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挂面的理化特性和感官质量研究
引用本文:刘锐,邢亚楠,张影全,王杰,卢洋洋,魏益民.挂面的理化特性和感官质量研究[J].中国粮油学报,2015,30(8):13-18.
作者姓名:刘锐  邢亚楠  张影全  王杰  卢洋洋  魏益民
作者单位:中国农业科学院农产品加工研究所/农业部农产品加工重点实验室,中国农业科学院农产品加工研究所/农业部农产品加工重点实验室,中国农业科学院农产品加工研究所/农业部农产品加工重点实验室
基金项目:现代农业产业技术体系建设专项(CARS-03);公益性行业(农业)科研专项经费资助(201303070)
摘    要:采集全国28家企业的60份普通挂面样品,测定其理化特性、烹调特性、感官质量,分析挂面产品质量现状,比较不同小麦产区间挂面质量的差异,研究质量要素间的关系。结果表明,挂面理化特性变异较大,感官质量整体较好,色泽和食味的差异是挂面感官差异的主要方面。与南方冬麦区相比,北方冬麦区的挂面含水率较低,色泽偏黄,煮后面条的黏性、食味及总分较高。在一定范围内(色泽b*值≤18.06、烹调吸水率≤197.2%、煮面10 min后鲜重≤27.4 g),熟面条的色泽、硬度和黏性评分分别随着挂面b*、吸水率和煮面10 min后鲜重的提高而改善,但超过该范围会对面条评分产生负向作用。挂面灰分含量和烹调吸水率对色泽评分有显著影响,可以用来预测面条色泽。色泽L*均匀性、煮面10 min后鲜重和灰分含量分别与面条硬度、弹性和光滑性评分呈负相关关系,影响显著。理化和烹调特性中的色泽a*值对面条感官总分影响最显著。

关 键 词:市售挂面  理化特性  烹调特性  感官质量  相关性  多元回归模型
收稿时间:2/9/2014 12:00:00 AM
修稿时间:2014/11/28 0:00:00

Physic-chemical properties and sensory quality of commercial dried Chinese noodles
Abstract:In order to study the quality of commercial dried Chinese noodles in China, 60 ordinary dried noodles were collected from 28 large-scale dried noodles enterprises. Chemical component, color, maximum curvature, cooking properties and sensory quality of dried noodles samples were analyzed. The quality status of noodles, the quality difference among noodles from the various producing areas and relationship of the measured quality parameters were investigated. The results showed that the variation in physic-chemical properties were wide. The variation in color and flavor were the main aspects of sensory quality variation of commercial dried noodles. Compared with winter wheat region in south China, dried noodles from winter wheat region in north China showed lower moisture, higher color b*, and higher scores in stickiness, flavor and total scores. The association between color b* and color score, water uptake and firmness score, and cooked weight at 10 min and stickiness score fit quadratic regression model significantly. To a certain extent (18.06, 197.2% and 27.4 g, for color b*, water uptake and cooked weight at 10 min, respectively), color, firmness and stickiness improve as these traits increase, respectively. The cooked noodles color could be predicted by ash content and water uptake during cooking, which accounted for 62.2% of their variations. Negative correlations were observed between color L* uniformity and firmness score, cooked weight at 10 min and elasticity score, and ash content and smoothness. The color a* had the most obvious effect on noodles total score.
Keywords:commercial dried Chinese noodles  physic-chemical properties  cooking quality  sensory quality  correlation  multiple regression analysis model
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