The aim of this work was to identify the three most significant wavelengths able to discriminate in the field those grapes ready to be harvested using a simplified, handheld, and low-cost optical device. Nondestructive analyses were carried out on a total of 68 samples and 1,360 spectral measurements were made using a portable commercial vis/near-infrared spectrophotometer. Chemometric analyses were performed to extract the maximum useful information from spectral data and to select the most significant wavelengths. Correlations between the spectral data matrix and technological (total soluble solids) and phenolic (polyphenols) parameters were carried out using partial least square (PLS) regression. Standardized regression coefficients of the PLS model were used to select the relevant variables, representing the most useful information of the full spectral region. To support the variable selection, a qualitative evaluation of the average spectra and loading plot, derived from principal component analysis, was considered. The three selected wavelengths were 670 nm, corresponding to the chlorophyll absorption peak, 730 nm, equal to the maximum reflectance peak, and 780 nm, representing the third overtone of OH bond stretching. Principal component analysis and multiple linear regression were applied on the three selected wavelengths in order to verify their effectiveness. Simple equations for total soluble solids and polyphenols prediction were calculated. The results demonstrated the feasibility of a simplified handheld device for ripeness assessment in the field. © 2014 by the American Society for Enology and Viticulture. All rights reserved.

Wavelength selection with a view to a simplified handheld optical system to estimate grape ripeness

Malegori, Cristina;
2014-01-01

Abstract

The aim of this work was to identify the three most significant wavelengths able to discriminate in the field those grapes ready to be harvested using a simplified, handheld, and low-cost optical device. Nondestructive analyses were carried out on a total of 68 samples and 1,360 spectral measurements were made using a portable commercial vis/near-infrared spectrophotometer. Chemometric analyses were performed to extract the maximum useful information from spectral data and to select the most significant wavelengths. Correlations between the spectral data matrix and technological (total soluble solids) and phenolic (polyphenols) parameters were carried out using partial least square (PLS) regression. Standardized regression coefficients of the PLS model were used to select the relevant variables, representing the most useful information of the full spectral region. To support the variable selection, a qualitative evaluation of the average spectra and loading plot, derived from principal component analysis, was considered. The three selected wavelengths were 670 nm, corresponding to the chlorophyll absorption peak, 730 nm, equal to the maximum reflectance peak, and 780 nm, representing the third overtone of OH bond stretching. Principal component analysis and multiple linear regression were applied on the three selected wavelengths in order to verify their effectiveness. Simple equations for total soluble solids and polyphenols prediction were calculated. The results demonstrated the feasibility of a simplified handheld device for ripeness assessment in the field. © 2014 by the American Society for Enology and Viticulture. All rights reserved.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/896740
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