Phenolic composition profile of cv. Tempranillo wines obtained from severe shoot pruning vines under semiarid conditions

Remote sensing technology captures spectral data beyond the visible range, making it useful for monitoring plant stress. Vis-NIR (Visible-Near Infrared) spectroscopy (400-1000 nm) is commonly used to indirectly assess plant status during drought. One example is the widespread use of normalized difference vegetation index (NDVI) that is strongly linked to green biomass. However, a knowledge gap exists regarding the applicability of this method to all the drought conditions and if it is a direct correlation to the water status of the plant.

The fortress of the Herodium, built towards the end of the first century BCE/ante Cristo, on the orders of Herod the Great, Roman client king of Judea, attests the expansion of Roman influence in the eastern Mediterranean. During archaeological excavations of the Herodium in 2017[1], a winery was discovered on the ground floor of the palace, with an assortment of clay vessels in situ, including large dolia – clay fermentation vessels each capable of fermenting up to 300-400 L of wine. Thanks to the recent progresses in the field of paleogenomics[2], we could analyse the organic material consistent with grape pomace at the bottom of these vessels, by extracting and sequencing the DNA using shotgun metagenomics and targeted capture, aiming for enrichment of DNA from fermentation associated microbes.

Two of the most harmful microbial metabolites for human health that can be present in wines and either fermented or raw foods are biogenic amines (BA) and ochratoxine A (OTA). Winemakers are aware of the need to avoid their presence in wine by using different strategies, one of them is the use of enzymes. Some recombinant laccases have been characterized and revealed as potential tools to degrade these toxic compounds in wine[1], specifically biogenic amines[2].

Secondary (or specialised) metabolites such as terpenes and phenolic compounds are produced by plants for various roles which include defence against pathogens and herbivores, protection against abiotic stress, and plant signalling. Additionally, these metabolites influence grapevine quality traits such as colour, aroma, taste, and nutritional value. However, the biosynthesis of these metabolites is often complex and controlled by multiple genes which in grapevine are predominantly uncharacterised.

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).