We've analyzed and compared the top 4 API providers supporting Soil Data for Nigerian developers and businesses. Find the right infrastructure fit for your startup below.
Written by Editorial Staffs as at 5th August, 2026
← Swipe to compare all 4 APIs →
iSDAsoil is an open-access soil data service developed by the International Soil and World Isric Data Centre for Africa, providing 30-meter resolution soil property maps across sub-Saharan Africa derived from machine learning models trained on thousands of soil samples collected across the continent. The iSDAsoil API provides programmatic access to this dataset, allowing agritech platforms, researchers, and farm advisory systems to query soil properties at any coordinates in Nigeria and across sub-Saharan Africa without requiring costly soil testing. The dataset covers 17 key soil properties including pH, organic carbon, total nitrogen, available phosphorus, potassium, calcium, magnesium, soil texture (percent sand, silt, and clay), bulk density, cation exchange capacity, and soil water holding capacity. These properties are provided at multiple soil depth layers — typically 0-20cm and 20-50cm — representing the root zone relevant for most agricultural crops. Having data at multiple depths allows for differentiated analysis of topsoil versus subsoil characteristics that affect nutrient availability and water retention differently. The spatial resolution of 30 meters is fine enough to capture field-level variation within a single farm. A typical Nigerian smallholder farm of 1-5 hectares may span several 30m grid cells, allowing soil property maps to show intra-farm variability. Areas with different soil textures, pH levels, or organic matter contents within the same farm can be identified through iSDAsoil queries, providing the data foundation for variable-rate fertilizer application recommendations that optimize input efficiency. Soil pH is among the most important parameters for crop productivity. Many Nigerian soils in humid forest zones tend toward acidity, limiting nutrient availability even when fertilizers are applied. iSDAsoil's pH data at the field level allows advisory tools to identify farms where lime application would unlock existing soil nutrients and dramatically improve fertilizer use efficiency, without requiring each farmer to pay for individual soil tests. Soil organic carbon is a key indicator of soil health, water retention, and natural nutrient supply. iSDAsoil's organic carbon data for Nigerian farmlands helps agritech platforms identify degraded soils with low organic matter that would benefit from organic inputs, compost, or cover cropping, and track the general state of soil health across agricultural landscapes for conservation planning. For agritech companies building farm advisory apps in Nigeria, iSDAsoil provides an immediate soil intelligence layer that can be queried for any farm location at negligible cost compared to laboratory soil testing. Rather than advising all farmers with the same generic fertilizer recommendations, apps can use iSDAsoil data to differentiate advice based on the actual soil properties measured at the farm's specific location. Agricultural lenders and microfinance institutions providing input loans to Nigerian farmers can use iSDAsoil data as one input into crop potential assessment. Fields with better soil physical and chemical properties carry lower agronomic risk, which can inform loan sizing or interest rates for input finance products. Integrating soil intelligence into credit scoring models makes agricultural lending more data-driven and less reliant on manual field visits. The iSDAsoil REST API accepts latitude and longitude coordinates and returns soil property values for the queried location. Responses include values at each depth layer and uncertainty estimates reflecting model confidence at the queried point. Applications that display soil data to users can include these uncertainty bounds to communicate the confidence level of the estimates clearly.
