A key parameter influencing crop growth is the availability of water and its spatial distribution within agricultural soils. The strong electrical response associated with variations in water content means that electrical geophysical methods such as Electrical Resistivity Tomography ( ERT ) are ideally suited for studying soil moisture dynamics. While relative changes in electrical resistivity allow conclusions to be drawn on the temporal variability of soil moisture in the subsurface, they do not provide quantitative estimates of soil moisture. Laboratory measurements of soil moisture and electrical resistivity - together with the fitting of a model to these data (e.g. Waxman-Smits) - enable the estimation of soil moisture from ERT models. While this method is established, examples are limited for Alfisols in general, and from African sites in particular. We present laboratory data on agricultural Alfisols from three sites in southern Africa, to define relationships between electrical resistivity and volumetric water content. We fit the data to several widely used models, and utilise the novel application of Akaike’s Information Criterion to identify the best model for each dataset. In addition to identifying which model is most suitable for each site, our findings also allow us to make conclusions on whether a single or multiple models are required per site, or even whether heterogeneities make the utilisation of a model inadvisable. We then compare our results against complementary laboratory datasets to explain which soil physical parameters are the main causes of variability in electrical response at each site.

Zinc (Zn) deficiency affects over 30% of the global population, with the highest burdens in developing countries reliant on cereal-based diets. As a major dietary staple in regions such as Sub-Saharan Africa and Latin America, common bean (Phaseolus vulgaris L.) represents a promising vehicle for addressing hidden hunger. This review critically evaluates the efficacy of various strategies to enhance Zn concentration in common bean, ranging from agronomic to genetic manipulation, and proposes promising strategies for biofortifying common bean in developing countries that are resource- and technology-limited. Biofortification strategies include agronomic practices, conventional breeding, and genetic engineering, each with distinct strengths and limitations. Agronomic methods such as soil and foliar fertilization can rapidly increase micronutrient content, but they require recurrent costs and may not be sustainable for smallholders without subsidies. Genetic engineering, particularly transgenic approaches, can significantly boost Zn levels; however, regulatory hurdles, cost of production, and public acceptance remain significant obstacles to widespread adoption. Conventional breeding is secure and widely adopted, but is time-consuming and limited by genetic diversity, making it less precise and slower than genetic engineering. We argue for a context-specific and integrated biofortification framework that prioritizes agronomic interventions such as biofertilizer, seed priming, soil Zn application, and foliar Zn application as approaches for quick results. Moderate- to long-term progress towards a biofortified common bean can be achieved using conventional breeding methods by selecting for local germplasm that accumulates higher Zn amounts in grain. On the other hand, genetic engineering is best for rapid, targeted nutrient enhancement where genetic diversity is lacking, but faces regulatory and acceptance challenges. We recommend that policymakers prioritize frameworks that harmonize these approaches, improve communication and education regarding the benefits of biofortified crop produce, subsidize and strengthen biofortified seed systems, and promote soil health initiatives.

Large sample surveys with households, or individuals within households, as the basic sampled units, are important sources of information on variables related to household income, economic activity, food security and nutritional status. In many circumstances the advantages of supplementing these surveys with sampling of the soil from fields or other land units which the households cultivate may seem obvious, as a source of information on the quality of the soil on which households depend, and potential limitations on their food security such as soil pH or nutrient status. However, it is not certain that household surveys, designed to examine social and economic variables, will be efficient for collecting soil information, or will provide adequate estimates of soil property means at scales of interest. Additional sampling might be necessary, so an attendant question is whether this is feasible. In this paper we use data on soil pH and soil carbon inferred by spectral measurements on soil specimens collected from land cultivated by households in Uganda and Ethiopia to estimate variance components for these properties, and from these the standard errors for mean values at District (Uganda) or Zone (Ethiopia) level by household surveys with different designs. Similar calculations were done for direct measurement of soil carbon and soil pH from a spatial sample in Malawi from which variograms were used to infer the variance components corresponding to the levels of a household survey. The results allow the calculation of sample sizes at different levels of the design, required to allow estimates of particular quantities to be obtained with specified precision. The numbers of sampled enumeration areas required to obtain estimates of district or zone-level means with the arbitrary specified precision were large, but the feasibility of such sampling must be judged for a particular application, and the precision appropriate for that. The presented method makes that possible.

