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…

Control of bacterial growth in carbonic maceration winemaking through yeast inoculation

Controlling the development of the bacterial population during the winemaking process is essential for obtaining correct wines[1]. Carbonic Maceration (CM) wines are recognised as high-quality young wines. However, due to its particularities, CM winemaking implies a higher risk of bacterial growth: lower SO2 levels, enrichment of the must in nutrients, oxygen trapped between the clusters… Therefore, wines produced by CM have slightly higher volatile acidity values than those produced by the destemming/crushing method[2].

Addition of glutathione-rich inactivated yeasts to white musts: effects on wine composition and sensory quality

Glutathione plays a key role in preventing some oxidative processes during winemaking. This molecule limits the must enzymatic oxidation, reacts with caffeic acid and generates a colourless compound that prevents subsequent browning. It also has a protective effect on wine aroma, preventing the oxidation of the volatile compounds with a high sensory impact.

The influence of pre-heatwave leaf removal on leaf physiology and berry development

Due to climate change, the occurrence of heatwaves and drought events is increasing, with significant impact on viticulture. Common ways to adapt viticulture to a changing climate include site selection, genotype selection, irrigation management and canopy management. The latter mentioned being for instance source-sink manipulations, such as leaf removal, with the aim to delay ripening.

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.

Adsorption of tetraconazole by organic residues and vineyard organically-amended soils 

Spain is the country with the largest wine-producing area in the EU and its productivity is largely controlled applying fungicides. However, residues of these compounds can move and contaminate surface and groundwater. The objective of this work was to evaluate the capacity of bioadsorbents from different origin to adsorb and immobilize tetraconazole by themselves or when applied as organic soil amendment, and to prevent soil and water contamination by this fungicide. The adsorption of tetraconazole by 3 organic residues: spent mushroom substrate (SMS), green compost (GC) and vine pruning sawdust (VP), as well as by vineyard soils unamended and amended individually with these residues at 1.5% (w/w) was evaluated using the batch equilibrium technique.