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叶菜型甘薯资源耐寒性评价体系研究 被引量:1

Evaluation system of cold tolerance of leaf⁃vegetable sweet potato resources
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摘要 【目的】比较不同叶菜型甘薯品种的耐寒性,找出能科学评价品种耐寒性的指标,建立可靠的耐寒性数学评价模型,筛选耐寒性强的叶菜型甘薯品种,为耐寒资源鉴定与筛选提供理论依据和参考。【方法】以13个叶菜型甘薯品种为材料,设置25℃为对照温度,10℃为低温胁迫温度,研究叶片中过氧化物酶(POD)、抗坏血酸过氧化物酶(APX)、过氧化氢酶(CAT)、超氧化物歧化酶(SOD)、可溶性蛋白(SP)、可溶性糖(SS)、组织含水率(TMC)、叶绿素(Chl)、类胡萝卜素(Car)及叶绿素a/b(Chl a/b)10个指标对低温胁迫的响应。以各单项指标的耐寒系数为衡量依据,运用主成分分析、聚类分析和逐步回归等方法进行耐寒性综合评价。【结果】通过主成分分析将10个单项生理指标转换为4个相互独立的综合指标;13个叶菜型甘薯品种按照耐寒性强弱划分为4类,即不耐寒型、轻度耐寒型、中度耐寒型、高度耐寒型;建立叶菜型甘薯耐寒性评价数学模型,D=0.283+0.0171X_(1)-0.074X_(3)+0.166X_(4)+0.409X_(5)-0.874X_(7)-0.067X_(8)+0.116X_(9)+0.030X_(10),估计精度大于95%;筛选出8个耐寒性鉴定指标,即POD、CAT、SOD、SP、TMC、Chl、Car及Chl a/b。【结论】低温胁迫条件下,不同叶菜型甘薯品种发生不同程度的生理变化。通过回归方程筛选获得的8个关键指标可用于叶菜型甘薯品种的耐寒性鉴定和预测。结合隶属函数综合评价模型得出,供试13个叶菜型甘薯品种中耐寒性最强的前3名为:福菜薯18、渝菜薯3号、广菜薯6号,可在早春推广种植耐寒能力强的品种,结合现代保温设施,使其提早上市从而抢占市场。 【Objective】The study aimed to compare the cold tolerance of different leaf⁃vegetable sweet potato varieties,find out the index that can scientifically evaluate the cold tolerance of varieties,establish a reliable mathematical evaluation model of cold tolerance,in order to screen out the leaf⁃vegetable sweet potato varieties with strong cold tolerance,and provide theoretical basis and reference for the identification and selection of cold tolerance resources.【Method】13 leaf⁃vegetable sweet potato varieties were used as materials,the temperature was set to 25℃as the control temperature and 10℃as the low temperature stress temperature,which could study peroxidase(POD),ascorbyl perox⁃idase(APX),catalase(CAT),superoxide dismutase(SOD),soluble protein(SP),soluble sugar(SS),tissue moisture content(TMC),chlorophyll(Chl),carotenoid(Car)and chlorophyll a/b(Chl a/b)response to cryogenic stress.The purpose was to use the cold tolerance coefficient of each individual index as the measurement basis,and use principal component analysis,cluster analysis and stepwise regression to carry out comprehensive evaluation of cold tolerance.【Result】By principal component analysis,10 individual physiological in⁃dicators were converted into 4 independent comprehensive indicators.13 leaf⁃vegetable sweet potato varieties were divided into 4 types accord⁃ing to their cold tolerance,namely,cold intolerance type,mild cold tolerance type,moderate cold tolerance type,and high cold tolerance type.Based on stepwise regression analysis,the mathematical evaluation model for cold tolerance of the leaf⁃vegetable sweet potato was estab⁃lished asD=0.283+0.0171X_(1)-0.074X_(3)+0.166X_(4)+0.409X_(5)-0.874X_(7)-0.067X_(8)+0.116X_(9)+0.030X_(10),with an estimation accu⁃racy greater than 95%.Furthermore,eight indexes,including POD,CAT,SOD,SP,TMC,Chl,Car and Chl a/b,were selected for cold tolerance identification in leaf⁃vegetable sweet potato.【Conclusion】Under low temperature stress conditions,different leaf⁃vegetable sweet potato varieties have different physiological changes.The eight key indicators obtained by regression equation screening can be used for the i⁃dentification and prediction of cold tolerance of different leaf⁃vegetable sweet potato varieties.Combined with the comprehensive evaluation model of the membership function,it is concluded that the top 3 varieties with the strongest cold tolerance among the 13 leaf⁃vegetable sweet potato varieties tested:Fucaishu No.18,Yucaishu No.3,and Guangcaishu No.6,which can promote and plant varieties with strong cold tol⁃erance in early spring,combined with modern thermal insulation facilities,so that they can be marketed early and seize the market.
作者 耿亚林 李瑶 潘攀 唐道彬 罗启燕 王季春 GENG Ya-lin;LI Yao;PAN Pan;TANG Dao-bin;LUO Qi-yan;WANG Ji-chun(College of Agronomy and Biotechnology,Southwest University/Key Laboratory of Biology and Genetic Breeding for Tuber and Root Crops in Chongqing,Chongqing 400700,China;Pengshui County Agricultural Technology Extension Center,Pengshui,Chongqing 409600,China)
出处 《西南农业学报》 CSCD 北大核心 2023年第3期532-540,共9页 Southwest China Journal of Agricultural Sciences
基金 重庆市技术创新与应用发展专项面上项目(cstc2021jscx-msxmX0010)。
关键词 叶菜型甘薯 耐寒性 主成分分析 聚类分析 隶属函数法 逐步回归 Leaf⁃vegetable sweet potato Cold tolerance Principal component analysis Cluster analysis Subordinate function value meth⁃od Stepwise regression
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