4.7 Article

NIR spectroscopy for the optimization of postharvest apple management

期刊

POSTHARVEST BIOLOGY AND TECHNOLOGY
卷 87, 期 -, 页码 13-20

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.postharvbio.2013.07.041

关键词

FT-NIR spectroscopy; 'Golden Delicious' apples; Storage; Predictive models; Classification models

资金

  1. Regione Lombardia, research project Valorvi - Valorizzazione e ottimizzazione delle filiere viticola e frutticola valtellinesi attraverso sistemi innovativi in postraccolta e trasformazioni ad alta qualita
  2. Regione Lombardia and European Social Fund for a Post-doctoral Research Fellowship (Progetto Dote Ricerca)

向作者/读者索取更多资源

Apples can be stored for long time under controlled temperature and atmosphere conditions, and therefore, non-destructive and rapid tools are required to assess fruit quality and to monitor changes during the postharvest period. The aim of this study was to evaluate the feasibility of NIR spectroscopy to optimize postharvest apple management and to follow changes in fruit quality during storage. An FT-NIR system operating in diffuse reflectance in the range 12,500-3600 cm(-1) was used to evaluate the physicochemical (dry matter, soluble solids, colour and firmness) and some nutraceutical characteristics (total phenolics, total flavonoids and antioxidant activity) of 'Golden Delicious' apples, which were stored for about six months at 1 degrees C in controlled atmosphere, over two subsequent years. Spectral data were elaborated by PLS regression and LDA classification techniques. Good correlation models between spectral data and chemical and physical parameters were obtained for soluble solids, a* colour coordinate and firmness (0.81 < R-2 < 0.90 in calibration and 0.79 < R-2 < 0.89 in cross validation). Even higher correlation values (0.89 < R-2 < 0.95 in calibration and 0.86 < R-2 < 0.92 in cross validation) were obtained for indexes correlated to the antioxidant capacity of apples. The classification technique Linear Discriminant Analysis was applied to spectral data, in order to discriminate apples on the basis of storage time. Average correct classification was higher than 93% in validation and close to 100% in calibration, indicating high, potential of NIR spectroscopy for the estimation of storage time of apple lots. (C) 2013 Elsevier B.V. All rights reserved.

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