机构地区:[1]宁夏大学农学院,宁夏银川750021 [2]宁夏大学西北退化生态系统恢复与重建教育部重点实验室,宁夏银川750021 [3]宁夏大学西北土地退化与生态恢复省部共建国家重点实验室培育基地,宁夏银川750021 [4]宁夏大学生命科学学院,宁夏银川750021
出 处:《干旱地区农业研究》2020年第1期280-289,共10页Agricultural Research in the Arid Areas
基 金:宁夏回族自治区牧草育种专项(2014NYYZ040101);国家自然科学基金(31860135);宁夏高等学校一流学科建设(生态学)资助项目(NXYLXK2017B06);宁夏回族自治区教育厅2018年高等学校科学研究项目(NGY2018024)。
摘 要:设置正常灌水处理(T1)、重度干旱处理(T2)2种处理,测定株高、穗重、单株粒重、千粒重和产量(单位面积产量)等性状,运用相关性分析、主成分分析、抗旱系数(DRC)、综合抗旱系数(CDRC)、加权抗旱系数(WDC)、隶属函数值(D)和聚类分析等方法,对成熟期不同甜高粱品系的抗旱性进行鉴定及指标筛选。结果表明:干旱胁迫对各性状均有显著影响(P<0.05);抗旱系数频次分析表明,各性状抗旱性敏感程度由大到小顺序为穗粒数>分枝数>株高>茎粗>千粒重>穗茎粗>穗重>穗长>单株粒重>产量;相关性分析表明:株高与穗重呈显著负相关(P<0.05),产量与穗粒数、穗重、单株粒重、千粒重呈极显著正相关(P<0.01),穗粒数与穗重、单株粒重呈极显著正相关(P<0.01),单株粒重与千粒重呈极显著正相关(P<0.01);通过主成分分析,将10个性状转化成5项新的互相独立综合指标,可代替88.087%原始所有性状抗旱信息;灰色关联度分析表明,各性状DRC与D的密切程度大小顺序为单株粒重>千粒重>穗粒数>产量>穗茎粗>分枝数>穗重>穗长>株高>茎粗。对D值进行聚类分析,将22个不同品系甜高粱分为5个抗旱级别,其中Ⅰ级3份、Ⅱ级7份、Ⅲ级6份、Ⅳ级4份、Ⅴ级2份。对聚类分析结果的抗旱系数进行抗旱性等级统计分析表明,除株高、茎粗和穗长以外,千粒重、单株粒重、穗重、穗粒数、D值、分枝数、穗茎粗、CDRC值和WDC值随着抗旱级别的升高而增加。逐步线性回归方程表明,千粒重、单株粒重、穗粒数、穗茎粗与D值密切相关。综上所述,干旱胁迫对甜高粱成熟期各性状均会产生显著影响,千粒重、单株粒重、穗粒数和穗茎粗可作为甜高粱成熟期直观、准确和简单的抗旱鉴定评价指标,筛选出成熟期抗旱性强的甜高粱品系为F417、F438、F6137。In order to screen out the drought-tolerant sweet sorghum cultivars(lines) and identification indicators, an experiment was conducted using 22 sweet sorghum cultivars(lines), normal irrigation(T1), severe drought(T2),plant height, spike weight, spike weight per plant, 1000-grain weight, and yield(yield per unit area) were measured. By using correlation analysis, principal component analysis, drought resistance coefficient(DRC),comprehensive drought resistance coefficient(CDRC value), weighted drought resistance coefficient(WDC value), membership function value(D value), cluster analysis, and other analytical methods, we did identification and index screening of drought resistance of different sweet sorghum varieties at maturity. The results showed that drought effected indicators remarkably(P>0.05). The frequency analysis of drought resistance coefficient showed that the drought resistance of each index was in the order of the grain number per spike>number of branches>plant height>culm diameter>1000-grain weight>spike culm diameter>spike weight>spike length>spike weight>yield. Correlation analysis showed that plant height was significantly negatively correlated with ear weight(P<0.05);yield was extremely significantly positively correlated with ear grain number, ear weight, kernel weight per plant, and thousand kernel weight(P<0.01);Ear weight and grain weight per plant were extremely significantly positively correlated(P<0.01);ear weight was extremely significantly positively correlated with grain number per ear(P<0.01);grain weight per plant was extremely significantly positively correlated with thousand-grain weight(P<0.01). By using principal component analysis, those indicators were transformed into 5 new independent comprehensive indicators, which could replace 88.087% information of all the original indicators. The grey correlation analysis showed that the correlation level of indicators’ DRC and D values ranked as spike weight per plant>1000-grain weight>grain number per spike>yield>spike culm diameter>
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