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Related Concept Videos

Response Surface Methodology01:16

Response Surface Methodology

81
Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
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Standardization and characterization of Mohanthal using response surface methodology.

M B Chaudhary1,2, K Jayaraj Rao2, Ankit Bihola3

  • 1School of Animal, Poultries and Fisheries Science, ICAR-Indian Agricultural Research Institute, Gogamukh, Assam, India.

Scientific Reports
|May 20, 2025
PubMed
Summary

This study optimized Mohanthal, a traditional Indian sweet, using Response Surface Methodology. The standardized formulation ensures consistent quality and flavor, paving the way for commercial production.

Keywords:
GheeMohanthalCentral composite designKhoa

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Area of Science:

  • Food Science and Technology
  • Traditional Indian Sweets
  • Ingredient Optimization

Background:

  • Mohanthal, a popular Indian sweet, suffers from inconsistent quality due to a lack of standardized preparation methods.
  • This variability impedes large-scale production and commercialization of this culturally significant dessert.

Purpose of the Study:

  • To optimize the ingredient formulation of Mohanthal using Response Surface Methodology (RSM).
  • To ensure consistent quality, texture, and flavor while preserving the traditional essence of Mohanthal.
  • To establish a scientifically validated and scalable production method.

Main Methods:

  • Response Surface Methodology (RSM) with a Central Composite Design (CCD) was employed.
  • Experiments evaluated the impact of varying ghee, khoa, and sugar levels on sensory, textural, and color attributes.
  • Chickpea flour quantity was maintained constant at 100g.

Main Results:

  • An optimized formulation was determined: 103.13g ghee, 27.70g khoa, 98.24g sugar, and 100g chickpea flour.
  • The optimized formulation yielded superior sensory and textural characteristics, including enhanced flavor, color, and consistency.
  • Developed quadratic models showed high predictive accuracy (R² > 0.90) for key attributes.

Conclusions:

  • The study successfully developed a standardized and optimized formulation for Mohanthal.
  • This research bridges traditional practices with modern food technology, enabling consistent quality control.
  • The findings support the scalability and commercialization potential of Mohanthal production.