Charlotte Florence Nellist

This study uses hyperspectral imaging and deep learning to classify multiple infections in wheat, achieving 81% accuracy for single and double infections.

This study analyzes the population genomics and molecular epidemiology of wheat powdery mildew in Europe, revealing population structure linked to wind patterns and identifying loci under selection, including fungicide targets and avirulence genes.

The paper identifies genetic regions associated with resistance to European canker in apple using QTL analysis across multiple phenotyping experiments.

This paper investigates the genomic variation in Phytophthora fragariae to identify pathogenicity-associated genes and finds that transcriptional variation, not sequence polymorphisms, is linked to race-specific avirulence.