Optimizing Sunflower Production Through the Use of GIS-Based Soil Fertility Management Strategy
| dc.contributor.author | Nungula, Emmanuely Z. | |
| dc.contributor.author | Massawe, Boniface J. | |
| dc.contributor.author | Chappa, Luciana R. | |
| dc.contributor.author | Nhunda, Daniel M. | |
| dc.contributor.author | Seleiman, Mahmoud F. | |
| dc.contributor.author | Ali, Nawab | |
| dc.contributor.author | Gitari, Harun I. | |
| dc.date.accessioned | 2024-11-19T12:40:26Z | |
| dc.date.available | 2024-11-19T12:40:26Z | |
| dc.date.issued | 2024-08 | |
| dc.description | Article | |
| dc.description.abstract | This study aimed to use a GIS-based approach in producing soil fertility maps and utilize the spatial data on achieving site-specific management of major nutrients in Morogoro, Tanzania. Soil samples were collected in six mapping units and analyzed for chemical properties such as pH, cation exchange capacity and electrical conductivity. ArcGIS 10.8 was used to produce nutrient variability maps of organic carbon, available P, total nitrogen and exchangeable K, Ca and Mg using the Inverse Distance Weight (IDW) interpolation method. The soil pH values ranged from 5.5 to 7.2. OC varied between 1.2 and 4.9g kg−1, TN ranged from low to medium (1.0 to 5.0g kg−1) whereas Av. P varied between l3.3 and 14.3mg kg−1. Exchangeable K, Ca and Mg had ranges (in cmol kg−1) of between 0.1 to 0.8 (low to medium), 3.8 to 15.6 (low to high) and 0.3 to 0.5 (low), cmol kg−1. The recommended amounts were 74, 44, 36, 35 and 12kg ha−1 for N, P2O5, K2O, MgO and CaO, respectively. Conducting soil analysis is key for monitoring the amount of nutrients that are available in the soil at time and space, to achieve site-specific nutrient management. | |
| dc.description.sponsorship | King Saud University, Riyadh, Saudi Arabia (RSPD2024R751). | |
| dc.identifier.citation | Nungula, E. Z., Massawe, B. J., Chappa, L. R., Nhunda, D. M., Seleiman, M. F., Ali, N., & Gitari, H. I. (2024). Optimizing sunflower production through the use of GIS-based soil fertility management strategy. Cogent Food & Agriculture, 10(1), 2390685. | |
| dc.identifier.uri | https://doi.org/10.1080/23311932.2024.2390685 | |
| dc.identifier.uri | https://ir-library.ku.ac.ke/handle/123456789/29400 | |
| dc.language.iso | en | |
| dc.publisher | Taylor & Francis Group | |
| dc.title | Optimizing Sunflower Production Through the Use of GIS-Based Soil Fertility Management Strategy | |
| dc.type | Article |