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  

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

作　　者：王洋洋 刘万代[1,2] 贺利 任德超 段剑钊 胡新 郭天财 王永华[1,2] 冯伟 WANG YangYang;LIU WanDai;HE Li;REN DeChao;DUAN JianZhao;HU Xin;GUO TianCai;WANG YongHua;FENG Wei(College of Agronomy,Henan Agriculture University/Key Laboratory of Regulating and Controlling Crop Growth and Development,Ministry of Education,Zhengzhou 450046;National Engineering Research Center for Wheat,Zhengzhou 450046;Wheat Research Institute,Shangqiu Academy of Agriculture and Forestry Sciences,Shangqiu 476000,Henan)

机构地区：[1]河南农业大学农学院/作物生长发育调控教育部重点实验室,郑州450046 [2]国家小麦工程技术研究中心,郑州450046 [3]商丘市农林科学院小麦研究所,河南商丘476000

出　　处：《中国农业科学》2022年第7期1301-1318,共18页Scientia Agricultura Sinica

基　　金：“十三五”国家重点研发计划“粮食丰产增效科技创新”(2017YFD0300204)。

摘　　要：【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行处理,设置的温度为-2℃(T1)、-4℃(T2)、-6℃(T3)、-8℃(T4)和-10℃(T5)以及对照(CK为当天大田温度),低温胁迫后的第2天测定小麦生理生化指标,将标准化后的各个生理指标进行主成分、隶属函数、聚类分析和逐步回归等多元统计分析。【结果】不同品种、水分、温度下的各单项生理生化指标之间大多存在着显著相关性,通过主成分分析将19个生理生化指标转化为6个相互独立的综合指标,其贡献度分别为55.972%、11.93%、7.168%、5.075%、4.236%和3.079%,代表了全部原始数据的87.459%的信息量,并根据隶属函数算法求出各处理的冻害程度综合评价值(F值)。以F值作为因变量,通过逐步回归分析筛选出7个关键指标,分别为叶绿素a、叶片含水量、脯氨酸、F;/F;、可溶性蛋白、MDA和SOD,并确立了定量估算F值的数学模型。同时,将F预测值与产量损失率进行相关性分析,线性方程决定系数R;=0.898,表明该F预测模型能够很好地评价冻害程度。进一步对F预测值进行聚类分析,可将不同冻害处理划分为5类:未受冻(D-CK、W-CK)、轻度受冻(D-T1、W-T1)、中度受冻(D-T2、W-T2、W-T3)、重度受冻(D-T3、W-T4)以及特重受冻(D-T4、W-T5、D-T5),其产量损失率分别为0、0-10%、10%-30%、30%-50%及50%以上,相同的温度和水分条件下弱春性品种的冻害程度重于半冬性品种,相同的品种和温度条件下不灌水处理的冻害程度重于灌水处理。具体考察所筛选的生理评价指标,随着低温胁迫的加重,叶绿素【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,19physiological 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;/F;,soluble protein,MDA and SOD,and the mathematical model for quantitative estimation of F value was established.At the same

关 键 词：冬小麦 晚霜冻害 灌水 综合评价 评估模型 

分 类 号：S512.1[农业科学—作物学] S426