Climate has posed serious impacts on the growth, development, and quality formation of wine grapes, particularly in conventional viticulture. Meteorological factors—including temperature, solar radiation, and precipitation—play a pivotal role in the physiological and metabolic processes of grape berries. There are also direct influences on the accumulation of the key secondary metabolites, such as flavonoids and aroma compounds, leading to the wine flavor, aroma, and overall quality. It is often required for accurate and reliable predictive models to clarify the relationships between meteorological parameters and grape metabolic responses against global warming and an increasing frequency of extreme weather events. Adaptive cultivation can be expected to advance precision viticulture. Existing prediction models are also limited to the hyperparameter sensitivity, generalization, and proneness to local optima. In this study, a domain-specific dataset was constructed with the meteorological indicators and metabolomic profiles of four wine grape varieties over multiple developmental stages. A forecasting framework (named IDBO-XGBoost) was also proposed to synergistically combine an improved dung beetle optimizer (IDBO) with the eXtreme gradient boosting (XGBoost) algorithm. Among them, the IDBO algorithm incorporated two enhancements: an osprey global exploration to strengthen the population diversity for less premature convergence, and another adaptive t-distribution mutation operator to balance global and local exploitation during the iterative process. The algorithm significantly improved the optimization efficiency, convergence speed, and solution quality. Extensive validation experiments were performed on nine benchmark test functions. The IDBO outperformed the standard Dung Beetle Optimizer in terms of precision and stability after optimization. Once applied to predict the accumulation of 12 key metabolite groups in wine grapes—including flavonols, flavanols, free and bound forms of terpenoids, norisoprenoids, and carbonyl compounds—the IDBO-XGBoost model demonstrated the superior predictive performance over all datasets. The better performance was achieved with an average increase of 8.5% in the coefficient of determination (R²), along with the average reductions of 9.4%, 7.7%, and 12.1% in the mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage error (MAPE), respectively, compared with the baseline XGBoost model. The prediction accuracy and robustness were significantly enhanced. Furthermore, the contribution rate of each meteorological feature was quantified to explore the underlying mechanisms using SHAP (Shapley Additive exPlanations) interpretability analysis. The predictions were obtained for the climatic variables' influence on the metabolic outputs. For instance, the moderate temperatures (DT_20-25) were positively correlated with the flavonol accumulation, whereas the high temperatures (DT₄₀) exhibited an inhibitory effect. Solar duration and effective accumulated temperature shared the divergent effects on the free and bound terpenoids, indicating the enzyme-mediated metabolic shifts. Additionally, the variety-specific effects were also observed on some influencing factors, such as the precipitation and temperature ranges, indicating the genetic dependency of the environmental responses. As such, an intelligent computational framework was provided to accurately predict the wine grape metabolic traits under varying climatic conditions. The ecophysiological mechanisms were determined to govern the grape quality. The interpretable machine learning can then bridge the gap between data-driven modeling and biological properties in the decision-making on the vineyard cultivation. The findings can hold substantial practical significance to mitigate the impacts of climate under grape cultivation, in order to enhance the resource use efficiency in the sustainable wine industry.

In order to clarify the significance of the division of small wine production regions in the eastern foothill of Helan Mountain in Ningxia, the free and bound aroma substances in the mature fruits of two wine grape varieties from four vineyards in the eastern foothill of Helan Mountain were determined by gas chromatography-mass spectrometry (GC-MS), and the influence of different parcels on the aroma composition of wine grapes was analyzed. The results showed that the soils of these four parcels were all sandy loam. The soil of the Gaojiazha parcel contained more clay, the Zhihui parcel was close to sandy soil, and the soil texture of the Huaxi and Jinshan parcels was between the Zhihui and Gaojiazha parcels. The 100-berry mass, 100-berry volume and titratable acid content of Chardonnay grapes from the Zhihui parcel were significantly higher than those of Chardonnay grapes from the Gaojiazha parcel. No significant variation in the 100-berry mass or 100-berry volume of ‘Cabernet Sauvignon’ berries was found among the different parcels. However, ‘Cabernet Sauvignon’ berries from the Jinshan parcel had higher soluble solids content but lower titratable acid content. The types and contents of aroma substances in ‘Cabernet Sauvignon’ and ‘Chardonnay’ berries were significantly different among these four parcels, mainly in terms of the amounts of C₆/C₉, norisoprenoids, esters and terpenes. ‘Chardonnay’ grapes from the Zhihui parcel contained more free (E)-2-hexenal, β-damasone and bound octanoic acid ethyl ester, and had stronger floral, fruity and green aromas based on odor activity values (OAVs). ‘Cabernet Sauvignon’ grapes from the Jinshan parcel contained more free (E)-2-hexenal and (Z)-3-hexen-1-ol, and had a stronger green aroma based on OAVs.

