Science-based decision support for formulating crop fertilizer recommendations in sub-Saharan Africa

Open Access Article; Published online: 31 Jan 2020In sub-Saharan Africa, there is considerable spatial and temporal variability in relations between nutrient application and crop yield, due to varying inherent soil nutrients supply, soil moisture, crop management and germplasm. This variability affects fertilizer use efficiency and crop productivity. Therefore, development of decision systems that support formulation and delivery of site-specific fertilizer recommendations is important for increased crop yield and environmental protection. Nutrient Expert (NE) is a computer-based decision support system, which enables extension advisers to generate field- or area-specific fertilizer recommendations based on yield response to fertilizer and nutrient use efficiency. We calibrated NE for major maize agroecological zones in Nigeria, Ethiopia and Tanzania, with data generated from 735 on-farm nutrient omission trials conducted between 2015 and 2017. Between 2016 and 2018, 368 NE performance trials were conducted across the three countries in which recommendations generated with NE were evaluated relative to soil-test based recommendations, the current blanket fertilizer recommendations and a control with no fertilizer applied. Although maize yield response to fertilizer differed with geographic location; on average, maize yield response to nitrogen (N), phosphorus (P) and potassium (K) were respectively 2.4, 1.6 and 0.2 t ha−1 in Nigeria, 2.3, 0.9 and 0.2 t ha−1 in Ethiopia, and 1.5, 0.8 and 0.2 t ha−1 in Tanzania. Secondary and micronutrients increased maize yield only in specific areas in each country. Agronomic use efficiencies of N were 18, 22 and 13 kg grain kg−1 N, on average, in Nigeria, Ethiopia and Tanzania, respectively. In Nigeria, NE recommended lower amounts of P by 9 and 11 kg ha−1 and K by 24 and 38 kg ha−1 than soil-test based and regional fertilizer recommendations, respectively. Yet maize yield (4 t ha−1) was similar among the three methods. Agronomic use efficiencies of P and K (300 and 250 kg kg−1, respectively) were higher with NE than with the blanket recommendation (150 and 70 kg kg−1). In Ethiopia, NE and soil-test based respectively recommended lower amounts of P by 8 and 19 kg ha−1 than the blanket recommendations, but maize yield (6 t ha−1) was similar among the three methods. Overall, fertilizer recommendations generated with NE maintained high maize yield, but at a lower fertilizer input cost than conventional methods. NE was effective as a simple and cost-effective decision support tool for fine-tuning fertilizer recommendations to farm-specific conditions and offers an alternative to soil testing, which is hardly available to most smallholder farmers

Variability of soybean response to rhizobia inoculant, vermicompost, and a legume-specific fertilizer blend in Siaya County of Kenya

Open Access JournalRhizobia inoculation can increase soybean yield, but its performance is influenced by among others soybean genotype, rhizobia strains, environment, and crop management. The objective of the study was to assess soybean response to rhizobia inoculation when grown in soils amended with urea or vermicompost to improve nitrogen levels. Two greenhouse experiments and one field trial at two sites were carried out. The first greenhouse experiment included soils from sixty locations, sampled from smallholder farms in Western Kenya. The second greenhouse experiment consisted of one soil selected among soils used in the first experiment where inoculation response was poor. The soil was amended with vermicompost or urea. In the two greenhouse experiments, Legumefix (inoculant) + Sympal (legume fertilizer blend) were used as a standard package. Results from the second greenhouse experiment were then validated in the field. Analysis of variance was done using SAS statistical software and mean separation was done using standard error of the difference for shoot biomass, grain yield nodulation, nodule effectiveness and nutrient uptake. In the first greenhouse trial, soybean response to inoculation was significantly affected by soil fertility based on nodule fresh weight and shoot biomass. Soils with low nitrogen had low to no response to inoculation. After amendment, nodule fresh weight, nodule effectiveness, nodule occupancy, and shoot dry biomass were greater in the treatment amended with vermicompost than those amended with urea (Legumefix + Sympal + vermicompost and Legumefix + Sympal + urea) respectively. Under field conditions, trends were similar to the second experiment for nodulation, nodule occupancy and nitrogen uptake resulting in significantly greater grain yields (475, 709, 856, 880, 966 kg ha −1) after application of vermicompost at 0, 37, 74, 111, and 148 kg N ha −1 respectively. It was concluded that soybean nodulation and biological nitrogen fixation in low fertility soils would not be suppressed by organic amendments like vermicompost up to 148 kg N ha −1

Dilemma of nitrogen management for future food security in sub-Saharan Africa – a review

Article purchased; Published online: 13 July 2017Food security entails having sufficient, safe, and nutritious food to meet dietary needs. The need to optimise nitrogen (N) use for nutrition security while minimising environmental risks in sub-Saharan Africa (SSA) is overdue. Challenges related to managing N use in SSA can be associated with both insufficient use and excessive loss, and thus the continent must address the ‘too little’ and ‘too much’ paradox. Too little N is used in food production (80% of countries have N deficiencies), which has led to chronic food insecurity and malnutrition. Conversely, too much N load in water bodies due mainly to soil erosion, leaching, limited N recovery from wastewater, and atmospheric deposition contributes to eutrophication (152 Gg N year–1 in Lake Victoria, East Africa). Limited research has been conducted to improve N use for food production and adoption remains low, mainly because farming is generally practiced by resource-poor smallholder farmers. In addition, little has been done to effectively address the ‘too much’ issues, as a consequence of limited research capacity. This research gap must be addressed, and supportive policies operationalised, to maximise N benefits, while also minimising pollution. Innovation platforms involving key stakeholders are required to address N use efficiency along the food supply chain in SSA, as well as other world regions with similar challenges

