terclim by ICS banner
IVES 9 IVES Conference Series 9 International Congress on Grapevine and Wine Sciences 9 2ICGWS-2023 9 Predicting provenance and grapevine cultivar implementing machine learning on vineyard soil microbiome data: implications in grapevine breeding

Predicting provenance and grapevine cultivar implementing machine learning on vineyard soil microbiome data: implications in grapevine breeding

Abstract

The plant rhizosphere microbial communities are an essential component of plant microbiota, which is crucial for sustaining the production of healthy crops. The main drivers of the composition of such communities are the growing environment and the planted genotype. Recent viticulture studies focus on understanding the effects of these factors on soil microbial composition since microbial biodiversity is an important determinant of plant phenotype, and of wine’s organoleptic properties. Microbial biodiversity of different wine regions, for instance, is an important determinant of wine terroir. While conventional methods for microbiome analysis are extensively used, application of modern Artificial Intelligence (AI) based methods could unravel non-linear associations between microbial taxa and environmental/plant genetic factors. Here we compare the performance of shallow and Deep Machine Learning methods to predict the geographical provenance and the planted grape cultivar solely based on the soil microbiota. We used 885 previously published microbial amplicon-sequencing datasets (16S) collected from vineyards located in 13 countries across 4 continents and planted with 34 Vitis vinifera cultivars representing the largest collection of vineyard microbiomes analyzed to date. This research also aimed at addressing some common challenges associated with most ML-based studies such as easy availability of models to non-technical researchers which is necessary for research reproducibility. To facilitate this, the models built in this study will be available through a GUI-based containerized web platform. Also, to provide compatibility of processed data from other 16S studies, a computational step will be included that merge the features either by taxonomy or sequence identity. This study will be beneficial in several ways such as inferring lost/mislabeled samples, identifying important location-specific and cultivar-specific taxa. Ultimately, this approach could be implemented for the identification of the genes regulating host/microbe interactions, which will provide valuable targets for breeding programs aimed at producing more sustainable crops.  

Acknowledgements: This study was supported by the National Institute of Food and Agriculture, AFRI Competitive Grant Program Accession number 1018617, and the National Institute of Food and Agriculture, United States Department of Agriculture, Hatch Program accession number 1020852.

DOI:

Publication date: October 5, 2023

Issue: ICGWS 2023

Type: Article

Authors

Carlos M. Rodríguez López1*, Lakshay Anand1

1Environmental Epigenomics and Genomics Group, Department of Horticulture, College of Agriculture, Food and environment, University of Kentucky, Lexington, Kentucky, USA

Contact the author*

Keywords

rhizosphere microbiome, provenance, plant-microbiome interactions, breeding, machine learning

Tags

2ICGWS | ICGWS | ICGWS 2023 | IVES Conference Series

Citation

Related articles…

Climate change and viticulture in Nordic Countries and the Helsinki area

The first vineyards in Northern Europe were in Denmark in the 15th century, in the southern parts of Sweden and Finland in the 18th century at 55–60 degrees latitude. The grapes grown there have not been made into wine, but the grapes have been eaten at festive tables. The resurgence of viticulture has started with global warming, and currently the total area of viticulture in the Nordic countries, including Norway, is estimated to be 400–500 hectares, most of which is in Denmark. Southern Finland, like all southern parts of Northern Europe, belongs to the cool-cold winegrowing area.

Decoupling the effects of water and heat stress on Sauvignon blanc berries

Climate changes have important consequences in viticulture, heat waves accompanied by periods of drought are encountered more and more frequently. This study aims to evaluate the single and combined effect of water deficit and high temperatures on the thiol precursors biosynthesis in Sauvignon blanc grapes. For this purpose, a protocol has been developed for the cultivation of berries on a solid substrate. The berries, collected at three different times starting from veraison and grown in vitro, were subjected to 4 different treatments: control (C), water stress (WS), heat stress (HS), combined water and heat stress (WSHS). Water stress was simulated by adding abscisic acid to the culture medium, while different temperatures, respectively 25°C and 35°C, were managed with two illuminated climatic chambers.

Sparkling wines and atypical aging: investigating the risk of refermentation

Sparkling wine (SW) production entails a two-steps process where grape must undergoes a primary fermentation to produce a base wine (BW) which is then refermented to become a SW. This process allows for the development of a new physicochemical profile characterized by the presence of foam and a different organoleptic profile.

Correlative study between degradation of rosé wine under accelerated conditions and under normal conditions

Several studies have tried to develop different methods to study the photodegradation of wine in an accelerated way, trying to elucidate the effect of light on the wine compounds[1]. In a previous study, our team developed a chamber that speeds up the photodegradation of rosé wine[2]. In the present work we have tried to establish a correlation between irradiation times in accelerated conditions and the natural exposure to the cycles of light that usually exist in markets or at home.

Oenological compatibility of biocontrol yeasts applied to wine grapes 

Antagonistic yeasts applied to wine grapes must be compatible with the thereafter winemaking process, avoiding competition with the fermentative Saccharomyces cerevisiae or affecting wine flavour. Therefore, fifteen epiphytic yeasts (6 Metschnikowia sp., 6 Hanseniaspora uvarum, 3 Starmerella bacillaris) previously selected for its biocontrol ability against Alternaria on wine grapes were evaluate for possible competition with S. cerevisiae by the Niche Overlap Index (NOI) employing YNB agar media with 10 mM of 17 different carbonate sources present in wine grapes (proline, asparagine, alanine, glutamic acid, tirosine, arginine, lisine, methionine, glicine, malic acid, tartaric acid, fructose, melibiose, raffinose, rhamnose, sucrose, glucose).