Unraveling the complexity of high-temperature tolerance by characterizing key players of heat stress response in grapevine

Traditional drought tolerant varieties such as Cabernet Sauvignon, Monastrell, and Syrah [1], have been used as parents in the grapevine breeding program initiated by the Instituto Murciano de Investigación y Desarrollo Agrario y Medioambiental (IMIDA) in 1997 [2]. This work presents the results of evaluating three new genotypes obtained from crosses between ‘Monastrell’ and ‘Cabernet Sauvignon’ (MC16 and MC80) and between ‘Monastrell’ and ‘Syrah’ (MS104), comparing their performance under conditions of water scarcity and high temperatures with that of their respective parental varieties. For this purpose, the six genotypes were cultivated under controlled irrigation conditions (60% ETc) and rainfed conditions.

Based on historical vine cultivation, the recent development of wine production in Drama wine region (Greece) has led to vine cultivation expansion of white and red varieties. The current cultivation of 500 ha of vineyards is expected to increase in the coming years. Natural terroir units (NTU) have been designed recently to support the production of high quality wines in the region [1]. The aim of this work is to evaluate the relevancy of the proposed NTUs regarding their suitability to produce wines of specific sensorial identity, and to provide guidelines for correct site selection for the expanding wine industry of the region.

Grapes are one of the world’s primary fruit crops, and pruning activities generate high amounts of annual wood wastes [1]. These pruning shoots contain valuable phenolic compounds and could have numerous potential applications [1,2]. Consequently, the aim of this work was to evaluate the physico-chemical properties of vine pruning residues with potential as enological additives. For this purpose, grapevine shoots from 12 varieties grown in Chile were collected during the winter of 2021.

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).

The vineyard has experienced a general increase in yields mainly due to the elevated use of technology which caused a quality loss of grapes in more than one case. A large percentage of the Spanish vineyard is covered by a Denomination of Origin which limits the productive level of the vineyards as one of its regulations. The maximum production limit is a variable characteristic of each vineyard and is not usually regulated by agronomic criteria, and this explains the fact that each vineyard can reach high quality with a totally different yield from that set by the Denomination of Origin.