利用仪器检测指标量化夏橙化渣程度  

Qantitative evaluation of Valencia orange mastication degree using texture properties detected by instrument

作　　者：陈红[1] 左婷[1] 伊华林[2] 余豹[1] 魏张奎 潘海兵[1] 

机构地区：[1]华中农业大学工学院,武汉430070 [2]华中农业大学园艺园林学院,武汉430070

出　　处：《农业工程学报》2014年第8期265-271,共7页Transactions of the Chinese Society of Agricultural Engineering

基　　金：中央高校基本科研业务费专项资金资助项目(2013PY127);十二五国家科技支撑计划"主要常绿果树新品种选育"(2013BAD02B02);国家现代柑橘产业技术体系专项基金(CARS-27)

摘　　要：为了量化评价夏橙化渣程度,利用仪器检测的指标建立夏橙感官化渣程度的预测模型,采集了湖北宜昌秭归的9种夏橙总计270个样品,首先测定了影响夏橙样本化渣程度的粗纤维成分含量,进行了夏橙化渣程度的感官评定分析,再利用质构仪的压缩试验、质地剖面TPA(texture profile analysis)试验、剪切试验模拟了口腔咀嚼果肉的过程。结果表明,粗纤维成分含量与质构参数之间存在显著相关性,质构参数与感官化渣程度之间的相关关系也十分显著,说明夏橙质构特性可以表征果肉的化渣性。进一步采用主成分回归分析法,以仪器测得的质构特征值为自变量,感官化渣程度为因变量进行回归分析,得到具有统计学意义决定系数R2为0.73的预测模型。由此表明,基于质构特性建立的夏橙化渣程度评价模型在一定程度上可以准确地评价夏橙的化渣程度,利用质构特性取代感官评定评价夏橙化渣程度是可行的,该研究可为夏橙化渣程度的检测提供参考。To evaluate Valencia orange mastication degree and establish a model for predicting the sensory mastication of Valencia orange quantitatively, nine kinds of Valencia orange, the number of each kind was 30, a total of 270 Valencia orange samples were collected. The research measured the content of crude fiber, sensory attributes, and textural properties of Valencia orange. Sensory evaluation was performed by a panel including eight trained people, and the average score of flesh attributes, residue, and mastication was recorded. Simulating the process of chewing the flesh, compression experiments, TPA tests, and shear tests were performed to analyze the textural properties. The averages and the standard deviations of the three tests were calculated. Statistically, differences were found for crude fiber content among all the cultivars of Valencia oranges. The crude fiber content of Frost and Campbell was significantly higher than others in the condition of significance levels （p＆lt;0.05）. The results of the sensory evaluation showed that the variation coefficient of flesh attributes, residue, and mastication was 0.4 or higher. The other textural indicators were significantly different, except for flexibility and adhesion in texture trails. Simple correlation analysis was performed between sensory evaluation, crude fiber content, and texture property parameters using SPSS software. The results indicated that the mastication degree and texture properties showed a significant correlation. Compression resistance, elastic modulus, hardness, springiness, shear force, and shear work were selected as a texture index to build a model. Collinearity diagnostics and principal component analysis were performed to eliminate collinearity, which was caused by a quite high correlation between textural indices. According to the feature vector of principal component and scores of each texture property parameter, the best subgroup of principal component factors was selected to build the regression model. Then, with principal comp

关 键 词：质构 纤维 压缩试验 化渣程度 夏橙 感官评价 

分 类 号：S666.4[农业科学—果树学]