This study aimed to assess bioactive compounds contents in cherry tomatoes and classify samples according to cultivation techniques. Simple and cost-effective analyses were conducted on 128 samples cultivated using hydroponic, organic, and conventional practices. An HPLC-FD method was validated in-house for eight biogenic amines while antioxidants were evaluated using total phenolic content and anti-radical activity assays (DPPH and ABTS+ assays). Chemometric evaluation was applied to extrapolate significant information from data-sets. Variable selection using correlation matrix and the Fisher test was performed. Principal component analysis and linear discriminant analysis were used to construct a mathematical model to classify samples. Correct classifications were achieved in training (95.2%), validation (98.5%), and testing (100%). The results showed that cherry tomatoes cultivated using different techniques could be discriminated based on bioactive profiles using chemometric approaches.
Bioactive compounds in cherry tomatoes (Solanum Lycopersicum var. Cerasiforme): Cultivation techniques classification by multivariate analysis / Rapa, Mattia; Ciano, Salvatore; Ruggieri, Roberto; Vinci, Giuliana. - In: FOOD CHEMISTRY. - ISSN 0308-8146. - 355:(2021), p. 129630. [10.1016/j.foodchem.2021.129630]
Bioactive compounds in cherry tomatoes (Solanum Lycopersicum var. Cerasiforme): Cultivation techniques classification by multivariate analysis
Rapa, Mattia
;Ciano, Salvatore;Ruggieri, Roberto;Vinci, Giuliana
2021
Abstract
This study aimed to assess bioactive compounds contents in cherry tomatoes and classify samples according to cultivation techniques. Simple and cost-effective analyses were conducted on 128 samples cultivated using hydroponic, organic, and conventional practices. An HPLC-FD method was validated in-house for eight biogenic amines while antioxidants were evaluated using total phenolic content and anti-radical activity assays (DPPH and ABTS+ assays). Chemometric evaluation was applied to extrapolate significant information from data-sets. Variable selection using correlation matrix and the Fisher test was performed. Principal component analysis and linear discriminant analysis were used to construct a mathematical model to classify samples. Correct classifications were achieved in training (95.2%), validation (98.5%), and testing (100%). The results showed that cherry tomatoes cultivated using different techniques could be discriminated based on bioactive profiles using chemometric approaches.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.