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Find articles, white papers and case studies from scale.ag. Use filters by topic: Agriculture, Epidemiology, Modeling, Tools.
Explores how mechanistic understanding of insect-mediated virus transmission can be integrated into epidemic risk models, improving prediction and management of plant viral outbreaks.
This article explores the overreliance on pure machine learning for modelling complex real-world systems, arguing it leads to brittle and non-causal models. It advocates for a hybrid future that integrates mechanistic modelling for structural understanding with data-driven techniques, guided by human expertise.
University of Cambridge news feature highlighting research on cassava viral epidemics and how integrating insect transmission processes into epidemic models improves risk assessment and disease management strategies.
User guide for AEF Crop Intelligence (https://aef-crop-intelligence.streamlit.app/), a decision support tool for farmers and agronomists that combines a Digital Twin of your field (a computer simulation of crop growth) with Satellite Intelligence (real-time observations from space) to help you optimize yield, manage diseases, and reduce input costs.
In plant disease epidemiology, limited observations are the norm. I outline how modern statistical and modelling approaches can transform these constrained datasets into powerful, actionable predictions for crop protection.
Durability of resistance depends on evolutionary pressure; model-based deployment (mixtures, rotations) can increase longevity.
Agent-based NetLogo model for CMD (varieties, whitefly vectors, roguing, replanting, economic outputs).
Sequential-Monte Carlo framework to incrementally update parameters of a stochastic plant epidemic model (notebooks included).