چكيده فارسي :
Rice agriculture plays an important role in the country’s economy. Rice is the main
foodstuff for about half of the world s population. For the last decades, rice consumption
has been expanding beyond the traditional rice-grown areas particularly in Asia and
Europe [1]. Many of the traditional methods of analysis for determining the physical,
chemical and mechanical properties to ensure the quality of rice are time consuming,
destructive, require expensive harmful reagents [2]. The desire is to replace the
traditional methods to find its quality with rapid, non-destructive, noninvasive methods.
for this purpose, four kinds of rice were selected from the agricultural lands in the
tonekabon in the north of Iran. Ten samples from each kind of rice were prepared. The
objective of this study is to classify rice samples based on the fingerprints of the IR
region by using the Infrared Spectroscopy (IRs). Therefore, thirty spectra were recorded
such as ten samples with three replicates. IR spectra were taken on every four kinds of
rice in the range of 400 to 4000 cm-1. All the spectral data were processed statistically
and resulting, the rice samples were classified using Principle Component Analysis
(PCA). Application of principal component analysis (PCA) to our experimental data
resulted in satisfactory classifications for all kinds of rice. Rice samples were effectively
distinguished in four discrete groups.
