HOSTED BY Original Research Article Electrical conductivity method for predicting yields of two yam (Dioscorea alata) cultivars in a coarse textured soil Mutair A. Akanji a,b,n , Suarau O. Oshunsanya a , Abdulrasoul Alomran b a Department of Agronomy, University of Ibadan, Ibadan, Nigeria b Soil Sciences Department, College of Food and Agricultural Sciences, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia article info Article history: Received 8 March 2018 Received in revised form 20 March 2018 Accepted 27 March 2018 Keywords: Crop yield Water yam Multiple linear regression models Blanket fertilizer application Wenner array abstract 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 cor- relations (r) of 0.83 and 0.84, respectively. The relationship between ECa and D1 and D2 were best fit with a cubic function (with r 2 ¼ 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 appli- cation to achieve optimum performance. & 2018 International Research and Training Center on Erosion and Sedimentation and China Water and Power Press. Production and Hosting by Elsevier B.V. This is an open access article under the CC BY-NC- ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). 1. Introduction Pedogenic and antropogenic factors often cause variation in the soil physical and chemical properties which have great influence on agricultural productivity. Naturally, soil is greatly hetero- geneous as its physical and chemical properties changes from point to point which affect crop productivity (Aminuddin, Zulkefli, Abd Razak, Abdul Munir, & Abdul Rahim, 2003). The hetero- geneous nature of the soil makes uniform or blank application of agricultural input such as fertilizer, irrigation, pesticides to be in- adequate for obtaining maximum productivity (precision agri- culture). Changes in crop productivity are functions of the changes in the physical and chemical properties of soil (Bauer & Black, 1994; Gardner & Clancy, 1996; Olson, McQuaid, Easterling, & Scheyer, 1996). In order to enhance yield, discriminate application of agricultural inputs is essential. This could be guided by carrying out a soil survey (Nieuwolt, Zaki Ghazali, & Gopinathan, 1982). These soil productivity indices were developed using soil physical and chemical properties to characterize variability between soil types in a field (Neill, 1979; Scrivner, Conkling, & Koeing, 1985). However, this method of soil productivity indices is expensive and time consuming due to the fact that it involves intensive soil sampling and laboratory analysis. Apparent soil electrical conductivity (ECa) is one of the sim- plest, cost effective soil measurements available to measure and map soil physical and chemical properties variability within field (Chan, Amin, Lee, & Mohammud, 2006). The soil ECa measure- ments integrate many soil properties affecting crop productivity such as soil texture, cation exchange capacity, drainage conditions, organic matter level, salinity and subsoil characteristics (Aimrun, Amin, Ahmad, Hanafi, & Chan, 2007). With field verification, it has been reported that the spatial measurements of soil ECa or electrical resistivity have potential for predicting crop yield variation caused by differences in soil phy- sical and chemical properties (Joshua & Mokuolu, 2016). The rapid spatial measurement of soil ECa has been demonstrated using both mobile electromagnetic (EM) induction (McNeil, 1992; Rhoades, 1992a; b; Carter, 1993; Jaynes, Colvin, & Ambuel, 1993; Kitchen, Sudduth, & Drummond, 1996) and mobile electrical re- sistivity equipment (Rhoades, 1992a; b; Carter, 1993). In instances Contents lists available at ScienceDirect journal homepage: www.elsevier.com/locate/iswcr International Soil and Water Conservation Research https://doi.org/10.1016/j.iswcr.2018.03.006 2095-6339/& 2018 International Research and Training Center on Erosion and Sedimentation and China Water and Power Press. Production and Hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Abbreviations: D1, Discorea alata L. (TDa 00/00194); D2, Discorea alata L. (TDa 00/ 00006) n Corresponding author at: Soil Sciences Department, College of Food and Agri- cultural Sciences, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia. E-mail address: mutairakanji@gmail.com (M.A. Akanji). Please cite this article as: Akanji, M. A., et al. International Soil and Water Conservation Research (2018), https://doi.org/10.1016/j. iswcr.2018.03.006i International Soil and Water Conservation Research ∎ (∎∎∎∎) ∎∎∎–∎∎∎