Merging two genomes: a holistic approach to disentangle rootstock-mediated drought and recovery responses

Undesirable compounds in wine, like OTA, biogenic amines, and pesticide residues, can negatively affect its quality and pose health risks to consumers. In addition, an excess of tannins can lead to an unpleasant rise in astringency and bitterness, which makes tannins another target of reduction.

Astringency is one of the leading quality factors in red wines.

When sparkling wine is served, the first attribute perceived is foam1. Bentonite is usually added to wine in order to cause particle flocculation

Downy mildew, caused by Plasmopara viticola, is the most economically impactful disease affecting grapevines. This polycyclic pathogen triggers both primary and secondary infection cycles, resulting in significant yield losses when effective disease control measures are lacking. Over the winter, the pathogen survives by forming resting structures, the oospores, derived from sexual reproduction, which produce the inoculum for primary infections. To optimize grapevine downy mildew control and obtain the desired levels of production while minimizing chemical inputs, it is crucial to optimize the timeframe for fungicide application. Disease forecasting models are useful to identify the infection risk.

Typically, subjective, and visual methods are used by grape growers to assess harvest maturity. These methods may not accurately represent the maturity of an entire vineyard – especially if extensive and representative sampling was not used. New technologies have been investigated for improved harvest management decisions. Spectroscopy methods utilizing the near-infrared region of the light spectrum is one such technology investigated as an alternative to classic methods and particularly the application of hyperspectral imaging (HSI) has recently gained attention in research. HIS is a spectroscopic technique that obtains hundreds of images at different wavelengths collecting spectral data for each pixel in the sample i.e., providing both spectral and spatial data.