Fast, and full microbiological wine analysis using triple cellular staining.

The implementation of food safety assurance systems in wineries involves ensuring that the wines produced do not pose a risk to consumer health and are therefore free from harmful substances, such as those that may be incorporated during the production process (pesticides, additives, etc.), allergens or mycotoxins.

To alter the vineyard microclimate and produce quality wine under a semi-arid climate, black geotextile inter-row mulch (M) was applied for two vintages (2016-2017). The grapes were sampled at three growing stages to conduct the untargeted metabolome and transcriptome analysis. The upregulated genes related to photosynthesis and heat shock proteins confirmed that M weakened the total light exposure and grapes suffered severe heat stress, resulting in lower sugar and higher acids at harvest. The integration of metabolome and transcriptome analysis identified the key genes responsible for the enhancements in phenylalanine, glutamine, ornithine, arginine, and C6 alcohol concentrations, and the downward trend in ε-viniferin, anthocyanins, flavonols, terpenes and norisoprenoids concentrations in M grapes.

Les travaux menés, dans le cadre du programme départemental pour la connaissance et la valorisation des terroirs viticoles, sur l’aire A.O.C. Coteaux du Languedoc / Pic Saint-Loup ont permis d’appliquer à l’échelle d’une Appellation d’Origine Contrôlée (13 communes), une méthodologie d’étude axée sur les aspects sol/climat/topographie qui concourent à l’identification des terroirs naturels, facteurs de typicité des vins.

The spatial distribution of powdery mildew is often heterogeneous between neighboring plots, with higher disease pressure in certain places

Modern grapevine breeding programs have overcome many challenges using genomic selection, which has allowed breeders to make targeted selections at earlier stages in the breeding process. However, the cost of genetic testing may present a burden for some programs, and markers often struggle to accurately predict quantitative traits. Recent advances in high throughput, high-dimensional data have provoked investigation into the use of high-dimensional phenomics as a low-cost addition to the grape breeder’s toolkit that may offer advantages in predicting quantitative traits. High-dimensional secondary trait (HDST) data has been employed in annual crops for prediction of agriculturally important traits such as yield.