 IVES 9 IVES Conference Series 9 Use of Lactiplantibacillus plantarum (ML PrimeTm) to improve malolactic fermentation of catarratto wine subjected to long post-fermentative maceration.

Use of Lactiplantibacillus plantarum (ML PrimeTm) to improve malolactic fermentation of catarratto wine subjected to long post-fermentative maceration.

Abstract

AIM: Lactiplantibacillus plantarum species is wordwide used as starter for malolactic fermentation [1,2]. For the first time, in the present study, the use of L. plantarum (ML PrimeTM, Lallemand wine) to produce white wines with post-fermentative maceration extended until 60 days has been investigated.

METHODS: unpressed grapes of Catarratto cultivar were inoculated with the indigenous selected strain CS182 Saccharomyces cerevisiae [3]. After 24 hours, ML PrimeTM was inoculated into grape must. For the control trials, malolactic fermentation occurred spontaneously. During the alcoholic fermentation the microbiological and chemical-physical parameters were evaluated. After 60 days of post-fermentation maceration, the wines transferred into steel tanks and subjected to volatile organic compound investigation and sensory analysis.

RESULTS: grape must showed values of malic acid of 1.90 g/L. Interestingly, 24 hours after inoculation of ML PrimeTM, malic acid was totally converted into lactic acid that reached values of 1.54 g/l. Spontaneous malolactic fermentation started one month later the end of alcoholic fermentation. Experimental wines subjected to malolactic fermentation with ML PrimeTM showed a reduction of acid and bitter taste and were characterized by intense creamy and freshness both at smell and taste. Acetic acid contents was lower than 0.3 g/L in all experimental trials.

CONCLUSIONS: inoculation of the ML PrimeTM before the addition of starter yeast into unpressed grape must allowed malolactic fermentation within 24-48h at 18°C. ML PrimeTM is an effective alternative to Oenococcus oeni to undertake malolactic fermentation in white wines subjected at long post-fermentative maceration

DOI:

Publication date: September 10, 2021

Issue: Macrowine 2021

Type: Article

Authors

Nicola Francesca

Department of Agricultural, Food and Forestry Science, University of Palermo, Viale delle Scienze 4, 90128 Palermo, Italy,Antonio, ALFONZO, Department of Agricultural, Food and Forestry Science, University of Palermo, Viale delle Scienze 4, 90128 Palermo, Italy Rosario, PRESTIANNI, Department of Agricultural, Food and Forestry Science, University of Palermo, Viale delle Scienze 4, 90128 Palermo, Italy Michele, MATRAXIA, Department of Agricultural, Food and Forestry Science, University of Palermo, Viale delle Scienze 4, 90128 Palermo, Italy Valentina, CRAPARO, Department of Agricultural, Food and Forestry Science, University of Palermo, Viale delle Scienze 4, 90128 Palermo, Italy Vincenzo, NASELLI, Department of Agricultural, Food and Forestry Science, University of Palermo, Viale delle Scienze 4, 90128 Palermo, Italy Paola VAGNOLI, Lallemand Italia, Via Rossini 14/B, 37060 Castel D’Azzano, VR, Italy Sibylle KRIEGER-WEBER, Lallemand S.A., Korntal-Münchigen, Germany. Giancarlo, MOSCHETTI, Department of Agricultural, Food and Forestry Science, University of Palermo, Viale delle Scienze 4, 90128 Palermo, Italy Luca, SETTANNI, Department of Agricultural, Food and Forestry Science, University of Palermo, Viale delle Scienze 4, 90128 Palermo, Italy Raimondo, GAGLIO, Department of Agricultural, Food and Forestry Science, University of Palermo, Viale delle Scienze 4, 90128 Palermo, Italy. Antonella, MAGGIO, Department of Biological, Chemical and Pharmaceutical Sciences and Technologies (STEBICEF), University of Palermo, Viale delle Scienze, Parco d’Orleans II, Palermo, building 17, Italy Nicola, FRANCESCA, Department of Agricultural, Food and Forestry Science, University of Palermo, Viale delle Scienze 4, 90128 Palermo, Italy.

Contact the author

Keywords

Lactiplantibacillus plantarum; malolactic fermentation; catarratto; sensory analysis

Citation

Downscaling of remote sensing time series: thermal zone classification approach in Gironde region

In viticulture, the challenges of local climate modelling are multiple: taking into account the local environment, fine temporal and spatial scales, reliable time series of climate data, ease of implementation and reproducibility of the method. At the local scale, recent studies have demonstrated the contribution of spatialization methods for ground-based climate observation data considering topographic factors such as altitude, slope, aspect, and geographic coordinates (Le Roux et al, 2017; De Rességuier et al, 2020). However, these studies have shown questions in terms of the reproducibility and sustainability of this type of climate study. In this context, we evaluated the potential of MODIS thermal satellite images validated with ground-based climate data (Morin et al, 2020). Previous studies have been encouraging, but questions remain to be explored at the regional scale, particularly in the dynamics of the massive use of bioclimatic indices to classify the climate of wine regions. The results at the local scale were encouraging, but this approach was tested in the current study at the regional scale. Several objectives were set: 1) to evaluate the downscaling method for land surface temperature time series, 2) to identify regional thermal structure variations. We used weekly minimum and maximum surface temperature time series acquired by MODIS satellites at a spatial resolution of 1000 m and downscaled at 500 m using topographical variables. Two types of analyses were performed:

Bioclimatic shifts and land use options for Viticulture in Portugal

Land use, plays a relevant role in the climatic system. It endows means for agriculture practices thus contributing to the food supply. Since climate and land are closely intertwined through multiple interface processes, climate change may lead to significant impacts in land use. In this study, 1-km observational gridded datasets are used to assess changes in the Köppen–Geiger and Worldwide Bioclimatic (WBCS)

Local adaptation tools to ensure the viticultural sustainability in a changing climate

[lwp_divi_breadcrumbs home_text="IVES" use_before_icon="on" before_icon="||divi||400" module_id="publication-ariane" _builder_version="4.19.4" _module_preset="default" module_text_align="center" module_font_size="16px" text_orientation="center"...

Short-term relationships between climate and grapevine trunk diseases in southern French vineyards

Late frost protection in Champagne

Probably one of the most counterintuitive impacts of climate change on vine is the increased frequency of late frost. Champagne, due to its septentrional position is historically and regularly affected by this meteorological hazard. Champagne has therefore developed a strong experience in frost protection with first experiments dating from the end of 19th century. Frost protection can be divided in two parts: passive and active. Passive protection includes all the methods that do not seek to modify the vine’s environment or resistance at the time of frost. The most iconic passive protection in Champagne is the establishment of the individual reserve. This reserve allows to stock a certain quantity of clear wine during a surplus year to compensate a meteorological hazard like frost during the following years. Other common passive methods are the control of planting area (walls, bushes, topography), the choice of grape variety, late pruning, or the impact of grass cover and tillage. Active frost protection is also divided in two parts. Most of the existing techniques tend to modify vine’s environment. Most of the time they provide warmth (candles, heaters, windmills, heating cables…), or stabilise bud’s temperature above a lethal threshold (water sprinkling). The other way to actively fight is to enhance the resistance of buds to frost (elicitors). The Comité Champagne evaluates frost protection methods following three main axes: the efficiency, the profitability, and the environmental impact through a lifecycle assessment. This study will present the results on both passive and active protection following these three axes.