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…

Grapevine cane pruning extract enhances plant physiological capacities and decreases phenolic accumulation in canes and leaves 

Vine cane extracts are a valuable byproduct due to their rich content of polyphenols, vitamins, and other beneficial compounds, which can affect and benefit the vine and the grapes. This study aims to evaluate the response of grapevine plants to irrigation with water supplemented with a vine cane extract, both at physiology response and phenolic composition in different parts of the plant (root, trunk, shoot, leaf, and berry).
Cane extract was obtained by macerating crushed pruning residues with warm water (5:1) and pectolytic enzymes. Two-year-old potted plants were irrigated with water (Control) while others were irrigated with cane extracts, either at 1:4 (w/v, cane extract/water; T 1:4) or at 1:8 (w/v, cane extract/water; T 1:8).

Evaluation of interception traps for capture of Xylotrechus arvicola (Coleoptera: Cerambycidae) in vineyards varieties from Protected Denomination of Origin León

Xylotrechus arvicola (Coleoptera: Cerambycidae) is a pest in vineyards (Vitis vinifera) in the main Spain wine-producing regions with Protected Denomination of Origin (PDO). The action of the larvae, associated to the spreading of wood fungi, causes damage especially in important varieties of V. vinifera. X. arvicola females lay eggs concentrated in cracks or under the rhytidome in the wood vines, which allows the emerging larvae to get into the wood and make galleries inside the plant being then necessary to prune intensively or to pull up the bored plants (1). The objective of the study was to evaluate captures of X. arvicola insects in five varieties of V. vinifera in PDO León.

Differences in metabolism among species and hybrids of the genus Saccharomyces during wine fermentation unveiled by multi-omic analysis 

Yeast species S. cerevisiae, S. uvarum, S. kudriavzevii and their hybrids present clear metabolic differences, even when we compared S. cerevisiae wine versus wild strain. These species and hybrids produced significantly higher amounts of glycerol, organic acids, 2,3-butanediol, and 2-phenyl ethanol and a reduction of the ethanol yield, properties very interesting in the sector to deal with climate change effects. To understand the existing differences, we have used several omics techniques to analyze the dynamics of the (intra- and extracellular) metabolomes and/or transcriptomes of representative strains of S. cerevisiae, S. uvarum, S. kudriavzevii, and hybrids.

Water availability at budbreak time in vineyards that are deficitary irrigated during the summer: Effect on must volatile composition


In recent years, Mediterranean regions are being affected by marked climate changes, primarily characterized by reduced precipitation, greater concurrence of temperature extremes and drought during the growing season, and increased inter-annual variability in temperatures and rainfall. Generally, high-quality red wines need moderate water deficit. Hence, irrigation may be needed to avoid severe vine water stress occurring in some vintages and soils with low holding capacity. The aim of this work was to evaluate the effects of soil recharge irrigation in pre-sprouting and summer irrigation every week (30 % ETO) from the pea size state until the end of ripening (RP) compared to exclusively summer irrigation every week (R) in the same way that RP, on must volatile composition at harvest.

Stomatal abundance in grapevine: developmental genes, genotypic variation, and physiology

Grapevine cultivation is threatened by the global warming, which combines high temperatures and reduced rainfall, impacting in wine quality and even plant survival. Breeding for varieties resilient to these challenges must address plant traits such as tolerance to supraoptimal temperatures and optimized water use efficiency while minimizing productivity and quality losses. Stomatal abundance (SA) determines the maximum leaf potential for transpiration and thus water loss and cooling. Since SA results from a developmental process during leaf emergence and growth, knowledge on the genetic control of this process would provide specific targets for modification.