Dietary selenium (Se) deficiency is widespread in Malawi, due to the limited supply of Se in the predominantly maize based-food system characterised by low Se concentration. In this study, the aim was to examine the spatial variation of Se in maize grains in Malawi, in relation to soil properties and landscape features. Co-located soil and maize grain samples were collected in a spatially representative survey. Selenium concentration in maize, soil properties, and environmental covariates were determined. Soil and environmental variables were tested as potential predictors of Se concentration in maize. A false discovery rate (FDR) control was used within a linear mixed model (LMM) framework. Selenium concentrations in maize ranged from below detection limits (7.69 & micro;g kg(-1)) to 1852 & micro;g kg(-1) with mean and median values of 39.1 and 16.8 & micro;g kg(-1) respectively. The ranges of concentrations of Se fractions in soil were (i) soluble Se 0.181-18.8 & micro;g kg(-1)with mean and median values of 3.94 and 3.29 mg & micro;g kg(-1) respectively; (ii) adsorbed Se 0.019-119 & micro;g kg(-1) with mean and median values of 3.72 and 3.02 & micro;g kg(-1) respectively; (iii) organically bound Se 9.43-1334 & micro;g kg(-1) with mean and median values of 123 and 92.3 & micro;g kg(-1) respectively. A LMM for maize Se concentration was used for which the independent log transformed variables of soil soluble Se, adsorbed Se, oxalate extracted oxides, soluble and exchangeable sulphur had predictive value (p 0.01 in all cases, with FDR controlled at 0.05). Downscaled mean annual temperature also explained some of the spatial variation in grain Se concentration. Spatial variation of Se in maize showed relationships with soil and environmental variables, which can be used to identify areas most at risk of Se deficiency and thus inform policy responses. However, only a small proportion of the variation was explained indicating more analysis of Se geochemistry in soil may provide more explanatory insights.

ContextThe potential yield of crops is not usually realised on farms creating yield gaps. Methods are needed to diagnose yield gaps and to select interventions. One method is the boundary line model in which the upper bound of a plot of yield against a potentially limiting factor is viewed as the most efficient response to that factor and anything below it has a yield gap caused by inefficiency of other factors. If many factors are studied, the cause of the yield gap can be identified (yield gap analysis, YGA). Though the boundary line is agronomically interpretable, its estimation and statistical inference are not straightforward and there is no standard method to fit it to data.ObjectiveWe review the different methods used to fit the boundary line, their strengths and weaknesses, interpretation, factors influencing the choice of method and its impact on YGA.MethodsWe searched for articles that used boundary lines for YGA, using the Boolean “Boundary*” AND “Yield gap*” in the Web of Science.ResultsMethods used to fit boundary lines include heuristic methods (visual, Binning, BOLIDES and quantile regression) and statistical methods (Makowski quantile regression, censored bivariate model and stochastic frontier analysis). In contrast to heuristic methods, which in practice require ad hoc decisions such as the quantile value in the quantile regression method, statistical methods are typically objective, repeatable and offer a consistent basis to quantify parameter uncertainty. Nonetheless, most studies utilise heuristic methods (87% of the articles reviewed) which are easier to use. The boundary line is usually interpreted in terms of the Law of the Minimum or the Law of Optimum to explain yield gaps. Although these models are useful, their interpretation holds only if the modelled upper limit represents a boundary and not just a particular realization of the upper tail of the distribution of yield. Therefore, exploratory and inferential analysis tools that inform boundary characteristics in data are required if the boundary line is to be useful for YGA.Conclusions and implicationsStatistical methods to fit boundary line models consistently and repeatably, with quantified uncertainty and evidence that there is a boundary limiting the observed yields, are required if boundary line methods are to be used for YGA. Practical and conceptual obstacles to the use of statistical methods are required. Bayesian methods should also be explored to extend further the capacity to interpret uncertainty of boundary line models.

