Effect of irrigation in cover cropping vineyards

Vine growth circumstances are becoming warmer and drier because of climate change. Higher temperatures advance ripening to a point in the season less conducive to the production of fine wine, while drought reduces yields (Van Leeuwen et al., 2019). Several wine-producing regions around the world have already recognized threats to their viticultural viability (Santos et al., 2020). An economical and cost-effective strategy for adaptation is the employment of late-ripening, drought-resistant plant material (varieties, clones, and rootstocks).

This study presents the preliminary results obtained in 2022, of the evaluation of three new crossbreed winegrape genotypes and their parental varieties, grown under controlled irrigation (60% ETc) and rainfed conditions in a wine-growing area with scarcity of water and high temperatures (Murcia, southeast Spain). The genotypes MC16 and MC80 were obtained from crosses between the varieties ‘Monastrell’ and ‘Cabernet Sauvignon’, and MS104 from crosses between ‘Monastrell’ and ‘Syrah’ [1]. The objective of this study was to analyse the physiological response and vegetative development of the 6 genotypes under the two irrigation conditions, and to study their effect on the content of soluble sugars and chlorophyll in the leaf.

Vine cane extracts are a valuable byproduct due to their rich content of polyphenols, vitamins, and other beneficial compounds, which can affect and benefit the vine and the grapes. This study aims to evaluate the response of grapevine plants to irrigation with water supplemented with a vine cane extract, both at physiology response and phenolic composition in different parts of the plant (root, trunk, shoot, leaf, and berry).
Cane extract was obtained by macerating crushed pruning residues with warm water (5:1) and pectolytic enzymes. Two-year-old potted plants were irrigated with water (Control) while others were irrigated with cane extracts, either at 1:4 (w/v, cane extract/water; T 1:4) or at 1:8 (w/v, cane extract/water; T 1:8).

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).

This essay was aimed to describe the clonal diversity of Oenococcus oeni in the malolactic fermentation of the carbonic maceration (CM) winemaking. The free and the pressed liquids from CM were sampled and compared to the wine from a standard winemaking with previous destemming and crushing (DC) of grapes [1]. O. oeni strain typification was performed by PFGE as González-Arenzana et al. described (2014) [2]. Results showed that 13 genotypes, referred as to letters, were distinguished from the 49 isolated strains, meaning the genotype “a” the 27%, the “b” the 14%, the “c” the 12%, the “d and e” the 10 % each other, and the remaining ones less than the 8% each one.