Chemical characterization of chestnut cultivars from three consecutive years: chemometrics and contribution for authentication

• Autor(a) principal: Barreira, João C.M.
• Data de Publicação: 2012
• Outros Autores: Casal, Susana, Ferreira, Isabel C.F.R., Peres, António M., Pereira, J.A., Oliveira, Beatriz
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10198/7342
• topic: Castanea sativa Mill.; Nutritional/chemical composition; Seasonal variability; Linear discriminant analysis

Four Castanea sativa Miller cultivars (Aveleira, Boaventura, Judia and Longal) belonging to the Protected Designation of Origin ‘‘Castanha da Terra Fria’’, from the Northeast of Portugal, were selected in 2006, 2007 and 2008. Their nutritional, fatty acids, triacylglycerols and tocopherols profiles were evaluated. Water was the major component, followed by carbohydrates, protein and fat, with energetic values lower than 190 kcal/100 g of fresh fruit. Oleic, linoleic and palmitic were the major fatty acids, 1-oleoyl-2-linoleoyl- 3-linoleoyl-sn-glycerol, 1-linoleoyl-2-linoleoyl-3-palmitoyl-sn-glycerol, 1-oleoyl-2-linoleoyl-3- oleoyl-sn-glycerol and 1-linoleoyl-2-oleoyl-3-palmitoyl-sn-glycerol were the prevalent triacylglycerols and c-tocopherol was the most abundant tocopherol. In each parameter, differences between cultivars, harvest year and the possible cultivar year interaction were screened through a two-way analysis of variance. Differences among cultivars have been attenuated by the variability among years, leading, in general, to a significant interaction effect, which resulted in a relative homogeneity regarding chemical parameters, showing that nutritional and chemical composition was influenced by seasonal variability. A stepwise linear discriminant model, based on 10 (a-tocopherol, c-tocotrienol, LLL, OLLn, d-tocopherol, c-tocopherol, d-tocotrienol, PLLn, protein and OOO) of the 38 initial evaluated variables was also established. The model allowed the complete discrimination of cultivars with overall sensibilities and specificities of 100%, for both original grouped data and leave-one-out cross-validation procedures. Furthermore, similar results were also obtained using only tocopherols data, showing their usefulness as a discriminant factor for chestnut cultivars.