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…

Quantification of polysaccharides of variety Pomaces of the D.O.Ca Rioja

Pomace is one of the main residues generated by the wine industry and represents an environmental problem. Currently, there is a growing interest in the revaluation of these products because different bioactive compounds can be obtained from them, such as polyphenols, grape seed oils and polysaccharides. Red grape pomace can be an important source of polysaccharides, but they are currently little studied and even less with viable and environmental extraction processes (green extraction), such as flash extraction. The residual amount of the fraction rich in pectin (residual pulp) and component rich in hemicellulose in the pomace and the strength of association of the pectin with the cellulose-xyloglucan network depend on the degree of extractability of the polysaccharides in red winemaking and on the winemaking conditions.

Tackling the 3D root system architecture of grapevines: a new phenotyping pipeline based on photogrammetry

Plant roots fulfil important functions as they are responsible for the acquisition of water and nutrients, for anchorage and stability, for interaction with symbionts and, in some cases, for the storage of carbohydrates. These functions are associated with the Root System Architecture (RSA, i.e. the form and the spatial arrangement of the roots in the soil). The RSA results from several biological processes (elongation, ramification, mortality…) genetically determined but with high structural plasticity.

Chemical and microbiological evaluation of Ribeiro wines (NW Spain)

Wine produced under Designation of Origin (DOP) Ribeiro, the oldest DOP in Galicia (NW Spain), are elaborated using local grape cultivars, grown at the valleys of Miño, Avia and Arnoia rivers. The landscape formed by slopes and terraces and the peculiar climate of continental character, softened by the proximity of Atlantic Ocean, make it an area of excellent aptitude for vine cultivation. In addition, small-scale farming and the use of traditional techniques for vineyard management provide a great diversity to Ribeiro wines. This study presents the evaluation of red and white wines (bottled or bulk wines) from DOP Ribeiro, produced between years 2018-2022.

Influence of irrigation frequency on berry phenolic composition of red grape varieties cultivated in four spanish wine-growing regions

The global warming phenomenon involves the frequency of extreme meteorological events accompanied by a change in rainfall distribution. Irrigation frequency (IF) affects the spatial and temporal soil water distribution but its effects on the phenolic composition of the grape have been scarcely studied. The aim of this work was to evaluate the effects of four deficit irrigation frequencies of 30 % ETo: one irrigation per day (T01), two irrigations per week (T03), one irrigation per week (T07) and one irrigation every two weeks (T15) on berry phenolic composition at harvest.

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.