James Jayeoba

NASARAWA STATE UNIVERSITY, KEFFI, NASARAWA STATE-NIGERIA, Agronomy, Faculty Member

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Professor Olumuyiwa James JAYEOBA is a Professor of Environmental Resource Modelling with over twenty –five years’ experience in Geo-Informatics, Digital soil Information, Geo-statistics, Remote sensing and Mapping

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Stockholm University

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Papers by James Jayeoba

Climate Change at a Global Concept: Impacts and Adaptation Measures

International Journal of Environment and Climate Change, Jun 21, 2024

Climate change is a global concern and has affected all nations. Daily observations, scientific a... more Climate change is a global concern and has affected all nations. Daily observations, scientific analyses, projections and recommendations on climate change and its global impacts, are needed at all levels of human and environmental development. This is important because of the conviction that approximately 3.3 to 3.6 billion people are highly vulnerable to climate change. Climate change has reduced food security, affected water quality and soil security, increased sea and land temperature, caused human mortality, caused soil damage through various kinds of erosion, increased flooding, and hindered efforts to achieve sustainable development goals. Climate change affects the global health, the global population and the global economy. This paper provides a general overview of the ideas and knowledge on concept of global climate change and maintains that climate change adaptation is required because of the increasing catastrophic events, which have reduced the quality of human life in all aspects (environment, health, economy, biodiversity). It has been suggested that global climate change research and development can help support advanced adaptation/mitigation measures.

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Spatial variability of soil organic carbon in a catchment of the Loess Plateau

Acta Agriculturae Scandinavica, Section B - Plant Soil Science, 2010

The issue of soil organic carbon (SOC) is of increasing concern. Because SOC, as an important soi... more The issue of soil organic carbon (SOC) is of increasing concern. Because SOC, as an important soil component in farming systems, is essential for improving soil quality, sustaining food production and quality, and maintaining water quality and as a major part of the terrestrial carbon reservoir, it plays an important role in the global carbon cycle. In this paper, a

Spatial Variability of Soil Organic Carbon in a Cassava field at Ekha Agro Farms, Lanlate, Oyo State, Nigeria

by Tunrayo Alabi and James Jayeoba

Soil Organic Carbon (SOC) is one of the most important parameters affecting the chemical, physica... more Soil Organic Carbon (SOC) is one of the most important parameters affecting the chemical, physical and hydraulic characteristics of natural soils. Knowledge of spatial variability in soil fertility is important for site specific nutrient management. The study was conducted on a 467 hectare commercial cassava farm located at Lanlate (7º 36'N and 3º 27'E), Oyo State, southwestern Nigeria. Soil samples were collected from eighty–eight (88) sites on a grid system at 0-30 cm and 30-60 cm depths. Coordinates (latitude and longitude) of the locations of the sampling sites were obtained with the aid of a hand held Global Positioning System (GPS) (Garmin eTrex Ventura®) receiver,. The Walkley and Black (1934) wet digestion method was used to determine soil organic carbon content. Spatial analysis of the classified SOC was done in a GIS environment. A GIS software package ArcGIS 10.2 and ArcGIS Geo-statistical Analyst Extension were used. Various interpolation techniques, ordinary kriging, Simple Normal Score, Universal kriging, Empirical Bayesian Kriging and Ordinary co-kriging were used to produce the spatial distribution of the SOC. Ordinary co-Kriging with Nitrogen as a covariate gave the best model predictions for both surface and sub-surface depth. The best fit semivariogram models for SOC were “K-Bessel” and “J-Bessel” for surface and subsurface depths respectively. The nugget-to-sill ratio(Co/Co + C) for soil organic carbon at the surface depth was 0.103 and 0.062 for sub surface soil, these indicated a strong spatial dependence for both top soil and subsoil. The spatial distribution of soil organic carbon at Ekha farm is dominated by the constitutive factors and the random factors together. Based on the spatial interpolation, two management zones were delineated for SOC at the surface and subsurface depths.

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Full Length Research Paper Growth, Nutrient Uptake and Dry Matter Yield of Maize (Zea Mays L) Grown in Soil Amended with Rice Husk and Sawdust Biochar

Abstract. The science of modern biochar for soil management and climate change mitigation is a re... more Abstract. The science of modern biochar for soil management and climate change mitigation is a relatively recent development and has gained increasing attention over the past few years. Experiments to assess the potential of rice husk and sawdust biochar were conducted in 2014 to improve the growth, nutrient uptake and dry matter yield of maize. The treatments were 0, 60, 120 g of rice husk and sawdust biochar. Results showed that rice husk and sawdust biochar had a significant effect on growth, leave area and biomass. In both trials, rice husk and sawdust biochar applied at 120 g/pot was significantly (P = 0.05) better in promoting growth (44.61 -24.17 cm) and (45.02 -24.76 cm); leave area (262.78 -138.42 cm) and (269.24 -140.34 cm) and biomass (97.70 -30.10 g) and (91.52 -36.31 g). Nitrogen, Phosphorus and Potassium uptake were also significantly influenced by rice husk and sawdust biochar application at both trials. 120 g/pot of rice husk and sawdust biochar produced the highest ...

