TY - GEN
T1 - Rice Grain Quality Determination Using FTIR Spectroscopy Method
AU - Prihasty, Wilda
AU - Nasution, Aulia M.T.
AU - Isnaeni,
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/5
Y1 - 2020/5
N2 - Indonesia is the third world's largest rice producer, which has wide variety of types and qualities of rice. Based on SNI 6128:2015, rice quality can be classified based on the form, colour and moisture content of the rice grain. On the other hand, rice is consumed to fulfill the nutritional needs of the body. So, it is important to know the type of rice which provide best nutrient content. In this paper, we report preliminary research to predictively determine the quality of rice based on amylose phenolic and flavonoid content measured using FTIR Spectroscopy technique. Chemical analysis method was used as a validation to this developed predictive system. Partial Least Square (PLS) were used to determine the levels of amylose, phenolic, and flavonoids of rice and the Principal Component Analysis (PCA) methods for clustering the types and quality of rices. Results showed that the coefficient of determination of the proposed prediction system of amylose content, phenolic and flavonoids were 0.95; 0.86; 0.95, respectively, with respective RMSE value were 1.4; 0.72; 0.44. Using this technique, rice samples used can be classified into three class of quality, i.e, high quality, premium quality, and the medium quality rice.
AB - Indonesia is the third world's largest rice producer, which has wide variety of types and qualities of rice. Based on SNI 6128:2015, rice quality can be classified based on the form, colour and moisture content of the rice grain. On the other hand, rice is consumed to fulfill the nutritional needs of the body. So, it is important to know the type of rice which provide best nutrient content. In this paper, we report preliminary research to predictively determine the quality of rice based on amylose phenolic and flavonoid content measured using FTIR Spectroscopy technique. Chemical analysis method was used as a validation to this developed predictive system. Partial Least Square (PLS) were used to determine the levels of amylose, phenolic, and flavonoids of rice and the Principal Component Analysis (PCA) methods for clustering the types and quality of rices. Results showed that the coefficient of determination of the proposed prediction system of amylose content, phenolic and flavonoids were 0.95; 0.86; 0.95, respectively, with respective RMSE value were 1.4; 0.72; 0.44. Using this technique, rice samples used can be classified into three class of quality, i.e, high quality, premium quality, and the medium quality rice.
KW - FTIR Spectroscopy
KW - Partial Least Square
KW - Principal Component Analysis
KW - Rice Grain Quality
UR - http://www.scopus.com/inward/record.url?scp=85093932121&partnerID=8YFLogxK
U2 - 10.1109/ICP46580.2020.9206464
DO - 10.1109/ICP46580.2020.9206464
M3 - Conference contribution
AN - SCOPUS:85093932121
T3 - 2020 IEEE 8th International Conference on Photonics, ICP 2020
SP - 38
EP - 39
BT - 2020 IEEE 8th International Conference on Photonics, ICP 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th IEEE International Conference on Photonics, ICP 2020
Y2 - 16 May 2020 through 18 May 2020
ER -