Background:Because micronutrient deficiencies affect public health, countries monitor population status by national-scale, multi-stage, micronutrient surveys (MNS). In design-based surveys, inclusion probabilities are specified for sample units and the corresponding sample weights allow design-unbiased estimates to be made of population parameters. Corrections may be possible on departures from the design; an alternative is to use linear mixed models (LMM), with an estimated covariance structure reflecting the sampling design, to obtain model-based estimates. Design:The Ethiopia National Micronutrient Survey (2016) specified inclusion probabilities at enumeration area (EA) and household (HH) levels, and sample weights are provided. However, the design was not followed as it would have resulted in insufficient sampling from women of reproductive age. Results:Having found no evidence that sample weights were informative for target serum micronutrient concentrations (Zn), we estimated LMM parameters, with Regions as fixed effects, and the variation of individuals nested within households, households within EA, and EA within regions, random effects. We obtained LMM standard errors, Best Linear Unbiased Estimates (BLUEs) of regional means, and empirical Best Linear Unbiased Predictions for sampled/unsampled EA and HH. The probability that each true regional mean exceeded the sufficiency threshold ( 65 μ g dL - 1 ) was evaluated. The variances of BLUEs of regional means, under alternative sampling designs, were bootstrapped from LMM variance components. Conclusions:We demonstrate use of LMM to obtain model-unbiased estimates and predictions when surveys deviate from the original design; and the use of LMM variance components to evaluate alternative designs for further sampling, or for sampling comparable populations.

The boundary line model has been proposed for interpretation of the plot of a biological response (such as crop yield) against a potentially-limiting variable from observations in a large set of scenarios across which other factors show uncontrolled variation. Under this model the upper bound of the distribution of data represents the limiting effect of the potential factor on the response. Methods have been proposed to fit this model, but we propose that an initial exploratory data analysis step is needed to evaluate evidence that (i) the model is plausible and (ii) that any limiting upper bound is exhibited by the data set (which could, in principle, not include any cases where the factor is limiting). We propose a statistic based on the density of observations in upper sections of early convex hull peels of the data plot. We evaluate this approach using various data sets, some of which have been used for boundary line analysis in previous studies.

IntroductionThe current study investigated the value of urine selenium (Se) concentration as a biomarker of population Se status in rural sub-Saharan Africa.MethodUrine and plasma Se concentrations were measured among children aged 6–59 months (n = 608) and women of reproductive age (WRA, n = 781) living in rural Zimbabwe (Murehwa, Shamva, and Mutasa districts) and participating in a pilot national micronutrient survey. Selenium concentrations were measured by inductively coupled plasma-mass spectrometry (ICP-MS), and urine concentrations were corrected for hydration status.ResultsThe median (Q1, Q3) urine Se concentrations were 8.4 μg/L (5.3, 13.5) and 10.5 μg/L (6.5, 15.2) in children and WRA, respectively. There was moderate evidence for a relationship between urine Se concentration and plasma Se concentration in children (p = 0.0236) and WRA (p = < 0.0001), but the relationship had poor predictive value. Using previously defined thresholds for optimal activity of iodothyronine deiodinase (IDI), there was an association between deficiency when indicated by plasma Se concentrations and urine Se concentrations among WRA, but not among children.DiscussionUrine Se concentration poorly predicted plasma Se concentration at sub-district scales in Zimbabwe, limiting its value as a biomarker of population Se status in this context. Further research is warranted at wider spatial scales to determine the value of urine Se as a biomarker when there is greater heterogeneity in Se exposure.