Ujuzi Kilimo Data is the data services layer of Ujuzi Kilimo, an East African agritech company that has built one of Africa's most comprehensive soil intelligence platforms through systematic soil sample collection and laboratory analysis across agricultural regions. The Ujuzi Kilimo Data API provides access to soil testing results, derived crop recommendations, and precision agriculture advisory services to agritech developers and agricultural service providers building farm advisory tools for African markets including Nigeria. Ujuzi Kilimo's core innovation is a soil testing and advisory system scaled for smallholder farmer economics. Traditional laboratory soil testing in Africa costs between $20-50 per sample, which is unaffordable for smallholder farmers with income levels of $1-5 per day. Ujuzi Kilimo has driven down testing costs through efficient sample collection programs, shared laboratory analysis, and spatially referenced soil databases that allow interpolation of soil properties to untested locations near tested ones. This cost reduction strategy makes soil intelligence economically viable at the smallholder scale that dominates African and Nigerian agriculture. The soil intelligence database that Ujuzi Kilimo has built through systematic sampling covers key agricultural regions with spatially referenced soil property measurements including pH, nitrogen, phosphorus, potassium, calcium, magnesium, organic carbon, and soil texture. This database is continuously expanded through ongoing sampling programs and allows soil property queries for locations near sampled areas through spatial interpolation models, providing soil data coverage that extends well beyond the specific sampling locations. Crop-specific nutrient recommendations generated from Ujuzi Kilimo's advisory models combine soil nutrient status with crop nutrient requirements at different growth stages to produce fertilizer prescriptions tailored to the actual soil deficiencies at each farm location. For a Nigerian farmer growing maize on a field with measured phosphorus deficiency and adequate nitrogen, the recommendation differs from a generic NPK formula — the Ujuzi Kilimo recommendation might specify a phosphorus-heavy starter fertilizer at planting with a reduced nitrogen topdress, reflecting the actual soil condition rather than average crop requirements. pH-based lime recommendations are among the highest-value outputs of the Ujuzi Kilimo system for Nigerian agriculture. Soil acidity is a widespread and underdiagnosed constraint on Nigerian crop yields, particularly in the forest zone soils of southern and central Nigeria where leaching over long periods has depleted base cations. Many Nigerian farmers apply fertilizer to acidic soils without liming first, drastically reducing fertilizer use efficiency. Soil-specific lime rate recommendations from Ujuzi Kilimo's data can unlock latent yield potential for Nigerian farmers at relatively low cost. Integration of Ujuzi Kilimo Data into Nigerian agritech applications allows those apps to move from generic crop advisory content — one-size-fits-all recommendations that apply equally to all farmers regardless of their specific soil conditions — to location-specific, soil-informed recommendations that are more accurate and more credible to farmers who know their specific fields have specific characteristics. This customization is what turns a generic advisory app into a trusted agronomic advisor. Agricultural input companies operating in Nigeria can use Ujuzi Kilimo Data to match their product portfolio to farmer soil needs at scale. Rather than promoting the same fertilizer blend to all farmers, input companies can use soil data to recommend specific products matched to demonstrated soil deficiencies, improving farmer outcomes, building brand loyalty, and enabling more targeted marketing and distribution. For Nigerian microfinance institutions and agricultural lenders offering input credit, soil quality data from Ujuzi Kilimo provides agronomic context for loan risk assessment. A farmer with good soil quality that is currently nutrient-deficient represents good lending risk if provided with the right inputs at the right time; a farmer with structural soil problems may need different support. Integrating soil intelligence into agricultural lending decisions moves the industry toward more accurate, data-driven risk assessment.
iSDAsoil is the soil data platform developed by iSDA (International Soil and World Isric Data Centre for Africa) as part of the Africa Soil Information Service program, providing machine learning-derived soil property maps at 30-meter resolution across the entirety of sub-Saharan Africa. As the most spatially detailed and comprehensive open soil dataset available for Africa, iSDAsoil is foundational infrastructure for precision agriculture, agronomic advisory services, and agricultural research across Nigerian and African agricultural landscapes. The soil mapping methodology behind iSDAsoil combines thousands of soil profile observations collected across sub-Saharan Africa with spatially explicit environmental co-variables — terrain attributes derived from digital elevation models, climate data, vegetation index time series, parent material maps, and land cover classifications — to train random forest machine learning models that predict soil properties at unsampled locations. These models are applied at 30-meter grid resolution across the entire sub-Saharan Africa domain, generating continuous prediction surfaces for each soil property. The dataset covers 17 key soil properties at two depth intervals: 0-20cm representing the topsoil layer most critical for seedbed preparation, early-stage nutrient uptake, and soil organic matter dynamics; and 20-50cm representing the subsoil layer relevant to deep-rooted crop water and nutrient access. Having properties at both depths allows differentiated analysis of topsoil versus subsoil conditions that affect management recommendations differently. Soil pH is among the most impactful iSDAsoil variables for Nigerian agriculture. Large areas of Nigerian farmland, particularly in the humid forest zones of southern Nigeria and the derived savanna of the middle belt, have inherently acidic