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Micronutrient deficiencies (MNDs) remain widespread among people in sub-Saharan Africa 1 – 5 , where access to sufficient food from plant and animal sources that is rich in micronutrients (vitamins and minerals) is limited due to socioeconomic and geographical reasons 4 – 6 . Here we report the micronutrient composition (calcium, iron, selenium and zinc) of staple cereal grains for most of the cereal production areas in Ethiopia and Malawi. We show that there is geospatial variation in the composition of micronutrients that is nutritionally important at subnational scales. Soil and environmental covariates of grain micronutrient concentrations included soil pH, soil organic matter, temperature, rainfall and topography, which were specific to micronutrient and crop type. For rural households consuming locally sourced food—including many smallholder farming communities—the location of residence can be the largest influencing factor in determining the dietary intake of micronutrients from cereals. Positive relationships between the concentration of selenium in grain and biomarkers of selenium dietary status occur in both countries. Surveillance of MNDs on the basis of biomarkers of status and dietary intakes from national- and regional-scale food-composition data 1 – 7 could be improved using subnational data on the composition of grain micronutrients. Beyond dietary diversification, interventions to alleviate MNDs, such as food fortification 8 , 9 and biofortification to increase the micronutrient concentrations in crops 10 , 11 , should account for geographical effects that can be larger in magnitude than intervention outcomes. Geospatial variation in the micronutrient composition (calcium, iron, selenium and zinc) of staple cereal grains is nutritionally important at subnational scales in Ethiopia and Malawi; these data could be used to improve surveillance of micronutrient deficiencies in the region.

Dietary zinc (Zn) deficiency is widespread globally, and in particular among people in sub-Saharan Africa (SSA). In Malawi, dietary sources of Zn are dominated by maize and spatially dependent variation in grain Zn concentration, which will affect dietary Zn intake, has been reported at distances of up to ~ 100 km. The aim of this study was to identify potential soil properties and environmental covariates which might explain this longer-range spatial variation in maize grain Zn concentration. Data for maize grain Zn concentrations, soil properties, and environmental covariates were obtained from a spatially representative survey in Malawi (n = 1600 locations). Labile and non-labile soil Zn forms were determined using isotopic dilution methods, alongside conventional agronomic soil analyses. Soil properties and environmental covariates as potential predictors of the concentration of Zn in maize grain were tested using a priori expert rankings and false discovery rate (FDR) controls within the linear mixed model (LMM) framework that informed the original survey design. Mean and median grain Zn concentrations were 21.8 and 21.5 mg kg −1 , respectively (standard deviation 4.5; range 10.0–48.1). A LMM for grain Zn concentration was constructed for which the independent variables: soil pH (water) , isotopically exchangeable Zn (Zn E ), and diethylenetriaminepentaacetic acid (DTPA) extractable Zn (Zn DTPA ) had predictive value ( p  < 0.01 in all cases, with FDR controlled at < 0.05). Downscaled mean annual temperature also explained a proportion of the spatial variation in grain Zn concentration. Evidence for spatially dependent variation in maize grain Zn concentrations in Malawi is robust within the LMM framework used in this study, at distances of up to ~ 100 km. Spatial predictions from this LMM provide a basis for further investigation of variations in the contribution of staple foods to Zn nutrition, and where interventions to increase dietary Zn intake (e.g. biofortification) might be most effective. Other soil and landscape factors influencing spatially dependent variation in maize grain Zn concentration, along with factors operating over shorter distances such as choice of crop variety and agronomic practices, require further exploration beyond the scope of the design of this survey.

