Tomato quality is one of the most important factors ensured the consistency of tomato market factors.A color analysis method was proposed for classifying the fresh tomato,with reference to the national standard GB 8852—88,defining the classification standards of tomato maturity.In this study,tomato was divided into the four categories,full ripe,ripe,half ripe,and green ripe.RGB images of tomato were collected,removing the background and filtering de-noi-sing,and then they were converted to HIS and HSV color models. Through the MATLAB programming,the mean values of the color components R,G,B,H,S,V,and I were obtained,and the deter-mination and selection of combination components were carried on u-sing SPSS software.Moreover,the discriminant analyses were then performed using Matlab.The results showed that the identification rates of the green ripe and validation sets were the best of all the three different discriminant functions,reached 100.00%,and the highest discrimination rates of half ripe tomato set was 94.74%. However,the identification rates of training and validation sets of ripe tomato were the lowest,identified as 76.67% and 70.00%,re-spectively.Those of the training and validation sets of full ripe were the highest,about 90.00%.In general,the discrimination and classi-fication of tomato with different maturity were realized using the ma-chine recognition system in the present study.%提出一种颜色分析方法用于新鲜番茄分类，以GB 8852—88标准为参考，定义番茄成熟度的分类标准(在研究中将其分成四类：完熟、成熟、半熟、绿熟)，将采集到的番茄 RGB图像，去除背景后，滤波去噪，转换成 HIS 颜色模型和 HSV颜色模型。通过 Matlab 编程获取 R、G、B、H、S、V、I各颜色分量的均值，运用 SPSS 软件进行判别筛选组合特征分量，运用 Matlab进行判别分析。分析结果显示，绿熟番茄在3种不同判别函数下训练集与验证集判别率均达到了100.00%；半熟番茄训练集判别率最高为94.74%，同时验证集判别率最高达到100%；成熟番茄训练集与验证集判别率最低，分别为76.67%和70.00%；完熟番茄训练集与验证集最高均为90.00%。总体上实现了不同成熟度番茄的判别分类。
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