Effect of application of kaolin and pinolene on grape berry cell death, berry shrinkage, and ethanol accumulation

A unique “terroir” can be found in southern Bolivia, which combines the specific features of climate, topography and altitude of high valleys, with the management of grapevines staked on trees. It is one of the rare remnants of agroforestry viticulture. A survey was carried out among 29 grapegrowers in three valleys, to characterize the structure and management of these vineyards, and identify the services they expect from trees. Farms were small (2.2 ha on average) and 85% of vineyards were less than 1 ha. Viticulture was associated with vegetable, fruit and fodder production, sometimes in the same fields. Molle trees were found in all plots, together with one or two other native tree species. Traditional grapevine varieties such as Negra Criolla, Moscatel de Alejandría and Vicchoqueña were grown with a large range of densities from 1550 to 9500 vines ha-1. From 18 to 30% of them were staked on trees, with 1.2 to 4.9 vines per tree. The management of these vineyards (irrigation, fertilization and grapevine protection) was described, the most particular technical operation being the coordinated pruning of trees and grapevines. Three types of management could be identified in the three valleys. Grapegrowers had a clear idea of the ecosystem services they expected from trees in their vineyards. The main one was protection against climate hazards (hail, frost, flood). Then they expected benefits in terms of pest and disease control, improvement of soil fertility and resulting yield. At last, some producers claimed that tree-staking was quicker and cheaper than conventional trellising. It can be hypothesized then that agroforestry is a promising technique for the agroecological transition of viticulture. Its contribution to the “terroir” of the high valleys of southern Bolivia and its link with the specificities of the wines and spirits produced there remain to be explored.

In response to changes in their environment, grapevines regulate transpiration using various physiological mechanisms that alter conductance of water through the soil-plant-atmosphere continuum. Expressed as bulk stomatal conductance at the canopy scale, it varies diurnally in response to changes in vapor pressure deficit and net radiation, and over the season to changes in soil water deficits and hydraulic conductivity of both soil and plant. It is necessary to characterize the response of conductance to these variables to better model how vine transpiration also responds to these variables. Furthermore, to be relevant for vineyard-scale modeling, conductance is best characterized using data collected in a vineyard setting. Applying a crop canopy energy flux model developed by Shuttleworth and Wallace, bulk stomatal conductance was estimated using measurements of individual vine sap flow, temperature and humidity within the vine canopy, and estimates of net radiation absorbed by the vine canopy. These measurements were taken on several vines in a non-irrigated vineyard in Bordeaux France, using equipment that did not interfere with ongoing vineyard operations. An inverted Penman-Monteith equation was then used to calculate bulk stomatal conductance on 15-minute intervals from July to mid-September 2020. Time-series plots show significant diurnal variation and seasonal decreases in conductance, with overall values similar to those in the literature. Global sensitivity analysis using non-parametric regression found transpiration flux and vapor pressure deficit to be the most important input variables to the calculation of bulk stomatal conductance, with absorbed net radiation and bulk boundary layer conductance being much less important. Conversely, bulk stomatal conductance was one of the most important inputs when calculating vine transpiration, further emphasizing the need for characterizing its response to environmental changes for use in vineyard water use modeling.

The increasingly frequent heat waves during grape ripening pose challenges for high quality wine grape production. Defoliation is a common practice that can improve the control of diseases in bunches, but also it increases the exposure to sunlight. Grapes exposed to solar radiation reach temperatures over the optimum for berry development and maturation. This makes the development of irrigation and canopy management techniques of great importance to maximize yield and grape quality. A field experiment was carried out during 2021 using Manto negro wine grapes to study the effect of applied irrigation and different light exposure levels on grape quality. Two irrigation treatments were imposed based on the frequency and amount of water doses in a four-block experimental vineyard at Bodega Ribas (Mallorca). Three light exposure treatments were randomly applied in each irrigation plot. The light treatments included exposed clusters from pea size, non-exposed clusters, and shaded clusters after softening. Leaf area index and canopy porosity was estimated every 2 weeks. Midday leaf water potential was measured weekly. Additionally, apparent electrical conductivity was measured between rows to estimate the soil water content variability. Light and temperature sensors were installed at the bunch level to quantify the differences in bunch temperature and light intensity among treatments. The effect of irrigation and cluster light exposure on berry weight, TSS, TA, malic acid, tartaric acid, K+, and pH were analysed at 5 moments along grape ripening. During different heat waves, the natural shading technique decreased the maximum bunch temperature around 10 °C respect to the exposed bunches in both irrigation strategies. The combination of defoliation and shading techniques after softening decreased TSS at harvest and affected most of the quality parameters during the last stages of ripening, showing an interesting technique to delay ripening in warm viticulture areas.

A pedological study was carried out from 2009 to 2017 in Beaujolais vineyard, to improve physical and chemical knowledge of soils. It was completed in 2016 and 2017 by the current study, dealing with microbial aspects, in order to build a reference frame for improved advice in soil management. Microbial biomass was measured on representative plots of the six most common soil types identified in Beaujolais and, for each soil type, on plots with different levels of the main impacting parameters: total organic carbon, pH, cation exchange capacity, extractable copper. A total of 59 soil samples were collected. Confirming the results of various trials carried out in Beaujolais over the past 20 years, the results of the present study showed that the soils were still alive, but exhibited a large variability of biological parameters, which appeared dependant on both pedological and anthropic factors. Therefore, a good interpretation of biological parameters and advice for vine growers must rely on a pedologically-based referential with differentiated main driving factors. For example, the control of pH is of primary importance in granitic soils and in no way organic matter addition can improve soil quality if pH is too low. Conversely, in calcareous soils, biological parameters are more directly affected by direct or indirect (cover crops for example) inputs of organic matter. The use of biological parameters, such as microbial biomass, is of great potential value to improve advice on agro-viticultural practices (soil management, fertilization, liming, etc.), basis of a sustainable wine production on fragile soils.

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.