Non-destructive rapid prediction method and device for fruit shelf life and freshness

Abstract

The invention provides a non-destructive and rapid prediction method and device for fruit shelf life and freshness. The method includes obtaining spectral data of fruits with different storage times and recording fruit storage time and environmental data; using a regression algorithm to establish a fruit storage time model, calculating weighted and corrected prediction values ​​based on the model prediction value combined with the number of samples, and calculating the discrimination threshold to judge the fruit The degree of freshness, and a method for formulating fruit shelf life based on the key change period data of fruit was proposed. Based on the above method, a fruit freshness analyzer was developed, including optical system, circuit system, control system, data storage and processing system; it can collect fruit spectral data and call the model to predict the fruit freshness. This method significantly improves the accuracy of fruit freshness and shelf life prediction, and can realize the non-destructive, rapid and accurate prediction of fruit freshness and shelf life, which provides technical reference for the development of rapid fruit freshness analyzer.

Description

technical field [0001] The invention relates to the field of spectral analysis, in particular to a non-destructive and rapid prediction method and device for fruit shelf life and freshness. Background technique [0002] Fruit shelf life is an important measure of fruit freshness and is an important parameter in the marketing process. It is generally believed that fruits within the shelf life are fresh fruits and suitable for consumption; while fruits outside the shelf period are stale fruits and are not suitable for consumption. It is not uncommon for fruit to be lost and wasted due to improper preservation conditions, which lead to a sharp drop in the freshness of the fruit, resulting in huge economic losses. Therefore, it is necessary to predict the degree of fruit freshness, and based on the results of judging the degree of fruit freshness, study the formulation method of fruit shelf life. [0003] Different fruits undergo different changes during storage. Even differen...

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Problems solved by technology

[0005] Currently reported based on methods such as near-infrared spectroscopy to predict the shelf life / shelf life of fruits or other agricultural products / foods, the common problems mainly include: using samples at different time points to establish a discriminant model, while for fruits or other agricultural products / foods There is no detailed and in-depth research on continuous changes, that is, the prediction accuracy is not high; in addition, the storage time classification can only be carried out for the samples to be tested, that is, it is determined that the samples to be tested belong to a certain storage stage, and there is no real realization based on data such as near-infrared spectroscopy. Prediction of sample shelf life / freshness

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