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…

Cumulative effect of deficit irrigation and salinity on vine responses

Climate change is increasing water needs in most of the wine growing regions while reducing the availability and quality of water resources for irrigation. In this context, the sustainability of Mediterranean viticulture depends on grapevine responses to the combinations of water and salt stress. With this aim, this work studies the effects of deficit irrigation and salinity on the physiology of the Tempranillo cultivar (Vitis vinifera L.) grafted onto a drought and salinity tolerant rootstock (1103 Paulsen).

Exploring intra-vineyard variability with sensor- and molecular-based approaches 

The application of remote and proximal sensing is a fast and efficient method to monitor grapevine vegetative and physiological parameters and is considered valuable to derive information on associated yield and quality traits in the vineyard. Further details can be obtained by the application of molecular analysis at the gene expression level aiming at elucidating how pathways controlling the formation of different grape quality traits are influenced by spatial variability. This work aims at evaluating intra-vineyard variability in grape composition at harvest and at comparing this with remotely sensed canopy vegetation data and molecular-based approaches.

Vineyard management practices to reduce sugar content on ‘Monastrell’ grapes

Climate change is resulting in more dry and hot summers, accelerating grape ripening and increasing berry sugars concentration. This results in wines with a higher alcohol content, which has a negative impact on wine quality, as well as, on consumer health. Agronomic practices that minimize these effects on berry composition and, consequently, on wine quality must be defined. In this work, different management practices have been assessed on rainfed ‘Monastrell’ grapevines in Jumilla (Murcia, Spain) from 2021 to 2023 vintages. Mulching, shading, application of kaolin and different types of pruning were evaluated, among others field adaptation practices.

Culturable microbial communities associated with the grapevine soil in vineyards of La Rioja, Spain

The definition of soil health is complex due to the lack of agreement on adequate indicators and to the high variability of global soils. Nevertheless, it has been widely used as synonymous of soil quality for more than one decade, and there is a consensus warning of scientists that soil quality and biodiversity loss are occurring due to the traditional intensive agricultural practices.
In this work we monitored a set of soil parameters, both physicochemical and microbiological, in an experimental vineyard under three different management and land use systems: a) addition of external organic matter (EOM) to tilled soil; b) no tillage and plant cover between grapevine rows, and c) grapevines planted in rows running down the slope and tilled soil.

Qualitative and productive characterization of a minority variety: ‘Branco lexítimo’ in DO Ribeira Sacra (Spain)

The actual climate changes, together with the strong regulation of the European Union and Spanish government, in search of sustainable viticulture, have forced the recovery of minority varieties, expanding the range of grape varieties, as well as the possible development of wines with unique profiles. In the Ribeira Sacra DO (Spain), a comparative study of the agronomic and qualitative behavior of the ‘Branco lexítimo’ variety has been carried out, compared to the majority white variety in the DO: ‘Godello’, located in the same study plot, with identic soil and climatic conditions. The study contemplated the analysis of phenology and leaf water potential, as well as the productive results and the analysis of the must quality, during four seasons: 2018 – 2021.