| Autor: |
Mutair A. Akanji, Suarau O. Oshunsanya, Abdulrasoul Alomran |
| Jazyk: |
angličtina |
| Rok vydání: |
2018 |
| Předmět: |
|
| Zdroj: |
International Soil and Water Conservation Research, Vol 6, Iss 3, Pp 230-236 (2018) |
| Druh dokumentu: |
article |
| ISSN: |
2095-6339 |
| DOI: |
10.1016/j.iswcr.2018.03.006 |
| Popis: |
Apparent Soil Electrical Conductivity (ECa) measurement is a rapid and accurate tool for measuring soil physical and chemical properties affecting crop productivity. This study uses ECa to predict yam yield. Soil ECa was measured at the depth of 0–15 cm, 15–30 cm and 30–45 cm using Miller 400D resistance meter with multi-electrode Wenner array. Soil samples were collected at the aforementioned depths and analyzed for selected physical and chemical properties. Two cultivars of water yam, Discorea alata L. (TDa 00/00194 (D1) and TDa 00/00006 (D2)) were planted and yield data were collected after harvesting. Data collected were analyzed using correlation, nonlinear and multiple linear regression analysis using Origin statistical software (Pro. V.8.1). Soil ECa at 0–15 cm correlated with the yields of D1 and D2 with correlations (r) of 0.83 and 0.84, respectively. The relationship between ECa and D1 and D2 were best fit with a cubic function (with r2 = 0.70 and 0.75, respectively). A Multiple linear regression model showed the interactive effect of soil physical and chemical properties as it affected the yields. The generated models showed that soil properties needed for growth and yields of D1 and D2 are different. Therefore, farmers should not plant both cultivars into the same soil environment or use blanket fertilizer application to achieve optimum performance. Keywords: Crop yield, Water yam, Multiple linear regression models, Blanket fertilizer application, Wenner array |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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