Geospatial Assessment of Soil Nutrient Limitations and Site-Specific Fertilizer Recommendations for Potato Farming Systems in Plateau State, Nigeria

Precision agriculture approaches require detailed understanding of soil nutrient heterogeneity to develop cost-effective fertilization strategies for sustainable food production. This study employed geospatial technologies to map soil nutrient limitations and formulate zone-specific fertilizer recommendations for potato production systems in Bokkos and Mangu Local Government Areas, Plateau State, Nigeria. Through systematic sampling of 240 georeferenced locations across 3,329.41 km², we analysed soil pH, organic carbon, nitrogen, phosphorus, and potassium using inverse distance weighting interpolation in ArcGIS. Results revealed severe nutrient stratification across the study landscape, with soil acidity affecting 77% of farmlands (pH 4.0-5.36), creating a primary constraint requiring approximately 2,050 km² of lime application. Nitrogen deficiency dominated 83.2% of the area (0.01-0.084% N), while phosphorus limitations encompassed 55.6% of farmlands (3.68-8.91 mg/kg). Conversely, potassium showed adequate levels across 51.5% of locations. Geographic clustering analysis identified three distinct soil management zones: Zone A (central volcanic belt, 45% coverage) exhibiting superior fertility with pH 5.68-7.0 and elevated N-P-K levels; Zone B (peripheral granitic areas, 35% coverage) showing moderate degradation; and Zone C (severely depleted regions, 20% coverage) requiring intensive rehabilitation. Economic analysis suggests prioritizing Zone B with balanced NPK fertilization could yield 300% return on investment, while Zone A requires only maintenance inputs. Zone C necessitates multi-year soil amendment programs combining lime (2-3 tons/ha), organic matter (5-10 tons/ha), and starter fertilizers. This research provides the first comprehensive nutrient prescription map for Plateau State potato systems, enabling farmers and extension services to implement precision fertilization strategies that could potentially increase yields by 40-60% while reducing input costs by 25-30% through targeted application.

Precision agriculture, soil fertility mapping, nutrient management zones, fertilizer recommendations, spatial interpolation

1. Alva, A.K., Ren, H., Moore, A.D. (2004). Effects of phosphorus with ammonium and nitrate on potato growth, yield and leaf phosphate fractions. Journal of Plant Nutrition, 27(11), 1793-1810. [Google Scholar] [Crossref]

2. Buol, S.W., Southard, R.J., Graham, R.C., McDaniel, P.A. (2011). Soil Genesis and Classification (6th ed.). Wiley-Blackwell, Ames, Iowa. [Google Scholar] [Crossref]

3. Certini, G., Corti, G., Agnelli, A., Sanesi, G. (2004). Carbon dioxide efflux and concentrations in two soils under temperate forests. Biology and Fertility of Soils, 37(1), 39-46. [Google Scholar] [Crossref]

4. CIP (International Potato Center).(2020).Potato facts and figures. Retrieved from https:// cipotato .org/potato/facts/ [Google Scholar] [Crossref]

5. FAOSTAT. (2016). Food and Agricultural Organization of the United Nations. FAO Statistical Database 2015. Retrieved from http://faostat3.fao.org/download/FB/CC/E [Google Scholar] [Crossref]

6. FAOSTAT. (2019). Food and Agricultural Organization of the United Nations. FAO Statistical Database. Retrieved from http://www.fao.org/faostat/en/data [Google Scholar] [Crossref]

7. FAOSTAT. (2022). Food and Agricultural Organization of the United Nations. FAO Statistical Database. Retrieved from http://www.fao.org/faostat/en/data [Google Scholar] [Crossref]

8. Gebbers, R., Adamchuk, V.I. (2010). Precision agriculture and food security. Science, 327(5967), 828-831. [Google Scholar] [Crossref]

9. Haynes, R.J. (1984). Lime and phosphate in the soil-plant system. Advances in Agronomy, 37, 249-315. [Google Scholar] [Crossref]

10. Jenny, H. (1941). Factors of Soil Formation: A System of Quantitative Pedology. McGraw-Hill, New York. [Google Scholar] [Crossref]

11. Kleinkopf, G.E., Westermann, D.T., Wille, M.J., Kleinschmidt, G.D. (1987). Specific gravity of Russet Burbank potatoes. American Potato Journal, 64(11), 579-587. [Google Scholar] [Crossref]

12. Kolawole, O.D., Wolka, K., Amsalu, A. (2019). Soil fertility management practices by smallholder farmers in Nigeria: Implications for sustainable agriculture. Agricultural Systems, 173, 500-515. [Google Scholar] [Crossref]

13. Opfergelt, S., Georg, R.B., Delvaux, B., Cabidoche, Y.M., Burton, K.W., Halliday, A.N. (2012). Mechanisms of magnesium isotope fractionation in volcanic soil weathering sequences, Guadeloupe. Earth and Planetary Science Letters, 341-344, 176-185. [Google Scholar] [Crossref]

14. Sanchez, P.A., Swaminathan, M.S. (2005). Cutting world hunger in half. Science, 307(5708), 357-359. [Google Scholar] [Crossref]

15. Tadesse, Y., Almekinders, C.J.M., Schulte, R.P.O., Struik, P.C. (2018). Understanding farmers' potato production practices and use of improved varieties in Chencha, Ethiopia. Journal of Crop Improvement, 32(5), 673-702. [Google Scholar] [Crossref]

16. Taiy, R.J., Onyango, C., Nkurumwa, A., Ngetich, K. (2017). Socioeconomic characteristics of smallholder potato farmers in Mauche Ward of Nakuru County, Kenya. Universal Journal of Agricultural Research, 5(5), 257-266. https://doi.org/10.13189/ujar.2017.050502 [Google Scholar] [Crossref]

17. Vanlauwe, B., Coyne, D., Gockowski, J., Hauser, S., Huising, J., Masso, C., Nziguheba, G., Schut, M., Van Asten, P. (2015). Sustainable intensification and the African smallholder farmer. Current Opinion in Environmental Sustainability, 8, 15-22. [Google Scholar] [Crossref]

18. Zemba, B.A.A., Wuyep, S.Z., Adebayo, A.A., Jahknwa, C.J. (2013). Growth and yield response of Irish potato (Solanum tuberosum) to climate in Jos-South, Plateau State, Nigeria. Global Journal of Human Social Science Geography, Geo-Sciences, Environmental Disaster Management, 13(5), 13-18. [Google Scholar] [Crossref]

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