Simulation of fertilizer application profitability for Tanzania

These scripts are used to predict if N application is profitable in maize farms in Tanzania. Incorporating soil characteristics, maize price predictions, fertilizer price and distance to markets.

This code is the basis for the analysis in: Palmas S, Chamberlin J (2020) Fertilizer profitability for smallholder maize farmers in Tanzania: A spatially-explicit ex ante analysis. PLoS ONE 15(9):e0239149. https://doi.org/10.1371/journal.pone.0239149

Code

• simulationsYieldModel/simulation_OPnetrev_rf.R: simulation to get an optimized nitrogen application amount for a maximum profitability.
• simulationsYieldModel/simulation_OPyield_rf.R: simulation to get an optimized nitrogen application amount for a maximum yield.
• simulationsYieldModel/simulation_ZERO_BK_rf.R: simulation for no nitrogen and a blanket nitrogen application amount.
• simulationsYieldModel/N_to_netrev.R: Definition of the fitness function to optimize for profitability.
• access.rmd: to estimate time from every pixel to to large cities.
• buildraster.R: function to use when constructing a raster from values in a table.
• fertilizer_price.rmd: simple model to create fertilizer price using city access, a mean fertilizer price and a correction factor depending on transportation costs.
• fertilizer_prof_measures.R: Methods for fertilizer profitability measures such as NUE, AVCR, MVCR.
• fitness.R: Methods for r squared and RMSE.
• maize_price_farmgate.rmd: To estimate maize farmgate prices depending on market prices in several locations and using market access.
• maize_price_market.rmd: Random forest model to predict maize market prices using multiple covariates.
• make_soilprice_table.R: Creates a table from multiple rasters that will be used in the simulation.
• preprocess_rasters.sh: Processes all original elevation, slope, soil, rainfall rasters to a common geometry to use in the analysis. It runs as a bash script in linux.
• rainfall_CV.R: To estimate coefficient of variance of the rainfall in Tanzania.
• Results_TablesFigures.rmd: To create tables and figures for the paper.
• run_simulations.sh:
• TZAPS_hhid_coords_extract.R: to extract covariates from many rasters into a table with the household measurements to use in the yield prediction.
• yield_response.R: Deprecated linear fit model for yield response. Superseded by random forest model.
• yield_response_fit.rmd: To fit a random forest model for yield using multiple covariates.

Data

• data/hh_summary_stats.csv: Contains all the household variable means used in the simulation.

• data/models/yield.rf2.rda: Random forest model used in the simulation.