High-throughput phenotyping and association analysis of belowground root traits under different nitrogen treatments in maize
With a team of three advisors—Jinliang Yang, Yufeng Ge, and Brian Rice—Niranjan Pokhrel is developing and optimizing image based high-throughput phenotyping to study critical root traits involved in nitrogen use efficiency (NUE) in maize. He will identify these traits using deep learning and computer vision techniques.
This project advances understanding of the genotype-phenotype relationship between root traits and its influence on NUE. This will allow for identifying genes that increase NUE, which enhances sustainable production by minimizing nitrogen loss.
Niranjan's work fosters interdisciplinary collaboration between plant geneticists and agricultural engineers, and provides a unique opportunity for a computational biology student. His overall research goal is to address current agricultural challenges by integrating genomics and phenomics with an advanced data science approach.