Integrating field surveys and remote sensing to optimize phosphorus resource management for rainfed rice production in the Central plateau of Burkina Faso

Abstract

Rice production in sub-Saharan Africa (SSA) is restricted by low water availability, soil fertility, and fertilizer input, and phosphate rock (PR) application is expected to increase production. Soil water conditions and soil types affect the efficacy of phosphorus fertilization in improving productivity. However, these factors are rarely discussed together. In this study, we aimed to investigate the soil types and soil water conditions in the fields, as well as their effects on rice productivity after phosphorus fertilization, and optimize the findings using remote sensing techniques. A soil profiling survey, followed by a field experiment in seven farmer fields, was performed in the Central plateau of Burkina Faso. The following treatments were applied: nitrogen and potassium fertilization without phosphorus (NK), PR application with NK (NK+PR), and triple super phosphate (TSP) application with NK (NK+TSP). Submergence duration and cumulative water depth were recorded manually. The inundation score, estimated using a digital elevation model, explained the distribution of soil types and soil water conditions and correlated negatively with sand content and positively with silt and clay content, indicating an illuvial accumulation of fine soil particles with nutrient transportation. The field experiment showed that although grain yield was significantly restricted by phosphorus deficiency, the increase in yield after phosphorus fertilization was higher in Lixisols and Luvisols than in Cambisols because of the low Bray-2-phosphorus content of Lixisols and Luvisols. The inundation score correlated positively with grain yields after NK+PR and NK+TSP treatments. In conclusion, soils with low inundation scores (mainly Lixisols and Luvisols) showed a drastic increase in grain yield after TSP application, whereas those with high inundation scores showed comparable yields after PR and TSP application despite the low phosphorus fertilization effect. Our findings would help optimize fertilization practices to increase rice productivity in SSA.

Fig 1. Observation points overlaid onto the topographical map of the study area.

Fig 2. Flowchart of the inundation score estimation process and the study design.

DEM, digital elevation model; AW3D30, ALOS World 3D-30m DEM (https://www.eorc.jaxa.jp/ALOS/en/aw3d30/data/index.htm); P. phosphorus.

Fig 3

Relationships between (A) water accumulation and longitudinal convexity and (B); water accumulation and cross-sectional convexity. Lixisols, Luvisols, and Cambisols: Soil type in the World Reference Base for Soil Resources (WRB) system [30].

Fig 4. Biplot of principal component analysis.

PC, principal component; Rain, cumulative precipitation during the growing season; WA, water accumulation score; LC, longitudinal convexity; CC, cross-sectional convexity; Submerge, submergence duration; Depth, cumulative water depth.

Fig 5. Relationships between inundation score and soil particle distribution, submergence duration, and cumulative water depth.

Points represent the mean ± standard error for the three years (2013–2015). Soil particles represent the weighted average sand, silt, and clay content in the 0–20 cm soil layer. If the relationship was significant, regression lines and equations were drawn (p <0.05). R²_adj, adjusted coefficient of determination; gray region, 95% confidence interval.

Fig 6

Relationships between inundation score and rice grain yield in the different fertilization treatments (A) and between the relative grain yield of PR+NK over TSP+NK (B). Points represent the mean ± standard error for the three years (2013–2015). If the relationship was significant, regression lines and equations were drawn (p <0.05). CT, without fertilization; NK, without P fertilization with N and K fertilization; NK+PR, PR application with N and K fertilization; NK+TSP, TSP application with N and K fertilization; N, nitrogen; P, phosphorus; PR, phosphate rock; K, potassium; R²_adj, adjusted coefficient of determination; gray region, 95% confidence interval.