Research library
AI in Agriculture
Studies conducted by the Farm Better Research Lab on how machine learning performs in working fields rather than in benchmarks. These write-ups are illustrative mock-ups.
Weather Intelligence
Hyper-local Rainfall Forecasting for Smallholder Plots Using Ensemble Machine Learning
We evaluate an ensemble of gradient-boosted trees and a lightweight temporal transformer trained on satellite reanalysis, ground station data and low-cost farm sensors to forecast rainfall at 1 km resolution across 480 smallholder plots.
A. Wanjiru, D. Okoth, M. Ferreira
Harvest Science
Computer Vision for Harvest Timing: Predicting Grain Moisture From Canopy Imagery
A convolutional model estimates maize grain moisture from smartphone canopy photographs, giving farmers a harvest window without laboratory sampling.
L. Mbeki, S. Haruna, P. Rossi
Pest & Disease
Early Warning of Fall Armyworm Outbreaks Through Crowd-Sourced Reports and Climate Signals
Combining farmer-submitted pest sightings with degree-day accumulation models, we forecast fall armyworm pressure two to three weeks ahead of visible infestation.
N. Achieng, T. Bello, R. Iyer
Water & Soil
Reinforcement-Learned Irrigation Scheduling Under Constrained Water Budgets
A policy trained in a calibrated soil-water simulator schedules irrigation events for horticultural plots operating under weekly water quotas.
K. Otieno, J. Lindqvist, F. Adeyemi
Yield Modelling
Season-Ahead Yield Prediction by Fusing Satellite Indices With Farm Management Records
We test whether adding farmer-entered management records to satellite vegetation indices improves season-ahead yield forecasts for maize and soybean.
C. Nakamura, B. Kimathi, E. Duarte
Adoption Studies
Do Farmers Act on AI Advice? A Field Study of Advisory Adoption Across 1,200 Farms
A mixed-methods study of how smallholder and mid-scale farmers interpret, trust and act on automated agronomic advisories.
G. Mutua, H. Svensson, I. Almeida