Modern sensor technologies can provide detailed information about soil variation which allows for more precise application of fertiliser to minimise environmental harm imposed by agriculture. However, growers should lose neither income nor yield from associated uncertainties of predicted nutrient concentrations and thus one must acknowledge and account for uncertainties. A framework is presented that accounts for the uncertainty and determines the cost–benefit of data on available phosphorus (P) and potassium (K) in the soil determined from sensors. For four fields, the uncertainty associated with variation in soil P and K predicted from sensors was determined. Using published fertiliser dose–yield response curves for a horticultural crop the effect of estimation errors from sensor data on expected financial losses was quantified. The expected losses from optimal precise application were compared with the losses expected from uniform fertiliser application (equivalent to little or no knowledge on soil variation). The asymmetry of the loss function meant that underestimation of P and K generally led to greater losses than the losses from overestimation. This study shows that substantial financial gains can be obtained from sensor-based precise application of P and K fertiliser, with savings of up to £121 ha−1 for P and up to £81 ha−1 for K, with concurrent environmental benefits due to a reduction of 4–17 kg ha−1 applied P fertiliser when compared with uniform application.

The dataset comprises primary data for the concentration of 29 mineral micronutrients in cereal grains and up to 84 soil chemistry properties from GeoNutrition project surveys in Ethiopia and Malawi. The work provided insights on geospatial variation in the micronutrient concentration in staple crops, and the potential influencing soil factors. In Ethiopia, sampling was conducted in Amhara, Oromia, and Tigray regions, during the late-2017 and late-2018 harvest seasons. In Malawi, national-scale sampling was conducted during the April–June 2018 harvest season. The concentrations of micronutrients in grain were measured using inductively coupled plasma mass spectrometry (ICP-MS). Soil chemistry properties reported include soil pH; total soil nitrogen; total soil carbon (C); soil organic C; effective cation exchange capacity and exchangeable cations; a three-step sequential extraction scheme for the fractionation of sulfur and selenium; available phosphate; diethylenetriaminepentaacetic acid (DTPA)-extractable trace elements; extractable trace elements using 0.01 M Ca(NO3)2 and 0.01 M CaCl2; and isotopically exchangeable Zn. These data are reported here according to FAIR data principles to enable users to further explore agriculture-nutrition linkages.Measurement(s)Trace Element • soil chemical propertiesTechnology Type(s)Inductively-Coupled Plasma Mass SpectrometryFactor Type(s)Geography • Staple cereal cropSample Characteristic - OrganismStaple cereal food cropsSample Characteristic - EnvironmentSmallholder farmingSample Characteristic - LocationEthiopia • Malawi

Liming has widespread and significant impacts on soil processes and crop responses. The aim of this study was to describe the relationships between exchangeable cation concentrations in soil and the relative yield of spring barley. The hypothesis was that yield is restricted by the concentration of a single exchangeable cation in the soil. For simplicity, we focused on spring barley which was grown in nine years of a long-term experiment at two sites (Rothamsted and Woburn). Four liming rates were applied and in each year the relative yield (RY) and the concentrations of exchangeable cations were assessed. Liming had highly significant effects on the concentrations of most exchangeable cations, except for Cu and K. There were significant negative relationships (either linear or exponential) between the exchangeable concentrations of Mn, Cd, Cr, Al, Fe, Cu, Co, Zn and Ni in soil and soil pH. The relationships between RY and the concentrations of selected exchangeable cations (Mn, Ca and Al) were described well using log-logistic relationships. For these cations a significant site effect was probably due to fundamental differences in soil properties. At both sites the concentrations of exchangeable soil Al were excessive (> 7.5 mg kg −1 ) and were most likely responsible for reduced barley yields (where RY ≤ 0.5) with soil acidification. At Rothamsted barley yield was non-limited (where RY ≥ 1) at soil exchangeable Mn concentrations (up to 417 mg kg −1 ) greater than previously considered toxic, which requires further evaluation of critical Mn concentrations.

