Development of a Non-Destructive Tool Based on E-Eye and Agro-Morphological Descriptors for the Characterization and Classification of Different Brassicaceae Landraces

Abstract

In recent years, Brassicaceae have piqued the interest of researchers due to their extremely rich chemical composition, particularly the abundance of antioxidants and anti-inflammatory compounds, as well as because of their antimutagenic and potential anticarcinogenic activity. Vegetables in this family can be found practically everywhere on the planet. In Italy, numerous varieties of Brassicaceae, as well as a diverse pool of local variants, are regularly cultivated. These landraces, which have a variety of peculiar features, have recently sparked increased interest, and the need to safeguard them to preserve genetic biodiversity has become a relevant topic. In the present study, eight distinct Brassicaceae folk varieties were studied using non-destructive tools (Multivariate Image analysis and agro-morphological descriptors). Eventually, the data were handled using explorative analysis (EA) and Soft Independent Modeling by Class Analogy (SIMCA). EA pointed out similarities/dissimilarities among the diverse investigated populations. SIMCA led to high sensitivity (>70%) in prediction (on the external test set) for seven (over eight) investigated classes. Although the investigated plants belong to different landraces, they bear strong similarities. This is mainly linked to the ability of Brassicaceae to hybridize. Despite this, the combination of colorgrams and SIMCA allowed for classifying samples with excellent accuracy.