鸡毛菜(Brassica rapa L.Chinensis Group.)的颜色变化动力学及两种货架期预测方法

Colour kinetic change and shelf life prediction of Chinese small cabbage(Brassica rapa L.Chinensis Group.)

实验测定了贮藏在278、283、288、293K四个温度下的鸡毛菜的颜色参数L*、-a*、b*、△E、h*和感官评价,并对L*和△E进行了动力学分析。结果表明,在实验温度范围内,鸡毛菜储藏的温度越低,颜色参数变化越慢。动力学分析显示,零级动力学比一级动力学更适合表现鸡毛菜L*和△E的变化规律。研究还采用Arrhenius方程对颜色变化速率常数k和温度T进行非线性拟合,得到L*和△E活化能Ea分别为82.09kJ/mol和100.26kJ/mol。最后得到依赖于时间、温度和颜色指标的鸡毛菜货架期预测方程(R2>0.95),从中根据不同的L*和△E终点可得到对应的货架期。就本研究而言,假定L*增加12%为终点时,鸡毛菜在四个温度下的预测货架期分别为11.8、5.5、2.6、1.3d。同时,Arrhenius方程与依赖于感官终点的动态颜色终点拟合方程结合预测的货架期曲线与感官寿命曲线则能得到更好的契合(两者绝对差值小于0.6d),两者结合能得到较为全面的货架期预测参数。

Color parameters L＊,a＊,b＊,△E,h＊ and sensory evaluation of Chinese small cabbage stored at 278,283,288 and 293K,respectively,were determined in this experiment,then kinetic analysis of L＊ and △E were also studied. Results showed that the lower the temperature Brassica Lapa L. Chinensis Group. stored, slower color parameters changes in the temperature range concerned. Kinetic analyses indicated that zero-order law was more appropriate than first -order reaction kinetics to describe L＊ and △E change. Nonlinear fitting of reaction rate k and temperature T based on Arrhenius function was also studied,from which active energy E a of L＊ and △E were 82.09kJ/mol and 100.26kJ/mol,respectively. Finally,the shelf life prediction function of Chinese small cabbage based on time,temperature and color index was obtained（R 2 ＆gt;0.95）,from which corresponding predicted shelf life could be calculated based on different ends of L＊ and △E. As for this research concerned,predicted shelf life of Brassica Lapa L. Chinensis Group. stored in four temperatures was 11.8,5.5,2.6 and 1.3 day,respectively,by assuming L＊ ended with 12% increasing. At the same time,shelf life curve resulted from Arrhenius function and linear-fitting function of dynamic color ends relied on sensory cutting point,was better corresponding to shelf life curve of sensory life,the difference between which was less than 0.6 day,the overall shelf life prediction parameters could be obtained based on the combination of two models.