The cultivation or ‘tillage’ system is one of the most important elements of agrotechnology. It affects the condition of the soil, significantly modifying its physical, chemical, and biological properties, and the condition of plants, starting from ensuring appropriate conditions for sowing and plant growth, through influencing the efficiency of photosynthesis and ultimately, the yield. It also affects air transmission and the natural environment by influencing greenhouse gas (GHG) emissions potentially. Ultimately, the cultivation system also has an impact on the farmer, providing the opportunity to reduce production costs. The described experiment was established in 1998 at the Brody Agricultural Experimental Station belonging to the University of Life Sciences in Poznań (Poland) on a soil classified as an Albic Luvisol, while the described measurements were carried out in the 2022/2023 season, i.e., 24 years after the establishment of the experiment. Two cultivation methods were compared: Conventional Tillage (CT) and No Tillage (NT). Additionally, the influence of two factors was examined: nitrogen (N) fertilization (0 N—no fertilization, and 130 N–130 kg N∙ha−1) and the growth phase of the winter wheat plants (BBCH: 32, 65 and 75). The growth phase of the plants was assessed according to the method of the Bundesanstalt, Bundessortenamt and CHemische Industrie (BBCH). We present the results of soil properties, soil respiration, wheat plants chlorophyll fluorescence, and grain yield. In our experiment, due to low rainfall, NT cultivation turned out to be beneficial, as it was a key factor influencing the soil properties, including soil organic carbon (SOC) content and soil moisture, and, consequently, creating favorable conditions for plant nutrition and efficiency of photosynthesis. We found a positive effect of NT cultivation on chlorophyll fluorescence, but this did not translate into a greater yield in NT cultivation. However, the decrease in yield due to NT compared to CT was only 5% in fertilized plots, while the average decrease in grain yield resulting from the lack of fertilization was 46%. We demonstrated the influence of soil moisture as well as the growth phase and fertilization on carbon dioxide (CO2) emissions from the soil. We can clearly confirm that the tillage system affected all the parameters discussed in the work.

The Ecological Survey of Northern Rhodesia (now Zambia), undertaken in the 1930s under the leadership of Colin G. Trapnell, was a seminal exercise to relate soil, vegetation, and agricultural practices through intensive field observation. In this article, we examine early activities of the survey in the Upper Valley region around the Kafue Flats and the neighbouring plateau, where Trapnell recognized how geomorphological processes of normal erosion gave rise to distinctive soils with associated vegetation communities and considerable potential for crop production. We consider how Trapnell's approach to fieldwork gave him a particular insight into how soil conditions constrained agriculture in the Zambian environment; the adaptive value of traditional practices; and how these were developed as communities moved and responded to social, economic, and environmental change. We argue that Trapnell's work was innovative and that distinctions must be drawn between his understanding and what has been called the ecological theory of development. Close attention to Trapnell's experience could inform modern efforts to understand indigenous knowledge of African soils and their agricultural potential.

Africa’s potential for scientific research is not yet being realized, for various reasons including a lack of researchers in many fields and insufficient funding. Strengthened research capacity through doctoral training programmes in higher education institutes (HEIs) in Africa, to include collaboration with national, regional and international research institutions, can facilitate self-reliant and sustainable research to support socio-economic development. In 2012, the Royal Society and the UK’s Department for International Development (now the Foreign, Commonwealth and Development Office) launched the Africa Capacity Building Initiative (ACBI) Doctoral Training Network which aimed to strengthen research capacity and training across sub-Saharan Africa. The ACBI supported 30 core PhD scholarships, all registered/supervised within African HEIs with advisory support from the UK-based institutes. Our ‘Soil geochemistry to inform agriculture and health policies’ consortium project, which was part of the ACBI doctoral training programme network, was implemented in Malawi, Zambia and Zimbabwe between 2014 and 2020. The aims of our consortium were to explore linkages between soil geochemistry, agriculture and public health for increased crop productivity, nutrition and safety of food systems and support wider training and research activities in soil science. Highlights from our consortium included: (i) the generation of new scientific evidence on linkages between soils, crops and human nutrition; (ii) securing new projects to translate science into policy and practice; and (iii) maintaining sustainable collaborative learning across the consortium. Our consortium delivered high-quality science outputs and secured new research and doctoral training funding from a variety of sources to ensure the continuation of research and training activities. For example, follow-on Global Challenges Research Funded Translation Award provided a strong evidence base on the prevalence of deficiencies in children under 5 years of age and women of reproductive age in Zimbabwe. This new evidence will contribute towards the design and implementation of a nationally representative micronutrient survey as an integral part of the Zimbabwe Demographic and Health Surveys conducted by the Ministry of Health and Child Care. The award also generated new evidence and a road map for creating quality innovative doctorates through a doctoral training landscape activity led by the Zimbabwe Council for Higher Education. Although our project and the wider ACBI has contributed to increasing the self-reliance and sustainability of research within the region, many challenges remain and ongoing investment is required.

