摘要
【目的】探究不同品种间燕麦脂肪酶活性的差异机制,分析影响燕麦脂肪酶活性的内在因素,为筛选低脂肪酶优质品种提供理论依据。【方法】选取3个燕麦主产地的6个主栽品种为研究对象,测定其脂肪酶活性、营养指标、物理性状及农艺指标。通过相关性分析筛选与燕麦脂肪酶密切相关的指标,通过聚类分析将多个燕麦样品按脂肪酶活性分类,通过主成分分析将具有相关性的数据组转化为便于统计分析的综合变量,考察燕麦品种间的脂肪酶活性差异;结合灰色关联度与多元逐步回归的分析方法,得出各品种与理想品种的关联度,并以脂肪酶活性为因变量,拟合得出脂肪酶活性预测模型,筛选低脂肪酶活性优质品种。【结果】脂肪酶活性与粗脂肪含量呈显著正相关(r=0.32,P<0.05),且脂肪含量、不饱和脂肪酸含量、脂肪酶活性、酸值4个指标的变化趋势一致;脂肪酶活性与粗蛋白含量呈极显著正相关(r=0.46,P<0.01),且脂肪酶活性越高的品种,其位于31—43 kD的电泳条带所占百分比越大;脂肪酶活性与籽粒容重呈极显著负相关(r=-0.71,P<0.01);脂肪酶活性与生育期呈极显著正相关(r=0.37,P<0.01);经灰色关联度分析知白燕18号、迪燕1号与理想品种X_(0)关联度较高,分别为0.951和0.883,属于低脂肪酶且高营养品种;经多元逐步回归,仅保留影响显著的容重与蛋白质含量作为自变量,建立脂肪酶活性预测模型Y(脂肪酶活性)=720.274-2.255×容重(g·L^(-1))+75.761×蛋白质含量(%),P<0.01,R^(2)为0.658。【结论】不同品种间燕麦脂肪酶活性差异明显,脂肪含量、蛋白质含量、容重、生育期是燕麦脂肪酶活性的主要影响因素,灰色关联法和逐步回归分析相结合建立的优质品种筛选与脂肪酶活性预测模型,可以有效地对燕麦品种进行综合评价,并优选出低脂肪酶活性品种。
【Objective】This study explored the differences and causes of oat lipase activity of different varieties.Providing a theoretical basis for screening varieties with low lipase activity and achieving stable enzyme inactivation effect of oat products.【Method】Six main varieties of three main oat planting regions were selected for the study,and their lipase activity,nutritional indexes,physical traits,and agronomic indexes were measured.To answer the differences in lipase activity of oat varieties,the indicators significantly related to oat lipase were screened by correlation analysis.Through cluster analysis,classified multiple oat samples by lipase activity.Transform data having correlations into composite variables for statistical analysis by principal component analysis.To derive a predictive model for lipase activity,an analytical method combining gray correlation and multiple stepwise regression was used.The indicators correlating with lipase activity were used as independent variables,and the lipase activity was used as dependent variables for quantitative model fitting.【Result】Lipase activity was significantly positively correlated with crude fat content(r=0.32,P<0.05),and the various trends of fat content,unsaturated fatty acid content,lipase activity,and acid value were consistent.Lipase activity was significantly positively correlated with crude protein content(r=0.46,P<0.01),and the higher lipase activity was,the higher percentage of electrophoretic bands located in 31-43 kD were.It was significantly negatively correlated with grain test weight(r=-0.71,P<0.01)and positively associated with growth period(r=0.37,P<0.01).Baiyan 18 and Diyan 1 had low lipase activity and high nutrition varieties according to grey relational analysis,and the relevance value with ideal variety X_(0) were 0.951 and 0.883,respectively.Stepwise regression analysis only retained the test weight and protein content as independent variables.The prediction model of lipase activity was established as Y=720.274-2.255×test weight(g·L^(-1))+75.761×protein content(%),P<0.01,R^(2)=0.658.【Conclusion】The varieties had significant effects on oat lipase activity.Protein content,fat content,test weight,and growth period were the main influencing factors of oat lipase activity.Grey relational analysis combined with stepwise regression analysis could be used to comprehensively evaluate oat varieties effectively and quickly select varieties with low lipase activity.
作者
相玉婷
王晓龙
胡新中
任长忠
郭来春
李璐
XIANG YuTing;WANG XiaoLong;HU XinZhong;REN ChangZhong;GUO LaiChun;LI Lu(College of Food Engineering and Nutritional Science,Shaanxi Normal University,Xi’an 710119;Baicheng Academy of Agricultural Sciences/China Oat and Buckwheat Research Center,Baicheng 137000,Jilin;Guilin Seamild Foods Co.,Ltd.,Guilin 541004,Guangxi)
出处
《中国农业科学》
CAS
CSCD
北大核心
2022年第21期4104-4117,共14页
Scientia Agricultura Sinica
基金
国家燕麦荞麦产业技术体系(CARS-07-E1)
陕西省创新团队(2020TD-049)
陕西省谷物科学国际联合研究中心(2019GHJD-15)。
关键词
燕麦品种
种植区域
脂肪酶活性
相关性分析
预测模型
oat varieties
planting area
lipase activity
correlation analysis
prediction model
