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…

Indicators of Sustainable Vineyard Soil Management: Metrics for Assessing Environmental Impacts

The vital role of soils in supporting life on our planet cannot be overstated. Soils provide numerous ecosystem services and functions, including biomass production, carbon sequestration, physical support, biological habitat, and genetic reserve, among others. Understanding the characteristics and sensitivity of soils in a specific terroir, along with effective soil management practices, is crucial for the sustainable management of natural resources.

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).

Late pruning, an alternative for rainfed vine varieties facing new climatic conditions

In Chile there is a dry farming area known as a traditional wine region, where varieties brought by the Spanish conquerors still persist. These varieties, in general, are cultivated under traditional systems, with low use of technical and economic resources, and low profitability for their grapes and wines. In this region, as in other wine grape growing areas, climatic conditions have changed significantly in recent decades. In particular, the occurrence of spring frosts, when bud break has already begun, have generated significant losses for these growers.

Agronomic behavior of three grape varieties in different planting density and irrigation treatments

In the O Ribeiro Denomination of Origin, there is a winemaking tradition of growing vines under a high-density plantation framework (8,920 vines/ha) and maintaining its vegetative cycle under rainfed conditions.
Currently, viticulture is advancing to plantation frames in which the density is considered medium (5,555 vines/ha), thus allowing mechanized work to be carried out for vineyard management operations. Although, the application of irrigation applied proportionally to the needs of the vegetative cycle of the vine, is a factor that increasingly helps a good development of the vine compared to the summer period, with increasingly uncertain weather forecasts.

Effect of foliar application of Ca, Si and their combination on grape volatile composition

Calcium (Ca) is an important nutrient for plants which plays key signaling and structural roles. It has been observed that exogenous Ca application favors the pectin accumulation and inhibition of polygalacturonase enzymes, minimizing fruit spoilage. Silicon (Si) is a non-essential element which has been found to be beneficial for improving crop yield and quality, as well as plant tolerance to diverse abiotic and biotic stress factors. The effect of Si supply to grapevine has been assessed in few investigations, which reported positive changes in grape quality and must composition.