Fruit sugar degree detection method and system based on genetic algorithm and extreme learning machine

Abstract

The invention discloses a fruit sugar degree detection method and system based on a genetic algorithm and an extreme learning machine. The method comprises the steps of: obtaining and preprocessing anoriginal near infrared spectrum of a fruit to be detected; screening out the optimal characteristic wavelength by using a genetic algorithm; inputting the optimal characteristic wavelength into a trained extreme learning machine prediction model, outputting soluble solid content information of fruits, and further obtaining fruit sugar degree information, wherein the extreme learning machine prediction model is established based on the corresponding relationship between the original near infrared spectrum of the fruit and the corresponding soluble solid content value. Wavelength is screened based on the genetic algorithm, a correlation coefficient of a predicted value and an actual value of a dependent variable in interactive verification of an extreme learning machine method is used as afitness function of the genetic algorithm, and the most appropriate wavelength is selected from 1557 spectral wavelengths of an original spectrum by using the genetic algorithm, so that the predictionprecision of the fruit sugar degree is greatly improved.

Description

technical field [0001] The invention relates to the technical field of apple sugar content detection, in particular to a fruit sugar content detection method and system based on a genetic algorithm and an extreme learning machine. Background technique [0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art. [0003] With the continuous development of society, people's living standards have also been continuously improved. In the choice of fresh fruits, factors such as appearance, color and fruit shape are taking smaller and smaller proportions, and more and more consumer groups pay more attention to the internal quality of related fruits, such as sugar content. Therefore, improving the intrinsic quality of fresh fruit products has become a necessary option under the current market situation. [0004] The soluble solids content of fruit directly affects the sugar content of fr...

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Problems solved by technology

[0004] The soluble solid content of fruit directly affects the sugar content of fresh fruit. At this stage, domestic related research starts relatively late, and there are problems such as immature scientific research technology, industrialization, scale, imperfect detection methods, and high cost.

In the rapid non-destructive testing of fruits, the obtained spectral results are often mixed with noise interference, coupled with other technical problems, it is difficult to obtain accurate data analysis

Moreover, there are not many relevant studies on the soluble solids content of fruits, whether domestic or foreign, and the methods for researching and predicting the sugar content of fruits are not universal.

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