&lt;p&gt;Soils are a significant store of organic carbon, globally storing an estimated 1550 Gt C to a depth of 1 metre. They are also substantial sources of greenhouse gas (GHG) emissions, contributing one-fifth of global CO&lt;sub&gt;2&lt;/sub&gt; emissions, one-third of CH&lt;sub&gt;4&lt;/sub&gt; emissions and two-thirds of N&lt;sub&gt;2&lt;/sub&gt;O emissions. Soil carbon in agricultural lands can represent a net sink or source of CO&lt;sub&gt;2&lt;/sub&gt; depending on microclimate, cropping history and land management. Zero-tillage is an increasingly popular strategy to minimise soil erosion, increase biological activity and promote soil health. However, the extent to which zero-tillage reduces GHG emissions whilst increasing soil carbon, compared to other management strategies, is extensively debated, and represents a crucial knowledge gap in the context of climate change mitigation. Contrasting tillage strategies not only affect the stability and formation of soil aggregates but also modify the concentration and thermostability of soil organic matter (SOC) associated within them. Understanding the thermostability and carbon retention ability of aggregates under different tillage systems is essential to ascertain potential terrestrial carbon storage and greenhouse gas release.&lt;/p&gt; &lt;p&gt;&amp;#160;&lt;/p&gt; &lt;p&gt;Across Brazil, zero-tillage accounts for c. 45% of agricultural management, thereby making it a critical agricultural management practice throughout South America. This has been a popular management strategy since the 1940s and provides long-term field sites for which to understand and elucidate the key mechanisms which govern carbon retention/mineralization across different tillage managements. We measured GHG release and characterized the concentration and thermostability of SOC within various aggregate size classes under both zero and conventional tillage using Rock-Eval pyrolysis. The geometry of the pore systems was quantified by X-ray Computed Tomography and used to link soil structural characteristics to organic carbon preservation, thermostability and GHG release. Soil samples were collected from experimental fields across Brazil, which had been under zero-tillage for as little as one year up to 31&amp;#8201;years, and from adjacent fields under conventional tillage.&lt;/p&gt; &lt;p&gt;&amp;#160;&lt;/p&gt; &lt;p&gt;Soils under zero-tillage had significantly increased pore connectivity whilst simultaneously decreasing interaggregate porosity, providing a potential physical mechanism for protection of SOC in the 0&amp;#8211;20-cm soil layer. Changes in the soil physical characteristics associated with the adoption of zero-tillage resulted in improved aggregate formation compared to conventionally tilled soils, especially when implemented for at least 15&amp;#8201;years. In addition, we identified a chemical change in composition of organic carbon to a more recalcitrant fraction following conversion to zero-tillage, suggesting aggregates were accumulating rather than mineralizing SOC. This study also revealed that, when combining all three GHG fluxes, potential global warming potential from zero-tilled soils was 50% smaller than that of conventionally tilled soils. These data reveal profound effects of different tillage systems upon soil structural modification, with important implications for the potential of zero-tillage to simultaneously increase carbon sequestration and decrease GHG release compared to conventional tillage, contributing to mitigating against climate change in these soils.&lt;/p&gt;

