Application of uv-led in wine as an alternative to sulphur dioxide

Globalisation and climate change have radically transformed world wine production upsetting the established order of wine ecologies. Ecological risks and the future of traditional agricultural systems are widely debated in anthropology, but very little is understood of the particular challenges posed by climate change to viticulture which is seen by many as the canary in the coalmine of global agriculture. Moreover, wine as a globalised embedded commodity provides a particularly telling example for the study of climate change having already attracted early scientific attention. Studies of climate change in viticulture have focused primarily on the production of systematic models of adaptation and vulnerability, while the human and cultural factors, which are key to adaptation and sustainable futures, are largely missing. Climate experts have been unanimous in recognising the urgent need for a better understanding of the complex dynamics that shape how climate change is experienced and responded to by human systems. Yet this call has not yet been addressed. Climate ethnography, coined by the anthropologist Susan Crate (2011), aims to bridge this growing disjuncture between climate science and everyday life through the exploration of the social meaning of climate change. It seeks to investigate the confrontation of its social salience in different locations and under different environmental guises (Goodman 2018: 340). By understanding how wine producers make sense of the world (and the environment) and act in it, it proposes to focus on the co-production of interdisciplinary knowledge by identifying and foreshadowing problems (Goodman 2018: 342; Goodman & Marshall 2018). It seeks to offer an original, transformative and contrasted perspective to climate change scenarios by investigating human agency -individual or collective- in all its social, political and cultural diversity. An anthropological approach founded on detailed ethnographies of wine production is ideally placed to address economic, social and cultural disruptions caused by the emergence of these new environmental challenges. Indeed, the community of experts in environmental change have recently called for research that will encompass the human dimension and for more broad-based, integrated through interdisciplinarity, useful knowledge (Castree & al 2014). My paper seeks to engage with climate ethnography and discuss what it brings to the study of wine environmental futures while exploring the limitations of the anthropological environmental approach.

Currently, the main goal of agriculture is to promote the resilience of agricultural systems in a sustainable way through the improvement of use efficiency of farm resources, increasing crop yield and quality under climate change conditions. This last is expected to drastically modify plant growth, with possible negative effects, especially in arid and semi-arid regions of Europe on the viticultural sector. In this context, the monitoring of spatial behavior of grapevine during the growing season represents an opportunity to improve the plant management, winegrowers’ incomes, and to preserve the environmental health, but it has additional costs for the farmer. Nowadays, UAS equipped with a VIS-NIR multispectral camera (blue, green, red, red-edge, and NIR) represents a good and relatively cheap solution to assess plant status spatial information (by means of a limited set of spectral vegetation indices), representing important support in precision agriculture management during the growing season. While differences between UAS-based multispectral imagery and point-based spectroscopy are well discussed in the literature, their impact on plant status estimation by vegetation indices is not completely investigated in depth. The aim of this study was to assess the performance level of UAS-based multispectral (5 bands across 450-800nm spectral region with a spatial resolution of 5cm) imagery, reconstructed high-resolution satellite (Sentinel-2A) multispectral imagery (13 bands across 400-2500 nm with spatial resolution of <2 m) through Convolutional Neural Network (CNN) approach, and point-based field spectroscopy (collecting 600 wavelengths across 400-1000 nm spectral region with a surface footprint of 1-2 cm) in a plant status estimation application, and then, using Bayesian regularization artificial neural network for leaf chlorophyll content (LCC) and plant water status (LWP) prediction. The test site is a Greco vineyard of southern Italy, where detailed and precise records on soil and atmosphere systems, in-vivo plant monitoring of eco-physiological parameters have been conducted.

Purpose of this research is to quantitatively assess the mineral component of vineyard soils, with particular attention to the mineralogical analysis of clays, which represent an element of high importance in the vineyard culture as well as in general agriculture. An X-ray diffraction (XRD) / thermogravimetric (TG) multi-technique analytical approach was developed, tested on soil samples taken from vineyards around the world. This codified analytical procedure was necessary to obtain precise qualitative and quantitative mineralogical data, globally comparable to distinguish the geopedological identity of the vineyards. Soil samples from vineyards of various locations were analysed, in very different geological conditions. The bulk-rock quantitative phase analysis (QPA) was obtained by the Rietveld method while the detailed composition of the clay-sized fraction was determined by modelling of the oriented X-ray diffraction patterns. The research provided a precise classification of the mineral component of soils, distinguishing the mineral phases of the clays and the so-called mixed-layer clay minerals. We found that the content in mixed layers can be directly correlated with the water retention and the cation exchange capacity ​​of the soil, while the presence of other clayey minerals and phyllosilicates in this research did not affect this CEC parameter, which codes the fertility level of the soils. The study demonstrates that terroir, in particular soils formed in complex or very different geological conditions, can only be effectively interpreted by properly analysing its mineral phases, in particular the mixed-layer clay component. These are characteristic abiotic ecological indicators, which may have specific eco-physiological influences on the plant.

45 non irrigated vineyards distributed in the DO (Denomination) Pla i Llevant de Mallorca and the DO Binissalem Mallorca were used to investigate the characteristics of production and quality and their relationships certain environmental factors and cultural practices. The grape varieties investigated are autochthonous to the island of Mallorca, Manto Negro and Callet as red and Prensal Blanc as white. All plants were measured for four consecutive years in the main production and quality parameters. Among the environmental factors, the type of soil has been studied, more specifically its water retention capacity, the planting density, the age of the vineyard and the level of viral infection. The presence or absence of virus seems to have no effect on any component studied in the varieties studied. For the white variety Prensal Blanc age is negatively correlated with production and the number of bunches, nevertheless it does not cause any effect on the required quality parameters. However, for the red varieties Callet and Manto Negro, the age of the plantation is the variable that best correlates with the quality parameters, therefore the old vines should be the object of preservation by the viticulturists and winemakers in order to guarantee its contribution to the quality of the wines made with these varieties.

Barolo DOCG is an economically important wine producing region in Northwest Italy. It is a small region of approximately 70 km2 gross area. The topography is very complex with steep sloped hills ranging in elevation from below 200 m to 550 m. Barolo DOCG wine is made exclusively from the Nebbiolo grape. Bioclimatic indexes are often used in viticulture to gain a better understanding of broader climate trends which can be compared temporally and geographically. These indexes are also used for identifying potential phenological timing, growing region suitability, and potential risks associated with expected climatic changes. Understanding how topography influences bioclimatic indexes can help with understanding of mesoscale climate behaviour leading to improved decision making and risk management strategies. The average monthly maximum and minimum temperatures, the Cool Night Index, the Huglin Index, and the monthly diurnal range (from July to October) were calculated using data from 45 weather stations within a 40 km radius of the Barolo DOCG growing area between the years 1996 and 2019. Linear and multiple regression models were developed using independent variables (elevation, aspect, slope) extracted from a digital elevation model to identify significant relationships. Bioclimatic indexes were then kriged with external drift using independent variables that showed significant relationships with the bioclimatic index using a 100 m resolution grid. The maximum monthly temperatures and the Huglin Index showed consistent significant negative relationships with elevation in all years. The minimum monthly temperatures showed no relationship with elevation but in some months a small but significant relationship was observed with aspect. Due to the lack of a relationship between minimum monthly temperatures and elevation compared to the significant relationship between maximum monthly temperatures and elevation, monthly diurnal range had a negative relationship with elevation.