DOI: 10.5281/zenodo.11115815
title: Maize management and yield of smallholder farmers in Sub-Saharan Africa between 2016 and 2022

description: Yield and management practices data were collected from smallholders’ maize fields from 2016 to 2022. All fields corresponded to maize grown in pure stands (no intercropping). Data were collected from five maize producing regions in Sub-Saharan Africa: (i) north-central Nigeria (n = 115), (ii) Rwanda and Burundi (n = 2720), (iii) central Zambia (n = 861), (iv) southwest Tanzania (n = 3710), and (v) eastern Uganda and western Kenya (n = 7367). Data were collected by One Acre Fund (https://oneacrefund.org/), an NGO that provides smallholder farmers access to agricultural training, credit, crop insurance services, and farming supplies. About half of the fields in the database comprised farmers who subscribed to the One Acre Fund program and the other half farmers who did not. 

Maize grain yield, plant density, and row spacing were measured in two randomly placed boxes of 36 square meters at harvest, avoiding field edges. Field geolocation was recorded in 70% of the observations. When missing, the field geolocation was defined based on the nearby town (21%) or associated district (9%) location for the purpose of retrieving climate data. Management practices associated with each field were reported by farmers, including sowing and harvest dates, cultivar name, fertilizer inputs (types and total quantities for both organic and inorganic), fertilization method, liming, weeding, and pesticides (mainly insecticides to control fall armyworms). Farmers also reported the incidence of adversities (such as pests, diseases, Striga witchweed, hail, and excess water). Field size was reported by farmers and, in those cases in which farmers could not provide an accurate measure of their field size, or there was a strong indication of mistakes (e.g., nutrient fertilizer rates out of range), One Acre Fund personnel took in-situ measurements to determine field size. Input rates per hectare were calculated as the ratio of the farmer-reported input amount and field size. Data were subjected to quality control to remove unlikely values. Maize yield outliers were detected with a Bonferroni Outlier Test. Observations with plant densities and fertilizer rates higher than four standard deviations from the mean were excluded as well as those without geolocation, no N or P data, and atypical sowing dates. After quality control, the database contains a total of 14,773 field observations.

Inorganic fertilizer rates were converted to nutrient rates (in elemental nutrients) following typical fertilizer nutrient contents. Organic fertilizers were encoded separately in two binary variables and one continuous variable, indicating whether compost was used, if that compost contained manure, and compost application rate. Likewise, cultivars were classified into hybrids or open pollination varieties (OPVs), which included local varieties, retained seed, and improved OPVs. For hybrids, we retrieved the associated crop cycle maturity (short, medium, and long), disease tolerance traits, and year of release from companies’ seed catalogs. Reported incidence of diseases and insect pests (e.g., anthracnose, aphids, blight, cutworms, drought, fall armyworm, stemborer, termites, and stalk or kernel rot) were simplified to two binary variables indicating whether the crop was affected by pests and/or diseases. Infestation by parasitic witchweeds (Striga hermonthica and S. asiatica) was considered as a separate variable. Fertilization methods were also simplified to whether the fertilizer was applied inside a hole or broadcasted in the surface. Number of weeding operations was simplified to zero, one or two or more weeding per season. Sowing dates were expressed as a deviation from the estimated average sowing date for each climate zone-season combination. Fields were grouped based on their location using the climate zone scheme developed by the Global Yield Gap Atlas Project (www.yieldgap.org). Isolated observations (more than three standard deviations from the median distance across sites within the climate zone) were excluded from their group. In the case of climate zones with two maize seasons, each crop season was considered as a separate group. Field elevation was retrieved from the Amazon Web Services Terrain Tiles. Total precipitation during the growing season, as well as for early, flowering, and grain filling phases, was retrieved from CHIRP.  For observations with field-level coordinates data, root-zone plant-available water-holding capacity was retrieved from the World Soil Information database, and soil clay content, pH, organic carbon, and effective cation exchange capacity from iSDA. Lastly, the topography wetness index (TWI) was calculated from the elevation data. 

Table 1. List of survey-derived variables.








Name
Type
Unit
Description


plant_date_dev
discrete
days
sowing date deviation from cluster average


pl_m2
continuous
# m2
plant density (plants per area)


row_spacing
continuous
cm
distance between rows


hybrid
binary
-
Was a commercial hybrid seed used?


hyb_mat
ordinal
-
hybrid maturity (early, medium, late)


hyb_yor
continuous
-
Year of release of the cultivar


hyb_tol_mln
binary
-
Tolerance to maize lethal necrosis


hyb_tol_msv
binary
-
Tolerance to maize streak virus


hyb_tol_gls
binary
-
Tolerance to gray leaf spot


hyb_tol_nclb
binary
-
Tolerance to northern corn leaf blight


hyb_tol_rust
binary
-
Tolerance to rust


hyb_tol_ear_rot
binary
-
Tolerance to ear rot


N_kg_ha
continuous
kg/ha
N fertilization rate


P_kg_ha
continuous
kg/ha
P fertilization rate


K_kg_ha
continuous
kg/ha
K fertilization rate


compost
binary
-
Was compost applied?


comp_t_ha
continuous
t/ha
compost rate


manure
binary
-
Did the compost contain manure?


fert_in_hole
binary
-
Was the fertilizer applied in a hole?


lime_kg_ha
continuous
kg/ha
lime rate


weeding
discrete
#
number of times the plot was weeded


pesticide
binary
-
Was any pesticide applied?


disease
binary
-
Was yield affected by diseases?


pest
binary
-
Was yield affected by pests?


striga
binary
-
Was yield affected by the Striga weed?


water_excess
binary
-
Was yield affected by water excess (heavy rain or flooding)?




 

Table 2. List of environmental variables. 

 






Name
Unit
Spatial resolution
Description
Source


GDD
°C days
30 arc-sec (1km)
Growing degree days
www.worldclim.org


AI
unitless
30 arc-sec (1km)
Aridity Index (annual precipitation over potential evapotranspiration)
www.worldclim.org


TS
°C
30 arc-sec (1km)
Temperature seasonality
www.worldclim.org


season_prec
mm
3 arc-min (5.6 km)
Total rainfall during the maize season (10% of planting to 50% of the harvest)
www.chc.ucsb.edu/data/chirps


season_prec_1
mm
3 arc-min (5.6 km)
Rainfall during the first third of the season
www.chc.ucsb.edu/data/chirps


season_prec_2
mm
3 arc-min (5.6 km)
Rainfall during the second third of the season
www.chc.ucsb.edu/data/chirps


season_prec_3
mm
3 arc-min (5.6 km)
Rainfall during the last third of the season
www.chc.ucsb.edu/data/chirps


elev
m.a.s.l.
75 meters
Elevation (altitude) above sea level
registry.opend26ata.aws/terrain-tiles


soil_rzpawhc
mm
1 km
Root zone plant-available water holding capacity
www.isric.org


soil_clay
%
30 meters
Clay content at 0-20cm soil depth
www.isda-africa.com 


soil_pH
-
30 meters
pH (H2O) at 0-20cm soil depth
www.isda-africa.com 


soil_orgC
g/kg
30 meters
Organic carbon at 0-20cm soil depth
www.isda-africa.com 


soil_ECEC
cmolc/kg
30 meters
Effective cation exchange capacity at 0-20cm soil depth
www.isda-africa.com 


twi
unitless
75 meters
Topographic Wetness Index
calculated from elevation