Innovative Sudoku Designs with Rectangular Sub-zones: Enhancing Experimental Precision in Paddy Field Trials
Prity Maji
Department of Agricultural Statistics, Bidhan Chandra Krishi Vishwavidyalaya, P.O- Krishi Vishwavidyalaya, West Bengal, 741252, India.
Mriganka Saha
Department of Agricultural Statistics, Bidhan Chandra Krishi Vishwavidyalaya, P.O- Krishi Vishwavidyalaya, West Bengal, 741252, India.
Vivek Kashyap
KVK, Deoghar, Jharkhand, 814152, India.
Shaon Chakraborty *
KVK, Deoghar, Jharkhand, 814152, India.
Krishnakali Roy
Department of Agricultural Statistics, Bidhan Chandra Krishi Vishwavidyalaya, P.O- Krishi Vishwavidyalaya, West Bengal, 741252, India.
Moupiya Roy
School of Agriculture, Seacom Skills University, Kendradangal, Birbhum, West Bengal, 731236, India.
Soumik Dey
Department of Agricultural Statistics, Division of Agriculture, Faculty Center for Agriculture, Rural and Tribal Development (ARTD), Ramakrishna Mission Vivekananda Educational and Research Institute, Morabadi, Ranchi, 834008, India.
Anurup Majumder
Department of Agricultural Statistics, Bidhan Chandra Krishi Vishwavidyalaya, P.O- Krishi Vishwavidyalaya, West Bengal, 741252, India.
*Author to whom correspondence should be addressed.
Abstract
This study investigates the application of a Sudoku square design with rectangular subzones for a field experiment on paddy cultivation conducted in 2022-2023 in West Bengal, India. Traditional row column experimental designs, such as the Latin Square Design (LSD), have been widely used in agricultural research. However, these designs have limitations in estimating a variety of effects due to their structure. The research addresses this limitation by employing a sudoku square design, which has introduced a notable framework for experimental analysis. Four distinct statistical models were employed to analyze the yield data. The models captured varying sources of variation. Type 1 identified three: row block, column block, and subzone. Type 2 added rows within BR and columns within BC. Type 3 included H-square within RB and V-square within CB. Type 4 combined all, revealing six sources in total. Although not all additional sources were statistically significant, variations such as treatment, row, subzone, row block, H-square within RB, and V-square within CB showed statistical significance. Model demonstrated the enhancement of their analytical capability to estimate the effects of these additional sources. The varying number of additional sources identified by each model highlighted the flexibility and robustness of the Sudoku square design in capturing complex effects in the experiment.
Keywords: Latin square design, row column design, rectangular subzone, sudoku square design