首页|Grapevine Rootstock and Scion Genotypes' Symbiosis with Soil Microbiome:A Machi ne Learning Revelation for Climate-Resilient Viticulture
Grapevine Rootstock and Scion Genotypes' Symbiosis with Soil Microbiome:A Machi ne Learning Revelation for Climate-Resilient Viticulture
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-According to news reporting based on a preprint abstract,our journalists obtained the following quote sourced from bi orxiv.org:"Given the impact of climate change on agriculture,the development of resilient crop cultivars is imperative."A healthy plant microbiota is key to plant productivity,influencing nutrient a bsorption,disease resistance,and overall vigor.The plant genetic factors cont rolling the assembly of microbial communities are still unknown."Here we examine if Machine Learning can predict grapevine rootstock and scion g enotypes based on soil microbiota,despite environmental variability.The study utilized soil microbial bacteriome datasets from 281 vineyards across 13 countri es and five continents,featuring 34 different Vitis vinifera cultivars grafted onto,often ambiguous,rootstocks.Random Forests,Adaptive Boost,Gradient Boos t,Support Vector Machines,Gaussian and Bernoulli Naive Bayes,k-Nearest Neighb or,and Neural Networks algorithms were employed to predict continent,country,scion,and rootstock cultivar,under two filtering criteria:retaining sparse cl asses,ensuring class diversity,and excluding sparse classes assessing model ro bustness against overfitting.Both criteria showed remarkable F1-weighted scores (>0.8) for all classes,for most algorithms.Moreover,successful rootstock and scion genotype prediction from soil microbiomes confirm s that genotypes of both plant parts shape the microbiome.
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