Matteo Dell’Acqua

The paper reports findings from a photosynthesis hackathon that identified key insights into genetic architecture using field photosynthesis data across four crop species.

The paper introduces SABER, a multiparental tomato population incorporating wild relatives for high-resolution QTL mapping, identifying known and novel QTL for agronomic traits.

The paper uses AI to phenotype leaf vein and stomatal traits in maize, finding independent genetic control between these traits.

This study analyzes the genetic diversity of cowpea using 10,617 accessions, revealing nine genetic groups and highlighting untapped genetic resources for crop improvement.

This study investigates the domestication history and genetic diversity of teff using genomic analyses, identifying key loci associated with seed color and panicle architecture.

This study identifies genetic variation affecting NPQ and PSII efficiency in maize using field-grown MAGIC population, highlighting CP24 as a key gene for photosynthetic improvement.

The paper identifies genetic variants associated with hypoxic tolerance in Arabidopsis by combining eGWAS and experimental validation, revealing the role of the MBR1/MED25 module in plant adaptation to rainy environments.

The paper characterizes teff genetic diversity and identifies climate-related adaptation patterns to inform breeding strategies for climate resilience.

This study characterizes Ethiopian barley genomes and links them to climate data to identify genomic regions for climate adaptation.