Soil Fertility Variability in Relation to the Yields of Maize and Soybean Under Intensifying Cropping Systems in the Tropical Savannas of Northeastern Nigeria

Kwari, J. D.; Kamara, A. Y.; Ekeleme, Friday; Omoigui, L O

doi:10.1007/978-90-481-2543-2_47

Cited by 7 publications

(5 citation statements)

References 10 publications

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“…In addition, sorting of soil materials as a result of clay eluviation and wind erosion has been reported as one of the major reason for a high sand fraction in the surface soils of northern Nigeria [54,55]. The low total C-contents (indicative of low organic matter content), total N and ECEC in the soils can be related to two factors; (i) inherently, the sandy nature of the parent material containing a low weatherable mineral reserve necessary for nutrient recharge and a small capacity for carbon storage, (ii) anthropogenically, through burning or complete removal of crop residues for livestock and other needs [56]. Many studies have reported low total C, total N and ECEC contents within the study area [9,13,14,57].…”

Section: Soil Characteristicsmentioning

confidence: 99%

Quantifying Variability in Maize Yield Response to Nutrient Applications in the Northern Nigerian Savanna

et al. 2018

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Diagnostic on-farm nutrient omission trials were conducted over two cropping seasons (2015 and 2016) to assess soil nutrients related constraints to maize yield in the northern Nigerian savanna agro-ecological zone and to quantify their variability. Two sets of trials were conducted side by side, one with an open pollinated maize variety (OPV) and the other one with a hybrid maize variety and each set had six equal treatments laid out in 198 farmers' fields. The treatments comprised (i) a control, (ii) a PK ('−N,' without N), (iii) an NK ('−P,' without P), (iv) an NP ('−K,' without K), (v) an NPK and (vi) an NPK + S + Ca + Mg + Zn + B ('+SMM,' NPK plus secondary macro-and micro-nutrients). Moderate to a large variability in most soil characteristics was observed in the studied fields. Consequently, cluster analysis revealed three distinct yield-nutrient response classes common for the two types of maize varieties. These define classes were fields that have (i) no-response to any nutrient, (ii) a large response to N and P and (iii) a large response to N alone. Although overall yield performance of OPV and hybrid varieties was similar, a distinct fourth class was identified for the hybrid variety, (iv) fields with a large response to N and secondary macro-and micro-nutrients. The results indicate that the large variability in soil nutrients related constraints need to be accounted for to optimize maize yield in the northern Nigerian savanna. The development of field-and area-specific fertilizer recommendations is highly needed, using simple decision support tools that consider variable soil fertility conditions and yield responses as obtained from this study.

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Section: Soil Characteristicsmentioning

confidence: 99%

Quantifying Variability in Maize Yield Response to Nutrient Applications in the Northern Nigerian Savanna

et al. 2018

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“…5 ). Low use of organic manure among farmers has been reported by Aliyu et al 16 in the same area, it was also reported to diminish attainable maize yield 27 , 28 . Cow dung manure was the most predominantly used (in 31% of cases) organic manure among the farmers (Fig.…”

Section: Resultsmentioning

confidence: 68%

Digital technology in maize nutrient management research in northern Nigeria amid COVID-19 pandemic

