[HTML][HTML] Comparative quantification of chlorophyll and polyphenol levels in grapevine leaves sampled from different geographical locations

E Martín-Tornero, RNM de Jorge Páscoa… - Scientific Reports, 2020 - nature.com
E Martín-Tornero, RNM de Jorge Páscoa, A Espinosa-Mansilla, ID Martín-Merás, JA Lopes
Scientific Reports, 2020nature.com
Near infrared spectroscopy (NIRS) and mid-infrared spectroscopy (MIRS) in combination
with chemometric analysis were applied to discriminate the geographical origin of grapevine
leaves belonging to the variety “Touriga Nacional” during different vegetative stages. Leaves
were collected from plants of two different wine regions in Portugal (Dão and Douro) over
the grapes maturation period. A sampling plan was designed in order to obtain the most
variability within the vineyards taking into account variables such as: solar exposition, land …
Abstract
Near infrared spectroscopy (NIRS) and mid-infrared spectroscopy (MIRS) in combination with chemometric analysis were applied to discriminate the geographical origin of grapevine leaves belonging to the variety “Touriga Nacional” during different vegetative stages. Leaves were collected from plants of two different wine regions in Portugal (Dão and Douro) over the grapes maturation period. A sampling plan was designed in order to obtain the most variability within the vineyards taking into account variables such as: solar exposition, land inclination, altitude and soil properties, essentially. Principal component analysis (PCA) was used to extract relevant information from the spectral data and presented visible cluster trends. Results, both with NIRS and MIRS, demonstrate that it is possible to discriminate between the two geographical origins with an outstanding accuracy. Spectral patterns of grapevine leaves show significant differences during grape maturation period, with a special emphasis between the months of June and September. Additionally, the quantification of total chlorophyll and total polyphenol content from leaves spectra was attempted by both techniques. For this purpose, partial least squares (PLS) regression was employed. PLS models based on NIRS and MIRS, both demonstrate a statistically significant correlation for the total chlorophyll (R2P = 0.92 and R2P = 0.76, respectively). However, the PLS model for the total polyphenols, may only be considered as a screening method, because significant prediction errors, independently of resourcing on NIRS, MIRS or both techniques simultaneously, were obtained.
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