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…

Induction of polyphenols in seedlings of Vitis vinifera cv. Monastrell by the application of elicitors

Contamination problems arising from the use of pesticides in viticulture have raised concerns. One of the alternatives to reduce contamination is the use of elicitors, molecules capable of stimulating the natural defences of plants, promoting the production of phenolic compounds (PC) that offer protection against biotic and abiotic stress. Previous studies on Cabernet-Sauvignon seedlings demonstrated that foliar application of elicitors methyl jasmonate (MeJ) and benzothiadiazole (BTH) increased proteins and PC involved in grapevine defence mechanisms. However, no trials had been conducted on Monastrell seedlings, a major winegrape variety in Spain.

Glucosidase and esterase salivary activities and their involvement in consumer’s wine sensory perception and liking

Wine flavour is the integration of distinct physiologically defined sensory systems that combine taste, aroma and trigeminal sensations, and it is a key determinant factor for the acceptance of wine by consumers. Volatile compounds, are important contributors to wine flavour, specially to aroma. These small and low-boiling point compounds are easily released into the air allowing to enter and move within the nasal or oral cavities where they can bind the olfactory receptors. Additionally, wine also contains aroma precursors, which are non-volatile compounds, but that can be broken down releasing volatile odorants. During wine tasting, all these chemicals (volatiles and non-volatiles) can be submitted to the action of salivary enzymes.

Application of UV-B radiation in pre- and postharvest as an innovative and sustainable cultural practice to improve grape phenolic composition

Ultraviolet radiation (UVR) is a minor part of the solar spectrum, but it represents an important ecological factor that influences many biological processes related to plant growth and development. In recent years, the application of UVR in agriculture and food production is emerging as a clean and environmentally friendly technology.
In grapevine, many studies have been conducted on the effects of ambient levels of UVR, but there are few considering the effects of UV-B application on grape phenolic composition under commercial growing or postharvest conditions.

Development and validation of a free solvent UHPLC/MS-MS method to analyse melatonin and its precursors in Spanish commercial wines  

Melatonin is a bioactive compound present in foods and beverages such as wines. During alcoholic fermentation, yeast transforms tryptophan into certain indole compounds, including melatonin. This paper aims to develop and validate a free solvent analytical method by ultra-high performance liquid chromatography coupled with high resolution mass spectrometry (UHPLC/MS-MS) to determine melatonin and its precursors (L-tryptophan, tryptamine, serotonin, tryptophol, N-acetylserotonin, 5-hydroxytryptophan, and 3- indoleacetic) that appropriately prevent the matrix effect.

Phenolic extraction and dissolved oxygen concentration during red wines fermentations with Airmixig M.I.™

During red wine fermentation, the extraction of phenolics compounds and sufficient oxygen provision are critical for wine quality [1,2]. In this trial, we aimed at evaluating the kinetics of phenolic extraction and dissolved oxygen during red wine fermentations using the airmixing system. Twenty lots of red grape musts were fermented in 300.000 L tanks, equipped with airmixing, using two injection regimes (i.e., high and low intensity, and high and low daily frequency). An oxygen analyzer was introduced into the tanks in order to record the concentration of dissolved oxygen over time.