摘要
利用水溶性壳聚糖作为脂肪的替代品,制作了不同脂肪替代度的低脂冰淇淋.采用质构仪和色差计分别对所制得的低脂冰淇淋品质进行分析,然后使用SPSS19.0对色差值与质构特性的结果进行主成分分析和相关性分析,并利用神经网络对其相关性进行验证和预测.结果表明,色差值与质构参数二者之间具有一定相关性(R=-0.916^-0.287).结合神经网络预测可知,色差值可以来预测冰淇淋的质构特性(R=0.922~0.957),说明冰淇淋外部的光学属性与其内部的质构属性之间存在着联系.
The fat in ice cream is substituted in different degrees by water-soluble chitosan in the present research.The quality of obtained low-fat ice creams is evaluated by using colorimeter and texture profile analyzer. Principal component analysis and correlation analysis of chroma and textural parameters are conducted by using SPSS19. 0,and the correlation is verified and predicted by using artificial neural networks. The results show that there is some correlation between colorimeter parameters and textural parameters（ R =- 0. 916-- 0. 287,P 〈0. 05 or P〈 0. 01）. Combined with the artificial neural network prediction,the chromatic aberration can be used to predict the texture properties of ice cream（ R = 0. 922- 0. 957）,and illustrate the relationship between the internal physical texture characteristics and external color values in ice cream.
出处
《烟台大学学报（自然科学与工程版）》
CAS
2015年第2期130-134,共5页
Journal of Yantai University(Natural Science and Engineering Edition)
基金
山东省高等学校科技计划资助项目(101660)
关键词
低脂冰淇淋
TPA
神经网络
色差
low-fat ice cream
TPA
artificial neural network
chromatic aberration
