Sweet cherry fruit cracking rate evaluation method based on entropy weight algorithm and machine learning technology

Abstract

The invention discloses a sweet cherry fruit cracking rate evaluation method based on an entropy weight algorithm and a machine learning technology, and the method comprises the steps: obtaining key parameters which comprise the environment temperature, the environment humidity, the soil temperature and the soil humidity; obtaining actual relative humidity of cracked fruits according to the relative humidity of the cherry shed; obtaining the index relation between the temperature and the water vapor pressure through an Emanuel formula, and then obtaining the saturation water vapor pressure E at any moment and any temperature T and the saturation water vapor pressure at the fruit cracking temperature; measuring the water vapor pressure e of the temperature T at any actual moment through a dry-wet bulb thermometer, and obtaining the real-time water vapor pressure of the cracked fruits; and according to the real-time water vapor pressure and the saturated water vapor pressure of the cracked fruits, obtaining the cracked fruit humidity during temperature variable fruit cracking at any moment. In cherry cultivation and production, objective and scientific fruit cracking rate data can be obtained through the method, environmental parameters can be adjusted in time, the fruit cracking amount is reduced, and economic losses are reduced.

Description

technical field [0001] The invention relates to the technical field of intelligent agriculture, in particular to a method for evaluating the cracking rate of sweet cherries using an entropy weight algorithm and machine learning technology. Background technique [0002] After a lot of research and investigation, in the cultivation and production process of sweet cherries, the farmers are most concerned about cracking fruit. The main reason for cracking fruit is: the higher the soil humidity, the easier it is for the fruit to absorb water, which will lead to cracking fruit. The higher the ambient temperature, the lower the fruit hardness. It will lead to fruit cracking. The higher the soil temperature, the more evaporated water vapor will be incorporated into the air, which will also easily lead to fruit cracking. Its fruit cracking will cause serious economic losses to farmers. Contents of the invention [0003] In the production and cultivation process of sweet cherries, ...

AI Technical Summary

Problems solved by technology

[0003] In the production and cultivation process of sweet cherries, because farmers cannot know the more scientific fruit cracking situation in advance, thus missing the time to improve the cultivation parameters, resulting in a large number of fruit cracking problems, this application adopts entropy weight algorithm and machine learning technology to design a predictive fruit cracking rate The evaluation method is used to assist farmers in production and cultivation

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