In the present research, the effects of grafting onto six rootstocks including ‘1103P’, ‘140R’, ‘101-14’, ‘3309C’, ‘SO4’ and ‘Beta’ on the accumulation of aromatic compounds in ‘Tannat’ (Vitis vinifera L.) grapes from the 2016 and 2017 vintages were studied by using gas chromatography-mass spectrometry (GC-MS). The results showed that the effect of different rootstocks on grape aroma was more significant for the 2016 vintage. ‘1103P’ could significantly increase the content of C₆/C₉ compounds in ‘Tannat’ grapes and free hexanol, (Z)-3-hexenol, (E)-2-hexenal and 1-hexanal were the characteristic C₆/C₉ compounds; ‘140R’ was beneficial to the synthesis of esters in ‘Tannat’ grapes, while ‘3309C’ showed a tendency to reduce the contents of C₆/C₉ compounds, esters and volatile phenols in ‘Tannat’ grapes. Both ‘Beta’ and ‘SO4’ increased the content of terpenes in ‘Tannat’ grapes from both vintages, and ‘SO4’ also could significantly increase the content of C₁₃-norisoprenoids in ‘Tannat’ grapes, with the characteristic ones being free (E)-β-damasone and (Z)-β-damasone. The research results provide a reference for the selection and application of the grafting rootstocks for ‘Tannat’ grapes in practical production.

In this study, the wine grape cultivar Vitis vinifera L. cv. ‘Petit Verdot’ was used as the scion for ‘101-14’, ‘5BB’, ‘SO4’, ‘Beta’ and ‘1103P’ rootstocks as well as self-rooted control. The volatile components of ‘Petit Verdot’ grape berries from the commercial harvest period in 2016-2017 were analyzed by using head space solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS). The results showed that the climate differences between vintages were the decisive factor affecting the contents of volatile components in ‘Petit Verdot’ grapes, which were also significantly affected by rootstocks. Compared with the self-rooted control, all five rootstocks significantly increased the contents of C₆/C₉ compounds in grapes. ‘5BB’ significantly increased the contents of C₁₃-norisoprenoids and terpenes, ‘1103P’ significantly increased the content of bound carbonyl compounds, ‘101-14’ significantly increased the content of free carbonyl compounds and significantly decreased the content of bound C₁₃-norisoprenoids, ‘Beta’ significantly increased the contents of bound C₁₃-norisoprenoids and terpenes, and ‘SO4’ significantly increased the contents of C₁₃-norisoprenoids, bound carbonyl compounds and free terpenes. Orthogonal partial least squares-discriminant analysis (OPLS-DA) results showed that C₆/C₉ compounds, such as (E)-2-hexenal, (Z)-2-hexenal and hexanal, were the common differential volatile components to differentiate the grafted grapes from the self-rooted ones. In general, grafting ‘Petit Verdot’ onto the rootstock ‘5BB’ in Beijing was conducive to the accumulation of terpenes and C₁₃-norisoprenoids in grapes during harvest.

Aging in oak barrels is widely used in enology which could bring flavor changes and aromatic complexity to wines. In the present study, the aroma compounds were analyzed from the ‘Merlot’ dry red wines, which were fermented in two types of fermenters (stainless steel tank and rotated oak barrel) and aged in six types of oak barrels (three geographic origins × two toasting degrees) for different time (0, 3, 6 and 9 months, respectively). Results showed that 30 volatiles were associated with barrels and increased during oak aging. The fermenters could influence the intensities of the toast, leathery, smoky, fruity, floral and caramel aromas. The concentration of whisky lactone, eugenol, cis-isoeugenol, and the intensities of the toast and spicy aromas were highest in the wines aged in American oak and were lowest in the wines aged in French oak barrels. The concentrations of guaiacol, syringol, trans-isoeugenol, furfural alcohol, vanilla, cis-whisky lactone enabled the medium toasting barrels to be distinguished from the light toasting ones. The compounds originating from the barrels could be used to distinguish the types of different barrels, but the other general grape-derived and fermentation-derived volatiles could not. The fermenters, oak species and toasting degrees of the barrels all had significant effects on the aroma profiles of the aged ‘Merlot’ dry red wines, but the influence of the geographic origin was not obvious.

Protein haze was one of the main causes of the instability of white wines. Proteins that caused haze or precipitation in white wines mainly came from grape fruits, and their compositions and contents were affected by many factors such as fruit diseases, harvesting methods and water stress. Unstable wine proteins were usually pathogenesis-related (PR) proteins of grapes, mainly chitinases and thaumatin-like proteins (TLPs), which had lower isoelectric point (pI) and smaller molecular weight, and were highly resistant to the low pH values of wines and the protease hydrolysis during fermentation. At present, the technology of protein stabilization and clarification in white wines mainly included bentonite fining, heat treatment, enzymatic hydrolysis, polysaccharide treatment and ultrafiltration methods. Among them, the most commonly used method was bentonite treatment. In this paper, the research progresses of the origin, mechanism and influencing factors of the unstable proteins in white wines were summarized, and the applications, advantages and disadvantages of various clarification techniques were also concluded, in order to provide some support for the theoretical and technological research of the protein stability in white wines in the future.