INFLUENCE OF STARTER NITROGEN APPLICATION ON YIELDS OF TWO SOYA BEAN VARIETIES GROWN ON FERRIC LUVISOL IN OYO STATE, NIGERIA (2016)
Nitrogen is a major soil nutrient for the growth and development of crops. Nitrogen deficiency in-between pre-nodulation and nodulation in soya bean is critical to enhancing its growth and yield. Decision Support Systems for Agro-technology Transfer (DSSAT) model like CROPGRO-soya bean could be a useful tool for predicting starter nitrogen requirement in soya bean. However, information on starter nitrogen application to overcome N-deficiency-induced-stress during early seedling growth and prediction using CROPGRO-soya bean is limited. This study was undertaken to investigate the effect of starter nitrogen on soya bean yield grown on ferric luvisol in Oyo State, Nigeria.Field experiment involving two soya bean varieties (TGx1485-1D and TGx1448-2E) and five starter nitrogen rates (0, 5, 15, 25 and 35 kg/ha) was carried out for two seasons at Ipapo and Gbonran in Itesiwaju Local Government Area of Oyo State. The experiment was laid out as split-plot in a randomised complete block design with three replications. Nitrogen rate and soya bean variety were main and sub-plot factors, respectively. Shoot Dry Weight (SDW, t/ha), Grain Yield (GY, t/ha), Harvest Index (HI) and Shoot Nitrogen Content (SNC, g/kg) were measured. In screenhouse, soil from each location was filled into pots (5 kg) and each variety was planted under optimum management practices in a completely randomised design with three replications. Data on days to seedling emergence, days to first pod appearance and days to physiological maturity were obtained, fitted and used to calibrate CROPGRO-soya bean model. Data on weather parameters, soil description and characterisation (pH, field capacity, permanent wilting point, bulk density and hydraulic conductivity) were used for predicting phenology and yield. Data were analysed using ANOVA at α0.05, and model outputs were evaluated with percentage error (PE).Nitrogen rate had no significant effect on SDW, while variety TGx1448-2E had significantly higher SDW (2.9±0.3) and GY (1.5±0.1) than TGx1485-1D (2.3±0.3 and 1.3±0.1, respectively) at both locations. Nitrogen rate had no significant effects on GY and HI at Gbonran. However, 15 kgN/ha produced a significantly highest GY (1.4±0.1) than the control (1.2±0.1), while HI at 5 kgN/ha (0.60±0.02) was highest at Ipapo. Variety TGx1485-1D had significantly higher HI (0.58±0.05) than TGx1448-2E (0.52±0.05) at both locations. Nitrogen rate had no significant effect on SNC at both locations. Variety TGx1485-1D had significantly higher SNC (33.0±1.5) than TGx1448-2E (26.0±1.5) at Ipapo. CROPGRO-Soya bean model predicted soya bean phenology across nitrogen rates within 0 – 1 day of the observed values at both locations. Predicted yield of TGx1485-1D was 1.5 t/ha across N rates with PE < 15%, while that of TGx1448-2E was 2.6 t/ha with PE > 30%. Application of starter nitrogen had no effect on yields of soya bean at Gbonran but 15 kgN/ha enhanced grain yield of soya bean at Ipapo. Variety TGx1448-2E had better biomass yield, while TGx1485-1D had better nitrogen content on ferric luvisol. Prediction of CROPGRO-soya bean model was reliable for phenology and yield of TGx1485-1D but not reliable for yield of TGx1448-2E