Late pruning modifies leaf to fruit ratio and shifts maturity period, affecting berry and wine composition in Vitis vinífera L. cv. ‘Malbec’ in Mendoza, Argentina

Morgani, Marianela Bustos; Fanzone, Martín; Peña, J. Perez; Sari, Santiago; Gallo, Agustina; Tournier, Mariana Gómez; Prieto, Jorge

doi:10.1016/j.scienta.2023.111861

Cited by 5 publications

(2 citation statements)

References 56 publications

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“…Meanwhile, in Vitis vinífera L. cv. 'Malbec', the yield of fresh leaves after pruning treatments increased over five folds compared with control, and the contents of carbohydrates also increased significantly (p < 0.05) [10]. The net photosynthetic rate (Pn), transpiration (Tr), and stomatal conductance (Gs) resulted in an increase in oil in Cinosi N.'s [11] study under summer pruning treatment.…”

Section: Introductionmentioning

confidence: 91%

Effect of Pruning Treatment on Growth Characteristics and Metabolites in Eucommia ulmoides Oliver (E. ulmoides)

Yang,

Xie,

et al. 2023

Forests

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The effect of pruning treatments on growth, photosynthesis characteristics, and metabolites were was studied in Eucommia ulmoides Oliver (E. ulmoides). The experiment was carried out from March–August 2019. Three treatments were used: non-pruned trees (CK), a height of 20 cm above the top edge of the flowerpot (T1), and a height of 10 cm above the top edge of the flowerpot (T2). The results showed that the branches branch number, leaves leaf number, and stem diameter increased significantly (p < 0.05) in pruning treatments compared with CK. Similarly, the net photosynthetic rate (Pn), stomatal conductance (Gs), transpiration rate (Tr), maximum photosynthetic efficiency (Fv/Fm), and non-photochemical quenching coefficient (NPQ) increased significantly in pruning treatments (p < 0.05). Interestingly, the contents of Chl a, Chl b, Chl, Car, and the rate between the Chl a content and the Chl b content increased significantly (p < 0.05) in T2, respectively. These verified that it was a better way to enhance the plants growth of E. ulmoides for pruning treatments. The GC-MS analysis showed that 36 different primary metabolites were identified, including 11 sugars, 13 acids, 5 alcohols, and 7 other compounds, the relative content of their metabolites were was higher in the T2 treatment than that in the T1 treatment, which was mainly concentrated in four main enrichment pathways (Galactose metabolism; Citrate cycle; Glyoxylate and dicarboxylate metabolism; and starch and sucrose metabolism) via KEGG analysis. Meanwhile, correlation analysis showed there were was a positive correlation between the accumulation of D-Galactose, D-Mannose, Succinic acid, and photosynthetic pigment content, and the rate of photosynthesis in T2 treatment (p < 0.05). The pruning height above the top edge of the flowerpot changed the accumulation of primary metabolites and promoted plant regeneration ability in E. ulmoides. Finally, the yield of main secondary metabolites from leaves (Genipin, Geniposide, Geniposidic acid, and Pinoresinol diglucoside) were was increased in pruning treatments by UPLC analysis. It provided a reference for the directional ecological cultivation of E. ulmoides.

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Section: Introductionmentioning

confidence: 91%

Effect of Pruning Treatment on Growth Characteristics and Metabolites in Eucommia ulmoides Oliver (E. ulmoides)

Yang,

Xie,

et al. 2023

Forests

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“…The tannin content in wine grapes increases with maturation. However, the increase in tannin content is influenced by various factors, such as grape varieties, the growth environment, and cultivation practices [ 8 , 9 , 10 ]. Therefore, monitoring tannin levels is crucial for timely adjustments in cultivation management, intervention in grape growth, and determining the optimal harvest period [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

Rapid Detection of Tannin Content in Wine Grapes Using Hyperspectral Technology

Zhang,

Wu,

Wang

et al. 2024

Life

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Wine grape quality is influenced by the variety and growing environment, and the quality of the grapes has a significant impact on the quality of the wine. Tannins are a crucial indicator of wine grape quality, and, therefore, rapid and non-destructive methods for detecting tannin content are necessary. This study collected spectral data of Pinot Noir and Chardonnay using a geophysical spectrometer, with a focus on the 500–1800 nm spectrum. The spectra were preprocessed using Savitzky–Golay (SG), first-order differential (1D), standard normal transform (SNV), and their respective combinations. Characteristic bands were extracted through correlation analysis (PCC). Models such as partial least squares (PLS), support vector machine (SVM), random forest (RF), and one-dimensional neural network (1DCNN) were used to model tannin content. The study found that preprocessing the raw spectra improved the models’ predictive capacity. The SVM–RF model was the most effective in predicting grape tannin content, with a test set R2 of 0.78, an RMSE of 0.31, and an RE of 10.71%. These results provide a theoretical basis for non-destructive testing of wine grape tannin content.

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