Method for detecting quality of figs based on near infrared spectrum

Abstract

The invention relates to the technical field of agricultural product detection, in particular to a method for detecting quality of figs based on near infrared spectrum. A random forest regression algorithm is an ensemble learning algorithm taking a decision tree as a base learner, CART decision trees are trained by using a Bagging ensemble learning technology and forming a forest, the decision trees in the forest are not associated (FIG1), and an average value of the results output by the decision trees is used as a regression result (FIG2), so that the problem of overfitting is solved, and the overall model has relatively high precision and generalization performance; and low RMSEC and RMSEP show that the random forest algorithm is used for predicting the internal quality of the green-peel figs, a good effect is achieved through experiments, and a large amount of experimental data proves that the random forest algorithm has higher fitting capacity than a partial least squares method and is not prone to over-fitting.

Description

technical field [0001] The invention relates to the technical field of agricultural product detection, in particular to a method for detecting the quality of figs based on near-infrared spectroscopy. Background technique [0002] Green fig is one of the earliest fruit tree species improved and cultivated by human beings, and the overall use value of the plant is high. Fig fruit is round in color, bright and juicy, with good taste and high nutritional value. The scale of artificial cultivation in my country has continued to expand in the past 20 years. With the improvement of consumers' living standards, the quality requirements for fruits are also increasing simultaneously. The texture of fruits is more and more concerned by consumers, such as hardness, elasticity, chewiness, adhesion, elasticity, cohesion, and stickiness. Wait. Most of the traditional texture instruments need to destroy the sample to measure the internal texture properties, the measurement efficiency is l...

AI Technical Summary

Problems solved by technology

Many scholars at home and abroad have used near-infrared spectroscopy to establish food texture prediction models, most of which widely use partial least squares to build models, but partial least squares still has the disadvantage of poor fitting ability

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