Use of multidimensional analysis for farm decision making following performance of five cowpea varieties on a farmer’s field.

Abstract

The contribution of other variables to crop yields are often ignored as use of Analysis of Variance (ANOVA) in farm decision making is often based on the treatment that gives the highest significant yield. The contribution of other crop growth parameters collected in the field were combined and factor in to make decision in a trial experiment to evaluate five cowpea varieties in a farmer‘s field. this experiment was conducted in 2007 and 2008 growing season to screen five cowpea varieties on an Inceptisol of humid forest zone of south eastern Nigeria. The varieties were, IT 98K – 205-15 (T1); IT 93K – 452-1 (T2); IT 98K -111-1 (T3); IT 97K – 461- 4 (T4) and IT 99K – 1122 (T5). Planting was done in early September 2007 and 2008 on the flat (no tillage) at 50 cm by 30 cm. Randomized complete block design was used. Each experimental unit measured 4 m by 4m replicated four times. Length of pod per plant, number of pod per plant, number of seed per plant, 100 seed weight and cowpea grain yield were data collected. The data were first subjected to Analysis of Variance (ANOVA). The growth parameters were fitted to a multiple (step  add-delete) regression model with cowpea yield as the response variable. The analysis showed that the growth parameter contributed in some cases greater than 50 % to the cowpea grain yield. The parameters that contributed to cowpea grain yield were pinned and subjected to Multi-Dimensional Analysis (MDA). By the MDA ranking variety IT98K-205-15 (T2) ranked the highest with 4.46 points and variety IT 99K- 1122 (T5) ranked second with 4.32 points.

Keywords: ANOVA, Humid zone, Multi-Dimensional Analysis, Decision making, Incetptisol.