Determination of quality related polyphenols in chilean wines by absorbance-transmission and fluorescence excitation emission matrix (a-teem) analyses

The development of new generations of multispectral satellites such as Sentinel-2 opens possibilities as to vine water status assessment (Cohen et al., 2019). Based on a three years field campaign, a model of Stem Water Potential (SWP) estimation on vine using four satellite bands in Red, Red-Edge, NIR and SWIR domains was developed (Laroche-Pinel et al., 2021). The model relies on SWP field measures done using a pressure chamber (Scholander et al., 1965), which is a common, robust and precise method to assess vine water status (Acevedo-Opazo et al., 2008). The model was mainly developed from from SWP measures on Syrah N (Laroche Pinel E., 2021).

A large scale monitoring was organized in different vineyards in the Mediterranean region in 2021. 10 varieties amongst the most represented in this area were monitored (Cabernet sauvignon N, Chardonnay B, Cinsault N, Grenache N, Merlot N, Mourvèdre N, Sauvignon B, Syrah N, Vermentino B, Viognier B). The model was used to produce water status maps from Sentinel-2 images, starting from the beginning of June (fruit set) up to September (harvest). The average estimated SWP for each vine was compared to actual field SWP measures done by wine growers or technicians during usual monitoring of irrigation programs. The correlations between mean estimated SWP and mean measured SWP were at the same level than expected by the model. (Laroche Pinel, 2021) The general SWP kinetics were comparable. The estimated SWP would have led to same irrigation decisions concerning the date of first irrigation in comparison with measured SWP.

Acevedo-Opazo, C., Tisseyre, B., Ojeda, H., Ortega-Farias, S., Guillaume, S. (2008). Is it possible to assess the spatial variability of vine water status? OENO One, 42(4), 203.
Cohen, Y., Gogumalla, P., Bahat, I., Netzer, Y., Ben-Gal, A., Lenski, I., … Helman, D. (2019). Can time series of multispectral satellite images be used to estimate stem water potential in vineyards? In Precision agriculture ’19, The Netherlands: Wageningen Academic Publishers, pp. 445–451.
Laroche-Pinel, E., Duthoit, S., Albughdadi, M., Costard, A. D., Rousseau, J., Chéret, V., & Clenet, H. (2021). Towards vine water status monitoring on a large scale using sentinel-2 images. remote sensing, 13(9), 1837.
Laroche-Pinel,E. (2021). Suivi du statut hydrique de la vigne par télédétection hyper et multispectrale. Thèse INP Toulouse, France.
Scholander, P.F., Bradstreet, E.D., Hemmingsen, E.A., & Hammel, H.T. (1965). Sap pressure in vascular plants: Negative hydrostatic pressure can be measured in plants. Science, 148(3668), 339–346.

Mediterranean vineyards have been traditionally grown under rainfed conditions, but in recent decades the irrigated area has increased significantly, seeking to minimize the adverse effects of severe water stress on grape quality and yield. Given the large area occupied by vineyards, and the increasing scarcity of water resources, it is necessary to develop strategies for the optimization and efficient use of water to reduce the risk of its overexploitation. The present study aims at valorizing previous knowledge generated in different research projects by means of a meta-analysis of the effects of water status management on vineyard performance.

The presence of unstable proteins in wines can affect their stability and clarity. Before bottling, winemakers need to be sure that the wine is stable. A large number of stability tests have been proposed, usually based on heating a sample with a specific time-temperature couple. In practice, none is effective to accurately assess the risk of instability. Moreover, the interpretation of the results of these tests changes according to the region.

Aims: Shiraz is the most widely cultivated grape variety in Australia, and is grown under a range of viticultural and climatic conditions. Given its importance to the Australian wine sector, a number of studies have been conducted in recent years which involved a comprehensive assessment of grape composition, in order to objectively predict wine quality and style outcomes.

In 2022, wine production was estimated at around 260 million hl. This high production rate implies to generate a large amount of by-products, which include grape pomace, grape stalks and wine lees. It is estimated that processing 100 tons of grapes leads to ~ 22 tons of by-products from which ~ 6 tons are lees [1]. Wine lees are a sludge-looking material mostly made of dead and living yeast cells, yeast debris and other particles that precipitate at the bottom of wine tanks after alcoholic fermentation. Unlike grape pomace or grape stalks, few strategies have been proposed for the recovery and valorisation of wine less [2].