Metabolomic profiling of heat-stressed grape berries 

Wine, a sensitive and intricate agricultural product, is being affected by climate change, which accelerates grapevine phenological stages and alters grape composition and ripening. This influences the synthesis of key aroma compounds, shaping wine’s sensory attributes [1]. The complex aroma profile, resulting from compound interactions, presents a metabolomics challenge to identify these indicators and their environmental change responses, which is being addressed using diverse analytical techniques.

Recently, foliar treatments with mineral-based compounds have shown positive effects on grapevine production by protecting grape from thermal excesses and reducing the decoupling between technological and phenolic maturity caused by climate change. Unraveling the effect of mineral particle applications on grape-associated microbes is pivotal for successful wine processing, due to the influence of the microbiota on wine composition and stability. To our knowledge, this is the first work that comprehensively studied the effects of kaolin and chabasite-rich zeolitites treatments on grape-related microorganisms (by real-time PCR quantification of total fungi, Hanseniospora uvarum, Metschnikowia pulcherrima, plant-associated bacteria and lactic acid bacteria), the expression of genes related to the flavonoid biosynthesis (PAL1, CHS1, F3H2, DFR, LDOX, UFGT, MYBA1, GST4, FLS4 genes) and the berry composition (°Brix, pH, acidity and anthocyanin concentrations) in cv. Sangiovese during ripening in two growing seasons (2019 and 2020).

The presence of undesirable compounds in wines, such as OTA, biogenic amines and pesticides residues, affects wine quality and can cause health problems for the consumer. The main tool that a winemaker has to reduce their content in the wine is fining. However, some of the fining agents commonly used in the winery can cause allergies or even increase the protein content in the wine, increasing the turbidity. To avoid these problems, the use of plant fibers may be an alternative, such as those from grape pomace[1] or other plant origins.

The main objective of the work was to develop a simple, robust and selective analytical tool that allows predicting the authenticity of Tempranillo wines from DOCa Rioja. The techniques of voltammetry and absorbance-transmission and fluorescence excitation emission matrix (A-TEEM) spectroscopy have been applied in combination with machine learning (ML) algorithms to classify red wines from DOCa Rioja according to region (Alavesa, Alta or Oriental) and category (young, crianza or reserva).

One of the most important effects of climate change in wine-growing areas is the advance of phenological stages, especially concerning early berry ripening. In the hottest seasons, this results in a lack of synchrony between sugar and phenolic ripeness. In order to cope with this fact, a general effort is being made by researchers and growers aiming at delaying ripening through different strategies. One of the proposed approaches is the application of elicitors. This study aims to assess the effect at the transcriptomic level of application of three elicitors (Vitalfit, Fruitel, and Protone) in Tempranillo.