Nitrogen and potassium application effects on productivity, profitability and nutrient use efficiency of irrigated wheat (Triticum aestivum L.)

The development of robust nutrient management strategies have played a crucial role in improving crop productivity, profitability and nutrient use efficiency. Therefore, the implementation of efficient nutrient management stratigies is important for food security and environmental safety. Amongst the essential plant nutrients, managing nitrogen (N) and potassium (K) in wheat (Triticum aestivum L.) based production systems is citically important to maximize profitable production with minimal negative environmental impacts. We investigated the effects of different fertilizer-N (viz. 0–240 kg N ha(-1); N(0)-N(240)) and fertilizer-K (viz. 0–90 kg K ha(-1); K(0)-K(90)) application rates on wheat productivity, nutrient (N and K) use efficiency viz. partial factor productivity (PFP(N/K)), agronomic efficiency (AE(N/K)), physiological efficiency (PE(N/K)), reciprocal internal use efficiency (RIUE(N/K)), and profitability in terms of benefit-cost (B-C) ratio, gross returns above fertilizer cost (GRAFC) and the returns on investment (ROI) on fertilizer application. These results revealed that wheat productivity, plant growth and yield attributes, nutrients uptake and use efficiency increased significantly (p<0.05)with fertilizer-N application, although the interaction effect of N x K application was statistically non-significant (p<0.05). Fertilizer-N application at 120 kg N ha(-1) (N(120)) increased the number of effective tillers (8.7%), grain yield (17.3%), straw yield (15.1%), total N uptake (25.1%) and total K uptake (16.1%) than the N(80). Fertilizer-N application significantly increased the SPAD reading by ~4.2–10.6% with fertilizer-N application (N(80)-N(240)), compared with N(0). The PFP(N) and PFP(K) increased significantly with fertilizer-N and K application in wheat. The AE(N) varied between 12.3 and 22.2 kg kg(-1) with significantly higher value of 20.8 kg kg(-1) in N(120). Fertilizer-N application at higher rate (N(160)) significantly decreased the AE(N) by ~16.3% over N(120). The N(120)treatment increased the AE(K) by ~52.6% than N(80) treatment. Similarly the RIUE(N) varied between 10.6 and 25.6 kg Mg(-1) grain yield, and increased significantly by ~80.2% with N(120) as compared to N(0) treatment. The RIUE(K) varied between 109 and 15.1 kg Mg(-1) grain yield, and was significantly higher in N(120) treatment. The significant increase in mean gross returns (MGRs) by ~17.3% and mean net returns (MNRs) by ~24.1% increased the B-C ratio by ~15.1% with N(120) than the N(80) treatment. Fertilizer-N application in N(120) treatment increased the economic efficiency of wheat by ~24.1% and GRAFC by ~16.9%. Grain yield was significantly correlated with total N uptake (r = 0.932**, p<0.01), K uptake (r = 0.851**), SPAD value (r = 0.945**), green seeker reading (r = 0.956**), and the RIUE(N) (r = 0.910**). The artificial neural networks (ANNs) showed highly satisfactory performance in training and simulation of testing data-set on wheat grain yield. The calculated mean absolute error (MAE), mean absolute percentage error (MAPE) and root mean square error (RMSE) for wheat were 0.0087, 0.834 and 0.052, respectively. The well trained ANNs model was capable of producing consistency for the training and testing correlation (R(2) = 0.994**, p<0.01) between the predicted and actual values of wheat grain yield, which implies that ANN model succeeded in wheat grain yield prediction.