Colored Anti-Hail Nets Modify the Ripening Parameters of Nebbiolo and a Smart NIRS can Predict the Polyphenol Features
Journal: Journal of Agronomy Research (Vol.4, No. 1)Publication Date: 2021-08-04
Authors : Alberto Cugnetto; Giorgio Masoero;
Page : 23-45
Keywords : colored anti-hail nets; in-vineyard elevation; polyphenols; Nebbiolo grape; NIRS; ripening; SCiOTM; vine;
Abstract
In the cultivation of vines the risk of hail appears to be increasing with the ongoing climate change. The use of protective plastic nets is spreading, but there is little knowledge on the additional processing costs and on the phenological and qualitative consequences, moreover, as depending on different colors of the nets. Thus, a randomized trial was carried out in Nebbiolo, a wine of great aging, testing three plastic anti-hail nets colored in green, gray and black. Results showed that 24% more-time was necessary for the canopy management practices under the nets. The black nets advanced the ripening process, with a berry weight decrease of about 13%. A significant decrease in the seed number per berry was observed under the black nets (-45%), while a rise (+102%) was observed under the green and gray nets with a parallel increase in the pH of the juice (+13%) and in malic acid (+28%) under the green nets. The berry skin did not show any significant differences in polyphenol and anthocyanin profiles, while the plants that matured in the upper part of the vineyard showed higher level in the berry skin extractable flavan-reactive to vanillin, and total polyphenol. On the other hand, in the seeds grown under green nets an increase in the extractable polyphenol compounds was observed, sign of a delay in seed ripening, with a higher tannin polymerization ratio, preserving the malic acid, and decreasing the acidity of the berry. In conclusion, the use of colored green may be a useful tool against excessive microclimatic warming and / or irradiation. The field internal variability affects much more the ripening dynamics than the nets used.
A second aim was to develop a smart NIR SCiOTM model for polyphenols and the results were in line with the favorable expectations, providing R2 predictions of about 0.74 from the skin and 0.81 from the seeds.
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