Luis Antonio Diaz-Garcia

The paper identifies a major locus for boron exclusion in wild Vitis species through genetic mapping and phenotyping, supporting its use in breeding boron-tolerant rootstocks.

The paper investigates the genetic factors influencing grapevine grafting success using a scion mapping population and identifies a QTL on chromosome 7 associated with increased success.

The paper presents a low-cost imaging and deep-learning pipeline to analyze root system architecture and soil moisture in grapevine rootstocks, revealing genetic and temporal variation in root traits.

This study identifies haplotype-specific expression of a terpene synthase gene as the source of linalool variation in Riesling grapevines, showing regulatory variation within terpene synthase clusters drives monoterpene diversity.

This study evaluates Vitis germplasm diversity to predict adventitious rooting traits, identifying genetic loci and developing genomic prediction models for improved grapevine rootstock breeding.

This paper introduces the Euler Characteristic Transform (ECT) for classifying plant shapes and predicting leaf venation from blade geometry using deep learning.

This study uses topological data analysis and deep learning to show that grapevine leaf blade and vasculature shapes are predictively linked, suggesting a one-to-one relationship between the two tissues.

This study uses QTL mapping and a foundation model for phenotyping to identify genetic loci associated with grapevine cluster compactness and yield traits.

This study identifies genetic loci associated with chloride exclusion in grapevines using GWAS and QTL mapping across a diverse germplasm collection.

This study uses hyperspectral radiometry and machine learning to screen grapevine rootstocks for boron tolerance, identifying genotypes with high B exclusion and photosynthetic resilience.

This paper demonstrates that hyperspectral sensing can identify salinity-tolerant grapevine germplasm with high throughput and non-destructive methods, showing better performance with a more expensive, sensitive device.

The paper develops a high-resolution morphospace model of grapevine leaves to predict synthetic leaves and improve classification accuracy.

This paper constructs and analyzes the first pangenomes for blueberry and cranberry, revealing high genetic diversity and identifying genes associated with disease resistance and fruit quality.

The paper uses PacBio sequencing to assemble and compare organelle genomes of American cranberry and its wild relatives, finding identical mitochondrial genomes and minimal plastid variation.

SOFIA is an R package that simplifies the creation of publication-quality Circos plots for genetic data by integrating R and Circos with minimal user intervention.

The paper constructs a high-density cranberry composite map using GBS and SSRs to enable molecular-assisted breeding and genomic studies.