Present nutrient management recommendations for irrigated rice in West Africa are typically uniform for large regions. Even with optimal crop management, spatial variability of indigenous nutrient supplies may cause low fertilizer efficiency, low productivity of expensive inputs and high losses to the environment. Substantial efficiency increases were achieved with site- and season-specific nutrient management approaches, but the relative importance of different components (site or season) or of the precision level used (field, scheme, or region) remained unclear. We conducted a field trial in the Senegal River valley to investigate short-range variability of indigenous nutrient supplies of N (INS), P (IPS), and K (IKS) on a three hectare farm, and subsequently used the field data and simulation tools to study the agro-economic effects of fertilizer management options with different precision levels. Spatial variability of soil characteristics and of indigenous nutrient supplies (IS) at field level was high and covered a large part of the variability reported in regional studies. INS ranged from 19 to 78 kg N ha-1, IPS ranged from 11 to 39 kg P ha-1, and IKS ranged from 70 to 150 kg K ha-1. Rice yield ranged from 2.2 to 6.0 Mg ha-1 in N omission plots, from 4.1 to 9.8 Mg ha-1 in P omission plots, and from 5.3 to 9.6 Mg ha-1 in K omission plots. The highest yield in the fully fertilized treatment was 11.6 Mg ha-1. Simulated potential yield was 11.8 Mg ha-1. Field-specific fertilizer management and an economically optimal target yield resulted in an average yield of 9.6 Mg ha-1 compared to 7.5 Mg ha-1 for the existing uniform recommendation. Net benefit from fertilizer use dropped by 19% as a result of reduced precision. Non-season-specific recommendations accounted for 12% of net benefit loss, whereas lower spatial precision contributed 7% to the net benefit loss. We concluded that uniform domain-specific recommendations within agro-ecological zones (i.e. adjusted to the seasonal yield potential) modified by crop diagnostics offer the best opportunities to optimize fertilizer efficiency and net benefits of fertilizer use for intensive irrigated rice-based systems in West Africa.

Rice-based (Oryza sativa L.) rainfed lowlands are the major cropping system in northeast Thailand. Average yields are low, which is generally explained by frequent drought events, low soil fertility, and poor fertilizer response. However, neither the relative importance of these factors nor their interaction is well understood. Therefore, we analyzed an existing database on fertilizer trials conducted between 1995 and 1997 at eight different sites in northeast Thailand with the objective to determine indigenous nutrient supplies, internal efficiencies, and recovery efficiencies of applied nutrients in rainfed lowland rice. Of particular interest was the effect of variety type (traditional) and water supply on these components. Comparison of N, P, and K concentrations in grain and straw (average N-P-K grain concentration of 11.0-2.7-3.4 g kg-¹; average N-P-K straw concentration of 5.2-0.9-16.4 g kg-¹) in the traditional-type varieties used at all trial sites with literature values showed no differences for these parameters between traditional and modern-type varieties or between irrigated and rainfed environments. In contrast, internal efficiencies of N, P, and K (average IEN: 46 kg grain per kg N uptake; IEP: 218 kg grain per kg P uptake; IEK: 25 kg grain per kg K uptake) were much lower than reported for irrigated systems, and the difference was greatest for K, which is mainly accumulated in the straw. Indigenous nutrient supply (average INS: 38 kg ha-¹; IPS: 10 kg ha-¹; IKS: 89 kg ha-¹) and recovery efficiency (average REN: 0.28 kg kg-¹; REP: 0.13 kg kg-¹; REK: 0.49 kg kg-¹) were low but comparable to the lower values reported from irrigated systems. Average seasonal field water resources seemed to reduce the indigenous nutrient supply but had no or little effect on internal efficiency and recovery efficiency. We concluded that the main reason for the low system productivity without and with fertilizer in northeast Thailand is the dominant use of traditional-type varieties with low harvest indices, which was the dominant cause for the observed low internal nutrient efficiency. Therefore, intensification of rainfed systems through substantially increased nutrient inputs can be recommended only where varieties with an average harvest index of close to 0.4 or higher are available.

How well could one predict the growth of a leafy crop from reflectance spectra from the soil and how might a grower manage the crop in the light of those predictions? Topsoil from two fields was sampled and analysed for various nutrients, particle-size distribution and organic carbon concentration. Crop measurements (lettuce diameter) were derived from aerial-imagery. Reflectance spectra were obtained in the laboratory from the soil in the near- and mid-infrared ranges, and these were used to predict crop performance by partial least squares regression (PLSR). Individual soil properties were also predicted from the spectra by PLSR. These estimated soil properties were used to predict lettuce diameter with a linear model (LM) and a linear mixed model (LMM): considering differences between lettuce varieties and the spatial correlation between data points. The PLSR predictions of the soil properties and lettuce diameter were close to observed values. Prediction of lettuce diameter from the estimated soil properties with the LMs gave somewhat poorer results than PLSR that used the soil spectra as predictor variables. Predictions from LMMs were more precise than those from the PLSR using soil spectra. All model predictions improved when the effects of variety were considered. Predictions from the reflectance spectra, via the estimation of soil properties, can enable growers to decide what treatments to apply to grow lettuce and how to vary their treatments within their fields to maximize the net profit from the crop.

