Physical Properties of Fresh Paddy (Oryza sativa) Cultivar MR297
Jhauharotul Muchlisyiyah (a,b), Rosnah Shamsudin (a,c,*), Roseliza Kadir Basha (a), Radhiah Shukri (d), and Syahmeer How (a)

a) Department of Process and Food Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia
b) Department of Food Science and Biotechnology, Faculty of Agricultural Technology, Universitas Brawijaya, Jalan Veteran Malang, 65145, Indonesia
c) Laboratory of Halal Science Research, Halal Products Research Institute, Universiti Putra Malaysia, Putra Infoport, 43400 Serdang, Selangor, Malaysia
d) Department of Food Technology, Faculty of Food Science and Technology, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia

Email corresponding author: rosnahs[at]upm.edu.my

Abstract

An examination of the physical attributes of Fresh Harvested Paddy (Oryza sativa) MR297 is crucial in designing a post-harvest system that integrates sorting, cleaning, drying, milling, and storage. In this study, the length, width, thickness, arithmetic mean diameter (Da), geometric mean diameter (Dg), equivalent diameter (De), true volume, calculated volume, surface area, projected areas (PAL, PAW, PAT), criteria projected area (CPA), true density, and bulk density of MR297 fresh paddy were measured to estimate the mass of MR 297 fresh paddy using sigmoid, power, linear, and quadratic functions. This study was performed at 17.5 % of moisture content. The models with the highest coefficient of determination (R^2) and lowest standard error of estimate (SEE) were recommended. Based on the observations, quadratic models became the best fit for mass prediction based on several physical parameters. However, the highest R^2 of the mass prediction was obtained by a model which utilized the calculated volume Y= 0.02766 + 0.00022 Vc with R^2=0.9770. Measuring three different axes toward the best-fitted model would still be required. For a model based on one single axis, the quadratic model with thickness is recommended for mass prediction (R^2 = 0.9665). The information obtained from this study will be useful in improving MR297 fresh paddy post-harvest handling.

Keywords: Mass modeling, MR297 paddy, Physical properties, Prediction

Topic: Agricultural product technology