Partial collection of data on potato yield for experimental planning

The aim of this study was to estimate the number of blank experiments (BE) (i.e., a uniformity trial) required to estimate the optimum plot size for use in experiments involving potato crops. The study was based on data on the mass of potato tubers (Solanum tuberosum L.) from 3456 hills (i.e., 24 rows of 144 hills each) obtained from a BE. Using these data, BE of different sizes (i.e., 2 rows of 24, 36, 48 and 72 hills) were planned to estimate optimum plot size. For each BE, 11 plot sizes (X) were planned based on the sum of adjacent hills, and the mean, variance and coefficient of variation (CV) between plots of the same size were calculated. Regression models for CV were adjusted in terms of X to estimate the optimum plot size. For each BE size, a bootstrap resampling method was used to estimate the sufficient number of BE to enable precise estimates of optimum plot size, mean and other statistics. It was found that a sampling potato hill yield of 39% of subdivisions within an experimental area where a potato experiment is to be performed is sufficient to estimate optimum plot size for the experiment. Plots composed of one row of six hills are sufficient to estimate potato yield.

Research highlights▶ We estimate the number of potato blank experiments to estimate the optimum plot size. ▶ Bootstrap resampling is adequate to estimate the number of blank experiments. ▶ 39% of the potato blank experiments is sufficient to estimate optimum plot size. ▶ Plots of one row of six hills are sufficient to estimate potato yield.