Inhibition of reductive characters in wine by cu-organic acids: predicting the duration of protection

All techniques usually used to assay proteins was not reliable in vegetable extract due to interferences with the components included in extracts like polyphenols, tanins, pectines, aromatics compounds. Absorbance at 280nm, Kjeldhal assay, Biuret and Lowry methods, Acid Bicinchonique technique and Bradford assay give the results depending on the composition of extract, on the presence or not of detergent and on the raw material (Marchal, 1995). Another difficulty in these extracts for the quantification of proteins comes from the large amount of water included in vegetable and the low concentration of proteins. Thus in red wines, proteins are usually not taken into account due to their low concentration (typically below 10 mgL-1) and to the presence of anthocyanis and polyphenols.

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.

The quality of grapevines measured by yield and must density in the northern part of Europe conditons can be characterized as a type of “cool climate” – vary strongly from year to year and from one production site to another. One hundred year observations in Johannisberg from 1890 to 1991 demonstrate for the yield formation a clear dependancy from the year combined with a steady increase in productivity; latter a proof of positive clonal selection efforts.

Despite the extensive research performed during the last decades, the multifactorial mechanism responsible for the white wine protein haze formation is not fully characterized. Herein, a new model is proposed, which is based on the experimental identification of sulfur dioxide as a major modulating factor inducing wine protein haze upon heating. As opposed to other reducing agents, such as 2-mercaptoethanol, dithiothreitol and tris(2-carboxyethyl)phosphine hydrochloride (TCEP), the addition of SO2 to must/wine upon heating cleaves intraprotein disulfide bonds, hinders thiol-disulfide exchange during protein interactions and can lead to the formation of novel inter/intraprotein disulfide bonds. Those are eventually responsible for wine protein aggregation which follows a nucleation-growth kinetic model as shown by dynamic light scattering [1].

Background: hydroxycinnamic acids (HCA), present in pulp and skin of grapes, are relevant compounds in red winemaking