soils due to geological parent materials and centuries of leaching. Low pH limits phosphorus availability, inhibits microbial activity, and reduces the effectiveness of nitrogen fertilizers. iSDAsoil's pH data for Nigerian agricultural areas helps agritech advisory platforms identify fields where lime application is needed before fertilizer programs will achieve full effectiveness. Soil organic carbon (SOC) from iSDAsoil provides a spatial picture of soil health and natural fertility across Nigerian farmlands. SOC is a critical indicator of soil biological activity, water retention capacity, structural stability, and natural nitrogen supply. Nigerian soils under long-term continuous cultivation without organic matter replacement — which describes a large share of Nigeria's smallholder farmland — have depleted SOC reserves that limit both yield potential and resilience to drought stress. SOC data helps identify areas where soil health restoration through composting, cover cropping, or agroforestry would have the greatest impact. Available phosphorus from iSDAsoil is particularly actionable for Nigerian fertilizer recommendation systems. Phosphorus is one of the most commonly deficient nutrients in Nigerian soils, and phosphorus deficiency is a major yield-limiting factor for legumes, cassava, and cereals across many zones. Knowing the initial available phosphorus level at a specific farm location allows fertilizer advisories to prescribe appropriate phosphorus application rates — neither underapplying (leaving yield on the table) nor overapplying (wasting inputs and risking environmental runoff). The REST API interface provides straightforward programmatic access to iSDAsoil data: submit a latitude-longitude pair and receive JSON responses containing soil property values with uncertainty estimates for the queried location. This simple query pattern requires minimal development effort to integrate into Nigerian agritech apps — any application that can make an HTTP request can query iSDAsoil soil properties for any farm location in Nigeria and use those values to drive soil-specific recommendations. For policy applications, iSDAsoil data enables national-scale soil condition mapping for Nigeria that informs agricultural development investment priorities, fertilizer subsidy allocation, land use planning, and food security projections based on underlying soil resource quality across different Nigerian states and agroecological zones.
NextYield by Ujuzi Kilimo is an agricultural data API that provides soil testing data, precision farming recommendations, and crop advisory services derived from Ujuzi Kilimo's soil intelligence platform focused on East and West Africa. Ujuzi Kilimo has built an extensive soil testing network and data model across African farming regions, and the NextYield API makes this data accessible to agritech developers building farm advisory platforms, digital extension services, and precision agriculture tools for African markets including Nigeria. The foundational insight behind Ujuzi Kilimo and NextYield is that African smallholder farmers make planting, fertilization, and management decisions with very little data about their specific soils and what those soils need. Generic fertilizer recommendations designed for average soil conditions are applied to fields with dramatically varying soil properties, resulting in either under-fertilization (crop underperformance) or over-fertilization (wasted inputs and cost). Soil-specific recommendations based on actual soil measurements dramatically improve fertilizer use efficiency and yields. Ujuzi Kilimo's soil testing program collects physical soil samples from African farms, analyzes them in certified laboratories for key parameters including pH, nitrogen, phosphorus, potassium, organic matter, and soil texture, and builds a spatially referenced database of soil properties across agricultural landscapes. NextYield APIs access this database plus derived recommendation models to provide crop-specific advice calibrated to the actual soil conditions at queried farm locations. Crop recommendations from NextYield are generated based on the intersection of soil properties, local climate data, and crop agronomic requirements. For a Nigerian farmer querying what inputs to apply to a specific field for a maize crop, NextYield can recommend fertilizer type, application rate, and timing based on the soil's measured nutrient levels and pH, rather than applying national average recommendations that may not reflect field reality. Yield prediction capabilities help Nigerian farmers and agricultural businesses plan harvests, optimize pre-sale agreements, and manage supply chain logistics. A farm advisory app that can tell a farmer their expected yield range for the current season based on soil quality, applied inputs, and weather helps that farmer make better decisions about storage, transport, and market timing. Agritech platforms in Nigeria focused on input sales optimization — whether direct-to-farmer apps or B2B agribusiness tools — can use NextYield to match specific fertilizer and soil amendment products to farm needs. Recommending the specific product and dose that the soil actually requires, rather than a generic NPK blend, improves outcome quality for farmers and builds trust in the advisory platform. For Nigerian agricultural lenders and microfinance institutions offering input credit, soil quality data from NextYield provides agronomic context for loan decisions. Farms with soil deficiencies that can be corrected with targeted inputs represent good lending candidates if the input recommendations are followed; farms with structural soil problems may warrant different loan structures or more intensive agronomic support. NextYield data is particularly relevant for Nigeria's fertilizer subsidy programs and agricultural input distribution systems. Government programs seeking to optimize subsidy allocation by directing the right inputs to farms that most need them can use soil intelligence to prioritize distribution based on demonstrated soil needs rather than administrative convenience. This data-driven approach to agricultural input programs improves the cost-effectiveness of government agricultural support spending.