Classification and Quality Analysis of Rice Grain Based on Dimensional Measurement During Hydrothermal Treatment

Classification and Quality Analysis of Rice Grain Based on Dimensional Measurement During Hydrothermal Treatment
  IJETT-book-cover           
  
© 2021 by IJETT Journal
Volume-69 Issue-8
Year of Publication : 2021
Authors : Suman Kumar Bhattacharyya, Sagarika Pal, Subrata Chattopadhyay
DOI :  10.14445/22315381/IJETT-V69I8P218

How to Cite?

Suman Kumar Bhattacharyya, Sagarika Pal, Subrata Chattopadhyay, "Classification and Quality Analysis of Rice Grain Based on Dimensional Measurement During Hydrothermal Treatment," International Journal of Engineering Trends and Technology, vol. 69, no. 8, pp. 145-154, 2021. Crossref, https://doi.org/10.14445/22315381/IJETT-V69I8P218

Abstract
The shape and dimensional appearance of rice kernels have a significant role in their classification. In this research, various dimensional parameters of rice grain have been measured and analyzed for their gradation using the Decision Tree Learning model, and also the grain samples have been treated through a typical Hydrothermal method for determining the characteristics related to its quality. Image processing techniques have been used for such measurement, and eight Indian rice varieties with low to high amylose content (15%–28% d.b.) have been chosen for the experimentation. Dimensional changes of rice kernel during Hydrothermal treatment have been modeled mathematically, and from the model equation, a new parameter termed the average logistic growth rate (KAvg ) has been obtained. It has been observed that the average logistic growth rate of the rice kernel is negatively correlated with its amylose content (Correlation coefficient -0.9618) and cooking time for food preparation (Correlation coefficient -0.9499), indicating a strong relationship with rice quality. All the experimental observations finally confirm that the combined Decision Tree Learning model and the mathematical model of rice grain growth during Hydrothermal treatment for grain quality analysis is a novel idea for getting a more precise classification of rice.

Keywords
Classification by Decision Tree Learning model, Dimensional changes of rice, Hydrothermal treatment, Logistic growth rate, Mathematical model.

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