The contribution of nitrogen by promiscuous soybeans to maize based cropping the moist savanna of Nigeria

Agronomic results indicate that maize grain yields generally are higher when the crop is planted following soybean than in continuous maize cultivation in the moist savanna agroecological zones of West Africa. Many factors have been hypothesized to explain this phenomenon, including enhanced N availability and the so-called `rotational effect'. There is, however, hardly any quantitative information on the residual N benefits of promiscuous soybeans to subsequent cereal crops grown in rotation with soybean. Three IITA promiscuous soybean breeding lines and two Brazilian soybean lines were grown in 1994 and 1995 at Mokwa in the southern Guinea savanna, Nigeria, to quantify the nitrogen contribution by soybeans to a succeeding crop of maize grown in rotation with soybean for two consecutive years, 1996 and 1997 using two methods of introducing 15N into soil (fresh 15N labelling and its residual 15N) and three maize cultivars (including one cultivar with high N use efficiency) used as reference plants. The nodulating soybeans fixed between 44 and 103 kg N ha−1 of their total N and had an estimated net N balance input from fixation following grain harvest ranging from −8 to 43 kg N ha−1. Results in 1996 and in 1997 showed that maize growing after soybean had significantly higher grain yield (1.2 – 2.3-fold increase compared to maize control) except for maize cultivar Oba super 2 (8644-27) (a N-efficient hybrid). The 15N isotope dilution method was able to estimate N contribution by promiscuous soybeans to maize only in the first succeeding maize crop grown in 1996 but not in the second maize crop in 1997. The first crop of maize grown after soybean accumulated an average between 10 and 22 kg N ha−1 from soybean residue, representing 17–33% of the soybean total N ha−1. The percentage 15N derived from residue recovery in maize grown after maize was influenced by the maize cultivars. Maize crop grown after the N-efficient hybrid cultivar Oba Super 2 (844-27) had similar 15N values similar to maize grown after soybeans, confirming the ability of this cultivar to use N efficiently in low N soil due to an efficient N translocation ability. The maize crop in 1997 grown after maize had lower 15N enrichment than that grown in soybean plots, suggesting that soybean residues contributed a little to soil available N and to crop N uptake by the second maize crop. The differential mineralization and immobilization turnover of maize and soybean residues in these soils may be important and N contribution estimates in longer term rotation involving legumes and cereals may be difficult to quantify using the 15N labelling approaches. Therefore alternative methods are required to measure N release from organic residues in these cropping systems

Can a combination of UAV-derived vegetation indices with biophysical variables improve yield variability assessment in smallholder farms?

Open Access Journal; Published online: 09 Dec 2020The rapid assessment of maize yields in a smallholder farming system is important for understanding its spatial and temporal variability and for timely agronomic decision-support. We assessed the predictability of maize grain yield using unmanned aerial/air vehicle (UAV)-derived vegetation indices (VI) with (out) biophysical variables on smallholder farms. High-resolution imageries were acquired with UAV-borne multispectral sensor at four and eight weeks after sowing (WAS) on 31 farmer managed fields (FMFs) and 12 nearby nutrient omission trials (NOTs) sown with two genotypes (hybrid and open-pollinated maize) across five locations within the core maize region of Nigeria. Acquired multispectral imageries were post-processed into three VIs, normalized difference VI (NDVI), normalized difference red-edge (NDRE), and green-normalized difference VI (GNDVI) while plant height (Ht) and percent canopy cover (CC) were measured within georeferenced plot locations. Result shows that the nutrient status had a significant effect on the grain yield (and variability) in NOTs, with a maximum grain yield of 9.3 t/ha, compared to 5.4 t/ha in FMFs. Generally, there was no relationship between UAV-derived VIs and grain yield at 4WAS (r 0.1), but significant correlations were observed at 8WAS (r ≤ 0.3; p < 0.001). Ht was positively correlated with grain yield at 4WAS (r = 0.5, R2 = 0.25, p < 0.001) and more strongly at 8WAS (r = 0.7, R2 = 0.55, p < 0.001), while the relationship between CC and yield was only significant at 8WAS. By accounting for within- and between-field variations in NOTs and FMFs (separately), predictability of grain yield from UAV-derived VIs was generally low (R2 ≤ 0.24); however, the inclusion of ground-measured biophysical variable (mainly Ht) improved the explained yield variability (R2 ≥ 0.62, Root Mean Square Error of Prediction, RMSEP ≤ 0.35) in NOTs but not in FMFs. We conclude that yield prediction with UAV-acquired imageries (before harvest) is more reliable under controlled experimental conditions (NOTs), compared to actual farmer managed fields where various confounding agronomic factors can amplify noise-signal ratio