Major characteristics and classification of soils in duduguru, obi lga of Nasarawa State, Nigeria

Agricultural Research Journal

Growth, Nutrient Uptake and Dry Matter Yield of Maize (Zea Mays L) Grown in Soil Amended with Rice Husk and Sawdust Biochar

International Journal of Scientific Research in Agricultural Sciences, 2016

The science of modern biochar for soil management and climate change mitigation is a relatively r... more The science of modern biochar for soil management and climate change mitigation is a relatively recent development and has gained increasing attention over the past few years. Experiments to assess the potential of rice husk and sawdust biochar were conducted in 2014 to improve the growth, nutrient uptake and dry matter yield of maize. The treatments were 0, 60, 120 g of rice husk and sawdust biochar. Results showed that rice husk and sawdust biochar had a significant effect on growth, leave area and biomass. In both trials, rice husk and sawdust biochar applied at 120 g/pot was significantly (P = 0.05) better in promoting growth (44.61-24.17 cm) and (45.02-24.76 cm); leave area (262.78 – 138.42 cm) and (269.24 – 140.34 cm) and biomass (97.70-30.10 g) and (91.52-36.31 g). Nitrogen, Phosphorus and Potassium uptake were also significantly influenced by rice husk and sawdust biochar application at both trials. 120 g/pot of rice husk and sawdust biochar produced the highest value of N uptake (5.25 – 0.52 %) and (5.25-0.52%); P (50.39 – 47.45 mg/kg) and (48.85 – 48.53 mg/kg) and K (5.25 – 0.54 cmol/kg) and (4.56 – 0.51 cmol/kg) in both trials. Rice husk and sawdust biochar applied at 120 g/pot was significantly higher in promoting dry matter accumulation in maize in both trials. Therefore, application of biochar as soil amendment had positive impact on plant growth with a value addition of acting as carbon sink in the soil, thereby mitigating climate change.

Geo-statistical Analyses of the Spatial Variation of Soil Reaction (pH) in Nasarawa State, North Central Nigeria

by Tunrayo Alabi and James Jayeoba

Geo-statistics provides a set of statistical tools for incorporating the spatial coordinates of s... more Geo-statistics provides a set of statistical tools for incorporating the spatial coordinates of soil observations in data processing, allowing for description and modeling of spatial patterns, prediction at unsampled locations, and assessment of the uncertainty attached to these predictions. A study was conducted in Nasarawa State with the aim of determining the spatial variability and distribution pattern of the soil pH in the thirteen local Government areas (LGAs) of the State. Geo-referenced soil samples were collected from the thirteen LGAs at the surface (0-15cm) and sub surface (15-30cm) depths. The pH of the soils was measured in water and potassium chloride (1M KCl) suspension in a 1:2.5 (soil: liquid ratio). Coordinates (latitude and longitude) of the locations of the sampling sites were obtained with the aid of a hand held Global Positioning System (GPS) (Garmin eTrex Ventura®) receiver. Spatial analysis of the classified soil pH was done in a GIS environment. A GIS software package ArcGIS 9.0 and ArcGIS Geo-statistical Analyst Extension were used. An interpolation technique called “Ordinary Kriging“ was used to produce the spatial distribution of the soil pH. Spatial analysis results showed that the best fit semivariogram models for pH in water were “Hole effect” and “spherical” for surface and subsurface depths respectively. pH in water at the surface depth had nugget/sill ratio (Co/Co + C) = 0.416 and subsurface depth = 0.817. The Spatial distribution maps of pH in water revealed that 0.1% representing 14.9km2 of the top soils (0 – 15) in Nasarawa State were very strongly acid (pH water < 5.1), while 2.4% (639.9km2) were strongly acid (pH 5.2 – 5.5) and 21.8% (5738.1km2) were slightly acid. Majority (75.7%) of the top soil however are moderately acid (5.6 – 6.0), representing a land area of 19, 918.9km2

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Geo-statistical Analyses of the Spatial Variation of Soil Reaction (p H) in Nasarawa State, North Central Nigeria

