Alfalfa Crop Management: Systemic Review and Meta-Analysis

Fungicide profitability on alfalfa interface that shows farm conditions, treatment costs, and profitability analysis results.

Project collaborators

Damon Smith and Shalini Yerukala, Department of Plant Pathology
Maria Oros, Data Science Institute

Project start and end dates

February 2025-April 2025

Project summary

Maria’s insight and motivation were instrumental in bringing the alfalfa meta-analysis manuscript to completion, and her drive consistently made the work better and more impactful. She also developed innovative ROI calculators for alfalfa, soybean, and corn, a valuable contribution that will benefit the farming community and agricultural decision-making for years to come.
Dr. Shalini Yerukala

Alfalfa is a cornerstone crop for dairy production, yet many of the management recommendations farmers rely on come from studies conducted decades ago under very different varieties, climates, and production systems. To bridge this gap, we developed a systematic review and meta-analysis that compiled and re-evaluated research on alfalfa management across the United States. By integrating results from field trials, expert knowledge, and modern statistical and machine-learning tools, we aimed to build a fully reproducible workflow that quantifies yield responses and economic returns under current production conditions.

This project established a reproducible, data-driven framework to quantify the agronomic and economic impacts of crop management practices in U.S. alfalfa production. We conducted a systematic review and meta-analysis of multi-year field trials to synthesize yield and disease-control responses to foliar fungicide applications and related management factors. The meta-analytic model integrated study-level covariates such as cutting interval duration, seed type, and growth stages to estimate overall and context-specific treatment effects. The resulting framework supports the next generation of decision tools, such as our ROI calculator, that translate research evidence into practical, data-driven guidance for farmers considering new fungicide products and management strategies.

Project deliverables