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Feasibility of Using Reflectance Spectra from Smartphone Digital Images to Predict Quality Parameters of Bananas and Papayas

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Author(s):
de Oliveira, Maisa Azarias ; Ribeiro, Michele Nayara ; Valente, Henrique Murta ; Mutz, Yhan da Silva ; Pinheiro, Ana Carla Marques ; Nunes, Cleiton Antonio
Total Authors: 6
Document type: Journal article
Source: FOOD ANALYTICAL METHODS; v. 17, n. 1, p. 9-pg., 2023-11-28.
Abstract

The present study aimed to build calibration models based on smartphone digital images to estimate bananas and papayas' sensory and physicochemical characteristics at different ripening stages. Three distinct image processing were evaluated: (i) the average red, green, and blue (RGB) values of the entire image, (ii) the number of pixels in each RGB value (the RGB histogram), and (iii) a reflectance spectrum mathematically obtained from the RGB triplet. Each approach was modeled with either multiple linear regression (MLR) or partial least squares (PLS) regression. The predicted variables were the sensory characteristics of ideal sweetness, ideal firmness, and global acceptance, and the physicochemical characteristics of total soluble solids (TSS) and firmness. The models obtained good responses for sensory and instrumental parameters, with the best being the modeled from the reflectance spectrum. The uniqueness of the obtained reflectance spectra captured the color changes throughout the fruit ripening. Furthermore, the obtained spectra allowed for data pre-treatments to be employed, leading to high R-2 > 0.9 and low error measured by external validation. Each modeled variable had a better performance with a specific pre-treatment. Therefore, the adoption of reflectance spectra from smartphone digital images led to a promising option to improve models' predictive performance, especially to assess fruit quality parameters. (AU)

FAPESP's process: 23/00474-4 - Sensors associated with the internet of things to connect the environment, genetics and processing to the chemical and sensory profile of specialty coffees
Grantee:Yhan da Silva Mutz
Support Opportunities: Scholarships in Brazil - Post-Doctoral