Bhartiya Krishi Anusandhan Patrika, volume 33 issue 3 (september 2018) : 218-220

Balanced designs for comparing test products with two controls in sensory trials

Sumeet Saurav, Cini Varghese, Mohd Harun, Seema Jaggi, Devendra Kumar
1<p>ICAR-Indian Agricultural Statistics Research Institute, PUSA, New Delhi-&nbsp;110 012, India</p>
Cite article:- Saurav Sumeet, Varghese Cini, Harun Mohd, Jaggi Seema, Kumar Devendra (NaN). Balanced designs for comparing test products with two controls in sensory trials . Bhartiya Krishi Anusandhan Patrika. 33(3): 218-220. doi: 10.18805/BKAP122.

Sensory trials are an integral part of food and nutrition experiments involving agricultural/animal produce to demonstrate some sensory fact. To draw definite conclusion from the study, it is important to eliminate or minimize all sources of error, and recognize and control all factors that may influence or interfere with the result. In addition to various potential sources associated with the preparation of the test products, there may be variability due to measurement or assessment process, order effects, carryover effects, assessor fatigue etc. Sometimes, designs are required which can provide higher precision estimates for the crucial product comparisons, at the cost of the comparisons which are of lesser interest, and will be estimated with lower precision. One situation where there is special interest in a subset of product contrasts arises when control products are included in the trial. A control product provides a calibration standard, which can serve as a basis for comparison of results across studies may be helpful to the panel. Here, a series of treatment vs. control designs for multi-session trials are obtained to deal with such situations.


  1. Aggarwal, M.L., Deng, L.Y. and Jha, M.K. (2004). Some new residual treatment effects designs for comparing test treatments with a control. Journal of Applied Statistics, 31 (9), 1065-1081.

  2. Aggarwal, M.L. and Jha, M.K. (2009). Constructions of residual treatment effects designs for comparing test treatments with a control. Communications in Statistics- Theory and Methods, 38(15), 2567-2577.

  3. Hedayat, A.S., Jacroux, M. and Majumdar, D. (1988). Optimal designs for comparing test treatments with a control. Statistical Science, 3, 363-370. 

  4. Hedayat, A.S. and Yang, M. (2005). Optimal and efficient crossover designs for comparing test treatments with a control treatment. Annals of Statistics, 33(2), 915-943.

  5. Hedayat, A.S. and Yang, M. (2006). Efficient crossover designs for comparing test treatments with a control treatment. Discrete Mathematics, 306, 3112-3124.

     

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