Comparison of methods for optimum plot size and shape for field experiments on paddy (Oryza sativa)

Abstract

The research work entitled “Comparison of methods for optimum plot size and shape for field experiments on paddy (Oryza sativa)” was conducted with the objective of estimation and comparison of methods for optimum plot size and shape for field experiments on high yielding variety of paddy. The study was based on primary data collected from a uniformity trial conducted in an area of 800m2 with Uma variety of paddy in virippu season 2018 at Integrated Farming System Research Station (IFSRS), Karamana. The crop was transplanted at a spacing of 20 cm × 15 cm. The field was divided in to 1.2 m × 1.2 m (1.44 m2) plots, after leaving a border of one meter from all the sides of the plot to eliminate the border effects, thus give rise to 400 basic units. Observations on plant height and number of tillers were recorded separately from each basic unit at monthly intervals and number of productive tillers, thousand grain weight, grain yield and straw yield were recorded separately from each basic unit at the time of harvest. The average height of the plant increased from 40.55 cm at one month after planting (MAP) to 121.37 cm at four MAP. The number of tillers per plant varied from 4 at two MAP to 14 at four MAP. The grain yield per basic unit varied from a minimum of 200 g to a maximum of 650 g with an average yield of 391.13 g per plot. The average straw yield was 0.501 kg. The first quartile (Q1) was observed at 0.410 kg and third quartile (Q3) was at 0.572 kg. The estimated average harvest index was 0.438 with a coefficient of variation (CV) of 20.78 per cent. The mean productive tillers estimated was 9 per plant. The correlation between productive tillers and grain yield was significant (0.128). Harvest index showed a very high significant correlation of 0.744 with grain yield. Soil fertility contour map was constructed based on yield data of all original basic units and by taking 3 × 3 and 5 × 5 moving average and the results of the analysis have shown that 3 × 3 moving average provided a more prominent picture of fertility status of the field and thus concluded that fertility gradient was more in horizontal

direction. Serial correlation of horizontal and vertical strip and mean squares between vertical and horizontal strips also revealed that fertility gradient was more pronounced in horizontal direction. The optimum plot size estimated by combining the basic units of 1.44 m2 into plots of different sizes along with CV for each plot size. The different methods used for the estimation of optimum plot size are maximum curvature method, Fairfield Smith’s variance law method, modified maximum curvature method, comparable variance method, cost ratio method, covariate method, based on shape of the plot method and Hatheway’s method. Generally these methods need not provide a unique estimate. The optimum plot size estimated under maximum curvature method and comparable variance method was 34.56 m2 (24 basic units) with rectangular shape and it was same for both methods. The optimum plot size estimated under covariate method by taking harvest index as covariate was also 34.56 m2. The optimum plot size estimated by considering length (X1) and breadth (X2) also provided same plot size (34.56 m2) with X1 =3 units and X2 =8. Optimum plot size under Hatheway’s method was estimated by choosing varying number of replications and difference between treatment means. A plot size of 37.44 m2 (26 basic units) for four replications and 10 per cent difference between the treatment means was found to be optimum under this method. The optimum plot size estimated under Fairfield Smith’s variance law method and modified maximum curvature method was 8.64 m2 and it was not considered as optimum because it was smaller in size. Optimum plot size under cost ratio method was obtained by considering different cost ratios of fixed cost K1 and variable cost K2. The estimated plot size under cost ratio method was 5.95 units with K1 = 10 and K2 = 1. The comparison of methods for optimum plot size was done based on CV. The maximum percentage reduction in CV was found to be with a plot size of 24 basic units and percentage reduction was very low thereafter. Hence maximum curvature method,

comparable variance method, covariate method and shape of the plot methods can be recommended for estimating optimum plot size for Uma variety of paddy for field experiments and the estimated optimum plot size was 34.56 m2 and the recommended shape was rectangular