Daniel H. Chitwood

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

The paper introduces a Python-based method using pseudo-landmarks and Procrustes analysis to compare leaf shapes across species and development, showing shape transitions and genetic correlations.

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.

The paper quantifies variation in apple fruit shape and size across diverse accessions and finds they are independent traits.

The paper examines how terroir and rootstock influence leaf shape in grapevines, identifying a specific morphological feature affected by these factors.

This study uses geometric morphometric modeling to show that Capsella bursa-pastoris leaf shape variation is strongly linked to temperature, with no change in variation over 100 years.

This study evaluates how internationality affects interdisciplinary learning in a US-Mexico graduate course bridging computational and plant science, finding that cultural and linguistic diversity influences expertise distribution and skill development.

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

This study uses morphometrics and phylogenomics to analyze coca species and their relatives, revealing gene flow and taxonomic implications for coca classification.

This paper introduces a method to model Cannabis leaf shape using pseudo-landmarks, enabling accurate prediction of genetic and developmental traits.

The paper analyzes QTLs for floral morphology differences between Gilia yorkii and G. capitata, identifying colocalized QTL intervals on chromosomes 6 and 9.

This paper uses persistent homology to analyze plant morphology across different organs and scales, finding that genetic factors affect both shoot and root structures in tomato plants.

The paper shows that auxin asymmetry models predict mirrored leaf asymmetries in decussate and distichous phyllotactic systems, confirmed by mutant and species analyses.

This paper identifies a loss-of-function mutant in the SoPIN1 clade in tomato, showing its role in maintaining epidermal auxin flux and proper organ initiation patterns.

The paper introduces a new tomato population for high-resolution QTL mapping and gene identification, demonstrating its utility for fine-mapping and epistatic QTL analysis.

This study identifies 7,200 eQTL regulating transcript levels of 5,300 genes in tomato, revealing complex genetic architecture and associations with biological processes and phenotypes.

The paper identifies auxin signaling and cell wall expansion genes as key factors in natural variation of shade avoidance in tomato, linking them to growth plasticity and QTL effects on stem elongation and developmental rate.

This study shows that shade avoidance in tomato plants alters leaf shape through changes in gene expression related to indeterminacy, not through juvenile leaf type prolongation.