Background: The Strengthening Capacity in Environmental Physics, Hydrogeology and Statistics for conservation agriculture research (CEPHaS) consortium sought to to strengthen research capacity among a network of African and UK researchers, and their respective institutions, to fill knowledge gaps on the impacts of conservation agriculture practices on the water cycle in cultivated soils. We examined experiences of consortium membership and, drawing on this information, determined key recommendations for future programmes with similar objectives. Methods: A mixed methods study encompassing an online survey (N=40) and semi-structured interviews (N=19) completed between June 2021 and February 2022 with CEPHaS consortium members from Malawi, UK, Zambia and Zimbabwe. Survey and interview data were analysed separately, using univariate statistics and framework synthesis respectively Results: Survey and interview findings were generally aligned, with both revealing a wide range of reported capacity strengthening gains resulting from CEPHaS engagement at both an individual and institutional level. Participants consistently expressed their CEPHaS involvement in positive terms with praise for the applied ‘learn by doing’ approach underpinning many of the activities as well as the engaging and highly inclusive leadership. There was evidence that the various trainings and resources provided through CEPHaS were valued, frequently utilised, and often transferred beyond the immediate CEPHaS membership for wider benefit. Resource provision and staff training were seen as foundational for long-term institutional benefits. Some challenges and suggested areas for improvement were reported by participants as were potential opportunities to facilitate greater impact. Conclusion: Our findings suggest that the basic ‘template’ of the CEPHaS consortium provided a strong basis for research capacity strengthening in Conservation Agriculture, especially at the level of individual researchers, and that this template could be further enhanced in any future iteration of the same or similar programme. Recommendations for replicating and enhancing CEPHaS programme strengths are presented.

A proper understanding of the residual value of zinc (Zn) is necessary for sustainable biofortification of food crops. This study aimed to establish the extent to which application of Zn at the national rate, plus two experimentally elevated rates, in one year provided any benefit to plant yield and nutritional quality in the following growing season. Residual effects of soil-applied Zn on grain Zn concentration and uptake were estimated by an experiment in which maize was grown in successive seasons at two agricultural research stations in Malawi, with Zn applied to the soil in the first season but not the second. At each site two common soil types were used: Lixisols and Vertisols. The study used three Zn fertilizer rates of 1, 30 and 90 kg Zn ha -1 applied to the soil in the previous cropping season, arranged in a randomized complete block design (RCBD) with 10 replications at each experimental site. At harvest, maize grain yield and Zn concentration in grain and stover were measured; Zn uptake by maize grain and stover were determined and Zn harvest index was calculated. Effects on grain yield and Zn uptake by the crop were assessed in relation to residual Zn fertilizer and soil type. Maize grain yield on plots in the second season where 30 kg Zn ha -1 had been applied exceeded that on second season plots where 1 kg Zn ha -1 had been applied by 25%. The grain Zn concentration and Zn uptake in the second season after fertilizer application were larger by 13% and 30% respectively on the plots which had received 30 kg Zn ha -1 than those which had received 1 kg Zn ha -1 . There was no evidence that applying Zn at 90 kg Zn ha -1 resulted in larger crop yield, grain Zn concentration, or Zn uptake the second year after application than was seen in plots the second year after application of 30 kg Zn ha -1 . The magnitude of the benefits attributed to residual effects of soil-applied Zn did not depend on soil type. Conclusively, the residual effects of 30 kg ha -1 of soil-applied Zn in the preceding season benefited the subsequent maize compared to the national recommendation of 1 kg Zn ha -1 . The benefits of larger applications of Zn than the current national recommendations should be considered across at least two seasons and for different crops.

