Application of fluorescence spectroscopy with multivariate analysis for authentication of Shiraz wines from different regions

With the aim of producing premium wines, it is admitted that moderate environmental stresses may contribute to the accumulation of compounds of interest in grapes. However the ongoing climate change, with the appearance of more limiting conditions of production is a major concern for the wine industry economic. Will it be possible to maintain the vineyards in place, to preserve the current grape varieties and how should we anticipate the adaptation measures to ensure the sustainability of vineyards? In this context, the question of the responses and adaptation of grapevine to abiotic stresses becomes a major scientific issue to tackle. An abiotic stress can be defined as the effect of a specific factor of the physico-chemical environment of the plants (temperature, availability of water and minerals, light, etc.) which reduces growth, and for a crop such as the vine, the yield, the composition of the fruits and the sustainability of the plants. Water stress is in many minds, but a systemic vision is essential for at least two reasons. The first reason is that in natural environments, a single factor is rarely limiting, and plants have to deal with a combination of constraints, as for example heat and drought, both in time and at a given time. The second reason is that plants, including grapevine, have central mechanisms of stress responses, as redox regulatory pathways, that play an important role in adaptation and survival. Here we will review the most recent studies dealing with this issue to provide a better understanding of the grapevine responses to a combination of environmental constraints and of the underlying regulatory pathways, which may be very helpful to design more adapted solutions to cope with climate change.

This study aims to create an updated, agile viticultural climate index (similar to the Winkler Index) by performing in-depth analyses of current and historical data from industry partners in several major winegrowing regions. The Winkler Index was developed in the early twentieth century based on analysis of various grape-growing regions in California. The index uses heat accumulation (i.e. Growing Degree Days) throughout the growing season to determine which grape varieties are best suited to each region. As viticultural regions are increasingly subject to the complexity and uncertainty of a changing climate, a more rigorous, agile model is needed to aid grape growers in determining which cultivars to plant where. For the first phase of this study, 21 industry partners throughout Napa Valley shared historical phenology, harvest, viticultural practice, and weather data related to their Cabernet sauvignon vineyard blocks. To complement this data, berry samples were collected throughout the 2021 growing season from 50 vineyard blocks located throughout 16 American Viticultural Areas that were then analyzed for basic berry chemistry and phenolics. These blocks have been mapped using a Geographic Information System (GIS), enabling analysis of altitude, vineyard row orientation, slope, and remotely sensed climate data. Sampling sites were also chosen based on their proximity to a weather station. By analyzing historical data from industry partners and data specifically collected for this study, it is possible to identify key parameters for further analysis. Initial results indicate extreme variability at a high spatial resolution not currently accounted for in modern viticultural climate indices and suggest that viticultural practices play a major role. Using the structure of data collection and analyses developed for the first phase, this project will soon be expanded to other wine regions globally, while continuing data collection in Napa Valley.

The use of rootstock of American origin has been the classic method of fighting against Phylloxera for more than 100 years. For this reason, it is interesting to establish if different rootstock modifies nutrient composition as well as trace elements content that could be important for determining the traceability of the vine products. A survey of four classic rootstocks (110-Richter, SO4, FERCAL and 1103-Paulsen) and four new ones (M1, M2, M3 and M4) provided by Agromillora Iberia. S.L.U., all of them grafted with the Tempranillo variety, has been carried out during 2019. The eight rootstocks were planted in pots of 500 cc, on three soils with very different characteristics from Castilla-La Mancha (Spain). In the month of July, the leaves were collected and dried in a forced air oven for seven days at 40ºC. Then, the samples were prepared for the analysis determination, carried out by X-Ray fluorescence spectrometry. The results obtained showed that in the case of content in mineral elements in leaf, separated by soil type, we can report the importance of few elements such as Si, Fe, Pb and, especially, Sr. The rootstock does not influence the composition of the vine leaf for the studied elements that are the most important in determining the geochemical footprint of the soil. The influence of the soil can be discriminated according to some elements such as Fe, Pb, Si and, especially, Sr.

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.

The main innovation in the VINIoT service is the joint use of two technologies that are currently used separately: vineyard monitoring using multispectral imaging and deployed terrain sensors. One part of the system is based on the development of artificial intelligence algorithms that are feed on the images of the multispectral camera and IoT sensors, high-level information on water stress, grape ripening status and the presence of diseases. In order to obtain algorithms to determine the state of ripening of the grapes and avoid losing information due to the diversity of the grape berries, it was decided to work along the first year 2020 at berry scale in the laboratory, during the second year at the cluster scale and on the last year at plot scale. Different varieties of white and red grapes were used; in the case of Galicia we worked with the white grape variety Treixadura and the red variety Mencía. During the 2020 and 2021 campaigns, multispectral images were taken in the visible and infrared range of: 1) sets of 100 grapes classifying them by means of densimetric baths, 2) individual bunches. The images taken with the laboratory analysis of the ripening stage were correlated. Technological maturity, pH, probable degree, malic acid content, tartaric acid content and parameters for assessing phenolic maturity, IPT, anthocyanin content were determined. It has been calculated for each single image the mean value of each spectral band (only taking into account the pixels of interest) and a correlation study of these values with laboratory data has been carried out. These studies are still provisional and it will be necessary to continue with them, jointly with the training of the machine learning algorithms. Processed data will allow to determine the sensitivity of the multispectral images and select bands of interest in maturation.