Failure to scale in digital agronomy: An analysis of site-specific nutrient management decision-support tools in developing countries

While many have extolled the potential impacts of digital advisory services for smallholder agriculture, the evidence for sustained uptake of such tools remains limited. This paper utilizes a survey of tool developers and researchers, as well as a systematic meta-analysis of prior studies, to assess the extent and challenges of scaling decision support tools for site-specific soil nutrient management (SSNM-DST) across smallholder farming systems, where "scaling" is defined as a significant increase in tool usage beyond pilot levels. Our evaluation draws on relevant literature, expert opinion and apps available in different repositories. Despite their acclaimed yield benefits, we find that SSNM-DST have struggled to reach scale over the last few decades and, with strong heterogeneity in adoption among intended stakeholders and tools. For example, the log odds of a SSNM-DST reaching 5-10 % of the target farmers compared with reaching none, decreases by ∼200% when a technical problem is stated as a reason for the tools' failure to be used at scale. We find a similar decrease in odds ratios when technical, socioeconomic, policy, and R&D constraints were identified as barriers to scaling by national extension and private systems. Meta-regression analysis indicates that the response ratio of using SSNM-DST over Farmer Fertilizer Practice (FFP) varies by non-tool related covariates, such as initial crop yield potential under FFP, current and past crop types, acidity class of the soil, temperature and rainfall regimes, and the amount of input under FFP. In general, the SSNM-DST have moved one step forward compared with the traditional 'blanket' fertilizer recommendation by accounting for in-field heterogeneities in soil and crop characteristics, while remaining undifferentiated in terms of demographic and socioeconomic heterogeneities among users, which potentially constrains adoption at scale. The SSNM-DSTs possess reasonable applicability and can be labeled 'ready' from purely scientific viewpoints, although their readiness for system-level uptake at scale remains limited, especially where socio-technical and institutional constraints are prevalent.

Establishment and validation of site specific fertilizer recommendation for increased barley (Hordeum spp.) yield, northern Ethiopia

Establishing model based balanced nutrient requirements for barley (Hordeum spp.) in the northern Ethiopia can solve the fertilizer recommendation problems and enhance crop yield. The Quantitative Evaluation of Fertility of Tropical Soils (QUEFTS) model was used to estimate balanced nitrogen (N), phosphorus (P) and potassium (K) requirements for barley production in Alaje, northern Ethiopia. The objectives were to (i) quantify soil N, P and K supply and recommend fertilizers using QUEFTS model; (ii) investigate response of QUEFTS fertilizer application on yield and nutrient uptake and (iii) validate QUEFTS model performance. The experiment had four treatments: (T1) model based fertilization; (T2) blended fertilization; (T3) farmers’ fertilization practices and (T4) control/no fertilizer. Soil information of the experimental plots were analyzed and used as model input to estimate soil nutrient supplies and recommend fertilizer. Yield and agronomic data were recorded and nutrient uptake and use efficiencies were analyzed. Model performance and accuracy were also checked using root mean square error, coefficient of determination, index of agreement and percent bias. The result revealed that the N, P and K soil supply ratio in the field experimental plots were 9:1:6. The higher grain yield of 4747 kg ha⁻¹ was recorded in the QUEFTS based fertilization plots. Validation results indicated that there is a good correlation between the QUEFTS predicted and observed grain yields implying that the QUEFTS model can be a base for development of simple and cost-effective decision support tools for nutrient management and fertilizer recommendations. Thus, the model performance and prediction accuracy is promising and can help farmers to adjust fertilizer application rates based on crop requirements.

Field-specific nutrient management using Rice Crop Manager decision support tool in Odisha, India

The requirement of rice (Oryza sativa L.) for fertilizer can depend on crop and soil management practices, which can vary among fields within a rice-growing area. A web-based decision support tool named Rice Crop Manager (RCM) was developed previously to calculate field-specific rates of fertilizer N, P, and K for rice in Odisha State in eastern India. We compared field-specific nutrient management calculated by RCM with farmers' fertilizer practice (FFP) and a blanket fertilizer recommendation (BFR), which used a uniform 80 kg N ha-1, 17 kg P ha-1, and 33 kg K ha-1. A total of 209 field trials were conducted in two seasons (kharif and rabi) for two years across ten districts in six agro-climatic zones. Grain yield was consistently higher with fertilization recommended by RCM than with FFP. Higher yield with RCM was attributed to a combination of applying more of the total fertilizer N at the critical growth stage of panicle initiation, applying more fertilizer N in kharif, and applying zinc. The RCM recommendation frequently increased yield compared to BFR as a result of improved N management, which included the adjustment of N rate for a target yield set slightly higher than historical yield reported by a farmer. Fertilization based on RCM rather than BFR reduced the risk of financial loss. The effectiveness of an RCM recommendation relative to BFR and FFP was consistent across rice varieties with different growth duration, irrigated and rainfed rice, and three categories of soil clay content. The RCM recommendation failed to increase yield relative to BFR in one of the six agro-climatic zones, where a higher rate of fertilizer P and/or K was apparently required. The nutrient management calculations used by RCM can be improved as new information and research findings become available. Experiences with RCM in Odisha can help guide the development of comparable nutrient management decision tools in other rice-growing areas.

Web-based tool for calculating field-specific nutrient management for rice in India

Site-specific nutrient management (SSNM) can be an alternative to a recommendation for uniform fertilizer use across a rice (Oryza sativa L.) production system within a country or region of a country. We developed a web-based decision support tool named Nutrient Manager for Rice (NMR), which used principles of SSNM to calculate fertilizer N, P, and K rates for individual fields based on a target yield set for each field. It also used expected growth duration of the rice variety, crop establishment method, and age of transplanted seedlings to calculate days after rice establishment for each of three applications of fertilizer N. NMR enabled P rates to match estimated removal of P with harvested grain and crop residue for the target yield set for each field. We compared field-specific fertilizer recommendations from NMR with uniform application of fertilizer provided by an existing blanket fertilizer recommendation for irrigated inbred rice (BFR) and farmer's fertilizer practices (FFP) in on-farm trials conducted in 74 irrigated rice fields across three growing seasons in the Cauvery Delta, Tamil Nadu, India. Grain yield was 0.6-0.7 Mg ha^-1 higher (P ≤ 0.05) with NMR than FFP in two of the three seasons, even though total fertilizer cost was comparable or less with NMR. Yield was comparable for NMR and BFR, but NMR reduced fertilizer N and P rates and total fertilizer cost compared to BFR. Use of NMR rather than BFR also had less risk of financial loss for a farmer. The likelihood of financial loss with a switch from FFP to BFR averaged 31%. It reduced to 18% with a switch from FFP to NMR. NMR facilitated the calculation of field-specific fertilizer N, P, and K management practices, which increased fertilizer use efficiency without loss in rice yield compared to a recommended uniform fertilizer management across fields.