Vol. 7, Issue 10, Part A (2025)

Field experiments conducted over five consecutive years (2015-2020) at the Department of Agronomy, IGKV, Raipur, started with plotting the graphical pattern of N, P, K nutrients. The graphical fertility patterns were found to change for the years 2015-2016 to 2019-2020. These fertility gradients were found to be curvilinear, and not straight-line across the field. So, the ANCOVA with fertility covariates, N, P, K individually or their sum (N+P+K) plot to plot, were found to reduce error variance more effectively than the RBD, thereby improving the precision of treatment comparisons. Both methods of covariate adjustment, using N, P, K separately andusing their sum of N, P and K, performed well, often competing with each other in efficiency. Thus, ANCOVA using soil fertility data offers a robust alternative to RBD, especially when blocks cannot be correctly determined apriori. Overall, ANCOVA consistently reduced experimental error more effectively than RBD, improving reliability of results. So, in field experiments with unknown fertility gradient, ANCOVA with soil nutrient covariates proves to be a superior and more efficient analytical alternative compared to conventional RBD.