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果蔬采摘后的品质会发生变化,为提高果蔬的商品价值,以灰色系统理论为基础,对果蔬品质的预测进行了研究。果蔬采用香蕉为研究对象,以表面颜色变化表征其品质特性,采用其图像作为输入数据,通过数字图像处理技术提取与颜色相关最为密切的H值作为特征参数。给出了品质预测系统和图像处理的流程,建立了灰色系统GM(1,1)模型,进而实现对香蕉品质预测的目的。试验结果表明,在2种预测情况下,用GM(1,1)模型对H值预测的最大残差百分比分别为3.245 3%、3.954 5%,残差较低,表明GM(1,1)模型可在香蕉等品质与颜色变化相关的果蔬贮藏、运输和销售过程中预测其品质变化。
The quality of fruits and vegetables after picking will change, in order to improve the value of fruits and vegetables, based on the gray system theory, fruit and vegetable quality prediction was studied. The fruits and vegetables used banana as the research object, characterizing their quality characteristics by the color change of the surface, taking the images as the input data and extracting the H value closest to the color as the characteristic parameter through the digital image processing technology. The process of quality prediction system and image processing is given, and the GM (1,1) model of gray system is established to predict the quality of banana. The experimental results show that the maximum residual percentage predicted by the GM (1,1) model for H value is 3.245 3% and 3.954 5%, respectively, with a low residual value, indicating that the GM (1,1) The model predicts quality changes in the storage, transport and marketing of fruits and vegetables related to quality and color changes such as bananas.