Method and system for detecting quality in fruit and vegetable drying process based on dynamic neural network

Abstract

The invention relates to a method and a system for detecting the quality in a fruit and vegetable drying process based on a dynamic neural network. The method comprises the following steps: collecting and storing a multispectral graph set of a fruit and vegetable slice sample set to be detected under multiple multispectral bands; preprocessing spectral graphs in the multi-spectral graph set; carrying out threshold segmentation on the processed image, and reconstructing pixel points of the segmented region of interest in each wave band into a one-dimensional sequence according to a sequence; performing zero padding processing on the one-dimensional sequence of each sample in the sample set under a plurality of wavebands, reconstructing a two-dimensional image, and adding one dimension to the data dimension in the reconstructed two-dimensional image set; and sequentially inputting the two-dimensional image set with one dimension added into the dynamic neural network for training according to a sequence of a plurality of wavebands, comparing a predicted value after training with an actual value to obtain an index for measuring the prediction capability, and adjusting the structure of the network and the number of times of training according to an effect. The method is beneficial to improving the prediction capability of the index and effectively improving the detection accuracy.

Description

technical field [0001] The invention relates to the technical field of quality detection in the drying process of fruits and vegetables, in particular to a quality detection method and system in the drying process of fruits and vegetables based on a dynamic neural network. Background technique [0002] Most fruits and vegetables are prone to rapid decay, dehydration and microbial growth during storage due to their rich water, sugar and other nutrients. Due to the improper handling of fruits and vegetables, our country produces hundreds of billions of economic losses every year due to the loss of fruits and vegetables. Therefore, the deep processing of fruits and vegetables is of great significance to the development of my country's modern food industry. Among them, drying is the first step in the deep processing of fruits and vegetables. It can inhibit the growth of microorganisms while evaporating the water of fruits and vegetables, and prolong the storage time. In the tr...

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Problems solved by technology

[0004] For this reason, the technical problem to be solved by the present invention is to overcome the problem of low detection accuracy in the prior art, thereby providing a quality detection method in the process of fruit and vegetable drying based on dynamic neural network with high prediction ability and thus effectively improving detection accuracy. and system

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