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Non-destructive identification of defects and classification of Hass avocado fruits with the use of a hyperspectral image

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Pisipilt

Kuupäev

2022

Kättesaadav alates

Ajakirja pealkiri

Ajakirja ISSN

Köite pealkiri

Kirjastaja

Estonian University of Life Sciences

Abstrakt

Sensory analysis and instrumental analytical methods are used in determining the maturity and quality monitoring of avocado fruits, which are labor-intensive and do not allow the determination of fruit quality in real time. The use of hyperspectral imaging (HSI) methods in the range of 400–1,000 nm and of the multivariate analysis was demonstrated for a non-destructive grading of Hass avocado fruits into quality classes according to the number of hidden defects. Using the sensory analysis, avocado fruits were separated into quality classes according to the number of defects after being stored for 10 days. Development of a classification model included several steps: image recording and analysis using the ANOVA and PCA method, image segmentation (selection of ROI), pre-processing (SNV-correction, centering), selection of a multivariate classification method (PLS-DA, SIMCA) and a spectral range, model verification. The analysis of hyperspectral images of avocado fruits has detected spectral regions with the maximal variance responsible for the change of the content of pigments and moisture within the avocado fruit exocarp. Comparison of PLS-DA and SIMCA models on the basis of best accuracy and test-validation results was carried out. Comparison of models showed SIMCA model as the most efficient model for fruit classification into quality classes depending on the number of hidden defects. The implementation of the developed approach as a digital avocado fruit sorting system at different stages of the product life cycle is proposed.

Kirjeldus

Received: January 15th, 2022 ; Accepted: April 19th, 2022 ; Published: May 2nd, 2022 ; Correspondence: Metlenkin.DA@rea.ru

Märksõnad

HSI, sensory analysis, chlorophyll, multivariate analysis, PCA, PLS-DA, SIMCA, articles

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