Artificial intelligence (AI)-based protein modeling for the interpretation of grapevine genetic variants

Beihong and Beimei were bred as winemaking cultivars released by Institute of Botany, the Chinese Academy of Sciences in 2008. The cultivars are selected from the population of ‘Muscat Hamburg’ (Vitis vinifera) ×V. amurensis. They are extended to most provinces in North of China because they have strong resistance to cold and disease and need not be buried in soil in winter. To better understand the effect of cropload on volatile compounds during wine-making, we surveyed volatiles composition and content of different cropload level in 3-years-old ‘Beihong’ and ‘Beimei’ vines which planted in east foot of Helan mountain of Ningxia (EHN).

Ellagitannins (ETs) have been reported to be the main phenolic compounds found in oak wood. These compounds, belonging to the hydrolysable tannin class of polyphenols, are esters of hexahydroxydiphenic acid (HHDP) and a polyol, usually glucose or quinic acid. They own their name to their capacity to be hydrolysed and liberate ellagic acid and they have an impact on astringency and bitterness sensation, which is strongly dependant on their structure. The toasting phase is particularly crucial in barrels fabrication and influences wood composition.

Wine, a sensitive and intricate agricultural product, is being affected by climate change, which accelerates grapevine phenological stages and alters grape composition and ripening. This influences the synthesis of key aroma compounds, shaping wine’s sensory attributes [1]. The complex aroma profile, resulting from compound interactions, presents a metabolomics challenge to identify these indicators and their environmental change responses, which is being addressed using diverse analytical techniques.

There is an increasing need in agriculture to adopt site-specific management (precision farming) because of economic and environmental pressures. Geophysical on-the-go sensors, such as the ARP (Automatic Resistivity Profiling) system, can effectively support soil survey by optimizing sampling density according to the spatial variability of apparent electrical resistivity (ER).

The hot and dry climate of the Demarcated Region of Douro (DRD), Portugal, particularly during the summer, induces soil water deficits that influence the growth and development of grapevines.