The aim of this work was to investigate the applicability of vis/NIR spectroscopy for rapid assessment of grape phytosanitary status, directly at the check point at grape consignment. A device for non-contact analysis at a distance between sensor and sample of 300 mm, in the spectral range 400-1650 nm was used. Acquisitions were carried out on healthy (1235 samples, 48%) and diseased bunches (1324 samples, 52%) from different white (Chardonnay, Grillo, Inzolia, Viognier) and red (Alicante, Nero d'Avola, Syrah) varieties.A classification analysis (Partial Least Squares - Discriminant Analysis, PLS-DA) was applied on grape spectra in order to test the classification performance of the system. The results obtained from PLS-DA models, in validation, gave a classification accuracy between 89.8% and 94.0%. Results demonstrated that the system is capable to provide useful information about wine grape phytosanitary status for a better management of the vinification process.

Rapid evaluation of grape phytosanitary status directly at the check point station entering the winery by using visible/near infrared spectroscopy / R. Beghi, V. Giovenzana, L. Brancadoro, R. Guidetti. - In: JOURNAL OF FOOD ENGINEERING. - ISSN 0260-8774. - 204(2017 Jul), pp. 46-54. [10.1016/j.jfoodeng.2017.02.012]

Rapid evaluation of grape phytosanitary status directly at the check point station entering the winery by using visible/near infrared spectroscopy

R. Beghi
Primo
;
V. Giovenzana
;
L. Brancadoro
Penultimo
;
R. Guidetti
Ultimo
2017

Abstract

The aim of this work was to investigate the applicability of vis/NIR spectroscopy for rapid assessment of grape phytosanitary status, directly at the check point at grape consignment. A device for non-contact analysis at a distance between sensor and sample of 300 mm, in the spectral range 400-1650 nm was used. Acquisitions were carried out on healthy (1235 samples, 48%) and diseased bunches (1324 samples, 52%) from different white (Chardonnay, Grillo, Inzolia, Viognier) and red (Alicante, Nero d'Avola, Syrah) varieties.A classification analysis (Partial Least Squares - Discriminant Analysis, PLS-DA) was applied on grape spectra in order to test the classification performance of the system. The results obtained from PLS-DA models, in validation, gave a classification accuracy between 89.8% and 94.0%. Results demonstrated that the system is capable to provide useful information about wine grape phytosanitary status for a better management of the vinification process.
Chemometrics; Consignment; Fruit; Infection; Non-destructive; Optical analysis; Food Science
Settore AGR/09 - Meccanica Agraria
lug-2017
Article (author)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/486917
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