Differentiation of L-Cysteine sources using spectral analysis and amino acids analysis /
L-cysteine is a food additive that is used in bakery ingredients. It is used as a stabilizer to soften the texture of bakery dough. However, L-cysteine's primary sources could be derived from animal and human parts, which lead to non-halal food sources. Five samples of pig bristle, human hair,...
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| Format: | Thesis Book |
| Language: | English |
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| Online Access: | http://studentrepo.iium.edu.my/handle/123456789/11197 |
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| Summary: | L-cysteine is a food additive that is used in bakery ingredients. It is used as a stabilizer to soften the texture of bakery dough. However, L-cysteine's primary sources could be derived from animal and human parts, which lead to non-halal food sources. Five samples of pig bristle, human hair, duck feather, chicken feather and cow horn, were extracted with 6M HCI and freeze-dried into a powder form. One gram of L-cysteine powder form from five different samples was analyzed using spectral fingerprinting profile and chromatography separation analysis. Spectral fingerprinting profile of L-cysteine sources was obtained by using combination of Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) and Raman spectroscopy. Meanwhile, the amino acid content of L-cysteine sources was analyzed through amino acid analysis (AAA) by ultra-high performance liquid chromatography (UHPLC). The result found that the ATR-FTIR is preferable as a fingerprinting tool rather than Raman spectroscopy in differentiating L-cysteine's primary sources. This is because the infrared ray can capture and compare the spectral fingerprinting profile of L-cysteine sources compare to Raman spectroscopy. Precisely, ATR-FTIR was able to differentiate the samples by the presence of dominant Amide I band at the wavenumber region between 1800 cm-1 - 1250 cm-1. Data pre-treatment by using KMO test, Barlett test and eigen value were carried out to determine data reliability. Five distinct groups were successfully differentiated in PCA. Accordingly, the amino acid content of L-cysteine sources was analyzed through AAA. The result showed that 17 amino acids concentration were successfully separated and identified in all five samples. The data also proved that human hair had the highest L-cysteine concentration compared to other samples. The separation of 17 amino acids by AAA lead to further identification of specific biomarker compounds. By using AAA data, all samples were successfully separated into different clusters with PCA aid. Based on the variable maximum rotation diagram, lysine to L-cystine ratio (LYS/CYS) was the only ratio located at the pig bristles cluster. In conclusion, ATR-FTIR and UHPLC have successfully differentiated L-cysteine sources through spectral fingerprinting profile and AAA, respectively. The initial screening through ATR-FTIR can interpret and differentiate L-cysteine origin sources through spectral fingerprinting profile. In fact, the implementation of diagnostic ratio as sample differentiation is another promising analytical approach for biomarker compounds. Therefore, this study could be used on an industrial scale to create a database and detect L-cysteine origin sources in commercial products. |
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| Item Description: | Abstracts in English and Arabic.
"A thesis submitted in fulfilment of the requirement for the degree of Master of Science (Halal Industry Sciences)." --On title page. |
| Physical Description: | xvi, 83 leaves : illustrations ; 30cm. |
| Bibliography: | Includes bibliographical references (leaves 68-74). |