食品科学 ›› 2011, Vol. 32 ›› Issue (13): 54-57.doi: 10.7506/spkx1002-6630-201113013

• 基础研究 • 上一篇    下一篇

基于颜色变化的青花菜叶绿素含量预测模型

许凤1,杨震峰2,裴娇艳1,郑永华1,*   

  1. 1. 南京农业大学食品科技学院 2. 浙江万里学院生物与环境学院
  • 出版日期:2011-07-15 发布日期:2011-07-02
  • 基金资助:
    “十一五”国家科技支撑计划重点项目(2006BAD30B03)

A Prediction Model for Chlorophyll Content in Post-harvest Broccoli Based on Color Parameter Changes

XU Feng1, YANG Zhen-feng2,PEI Jiao-yan1, ZHENG Yong-hua1,*   

  1. 1. College of Food Science and Technology, Nanjing Agricultural University, Nanjing 210095, China; 2. College of Biological and Environmental Sciences, Zhejiang Wanli University, Ningbo 315100, China
  • Online:2011-07-15 Published:2011-07-02

摘要: 为研究青花菜贮藏期间叶绿素含量和颜色变化的关系,通过不同温度贮藏实验建立基于颜色参数-a/b值的叶绿素含量预测模型。将青花菜贮藏在273、278、283、293、303K条件下,测定花蕾-a/b值和叶绿素含量的变化。基于Arrhenius动力学方程分别建立青花菜-a/b值、叶绿素含量与贮藏时间和温度之间的动力学模型,再根据-a/b值与叶绿素含量变化的线性关系,进一步建立基于-a/b值的叶绿素含量预测模型。在275、280、285、295、305K贮藏温度条件下对基于-a/b值的叶绿素含量预测模型进行验证,预测的相对误差(RE)为4.31%,预测精度较高。因此该预测模型可以较好的预测在273~305K温度条件下青花菜叶绿素含量的变化状况,从而可为应用颜色参数的检测方法来检测青花菜的品质提供依据。

关键词: 青花菜, 叶绿素含量, 颜色, 预测模型

Abstract: In order to explore the relationship between chlorophyll content and color change of post-harvest broccoli during storage, a prediction model for chlorophyll content was established based on color parameter changes. Freshly harvested broccoli was stored at different temperatures (273, 278, 283, 293 K and 303 K), and the color parameter -a/b value and chlorophyll content of broccoli were determined. Kinetic models of -a/b value and chlorophyll content with respect to storage time and temperature were established on the basis of Arrhenius equation. In addition, a prediction model for chlorophyll content based on -a/b value was further developed according to the linear relationship between chlorophyll content and -a/b value. Moreover, the prediction model for chlorophyll content based on -a/b value was validated using broccoli stored at 275, 280, 285, 295 K and 305 K with a relative prediction error of 4.31%. The chlorophyll content of broccoli can be accurately predicted at the storage temperature from 273 K to 305 K using this prediction model. Therefore, the prediction model is acceptable for applying the color parameter -a/b to evaluate broccoli quality.

Key words: broccoli, chlorophyll content, color parameter, prediction model

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