- Evaluation of precision agriculture technologies for optimizing water use in smallholder maize production under variable rainfall - Development of a community-based agroforestry model for climate-resilient livelihoods in degraded lands - Assessment of drone-based multispectral imagery for early detection of foliar diseases in tomato crops - Integrated watershed management using GIS for sustainable irrigation in mixed-cropping systems - Genetic and phenotypic characterization of native tree species for urban forestry rehabilitation - Use of biochar and compost co-application to enhance soil health and crop yield in tropical soils - Impact of post-harvest processing choices on shelf-life and quality of tropical fruits - Evaluation of pest management strategies combining pheromone traps and biological control in cacao plantations - Optimization of silvopasture systems for dairy productivity and carbon sequestration - Modeling climate change impacts on timber yield and forest fire risk under different management scenarios

Project Abstract

This study integrates agronomic, ecological, and socio-economic approaches to advance sustainable intensification across crops, forestry, and agro-ecosystems under variable rainfall and climate pressures. It evaluates precision agriculture technologies (sensor networks, variable-rate irrigation, and data-driven decision-support tools) to optimize water use in smallholder maize production, contrasting sites with contrasting rainfall patterns to quantify water savings, yield stability, and input efficiency. Concomitantly, a community-based agroforestry model is developed and tested in degraded landscapes, emphasizing participatory planning, species selection, and planting design to restore soil health, sequester carbon, diversify incomes, and improve microclimates, with livelihoods assessed through resilience indices and cost–benefit analyses. A remote-sensing workflow employing drone-based multispectral imagery is established to enable early detection of foliar diseases in tomato crops, integrating spectral indices, machine-learning classification, and ground-truth validation to reduce reaction time and fungicide usage. In a watershed context, GIS-driven integrated management is implemented to optimize irrigation scheduling across mixed-cropping systems, incorporating hydrological modeling, soil moisture dynamics, and stakeholder-driven scenarios to improve water-use efficiency at landscape scales. Parallel genetic and phenotypic surveys of native tree species inform urban forestry rehabilitation by identifying adaptive traits, guiding provenance selection, and enhancing urban resilience to heat and pests. Soil health is enhanced through the co-application of biochar and compost, with experiments monitoring soil physicochemical properties, microbial activity, nutrient cycling, and crop responses across tropical soils, generating guidelines for dosage and application timing. Post-harvest value chains for tropical fruits are analyzed to determine how processing choices influence shelf-life, quality attributes, and market access, informing best-practice protocols for minimal losses and extended market reach. In cacao agroecosystems, an integrated pest management framework combines pheromone traps with biological control agents, evaluating synergistic effects on pest suppression, non-target impacts, and economic viability under varying ecological conditions. Silvopasture systems are optimized to balance dairy productivity with carbon sequestration, evaluating forage productivity, canopy structure, animal performance, and greenhouse gas fluxes under different management regimes. Modeling tools project climate-change impacts on timber yield and forest fire risk, incorporating emission scenarios, stand structure, and adaptive management strategies to support risk-informed silvicultural planning. Throughout, the research employs participatory co-design, robust field experiments, high-resolution remote sensing, and scenario analysis to generate transferable guidelines for farmers, foresters, urban planners, and policymakers. The integrated findings illuminate trade-offs and synergies among water use efficiency, soil and biodiversity restoration, post-harvest quality, pest management, livestock integration, and climate adaptation, contributing to resilient food systems and multifunctional landscapes in tropical and subtropical regions.

Project Overview

What This Project Is About

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This project explores a set of agriculture and forestry ideas aimed at improving farming efficiency, environmental health, and resilience to climate change. It covers smart farming tools, forest-based livelihoods, early disease detection, water management, soil health, post-harvest quality, pest control, pasture systems, and climate risk modeling. The goal is to understand how these approaches work together to support sustainable food and tree resources in varied settings.

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The Problem It Addresses

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Objectives of the Project

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1. Assess how precision farming tools can save water in maize under unpredictable rainfall.
2. Develop an agroforestry model that supports climate resilience on degraded lands.
3. Test drone imagery for early detection of tomato leaf diseases.
4. Explore GIS-based watershed planning for sustainable irrigation in mixed crops.
5. Characterize native trees for urban forestry rehabilitation.
6. Evaluate biochar and compost blends to boost soil health and yields.
7. Examine how post-harvest choices affect fruit shelf-life and quality.
8. Review pest management combining pheromone traps and biological controls in cacao.
9. Analyze silvopasture options to balance dairy productivity and carbon storage.
10. Model climate risks to timber yield and forest fire under different management scenarios.

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What You Will Do Step by Step

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1) Review related literature and select a site or case studies. 2) Collect data on rainfall, soil, crops, and farm practices. 3) Apply simple tools to monitor water use and crop health. 4) Implement or simulate agroforestry and soil improvement practices. 5) Use images from drones or public data to detect plant stress. 6) Map watersheds and plan irrigation under best-fit scenarios. 7) Analyze data to compare outcomes across approaches. 8) Synthesize findings into practical recommendations.

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Expected Outcome