摘要
本文采用气相色谱技术获取48个品种燕麦粉、40个品种小麦面粉及105个运用平衡不完全随机区组的试验方法设计得到的燕麦小麦复配粉定量样本的脂肪酸组成信息,分析其棕榈酸、油酸和亚油酸的含量,油酸/亚油酸、棕榈酸/油酸、棕榈酸/亚油酸的比值及相关性;根据燕麦和小麦中脂肪酸组成的相似性确定用于面粉中燕麦粉添加量的定量分析指标,根据脂肪酸含量间的差异性体现不同梯度的燕麦粉添加复配粉中脂肪酸含量的变化趋势,在此基础上建立判别分析三维图及Fisher线性判别函数,直观地呈现出复配粉中各脂肪酸的分布特点,进而对面粉中燕麦粉的添加量进行定量判别。本研究在分析燕麦和小麦中脂肪酸异同点的基础上为燕麦产品安全监测及品质控制提供了一个适用广泛、灵敏度高、可行性强的重要借鉴方法。
The fatty acid composition of 48 varieties of oat flour, 40 varieties of wheat flour, and 105 oat-wheat composite flours obtained using a balanced incomplete randomized block design were acquired using the gas chromatography technique. The contents of palm acid, oleic acid, and linoleic acid, and the ratios and correlations of oleic acid/linoleic acid, palm acid/oleic acid, and palm acid/linoleic acid of the samples were analyzed. The similarity of fatty acid composition in oat and wheat flours was used to determine the indexes for quantitative analysis of the amount of oat flour added to wheat flour, and the difference in the fatty acid content was used to reflect the variation trend of fatty acid content in composite flour with different ratios of added oat flour. Based on these results, a three-dimensional map for discriminant analysis and Fisher linear discriminant functions were established to clearly present the distribution features of fatty acids in the composite flour, and then the amount of oat flour added to wheat flour was quantitatively determined. Based on the analysis of the similarities and differences in the fatty acid composition and content of oat and wheat flour, this study provides an important reference method with a wide application, high sensitivity, and strong feasibility for the safety surveillance and quality control of oat products.
作者
王超群
张晖
钱海峰
王立
齐希光
WANG Chao-qun ZHANG Hui QIAN Hai-feng WANG Li QI Xi-guang(School of Food Science and Technology, Jiangnan University, Wuxi 214122, China)
出处
《现代食品科技》
EI
CAS
北大核心
2016年第11期316-322,315,共8页
Modern Food Science and Technology
基金
国家"十二五"科技支撑计划项目(2012BAD37B08)
关键词
气相色谱
燕麦粉
脂肪酸
判别分析
定量检测
gas chromatography
oat flour
fatty acids
discriminant analysis
quantitative detection