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…

Quantifying water use diversity across grapevine rootstock-scion combinations

Vines require proper light levels, temperature, and water availability, and climate change is modifying these factors, hampering yield and quality. Despite the large diversity of rootstocks, varieties, and clones, we still lack knowledge of their combined effects and potential role in a warmer and dryer future. Therefore, we aim to characterize some of the existing diversity of rootstocks and genotypes and their interaction at the eco-physiological level, combining stomatal conductance (gs) and chlorophyll a fluorescence analysis.

Influence of p-Coumaric Acid and Micronutrients on Growth and 4-Ethylphenol Production by Brettanomyces bruxellensis

The wine spoilage caused by Brettanomyces bruxellensis is one of the global concerns for winemakers. Detecting the presence of B. bruxellensis using routine laboratory culture techniques becomes challenging when cells enter the viable but not culturable (VBNC) state. This study aims to investigate the impact of p-coumaric acid (a volatile phenol precursor) and micronutrients on B. bruxellensis’ culturability, viability, and volatile phenol production under sulfite stress. In red wine, exposure to a high sulfite dose (100.00 mg L-1 potassium metabisulfite) resulted in immediate cell death, followed by a recovery of culturability after two weeks.

Biodiversity and biocontrol ability of Trichoderma natural populations in soil vineyards from Castilla y León region (Spain)

Trichoderma is a microorganism present in many agricultural soils and some of its species could be used as natural biological control agents. In this work, the presence of natural populations of Trichoderma was estimated in soil vineyard and its biocontrol capacity against Phaeoacremonium minimum, one of the main agent causals of grapevine trunk diseases instead of using pesticides. Moreover, physicochemical variables in soil such as pH, organic matter and nutrients were evaluated to determine a possible correlation to natural populations of Trichoderma.

Impact of toasting and botanical origin on oak wood (Q. sp.) volatilome using untargeted GCxGC-ToFMS analysis

Many works have been carried out to identify the key aroma volatile compounds of oak wood (e.g., whisky-lactone, furfural, maltol, eugenol, guaiacol, vanillin) using conventional gas chromatography coupled with olfactometry and mass spectrometry (GC-O-MS). Inspired by recent untargeted approaches in the field of food “omics”, this work aims to extend our knowledge on the impact of cooperage process on the volatile composition of oak wood using two-dimensional comprehensive gas chromatography coupled with time of flight mass spectrometry (GCxGC-ToFMS).

Biotype diversity within the autochthonous ‘Bobal’ grapevine variety

Bobal is the second most widely grown Spanish red grape variety (54,165 has), mainly cultivated in the Valencian Community and especially, in Utiel-Requena region (about 67% of 34,000 has). In this study, agronomic and enological parameters were determined in 98 biotypes selected during 2018 and 2019 in more than 50 vineyards over 50 years-old in the Utiel-Requena region. Moreover, a multi-criteria approach considering temperature and rainfall (Fig. 1A), among other parameters, was made to establish three different zones within the region (Fig. 1B), where in the future the selected biotypes will evaluated. In fact, in 2020, 4 replicates and 12 vines per biotype were planted in an experimental vineyard to preserve this important intra-cultivar diversity.