Avola almond is part of the “Traditional Italian Agri-food Product” (PAT) list, as established by The Italian Ministry of agricultural food, forestry and tourism policies; this endorsement testifies its status as a high added-value product, and, consequently, it highlights the need of analytical methodologies suitable for its authentication. For these reasons, in the present study, the possibility of developing a non-destructive approach, aimed at distinguishing almonds cultivated in the Avola area from others presenting a different geographical origin, has been investigated. To fulfil this purpose, 227 almonds, cultivated in the Avola area or in other Italian territories, have been analysed by near infrared (NIR) spectroscopy coupled with Partial Least Squares-Discriminant Analysis (PLS-DA) and Soft Independent Modelling of Class Analogies (SIMCA). The two tested approaches achieved satisfactory results (in external validation) indicating both of them would represent a suitable tool for the purpose of the study. © 2019 Elsevier Inc.
Authentication of “Avola almonds” by near infrared (NIR) spectroscopy and chemometrics / Firmani, Patrizia; Bucci, Remo; Marini, Federico; Biancolillo, Alessandra. - In: JOURNAL OF FOOD COMPOSITION AND ANALYSIS. - ISSN 0889-1575. - 82:(2019). [10.1016/j.jfca.2019.103235]
Authentication of “Avola almonds” by near infrared (NIR) spectroscopy and chemometrics
Firmani, Patrizia;Bucci, Remo;Marini, Federico;Biancolillo, Alessandra
2019
Abstract
Avola almond is part of the “Traditional Italian Agri-food Product” (PAT) list, as established by The Italian Ministry of agricultural food, forestry and tourism policies; this endorsement testifies its status as a high added-value product, and, consequently, it highlights the need of analytical methodologies suitable for its authentication. For these reasons, in the present study, the possibility of developing a non-destructive approach, aimed at distinguishing almonds cultivated in the Avola area from others presenting a different geographical origin, has been investigated. To fulfil this purpose, 227 almonds, cultivated in the Avola area or in other Italian territories, have been analysed by near infrared (NIR) spectroscopy coupled with Partial Least Squares-Discriminant Analysis (PLS-DA) and Soft Independent Modelling of Class Analogies (SIMCA). The two tested approaches achieved satisfactory results (in external validation) indicating both of them would represent a suitable tool for the purpose of the study. © 2019 Elsevier Inc.File | Dimensione | Formato | |
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