A rule-based corn crop cycle planning system enhanced with machine learning–assisted yield estimation and risk assessment, designed to make agriculture smarter and more accessible for every farmer.
To provide small-scale corn farmers with a transparent, agriculturally-sound decision support system that combines validated farming knowledge with predictive analytics — empowering informed decisions at every stage of the crop cycle.
A future where every farmer, regardless of scale or technical expertise, has access to intelligent crop planning tools that increase yield, reduce risk, and promote sustainable corn production practices.
Corn farmers, particularly small-scale producers, face several interrelated challenges that hinder effective crop management and optimal yield. These are the core problems MaizeGuide aims to solve.
Lack of structured, time-based guidance on farming activities throughout the corn crop cycle.
Difficulty in assessing potential outcomes and risks with current farm conditions.
Limited access to decision support systems that are both accurate and understandable.
Overreliance on experience-based decision-making without predictive insight.
Existing systems either lack actionable guidance or depend on complex technologies.
Existing studies excel in individual areas but no single system combines all four critical capabilities. MaizeGuide is the first to integrate all of them.
| Study | Crop Planning Tasks | Yield Prediction | Risk Assessment | ML Integration |
|---|---|---|---|---|
| Jeong et al. (2016) | ||||
| Liakos et al. (2018) | ||||
| Rose et al. (2016) | ||||
| Tittonell et al. (2010) | ||||
| MaizeGuide (Proposed) |
A seamless flow from farmer inputs to actionable recommendations, integrating rule-based planning with ML-powered predictions.
Encodes corn growth stages, agricultural best practices, and daily task logic for structured crop planning.
Regression & classification models for yield estimation and risk assessment trained on agricultural datasets.
Historical yield data, climate records, and soil information from verified agricultural agencies.
Modern, responsive web application with interactive dashboards for task management and crop insights.
Interactive charts, progress indicators, and visual dashboards for yield estimation and task completion tracking.
Scalable cloud infrastructure with containerization for reliable access and remote data management.
A multidisciplinary team of researchers, engineers, and agricultural experts committed to smarter farming solutions.