Machines and fire: developing a rapid detection system for grapevine smoke contamination using NIR spectroscopy and machine learning modelling

A major topic in viticultural research is the analysis of the relationships between climate on one side, and grape and wine quality on the other. It is well known that climatic conditions

Introduction increasing sustainability is essential and a societal challenge, requiring fundamental changes in behaviour and attitudes. This applies to both producers and consumers. For the wine industry in particular, such a change is a major challenge. An eip-agri research project is evaluating the introduction of a returnable glass system in the german wine industry as a key solution for increasing sustainability. Given the need for change associated with a returnable system, the project is theoretically grounded in systems innovation, as this approach provides solutions for complex, transformative change.

In the Champagne’s region, a complete press cycle is a series of pressure increases (squeezes) and decreases (returns). After alcoholic fermentation, the two wines (the “cuvee” and the “tailles”) obtained from grape juice fractions exhibit strong differences for numerous characteristics. Nevertheless, there is no study of the impact of the press cycle, followed after each pressure increase (22-28 steps), on wine colour, current analyses and phenolic composition. So, the aim of this study (vintage 2020) was to investigate the composition changes of Pinot noir and Pinot meunier wines, produced from 22-28 grape juices isolated for each complete pressing cycle.

Germicidal ultraviolet-C (UV-C) light has shown promising results for suppression of several plant-pathogenic microorganims, including Erysiphe necator, which attacks grapevine. In Washington State the majority of winegrape production is in a semi-arid steppe environment, with historically low powdery mildew disease pressure, making it a promising area to deploy UV-C as a disease management tool. Trials focusing on UVC application timing and frequency will assist in developing regionally-appropriate application recommendations for eastern Washington State.

The project VINIoT pursues the creation of a new technological vineyard monitoring service, which will allow companies in the wine sector in the SUDOE space to monitor plantations in real time and remotely at various levels of precision. The system is based on spectral images and an IoT architecture that allows assessing parameters of interest viticulture and the collection of data at a precise scale (level of grape, plant, plot or vineyard) will be designed. In France, three subjects were specifically developed: evaluation of maturity, of water stress, and detection of flavescence dorée. For the evaluation of maturity, it has been decided first to work at the berry scale in the laboratory, then at the bunch scale and finally in the vineyard. The acquisition of the spectral hyperstal image as well as the reference analyzes to measure the maturity, were carried out in the laboratory after harvesting the berries in a maturity monitoring context. This work focuses on a case study to predict sugar content of three different grape varieties: Syrah, Fer Servadou and Mauzac. A robust method called Roboost-PLSR, developed in the framework of this work (Courand et al., 2022), to improve prediction model performance was applied on spectra after the acquirement of hyperspectral images. Regarding the evaluation of water stress, to work with a significant variability in terms of water status, it has been worked first with potted plants under 2 different water regimes. The facilities have allowed the supervision of irrigation and micro-climatic conditions. The regression models on agronomic variables (stomatal conductance, water potential, …) are studied. To detect flavescence dorée, the experimental plan has consisted of work at leaf scale in the laboratory first, and then in the field. To detect the disease from hyper-spectral imaging, a combination of multivariate curve resolution-alternating least squares (MCR-ALS) and factorial discriminant analysis (FDA) was proposed. This strategy proved the potential towards the discrimination of healthy and infected leaves by flavescence dorée based on the use of hyperspectral images (Mas Garcia et al., 2021).