摘要
选取中国小麦主产区山西、安徽和河南的5个不同品种小麦,通过相关性分析和多元线性回归分析研究小麦品质与小麦粉粉质和鲜湿面品质之间的关系。结果表明:鲜湿面品质与小麦直链淀粉、灰分含量呈极显著负相关(P<0.01),与小麦支链淀粉、蛋白质、湿面筋含量呈极显著正相关(P<0.01),与小麦脂肪含量呈显著负相关(P<0.05);鲜湿面品质与小麦粉稳定时间、评价值呈极显著正相关(P<0.01),与小麦粉弱化度、公差指数呈极显著负相关(P<0.01),与小麦粉形成时间、带宽呈显著正相关(P<0.05),与小麦粉吸水率呈显著负相关(P<0.05)。通过多元线性回归分析得到小麦品质与鲜湿面感官评价总分和质构硬度之间的多元线性回归模型,模型决定系数分别为0.983,0.993;模型均为极显著(P<0.001),验证实验得到感官总分实际值为71分,模型预测值为70.3分;质构硬度实际值为5.938kg,模型预测值为6.050kg。模型可较好地通过小麦品质预测其制得的鲜湿面品质。
In this study, five different varieties of Chinese wheats： ＂Jimai 22＂, ＂Yanmong 19＂, ＂Yannong 5158＂, ＂Aikang 58＂, ＂＇Lunxuan 988＂ from the main producing area in China： Shanxi, An hui and Henan were selected. The main physical and chemical characters, such as the content of protein, ash, starch, et al, as well as the farinograph property of flour milled by those five different varieties of wheats, were described, and the sensory evaluation and textural properties （TPA） of fresh noodle made from those flour were determined. The correlation between wheat quality and farinograph prop erty and quality of fresh noodles were all analyzed. The result showed that the amylose and ash content of wbeat had extremely significant negative correlation （P〈0.01） with the sensory evaluation score of fresh noodles, while, had extremely significant positive correlation （P〈0.01） with the TPA parameters： hardness, gumminess and chewiness; the contents of amylopectin, protein, ash and wet gluten had extremely significant positive correlation with the sensory evalu ation score of fresh noodles, while had extremely significant negative correlation （P〈0.01） with the TPA parameters： hardness, gumminess and chewiness. However, the content of fat had significant neg alive correlation （P〈0.05） with the quality of fresh noodles. As for the correlation between wheat flour farinograph property and quality of fresh noodle made from those flour, we found that the stability and quality number of wheat flour had extremely significant positive correlation （P〈0.01） with quality of fresh noodle; the softening and MTI of wheat flour had extremely significant negative correlation （P〈0.01） with quality of fresh noodle; the development time and bandwidth at peak of wheat flour had significant positive correlation （P〈0.05） with the quality of fresh noodles; the water absorption of wheat flour had significant negative correlation （P〈0.05） with the quality of fresh noodles. Then, the multiple linear regression model between the quality characters of wheat and the sensory evaluation score of fresh noodles were along with the TPA parameter： hardness was established by multiple linear regression analysis. The value of R of those two models were 0.983 and 0.993, respectively; The signifl cance of those two models were all extremely significant （P〈0.001）. The verify experiment showed that the actual value of the sensory evaluation score of fresh noodles was 71 with the predicted value from model was 70.3; The actual value of TPA hardness was 5.938 kg with the predicted value from model of 6.050 kg. The model can predict the quality of fresh noodles by wheat quality.
作者
邓航
周文化
李立华
DENG Hang1,2 ,ZHOU Wen-hua1,2, LI Li-hua1,2(1. School of Food Science and Engineering, Central South Forestry University of Science and Technology Changsha , Hunan 410004, China ; 2. Grain and Oil Processing and Quality Control of Collaborative Innovation Center in Hunan Province, Changsha, Hunan 410004, Chin)
出处
《食品与机械》
CSCD
北大核心
2017年第12期6-11,共6页
Food and Machinery
基金
2017湖南省创新平台与人才计划(编号:2017TP1021)
关键词
小麦
鲜湿面
相关性
多元线性回归
wheat
fresh noodle
correlation
multiple linear regres sion
