A novel dataset and deep learning object detection benchmark for grapevine pest surveillance

AIM: Color is one of the main qualitative parameters of a wine. As a matter of fact, immediately after having opened a bottle of wine, color, even before aroma and taste, is the first sensorial parameter to be evaluated by the consumer It can change according to various factors depending on the characteristics of the grapes or on the different production and storage processes. This study aims to evaluate the color differences on Lugana wines that are fermented with different yeast and nitrogen supply.

The Intergovernmental Panel on Climate Change (IPCC) forecasts an increase in global temperature and a decrease in relative humidity (RH) in the coming decades, which may have implications for berry ripening and composition.

s it is well known, myo and scyllo-inositol are two characteristic sugars of grape must and, for this reason, their quantification has been proposed to control the authenticity of the concentrated and rectificated grape must.

This study aimed to determine mineral composition in red wine obtained from cv. Teran (Vitis vinifera L.), autochtonous Croatian grape variety. Six different vinification treatments, including the control treatment (7-day standard maceration), were performed to study the effects of: 48-hour pre-fermentative mash cooling (8 °C) followed by prolonged post-fermentative maceration of 13 days (C15), 28 days (C30), and saignée technique (juice runoff) proceeded with prolonged post-fermentative maceration of 13 days (CS15); and effect of 48-hour heating (50 °C) followed by prolonged post-fermentative maceration of 13 days (H15) and 28 days (H30) on macro- and microelements in wine.

Air temperature is the key driver of grapevine phenology and a significant environmental factor impacting yield and quality for a winegrape growing region. In this study the optimal downscaled CMIP5 ensemble for computing thegrowing season average temperature (GST) viticulture climate classification index was determined to spatially compute on a decadal basis predictions of the GST climate index and the grapevine sugar ripeness (GSR) model for Pinot Noir throughout the Willamette Valley (WV) American Viticultural Area (AVA). Forecasts for average temperature and a 220 g/L target sugar concentration level were computed using daily Localized Constructed Analogs (LOCA) downscaled CMIP5 historic and Representative Concentration Pathways (RCP) future climate projections of minimum and maximum daily temperature. We explore spatiotemporal trends of the GST climate classification index and Pinot Noir specific applications of the GSR phenology model for the WV AVA. Spatiotemporal computations of the GST climate index and Pinot Noir specific applications of the GSR model enable the opportunity to explore relationships between their computed values with one intent being to provide updated GST ranges that better align with current temperature-based modeling understanding of Pinot Noir grapevine phenology and the viticultural application of LOCA CMIP5 climate projections for the WV AVA. The Pinot Noir specific applications of the GSR model or the GST index with updated bounds indicate that the percent of the WV AVA area suitable for Pinot Noir production is currently at or near its peak value in the upper 80s to lower 90s of this century.