Abstract. The communication of uncertainty is not only a challenge when soil information has been produced but also in the planning stage. When planning a survey of soil properties it is necessary to make decisions about the sampling density. Sampling density determines both the quality of predictions and the cost of fieldwork. In this study, we considered four ways in which the relationship between sample density and the uncertainty of predictions can be related, based on prior information about the variability of the target quantity. These were offset correlation, prediction intervals, conditional probabilities of the interpretation errors and implicit loss functions. Offset correlation is a measure of the consistency of kriging predictions made from sample grids with the same spacing but different origins. Prediction intervals and conditional probabilities are based on the prediction distribution of the variable of interest. All four of these methods were investigated using the information on soil pH and Se concentration in grain in Malawi. They were presented to a group of stakeholders, who were asked to use them in turn to select a sampling density. Their responses were evaluated and they were then asked to rank the methods based on their effectiveness, in their experience, and in terms of finding a level of uncertainty that they were able to tolerate when deciding about a sampling grid spacing. Our results show that the approach that stakeholders favoured was offset correlation, and some approaches were not well understood (conditional probability and implicit loss function). During feedback sessions, the stakeholders highlighted that they were more familiar with the concept of correlation, with a closed interval of [0,1] and this explains the more consistent responses under this method. The offset correlation will likely be more useful to stakeholders, with little or no statistical background, who are unable to express their requirements of information quality based on other measures of uncertainty.

Achieving household and national food security is the core focus for policy makers in sub-Saharan Africa (SSA). However, land degradation and dearth of effective soil nutrient management strategies for spatially variable soils is significantly contributing to food insecurity in SSA. The aim of this study was to establish the spatial variability of soil secondary and micronutrients (SMN) under smallholder maize production system in sub-humid condition of Zimbabwe. Geo-referenced samples collected in all maize fields in seven of the eleven villages in ward 10 of Hurungwe district using purposive sampling were analyzed for Ca, Mg, Fe, Mn, Cu and Zn using standard methods. Pearson's correlation analysis was conducted to reveal the relationships among the nutrient status. The linear mixed model (LMM) was used to analyse spatial variation of the data with evidence for spatial dependence in the random component of the model assessed by calculating Akaike's information criterion (AIC). The results indicate that only Ca was significantly (p < 0.05) influenced by field type with larger concentrations in home fields compared to outfields. Soil texture had a significant (p < 0.05) effect on Ca, Mg and Zn with the largest values for Ca and Mg found in the sandy clay loams (with the largest clay content) compared to sand, loamy sand and sandy loam. Loamy sand had the largest Zn concentration with sandy clay loams having the least. There was evidence for spatial dependence in Ca and Mg with field type, latitude and longitude as fixed effects; hence these nutrients were mapped in the GIS environment. It can be concluded that SMN tend to be deficient in some areas and vary spatially as influenced by soil intrinsic conditions and management, even at ward level.

The present study aimed to investigate the influence of genotypic differences on responses to zinc and iron agronomic biofortification among yields of finger millet. A field experiment was conducted over two seasons in farmers’ fields in Ethiopia (2019, 2020). The experimental design had 15 treatment combinations comprising three finger millet genotypes and the applications of different combinations of zinc and iron mineral fertilizers. Five soil-applied fertilizer treatments (20 kg h−1 FeSO4 + 25 kg h−1 ZnSO4 + NPKS, 25 kg ha−1 ZnSO4 + NPKS, 20 kg ha−1 FeSO4 + NPKS, NPKS, and 30% NPKS) at two locations (Gojjam and Arsi Negelle, Ethiopia) and using two slope positions (foot and hill) were replicated four times in a randomized complete block design. Grain yield and biomass were evaluated on a plot basis. Plant height, total and productive tiller number, finger length of the longest spike and number of fingers per main ear were measured at the maturity stage. The combined soil application of FeSO47H2O and ZnSO47H2O increased the yield of the Meba genotype by 51.6%. Additionally, ZnSO47H2O fertilizer application increased the yield of the Urji genotype by 27.6%. A yield enhancement of about 18.3% of the Diga-01 genotype was achieved due to the FeSO47H2O fertilizers’ application. The findings of the present study suggest that the influence of Zn and Fe agronomic biofortification on the yield of finger millet could be affected by genotype differences and environmental conditions.