DOAJ Open Access 2024

Non-destructive detection of total acid of red globe grapes based on map fusion technique

Sheng Gao Jian-hua Xu

Abstrak

Total acid is an important indicator of the internal quality of red globe grapes. This paper proposed a non-destructive method for the determination of total acid of red globe grapes based on hyperspectral fusion technique. A non-linear LSSVM prediction model based on spectral information, image information and the fusion of the two was built respectively for total acid. The results showed that the MSC-CARS-SPA-LSSVM model of samples about total acid built by fusing the spectra after feature wavelength extraction using the MSC-CARS-SPA algorithm and the image information after dimensionality reduction by the PCA algorithm using the graph fusion technique worked best. The correlation coefficients of the prediction sets of the optimal LSSVM model was 0.9907, which improved the accuracy over the unilateral models based on spectral or image information. A new method for nondestructive detection of total acid of red globe grapes by map fusion technique was discovered.

Penulis (2)

S

Sheng Gao

J

Jian-hua Xu

Format Sitasi

Gao, S., Xu, J. (2024). Non-destructive detection of total acid of red globe grapes based on map fusion technique. https://doi.org/10.1016/j.atech.2024.100406

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Informasi Jurnal
Tahun Terbit
2024
Sumber Database
DOAJ
DOI
10.1016/j.atech.2024.100406
Akses
Open Access ✓