Abstract

Lentil (Lens culinaris Medik.) is the fourth most important pulse crop in the world after bean (Phaseolus vulgaris L.), pea (Pisum sativum L.), and chickpea (Cicer arietinum L.). Canada is the world's largest exporter of lentils, while in Italy lentils are a minor legume and can be found in restricted areas. However, Italian lentils present unique and characteristic qualities giving them a higher value, so that many of them have obtained international and national marks linked to their geographical origins, such as "protected geographical indication" (PGI), "traditional food products" (PAT) and Slow Food Presidium. For these reasons, there is a growing demand for analytical methods able to certify the declared geographical origin of lentils, in order to protect consumers and producers from fraud and unfair competition. In the present work, the potential of infrared spectroscopic fingerprinting technique for the geographical origin traceability of lentils was investigated. In particular, lentil samples from two different countries, i.e. Italy and Canada, were collected from retail markets and analysed by Fourier transform near- and mid-infrared spectroscopy (FT-NIR, FT-MIR). After a suitable pretreatment of the raw spectral data, Linear Discriminant Analysis (LDA) was used examining the FT-NIR and FT-MIR fingerprints separately and in combination in order to evaluate the spectral range mostly influenced by geographical origin. The LDA classification results were expressed in terms of recognition and prediction abilities (cross validation and external validation). Good classification results were obtained for both FT-NIR and FT-MIR ranges with FT-MIR one giving better prediction abilities, i.e. 95% and 92% for cross and external validation, respectively. The combination of the FT-MIR and F-NIR did not improve the model performances. These findings demonstrated the suitability of the methods developed to discriminate geographical origin of lentils and confirmed the applicability of the infrared spectroscopy, in combination with chemometrics, to solve geographic origin issues of foodstuffs.

Autore Pugliese

• De Girolamo Annalisa , Logrieco Antonio Francesco , Lippolis Vincenzo

Tutti gli autori

• V. Innamorato; F. Longobardi; M. Cortese; V. Lippolis; A. De Girolamo; A. Logrieco

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Anno di pubblicazione

2017

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