Signal Processing Strategies in FT-NIR and FTIR Spectra of Palm Oils
In the palm oil industry, iodine value (IV) has become an important parameter in quality control that measures the degree of unsaturation of the oils. However, it is difficult to obtain the IV chemically. In other hand, the use of instrumental analysis in IV determination accurately needs suita...
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| Main Authors: | , , , , |
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| Format: | Proceeding |
| Language: | English |
| Published: |
IEEE
2014
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/4438/1/Nor%20Fazila.pdf http://ir.unimas.my/id/eprint/4438/ http://10.1109/CSPA.2014.6805728 |
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| Summary: | In the palm oil industry, iodine value (IV)
has become an important parameter in quality control
that measures the degree of unsaturation of the oils.
However, it is difficult to obtain the IV chemically. In
other hand, the use of instrumental analysis in IV
determination accurately needs suitable data preprocessing.
In this study, we proposed the strategy for
pre-processing the FT-NIR and FTIR spectra data in
analyzing the IV of non-fried and fried palm oils. The
utility and effectiveness of four data pre-processing
which are column standardization, mean centre and
combination of row scaling with column
standardization and mean centre were applied. The
effect of data splitting methods which are duplex and
kenstone was also investigated in the Partial Least
Squares (PLS) regression model of palm oils. From the
result, the use of different data pre-processing provides
different quality of prediction model. Either the
application of the row scaling and column scaling
individually or combination of both methods may
improve the quality of the model. It is concluded that
the data pre-processing is context dependent which is
depend on the nature of the dataset and there can be no
single method for general use. |
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