Geo-statistics provides a set of statistical tools for incorporating the spatial coordinates of s... more Geo-statistics provides a set of statistical tools for incorporating the spatial coordinates of soil observations in data processing, allowing for description and modeling of spatial patterns, prediction at unsampled locations, and assessment of the uncertainty attached to these predictions. A study was conducted in Nasarawa State with the aim of determining the spatial variability and distribution pattern of the soil pH in the thirteen local Government areas (LGAs) of the State. Georeferenced soil samples were collected from the thirteen LGAs at the surface (0-15cm) and sub surface (15-30cm) depths. The pH of the soils was measured in water and potassium chloride (1M KCl) suspension in a 1:2.5 (soil: liquid ratio). Coordinates (latitude and longitude) of the locations of the sampling sites were obtained with the aid of a hand held Global Positioning System (GPS) (Garmin eTrex Ventura®) receiver. Spatial analysis of the classified soil pH was done in a GIS environment. A GIS software package ArcGIS 9.0 and ArcGIS Geostatistical Analyst Extension were used. An interpolation technique called "Ordinary Kriging" was used to produce the spatial distribution of the soil pH. Spatial analysis results showed that the best fit semivariogram models for pH in water were "Hole effect" and "spherical" for surface and subsurface depths respectively. pH in water at the surface depth had nugget/sill ratio (C o /C o + C) = 0.416 and subsurface depth = 0.817. The Spatial distribution maps of pH in water revealed that 0.1% representing 14.9km 2 of the top soils (0 -15) in Nasarawa State were very strongly acid (pH water < 5.1), while 2.4% (639.9km 2 ) were strongly acid (pH 5.2 -5.5) and 21.8% (5738.1km 2 ) were slightly acid. Majority (75.7%) of the top soil however are moderately acid (5.6 -6.0), representing a land area of 19, 918.9km 2 .

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Climate Change at a Global Concept: Impacts and Adaptation Measures

International Journal of Environment and Climate Change, Jun 21, 2024

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Spatial variability of soil organic carbon in a catchment of the Loess Plateau

Acta Agriculturae Scandinavica, Section B - Plant Soil Science, 2010

Spatial Variability of Soil Organic Carbon in a Cassava field at Ekha Agro Farms, Lanlate, Oyo State, Nigeria

by Tunrayo Alabi and James Jayeoba

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Full Length Research Paper Growth, Nutrient Uptake and Dry Matter Yield of Maize (Zea Mays L) Grown in Soil Amended with Rice Husk and Sawdust Biochar

Major characteristics and classification of soils in duduguru, obi lga of Nasarawa State, Nigeria

Agricultural Research Journal

Growth, Nutrient Uptake and Dry Matter Yield of Maize (Zea Mays L) Grown in Soil Amended with Rice Husk and Sawdust Biochar

International Journal of Scientific Research in Agricultural Sciences, 2016

Geo-statistical Analyses of the Spatial Variation of Soil Reaction (pH) in Nasarawa State, North Central Nigeria

by Tunrayo Alabi and James Jayeoba

Download

Geo-statistical Analyses of the Spatial Variation of Soil Reaction (p H) in Nasarawa State, North Central Nigeria

Geo-statistics provides a set of statistical tools for incorporating the spatial coordinates of s... more Geo-statistics provides a set of statistical tools for incorporating the spatial coordinates of soil observations in data processing, allowing for description and modeling of spatial patterns, prediction at unsampled locations, and assessment of the uncertainty attached to these predictions. A study was conducted in Nasarawa State with the aim of determining the spatial variability and distribution pattern of the soil pH in the thirteen local Government areas (LGAs) of the State. Georeferenced soil samples were collected from the thirteen LGAs at the surface (0-15cm) and sub surface (15-30cm) depths. The pH of the soils was measured in water and potassium chloride (1M KCl) suspension in a 1:2.5 (soil: liquid ratio). Coordinates (latitude and longitude) of the locations of the sampling sites were obtained with the aid of a hand held Global Positioning System (GPS) (Garmin eTrex Ventura®) receiver. Spatial analysis of the classified soil pH was done in a GIS environment. A GIS software package ArcGIS 9.0 and ArcGIS Geostatistical Analyst Extension were used. An interpolation technique called "Ordinary Kriging" was used to produce the spatial distribution of the soil pH. Spatial analysis results showed that the best fit semivariogram models for pH in water were "Hole effect" and "spherical" for surface and subsurface depths respectively. pH in water at the surface depth had nugget/sill ratio (C o /C o + C) = 0.416 and subsurface depth = 0.817. The Spatial distribution maps of pH in water revealed that 0.1% representing 14.9km 2 of the top soils (0 -15) in Nasarawa State were very strongly acid (pH water < 5.1), while 2.4% (639.9km 2 ) were strongly acid (pH 5.2 -5.5) and 21.8% (5738.1km 2 ) were slightly acid. Majority (75.7%) of the top soil however are moderately acid (5.6 -6.0), representing a land area of 19, 918.9km 2 .

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