3 citations · 5 across the 11 of their papers we have counts for
12 papers
Automated Maize Ear Phenotyping Using 3D Reconstructions
Ritwesh A. Kumar, Som Tripathi, Peja Matthews +5
Maize kernel traits such as row number, kernels per row, and kernel size vary largely for genetic reasons and are consistently associated with regions of the genome that influence…
AI-enabled Low-Cost 3D Maize Ear Morphometry Platform at Breeding Scale
Therin Young, Elijah Rodriguez, Lisa Coffey +4
Maize ear geometry (length, width, curvature, and volume) is closely tied to yield and grain-filling outcomes, but existing high-throughput phenotyping pipelines remain constrained…
AI-integrated models for assessing agricultural resilience
Joshua R. Waite, Dana Golden, Brett Indelicato +8
Agricultural supply chains are vulnerable to disruptions through linked biophysical and economic systems. We develop an AI-powered tool that integrates economic models (GTAP) with…
Towards smart canopies: Algorithmic design of maize canopy architectures that maximize light use efficiency
Nasla Saleem, Talukder Zaki Jubery, Yan Zhou +4
We present a computational framework that integrates functional-structural plant modeling (FSPM) with an evolutionary algorithm to optimize three-dimensional maize canopy architect…
FloraForge: LLM-Assisted Procedural Generation of Editable and Analysis-Ready 3D Plant Geometric Models For Agricultural Applications
Mozhgan Hadadi, Talukder Z. Jubery, Patrick S. Schnable +4
Accurate 3D plant models are crucial for computational phenotyping and physics-based simulation; however, current approaches face significant limitations. Learning-based reconstruc…
Accessing the Effect of Phyllotaxy and Planting Density on Light Use Efficiency in Field-Grown Maize using 3D Reconstructions
Nasla Saleem, Talukder Zaki Jubery, Aditya Balu +5
High-density planting is a widely adopted strategy to enhance maize productivity, yet it introduces challenges such as increased interplant competition and shading, which can limit…
MaizeField3D: A Curated 3D Point Cloud and Procedural Model Dataset of Field-Grown Maize from a Diversity Panel
Elvis Kimara, Mozhgan Hadadi, Jackson Godbersen +6
The development of artificial intelligence (AI) and machine learning (ML) based tools for 3D phenotyping, especially for maize, has been limited due to the lack of large and divers…
MaizeEar-SAM: Zero-Shot Maize Ear Phenotyping
Hossein Zaremehrjerdi, Lisa Coffey, Talukder Jubery +6
Quantifying the variation in yield component traits of maize (Zea mays L.), which together determine the overall productivity of this globally important crop, plays a critical role…
Procedural Generation of 3D Maize Plant Architecture from LIDAR Data
Mozhgan Hadadi, Mehdi Saraeian, Jackson Godbersen +8
This study introduces a robust framework for generating procedural 3D models of maize (Zea mays) plants from LiDAR point cloud data, offering a scalable alternative to traditional…
Pheno-Mapper: An Interactive Toolbox for the Visual Exploration of Phenomics Data
Youjia Zhou, Methun Kamruzzaman, Patrick Schnable +3
High-throughput technologies to collect field data have made observations possible at scale in several branches of life sciences. The data collected can range from the molecular le…
Hyppo-X: A Scalable Exploratory Framework for Analyzing Complex Phenomics Data
Methun Kamruzzaman, Ananth Kalyanaraman, Bala Krishnamoorthy +2
Phenomics is an emerging branch of modern biology that uses high throughput phenotyping tools to capture multiple environmental and phenotypic traits, often at massive spatial and…
A Bayesian Network approach to County-Level Corn Yield Prediction using historical data and expert knowledge
Vikas Chawla, Hsiang Sing Naik, Adedotun Akintayo +4
Crop yield forecasting is the methodology of predicting crop yields prior to harvest. The availability of accurate yield prediction frameworks have enormous implications from multi…