Temperature-based phenology modelling for the grapevine 

The production of Port Wine requires the addition of grape spirit to stop the fermentation, ensuring the desired sweetness

The fortress of the Herodium, built towards the end of the first century BCE/ante Cristo, on the orders of Herod the Great, Roman client king of Judea, attests the expansion of Roman influence in the eastern Mediterranean. During archaeological excavations of the Herodium in 2017[1], a winery was discovered on the ground floor of the palace, with an assortment of clay vessels in situ, including large dolia – clay fermentation vessels each capable of fermenting up to 300-400 L of wine. Thanks to the recent progresses in the field of paleogenomics[2], we could analyse the organic material consistent with grape pomace at the bottom of these vessels, by extracting and sequencing the DNA using shotgun metagenomics and targeted capture, aiming for enrichment of DNA from fermentation associated microbes.

Grapevine rootstock is basic to achieve good adaptation of the vine to ground and environment.

Deleterious mutations that severely reduce population fitness are rapidly removed from the gene pool by purifying selection. However, evolutionary drivers such as genetic drift brought about by demographic bottlenecks may comprise its efficacy by allowing deleterious mutations to accumulate, thereby limiting the adaptive potential of populations. Moreover, positive selection can hitchhike mildly deleterious mutations due to linkage caused by lack of recombination. Similarly, in the context of species domestication, artificial selection mimics these evolutionary processes, which can have undesirable consequences for production and resilience. In this study, we evaluated the extent of the accumulation of deleterious mutations and the magnitude of their effects (also known as genetic load) at the whole-genome scale for ca.

Recent developments in satellite technology have yielded a substantial volume of data, providing a foundation for various machine learning approaches. These applications, utilizing extensive datasets, offer valuable insights into Earth’s conditions. Examples include climate change analysis, risk and damage assessment, water quality evaluation, and crop monitoring. Our study focuses on exploiting satellite thermal and multispectral imaging, and vegetation indexes, such as NDVI, in conjunction with ground truth information about soil type, land usage (forest, urban, crop cultivation), and irrigation water sources in the Trentino region in North-East of Italy.