Characterized one of the largest collections of grapevine rootstocks (non-vinifera)

In Ancient Egypt, wine was a luxury product consumed mainly by the upper classes and the royal family and offered to gods in daily religious rituals in the temples. Since the Predynastic (4000-3100 BC) period, wine jars were placed in tombs as funerary offerings. From the Old Kingdom (2680-2160 BC) to the Greco-Roman (332 BC-395 AD) period, viticulture and winemaking scenes were depicted on the private tombs’ walls. During the New Kingdom (1539-1075 BC), wine jars were inscribed to indicate: vintage year, product, quality, provenance, property and winemaker’s name and title.

Aim: Wine quality and character are defined in part by the terroir in which the grapes are grown. Metabolomic techniques, such as nuclear magnetic resonance (NMR) spectroscopy and inductively coupled plasma mass spectrometry (ICP-MS), are used to characterise wines and to detect wine fraud in other countries but have not been extensively trialled in Australia. This study aimed to investigate the use of ICP-MS and NMR to characterise a selection of Pinot noir wines.

Water tolerance in plants is often associated with the accumulation of osmotic protectants, which are secondary metabolites that can help the plant to cope with water stress. One of the key osmotic protectants is a sugar called Raffinose, which is synthesized by a family of enzymes called Raffinose synthases. In this work, we focused on one of these enzymes, VviRAF2, which is a gene that shows different expression levels and genetic variants (SNPs) among different grapevine cultivars, ranging from tolerant to susceptible to water stress, and the transcription factors that may regulate the expression of this gene family.

Global climate change is exerting an influence on vine phenology, leading to a decoupling of technological and phenolic maturity of grapes. This results in the modification of berry chemical composition, which can translate into wines with excessive astringency. The addition of mannoproteins (MP) to wine has been proposed as a way of mitigating this problem, since some studies have shown that MPs can modulate wine astringency. However, the mechanism underlying the astringency modulation effect of MPs is not well known and it seems to be dependent on the compositional and structural characteristics of the MP.

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).