“Popular field designs used in plant breeding” ( Seminar Synopis)

 

UNIVERSITY OF AGRICULTURAL SCIENCES, BANGALORE

DEPARTMENT OF GENETICS AND PLANT BREEDING

Seminar - GPB 682 (0+1)

“Popular field designs used in plant breeding”

Experimental design plays a crucial role in agricultural research by ensuring reliable results, minimizing experimental error, and enabling valid statistical inferences. The history of experimental design traces back to James Lind’s scurvy experiment (1747) and the pioneering contributions of Sir R.A. Fisher (1926, 1935), who established statistical methods for field trials. Experimental design aims to reduce soil heterogeneity, partition total variation, and test treatment significance effectively.

The basic principles—replication, randomization, and local control—form the foundation for enhancing experimental precision. Basic designs like Completely Randomized Design (CRD), Randomized Complete Block Design (RCBD), and Latin Square Design (LSD) are simple and widely used but suited mainly for limited treatments and homogeneous fields. More advanced designs include Split Plot Design (SPD) for multifactorial experiments, Lattice Design (LD) for handling large numbers of treatments, and Augmented Design (AD) for evaluating unreplicated germplasm lines alongside checks. Special designs like the Honeycomb Design (Fasoulas, 1973) enable competition-free evaluation in self-pollinated crops, while Grid Design (Gardner, 1961) improves mass selection by dividing fields into small, uniform strata. Together, these designs ensure reliability, reduce bias, and maximize genetic gain in crop improvement programs.

In wheat, Redhu et al. (2025) demonstrated that Alpha Lattice Design improved precision by 24% over RCBD in identifying heat-resilient genotypes. Saba et al. (2017) used the Augmented Design in common bean germplasm evaluation, where principal component analysis revealed key traits linked to maturity and productivity. Katsileros et al. (2023) showcased the utility of the Honeycomb Design with the introduction of the rhoneycomb R package, which enables construction, visualization, and analysis of honeycomb field trials for precise single-plant selection.

Experimental designs are indispensable in plant breeding for ensuring precision, reliability, and unbiased selection. Each design has unique applications, and the choice depends on crop type, field variability, number of treatments, and breeding objectives. Advanced designs like lattice, honeycomb, and augmented designs are especially valuable for handling large populations and environmental heterogeneity, ultimately accelerating crop improvement programs.

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REFERENCES:

1. Redhu, M., Singh, V., Nimbal, S., Niwas, R., Yashveer, S., Langaya, S., Shehrawat, S., Chawla, R., Rahimi, M., Dhukia, M., and Aman. (2025). Assessing alpha lattice design for heat stress indices and yield stability in wheat genotypes. Sci. Rep., 15(1):27738.

2. Saba, I., Sofi, P.A., Zeerak, N.A., Mir, R.R., and Gull, M. (2017). Using augmented design for evaluation of common bean (Phaseolus vulgaris L.) germplasm. Int. J. of Curr. Microbiol. Appl. Sci., 6(7):246-254.

3. Katsileros, A., Antonetsis, N., Gkika, M.G., Tani, E., Tokatlidis, I., and Bebeli, P.J. (2023). rhoneycomb: An R package for the construction and analysis of honeycomb selection designs. Softw. Impacts., 16:100490.

4. Singh, P., and Narayanan, S.S. (1993). Biometrical Techniques in Plant Breeding. New Delhi, India: Kalyani Publishers.