership function, cluster analysis and step wise regression. 【Result】 There were significant correlations among the individual physiological and biochemical indexes under different cultivars, water contents and temperatures. Through principal component analysis, 19 physiological and biochemical indexes were transformed into 6 mutually independent comprehensive indexes, whose contribution degrees were 55.972%, 11.93%, 7.168%, 5.075%, 4.236% and 3.079%, respectively, representing 87.459% information of all original data. According to the membership function algorithm, the comprehensive evaluation value ( F value ) of freezing injury degree of each treatment was calculated. Take F value as the dependent variable, the seven key indexes were selected by stepwise regression analysis, namely chlorophyll a, leaf water content, proline, F_v/F_m, soluble protein, MDA and SOD, and the mathematical model for quantitative estimation of F value was established. At the same time, the correlation between F prediction value and yield loss rate was analyzed, and the linear equation determination coefficient R ²= 0.898, indicating that the F prediction model could well evaluate the freezing injury degree. F predicted value could be divided into five categories by further cluster analysis: non-freezing (D-CK, W-CK), mild frozen (D-T1, W-T1), moderate frozen (D-T2, W-T2, W-T3), severe frozen (D-T3, W-T4), and extremely severe frozen (D-T4, W-T5, D-T5). Corresponding yield loss rate were 0, 0-10%, 10%-30%, 30%-50% and more than 50%, respectively. Under the same temperature and moisture conditions, the freezing injury degree of weak spring varieties was heavier than that of semi-winter varieties, and the freezing injury degree of no irrigation treatment was heavier than that of irrigation treatment under the same varieties and temperature conditions. With the increasing of low temperature stress, chlorophyll a, leaf water content and F_v/F_m showed a decreasing trend, the activities of proline, soluble protein and SOD increased first and then decreased, while MDA showed an opposite trend. According to the clustering results, under the same temperature and water conditions, the freezing injury degree of weak spring cultivars was more serious than that of semi-winter cultivars. Under the same variety and temperature conditions, the freezing damage degree without irrigation was worse than that under irrigation. 【Conclusion】Therefore, the semi-winter varieties should be selected in the areas prone to late frost in production, and the irrigation management should be strengthened before a cold wave according to the weather forecast. When freezing injury happened, the injury degree could be accurately assessed in timely through the evaluation index and quantitative model, which was conducive to prevention and control of late frost injury, and provides technology basis for production recovery and decision management after freezing disaster.