Nano Urea formulations for more wheat yield evaluated by AMMI and BLUP effects of
treatments under irrigated conditions at North Western Plains Zone and Central Zone

Abstract:

AMMI analysis of wheat yield for nano urea formulations treatments had observed highly significant variations due to treatments, locations, and TxL interactions with 44.6%, 33.5%, and 12.8% respectively. Thousands of grains weight of treatments observed that the first AMMI interaction component contributed to 78.9% whereas AMMI2,  AMMI3, AMMI4 accounted for 10.2%, 3.5%, 2.3% respectively. AMMI analysis-based measures ASV & ASV1 have utilized 73.4% of interaction sum of squares and T6, T8, T5 recommended by ASV1 whereas ASV pointed for T6, T8, T5 treatments for wheat yield. Measures MASV1 and MASV based on all significant IPCAs of the AMMI analysis for thousands grains weight and considered 94.9% of interactions sum of squares had recommended T6, T5, T11 and T6, T8, T7 treatments for stable performance respectively. Superiority index measures had considered 65% and 35% of ratios of average value and stable performance in weighted average observed suitability of T8, T3, T6 treatments for wheat yield. Analytic adaptability measures based on BLUP of treatments effects settled for T3, T4, T7 treatments as far as thousands of grains weight was considered in the present study. Biplot analysis observed a very tight positive relationship of ASV with ASV1, W1 , W2, W3, W4, W5, W6, WAASB , MASV with MASV1 values. Analytic measures PRVG , HMPRVG expressed strong bondage with BLUE and  BLUP effects of treatments for wheat yield. The clustering pattern for thousands of grains weight had expressed first consisted of superiority indexes corresponding to mean, GAI, HM of treatments effects irrespective of BLUE and BLUP estimates joined hands in the first cluster and next cluster was of analytic measures PRVG, HMPRVG for treatments effects irrespective of BLUE and BLUP estimates with IPC1 measures in the present study. Recent analytic measures for adaptability and superior performance of treatments would be more suitable for large-scale recommendations.