Development of improved fertilizer recommendations entirely based on field experiments is time-consuming and costly. We employed a combination of two simulation models and selected field data to develop alternative fertilizer recommendations (AFR) for irrigated rice (Oryza sativa L.) in Bagre, Burkina Faso. Existing fertilizer recommendations are 82 kg N ha(-1) (wet season) or 105 kg N ha(-1) (dry season), 31 kg P ha(-1), and 30 kg K ha(-1). The model RIDEV was used to improve timing of sowing date to avoid cold-induced sterility and timing of N fertilizer applications. The model FERRIZ was used to determine AFR, based on estimations of indigenous nutrient supply for N, P, and K; yield potential (Y(pot)); internal N, P, and K efficiency of rice; fertilizer N, P, and K recovery fractions; and fertilizer and rice prices. Simulations suggested decreasing P and K doses to 21 kg P ha(-1) and 20 kg K ha(-1) but increasing the N dose to 116 kg N ha(-1) in the wet season (Y(pot) = 8 t ha(-1)) and to 139 kg N ha(-1) in the dry season (Y(pot) = 9 t ha(-1)). Alternative fertilizer recommendations keep the P balance neutral, but a negative K balance was tolerated based on the high soil K supply. Compared with existing recommendations, yield gains of up to 0.5 t ha(-1) were simulated at equal costs. These yield gains were more than confirmed in farmers' fields during four consecutive growing seasons. Alternative fertilizer recommendations increased gross returns above fertilizer costs by an average of about US$ 160 per season compared with both farmers' practice and existing recommendations.

Yield, yield gaps, input use, N-use efficiency, productivity, and profitability of irrigated rice in Burkina Faso were determined for a typical irrigation scheme in the dry season (DS) 1999 and the wet season (WS) 2000. Objectives were to analyze agro-economic constraints and opportunities and determine ways to overcome such constraints. The simulation model RIDEV was used to analyze farmers' crop management practices, revealing considerable deviation between actual and optimal timing of crop management interventions. This diversity of cropping practices caused considerable variation of internal efficiency of N (IEN), partial factor productivity of N (PFPN), N recovery fraction (RFN), rice (Oryza sativa L.) grain yields, and net benefits of N-use. The results showed a clear relation between plant N uptake and yield (mean IEN of 48 kg grain kg(-1) N uptake in farmer's fields), but the relation between N applied and yield was scattered. The PFPN varied from 16 to 52 kg grain kg(-1) N applied (mean of 35 kg grain kg(-1) N applied) due to a large range of fertilizer N recovery rates (RFN = 7-77%; mean of 37%). Farmers' average yields were 4.9 Mg ha(-1) in the DS and 3.6 Mg ha(-1) in the WS, but yields were very variable and ranged from 0.9 to 7.9 Mg ha(-1) in the DS and from 1.0 to 7.9 Mg ha(-1) in the WS. Yield gaps between average farmer's yield and best farmer's yield were high (3.0 Mg ha(-1) in the DS and 4.3 Mg ha(-1) in the WS), indicating considerable scope for yield increases in both seasons. Net benefits to irrigated rice cropping were mostly positive (avg. $418 (US) ha(-1)) in the dry season, but very low in the wet season (avg. $108 (US) ha(-1)). Partial budget analysis of fertilizer use revealed considerably lower value/cost ratios of fertilizer use in the wet season (mean V/C: 1.5) compared with the dry season (mean V/C: 2.9). It was concluded that improved crop management practices are the key to reach higher yields and financial returns without additional investments.