Fruit soluble solid indirect nondestructive testing method and system
A non-destructive testing and soluble technology, applied in measuring devices, material excitation analysis, instruments, etc., can solve the problems of inability to detect the soluble solids content of fresh fruits, improve training speed and accuracy, strong practicability, and simple sample preparation Effect
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Embodiment 1
[0035] A kind of indirect non-destructive detection method of fruit soluble solids, such as figure 1 shown, including the following steps:
[0036] S1. The leaves on the fruit to be detected are heated at a constant temperature until the quality of the leaves does not change, and the spectrum of the leaves is collected based on laser-induced breakdown spectroscopy technology to obtain the spectral characteristics of the leaves; preferably, after collecting the spectra of the leaves, The collected spectra were peak-finded and redundantly removed to obtain the spectral characteristics of the leaves. Specifically, in this embodiment, a genetic algorithm is used to remove redundancy from the spectrum after peak finding.
[0037] S2. Input the obtained leaf spectral features into the pre-trained soluble solids detection model to obtain the classification level of soluble solids content;
[0038] Among them, the soluble solids detection model is a machine learning model. Specific...
Embodiment 2
[0052] An indirect nondestructive detection system for fruit soluble solids, comprising:
[0053] The feature extraction module is used to heat the leaves on the fruit to be detected at a constant temperature until the quality of the leaves does not change, and collect the spectra of the leaves based on laser-induced breakdown spectroscopy to obtain the spectral characteristics of the leaves;
[0054] The soluble solids detection module is used to input the leaf spectral characteristics into the pre-trained soluble solids detection model to obtain the classification level of the soluble solids content;
[0055] Among them, the soluble solids detection model is a machine learning model.
[0056] Preferably, the above-mentioned indirect nondestructive detection system for fruit soluble solids further includes: a model training module, configured to execute steps S01-S03 provided in Embodiment 1 of the present invention.
[0057] The relevant technical features are the same as t...
Embodiment 3
[0059] A computer-readable storage medium, the computer-readable storage medium includes a stored computer program, wherein, when the computer program is run by a processor, the device where the storage medium is located is controlled to execute a method provided in Embodiment 1 of the present invention. An indirect nondestructive detection method for fruit soluble solids.
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