Aliyu,

Shehu,

Adam

2024

Sci Rep

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The COVID-19 pandemic has been a life threatening and spreads wildly with physical human contact. Physical distancing is recommended by health experts to prevent the spread; thus, agronomic research has to be designed in conformity to this preventive standard during the pandemic. Consequently, this study was designed to evaluate the reliability of using digital tools in nutrient management research amid the COVID-19 pandemic in northern Nigeria. Fifty extension agents (EAs) were selected across 15 LGAs of Kaduna and Kano states. The EAs were trained on how to generate fertilizer recommendation using an android mobile phone-based nutrient expert (NE), to measure farmers’ field sizes using UTM Area measure mobile phone app, and open data kit to record, submit and aggregate data during the exercise. Each EA covered 50 farms, where two nutrient management practices—one determined by the farmers: farmer fertilizer practice (FFP), and the other generated using the NE were evaluated. Results show that around 90% of the farmers have an average field size of 1.13 ha. All selected farmers used improved maize varieties for planting, among which 21% been able to use the exact recommended or lower seed rate. Use of inorganic fertilizer was 33% higher than the average recommended NE rate, while average yield of the NE fields was 48% higher than for the FFP. The results of this study indicate that yield can be improved with site-specific nutrient management (SSNM) extension approach. The SSNM using digital tools as the NE seem promising and befits to agronomic research in northern Nigeria amid the COVID-19 pandemic.

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“…The concentration of available Cu (1.07 mg kg −1 ) was low and there was relatively high concentration of Mn (46 mg kg −1 ) and Fe (178 mg kg −1 ) due to the slightly acidic pH (5.6) of the soil (Table 1). Available soil P in the field (8.6 mg kg −1 ) was as low, as is common in sandy savanna soils with low organic matter content (Kwari et al, 2011).…”

Section: Experimental Site and Soil Descriptionmentioning

confidence: 81%

Integrated management of Striga gesnerioides in cowpea using resistant varieties, improved crop nutrition and rhizobium inoculants

et al. 2022

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Background Cowpea is a grain legume of major importance in sub-Saharan Africa where it is cultivated by smallholder farmers on poor soils and production is often constrained by the parasitic weed Striga gesnerioides. Method Experiments were conducted to assess the potential of rhizobium inoculation to mitigate Striga infection and increase cowpea productivity. We infested soils with S. gesnerioides and assessed the impact of treatments combining cowpea genotypes and bradyrhizobium inoculation on Striga dynamics and cowpea yield. In total, 20 cowpea genotypes were included, of which nine were resistant to Striga and 11 were susceptible. In the first experiment these were factorially combined with three inoculation options (two bradyrhizobium strains USDA3384 and IRJ2180A, and uninoculated control) in a screen-house using potted sterile soils. Second, the same trial was repeated in the field with basal phosphorus applied at sowing and a fourth treatment of fertilizer-N (urea) included testing whether N was limiting cowpea growth. The field trial also included a separate treatment with no input that served as a negative check. Result Significant genotype x treatment interactions were observed in nodule counts, Striga attachment, emergence, and cowpea shoot growth in the screen-house. There were few nodules across all cowpea lines. Striga counts were the lowest for resistant varieties with no emerged plants. Rhizobial inoculants depressed Striga counts with consistent differences across cowpea genotypes. Inoculation with IRJ2180A performed the best against Striga attachment in resistant genotypes, and against Striga emergence in susceptible genotypes. In the field trial, cowpea grown without inputs had the least number of nodules. The genotype x treatment interaction was significant: resistant cowpea genotypes were free of emerged Striga while there was much more Striga emergence without input addition with susceptible genotypes. A significant genotype x treatment interaction was observed on cowpea grain yield. Yield response to inoculation was clearest with resistant genotypes inoculated with the strain IRJ2180A. Conclusion The integrated use of Striga-resistant cowpea lines, basal phosphorus fertilizer and elite bradyrhizobium inoculants is a promising approach to mitigate Striga infection and increase cowpea productivity.

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Soil Fertility Variability in Relation to the Yields of Maize and Soybean Under Intensifying Cropping Systems in the Tropical Savannas of Northeastern Nigeria

Cited by 7 publications

References 10 publications

Quantifying Variability in Maize Yield Response to Nutrient Applications in the Northern Nigerian Savanna

Quantifying Variability in Maize Yield Response to Nutrient Applications in the Northern Nigerian Savanna

Digital technology in maize nutrient management research in northern Nigeria amid COVID-19 pandemic

Integrated management of Striga gesnerioides in cowpea using resistant varieties, improved crop nutrition and rhizobium inoculants

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