Automated trichome counting in soybean using advanced image‐processing techniques

Computer vision and machine learning enabled soybean root phenotyping pipeline

(2020) Kevin G. Falk et al.   Plant Methods

Hydrogel-based transparent soils for root phenotyping in vivo

(2019) Lin Ma et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

A deep learning framework to discern and count microscopic nematode eggs

(2018) Adedotun Akintayo et al.   Scientific Reports

Semiautomated Feature Extraction from RGB Images for Sorghum Panicle Architecture GWAS

(2018) Yan Zhou et al.   PLANT PHYSIOLOGY

High-resolution computational imaging of leaf hair patterning using polarized light microscopy

(2012) Marcelo Pomeranz et al.   PLANT JOURNAL

Transcript profiling reveals expression differences in wild-type and glabrous soybean lines

(2011) Matt Hunt et al.   BMC PLANT BIOLOGY

Trichome density of main stem is tightly linked to PepMoV resistance in chili pepper (Capsicum annuum L.)

(2010) Hyun Jung Kim et al.   THEORETICAL AND APPLIED GENETICS