Repository for version control of the BrAPI specifications

Utilities for field trial analysis.

Code for "Using machine learning to combine genetic and environmental data for maize grain yield predictions across multi-environment trials" (Fernandes et. al 2024)

📈🌱 Mixed Models for Agriculture in R

We present here a 1D convolutional neural network model to predict grain protein content using spectroscopic data of multiple cereals

Using near-infrared spectroscopy (NIRS) and machine learning to determine oleic acid content from peanut raw grains

Tools and Statistical Procedures in Plant Science

Modeling of nutritional traits from multiple crops using NIRS and machine learning/statistics

📉🌱 R für Bio- und Agrarwissenschaftler

Diallel analysis of carrot phenotypes

Python library for data extraction from drone orthomosaics in plant breeding trials.

Analysis of Selection Index in Plant Breeding

List of papers related to Agricultural Statistics, Plant Breeding, and Quantitative Genetics

Bioinformatic workflow, statistical analysis and figure preparation for the "Wild again: Recovery of a beneficial Cannabis seed endophyte from low domestication genotypes" MS

Gradient Boosting Regression (GBR, https://github.com/scikit-learn/scikit-learn) model for genomic predictions

A Python library for Statistical Analysis and Simulations of Plant Breeding Experiments, designed specifically for researchers and students who are new to programming but want to understand field design concepts through practical implementation.

This repository serves to document, share, and collaborate on scripts used in the University of Arkansas fruit breeding lab.

Data repository for the paper of the same name.

Using Computational Intelligence and Machine Learning methods for trait prediction in genetic improvement (plant breeding) programs.

Combining ability analysis for Line x Tester design in R.