Klará Panzarová

The paper identifies Dry2.2 as a locus influencing bet-hedging strategies in barley under stress, revealing how population-level variance can be genetically controlled.

This study uses high-throughput phenotyping and machine learning to predict harvest-related traits in barley under drought conditions, achieving high accuracy with early and late-stage predictors.

The paper integrates multi-omics and phenotyping data to identify molecular signatures of potato responses to abiotic stresses.