Liu, L. 2020. Assessing and modeling crop yield and soil carbon in smallholder fields in Africa and Central America. Dissertation, Michigan State University, East Lansing, MI.
Research on developing and testing agricultural tools for smallholder agricultural producers remains limited , despite the fact that new tools designed to improve agronomic management and resilience of cropping systems are becoming increasingly available also in developing countries. The overarching goal of this dissertation was to evaluate the efficacy of agricultural technologies, like process-based crop simulation models, to improve food production forecasts and crop yields in smallholder fields in low-income countries (Chapter 1).
Chapter 2 presents the development and the validation of a new maize yield forecasting system for the Government of Tanzania. In this study, a field-based survey was integrated with a process-based crop model, Systems Approach to Land Use Sustainability (SALUS) to provide accurate and timely maize yield forecasts for small fields in Tanzania. In spite of a wide range of maize growing conditions, the method developed in the chapter has shown to provide reliable forecasts across three districts in Tanzania 14-77 days prior to crop harvest.
Chapter 3 investigates how climate impact assessment differs when using the averaged value simulated with each climate model from the Coordinated Regional Climate Downscaling Experiment (CORDEX) program, versus one simulated value with one single delta-method projected climate based on average changes in climatic variables. This analysis was performed using SALUS-simulated grain yield, Soil Organic Caron (SOC) and soil inorganic Nitrogen (N) for 60 sites from Chapter 2. The simulated climate impact on soil N and SOC using the delta-method climate was close to the average simulated impact using each climate model, but the adverse impact on grain yield was projected to be lower.
Chapter 4 focuses on agronomic management that could increase the yield of yam while improving soil fertility in Ghana. In this study, I first parameterized yam in the SALUS model using field experiment data from three N and phosphorous (P) fertilizer treatments combined with two yam cropping in two distinct agroecological zones in Ghana for two years. The calibrated and validated SALUS-Yam model was used to assess the impact of four management treatments: continuous unfertilized rainfed yam (control), pigeonpea-yam rotation, yam with 3 Mg/ha pigeonpea residue incorporated, and yam with 23-23 kg/ha N-P2O5 fertilizer added. The results showed that incorporating pigeonpea residues into yam fields produced the highest yam tuber yield and reduced SOC compared to the other treatments. This work also confirmed that yam cultivation in Ghana was mostly limited by lack of nutrients (N, P or both), as opposed to drought.
Chapter 5 presents within-field variability of smallholder fields. From field observations in Tanzania, maize-based fields across more than 60 sites in three districts in Tanzania contained considerable variability in plant density (median CV 20-30%) and grain yield (median CV 30-36%). Grain yield variability was correlated with in-season vegetation indices, particularly the green chlorophyll vegetation index. The coefficient of variation of normalized difference vegetation index became smaller as the spatial resolution became coarser. The analysis was performed using images of distinct spatial resolutions for smallholder yam and pigeonpea fields in Ghana, and bean growing areas in Honduras.
Lessons from the research projects and recommendations on using agricultural technologies for international agricultural development are outlined in Chapter 6.
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