Classification of Hass avocado (persea americana mill) in terms of its ripening via hyperspectral images
- Jhon Pinto, * Universidad Industrial de Santander, Colombia https://orcid.org/0000-0002-1953-1691
- Hoover Rueda-Chacón Universidad Industrial de Santander, Colombia https://orcid.org/0000-0002-6763-8629
- Henry Arguello Universidad Industrial de Santander, Colombia https://orcid.org/0000-0002-2202-253X
Abstract
The use of non-invasive and low-cost methodologies allows the monitoring of fruit ripening and quality control, without affecting the product under study. In particular, the Hass avocado is of high importance for the agricultural sector in Colombia because the country is strongly promoting its export, which has generated an expansion in the number of acres cultivated with this fruit. Therefore, this paper aims to study and analyze the ripening state of Hass avocados through non-invasive hyperspectral images, using principal component analysis (PCA) along with spectral vegetation indices, such as the normalized difference vegetation index (NDVI), ratio vegetation index (RVI), photochemical reflectance index (PRI), colorimetry analysis in the CIE L*a*b* color space, and color index triangular greenness index (TGI). In particular, this work conducts a quantitative analysis of the ripening process of a population of 7 Hass avocados over 10 days. The avocados under study were classified into three categories: unripe, close-to-ripe, and ripe. The obtained results show that it is possible to characterize the ripening state of avocados through hyperspectral images using a non-invasive acquisition system. Further, it is possible to know the post-harvest ripening state of the avocado at any given day.
Author Biographies
System Engineer, Department of Computer Science, Universidad Industrial de Santander, Bucaramanga -Colombia, jpintobarrera@gmail.com
*Corresponding author
Ph.D. in Electrical and Computer Engineering, Department of Computer Science, Universidad Industrial de Santander, hfarueda@gmail.com
Ph.D. in Electrical and Computer Engineering, Department of Computer Science, Universidad Industrial de Santander, henarfu@uis.edu.co
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