Rapid Assessment of Badea (Passiflora quadrangularis L.) Maturity Degree by Digital Image Analysis and Multivariate Statistical Techniques
DOI:
https://doi.org/10.18779/ingenio.v9i1.1104Keywords:
Maturity index, multivariate analysis, tropical fruit, RGB, PLS-DAAbstract
Fruits and vegetables are essential for a healthy diet worldwide, but due to their perishable nature, they are among the most wasted foods. According to the Food and Agriculture Organization (FAO), approximately 45% of food is lost before reaching consumers. Proper handling during and after harvest is crucial to reducing this waste, including identifying the optimal ripening point for both harvest and sale. Passiflora quadrangularis (badea), a traditional South American crop rich in antioxidants, generates significant income for vulnerable communities. Determining the ripeness of badea is key to ensuring better quality and reducing post-harvest losses. In this study, a physicochemical characterization was carried out by days of ripening, and images of the badea were used at three stages of ripeness: green-ripe, early-ripe, and ripe. The physicochemical characterization suggests average pH values of 5,73 and a maturity index of 11,62%, as indicators of an early ripening stage suitable for harvest. These images were analyzed using multivariate statistical methods, including Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA), to identify visual patterns and classify ripeness levels. The model achieved a training accuracy of 100% and a validation accuracy of 83%. These methodologies offer a fast and non-invasive method for assessing fruit ripeness, facilitating informed decisions about the optimal time for harvest and helping to reduce post-harvest waste.
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