Quantifying the prevalence of (non)-response to fertilizers in sub-Saharan Africa using on-farm trial data

Nutr Cycl Agroecosyst https://doi.org/10.1007/s10705-021-10174-1 (0123456789().,-volV) ( 01234567 89().,-volV) ORIGINAL ARTICLE Quantifying the prevalence of (non)-response to fertilizers in sub-Saharan Africa using on-farm trial data Generose Nziguheba . Joost van Heerwaarden . Bernard Vanlauwe Received: 5 March 2021 / Accepted: 20 September 2021 Ó The Author(s) 2021 Abstract Poor and variable crop responses to fertilizer applications constitute a production risk and may pose a barrier to fertilizer adoption in sub-Saharan Africa (SSA). Attempts to measure response variability and quantify the prevalence of non-response empirically are complicated by the fact that data from on-farm fertilizer trials generally include diverse nutrients and do not include on-site replications. The first aspect limits the extent to which different studies can be combined and compared, while the second does not allow to distinguish actual field-level response variability from experimental error and other residual variations. In this study, we assembled datasets from 41 on-farm fertilizer response trials on cereals and legumes across 11 countries, representing different nutrient applications, to assess response variability and quantify the frequency of occurrence of non- response to fertilizers. Using two approaches to account for residual variation, we estimated nonresponse, defined here as a zero agronomic response to fertilizer in a given year, to be relatively rare, affecting 0–1 and 7–16% of fields on average for cereals and legumes respectively. The magnitude of response could not be explained by climatic and selected topsoil variables, suggesting that much of the observed variation may relate to unpredictable seasonal and/or local conditions. This implies that, despite demonstrable spatial bias in our sample of trials, the estimated proportion of non-response may be representative for other agro-ecologies across SSA. Under the latter assumption, we estimated that roughly 260,000 ha of cereals and 3,240,000 ha of legumes could be expected to be non-responsive in any particular year. Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/ s10705-021-10174-1. Keywords Absolute response  Cereals  Fertilizer intensity based-response  Legumes  Representativeness G. Nziguheba (&) B. Vanlauwe  Central Africa hub coordination office, International Institute of Tropical Agriculture, P O Box 30772-00100, Nairobi, Kenya e-mail: J. van Heerwaarden (&) Plant Production Systems, Mathematical and Statistical Methods, Wageningen University, P.O .Box 430, 6700. AK Wageningen, The Netherlands e-mail: Introduction Low agricultural productivity, recurrent food shortages and high prevalence of food insecurity in subSaharan Africa (SSA) have led to repeated calls to intensify agriculture, with a particular focus on 123 Nutr Cycl Agroecosyst addressing the widespread soil fertility depletion in agricultural lands (UN Millennium project 2005; Sanchez 2010; Shapouri et al. 2010; Andriesse and Giller 2015; Binswanger-Mkhize and Savastano 2017). Sustainable agricultural intensification is viewed as a prerequisite for combatting food insecurity and reversing the trend of natural resource degradation (Tittonell and Giller 2013; Vanlauwe et al. 2014; Zurek et al. 2015), and an increased use of mineral fertilizers is considered to be an essential part of the solution (IFDC 2006; Sanchez 2010; Holden 2018). Despite efforts to enhance the use of fertilizers in the region (Druilhe and Barreiro-Hurle 2012; Jayne et al. 2018), average application rates remain very low, with recent studies reporting an average fertilizer use around 14 kg ha-1 (Bonilla Cedrez et al. 2020), though there is a wide variability between countries, with averages of some countries surpassing 50 kg ha-1 (Liverpool-Tasie et al. 2017; Sheahan and Barret 2017). While the accessibility to fertilizers remains a main constraint to the widespread use of fertilizers by smallholder farmers, the production risk associated with poor crop responses caused by variable weather conditions (Mafongoya et al 2007) and/ or by local edaphic constraints (e.g. limited soil rootable zone or water holding capacity and soil organic matter) i.e. the so-called non-responsive soils (Vanlauwe et al. 2010), could discourage farmers to invest in fertilizers (Holden 2018; Schut and Giller 2020). A lack of crop response to the application of fertilizers represents an obvious economic loss to farmers and, if enduring, may make fertilizer application unattractive to farmers and potentially harmful to the environment. Determining the rate of incidence of non-response to fertilizer is needed to understand the magnitude of the problem, and this requires on-farm observations on the variability in yield responses. While there is a diverse literature reporting on response variability observed in on-farm trials performed at different spatial scales across SSA (Tittonel et al. 2007; Kihara et al. 2016; Zingore et al. 2007; Ronner et al. 2016; Njoroge et al. 2017; Ichami et al. 2019; Roobroeck et al. 2021; Garba et al. 2018; Wortmann et al. 2017), few quantify the proportion of fields that fail to show an appreciable response in a given year. Two methodological issues make the quantification of non-response in on-farm data more challenging than it may seem. First, quantifying inadequate yield response in a dataset on fertilizer 123 responses requires a measure against which observations can be compared. For single nutrient fertilizers, the agronomic efficiency (AE), the amount of extra produce per quantity of nutrient applied, which is commonly reported while assessing response to inputs (Olk et al. 1999; Ngome et al. 2013; Kaizzi et al. 2012; Vanlauwe et al. 2016; Kamanga et al. 2014; Xu et al. 2014; Adiele et al. 2020) provides such a measure. However, an equivalent metric does not exist for multi-nutrient fertilizers which are typically used in on-farm trials and by farmers in SSA, often with varying rates for the different nutrients, and which are expected to illicit different yield responses to the same total amount of fertilizer. One solution is to restrict comparisons to cases where the same fertilizer is applied, but this obviously limits the scope and applicability of such analyses, given that various types of fertilizers are used in SSA. Another option is to look at economic efficiencies only, since these can be calculated on any type of fertilizer (Jayne and Rashid 2013), but the variation in response is then determined to a large extent by differences in input prices (Bonilla Cedrez et al. 2020), which can vary over space and time, therefore requiring additional estimates of agronomic response for proper interpretation and translation to current conditions. The second issue relates to the lack of on-site replication that tends to characterize on-farm trials (Bielders and Gérard 2015; Njoroge e (...truncated)