High-throughput sequencing analysis based on nematode indices revealed healthier soils of organic vineyards 

Domesticated grapes are assumed to have originated in the Middle East. However, a considerable number of species are native in East Asian countries such as China, Korea and Japan as well. Evidence suggests that a total of seven species and eight varieties have been found to be native to Japan. A wide level variation in morphology, genetic and fruit composition exist in wild grape native to Japan.

In recent years there has been a growing demand for alternative packaging designs in the food industry focused on diminishing the carbon footprint. Despite the environmental advantages of cans versus bottles, the traditional environment of wine has hindered the establishment of less contaminant containers. In this context, the objective of this study was to understand and generate knowledge about consumers´ perception of canned wines in comparison to bottled wines.

Multiple sclerosis (MS) is a multifactorial autoimmune disease associating demyelination and axonal degeneration developing in young adults and affecting 2–3 million people worldwide. Plant polyphenols endowed with many therapeutic benefits associated with anti-inflammatory and antioxidant properties represent highly interesting new potential therapeutic strategies. We recently showed the safety and high efficiency of grape seed extract (GSE), a complex mixture of polyphenolics compounds comprising notably flavonoids and proanthocyanidins, in an experimental autoimmune encephalomyelitis (EAE) mouse model of MS.

The fungicidal effect of UV-C radiation (100-280 nm wavelength) is well known, but its applicability for the control of pathogenic molds of grapes is conditioned by its effect on the host and by the risks inherent in its handling[1].
As an alternative, the effect in vitro of UV-B radiation (280-315 nm) on the main pathogenic molds of grapes has been studied: Botrytis cinerea, Aspergillus niger, Penicillium expansum and Rhizopus stolonifer.

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).