Differentiation unclean and cleaned edible birds nest using multivariate analysis of amino acid composition data

Lee Chia Hau, . and Lee Ting Hun, . and Norfadilah Hamdan, . and Cheng Kian Kai, . and Nurul Alia Azmi, . Differentiation unclean and cleaned edible birds nest using multivariate analysis of amino acid composition data. pp. 677-691. ISSN 2231-8526

Edible Birds Nest (EBN) has been used as a health modulator for many centuries. Nutrient degradation in EBN always happen during cleaning process due to many factors such as temperature and long soaking time in water. The present study attempts to find the difference between unclean and cleaned EBN in their amino acid composition. A total of 65 EBN samples were collected directly from swiftlet premises in 13 states of Malaysia to ensure the coverage of geographical location differences. A standardized cleaning method had been adapted from the industry to clean the collected EBN sample in the lab. Then it was analysed for amino acids composition. After that OPLS-DA multivariate model was used to discriminate the unclean and cleaned EBN on 18 types of amino acids composition. The model was robust with classification and predictive ability of 76.1 and 64.5 respectively. The model was further validated with sample blind test and 100 of the sample was accurately fall into their respective cluster unclean and cleaned EBN. The findings suggest that three major amino acids with the highest VIP value were Aspartic acid Methionine and Glutamic acid and proposed as the marker for discriminating the unclean and cleaned EBN.

Full text available from: Official URL: http://www.pertanika.upm.edu.my/resources/files/Pe...

Abstract

Edible Birds Nest (EBN) has been used as a health modulator for many centuries. Nutrient degradation in EBN always happen during cleaning process due to many factors such as temperature and long soaking time in water. The present study attempts to find the difference between unclean and cleaned EBN in their amino acid composition. A total of 65 EBN samples were collected directly from swiftlet premises in 13 states of Malaysia to ensure the coverage of geographical location differences. A standardized cleaning method had been adapted from the industry to clean the collected EBN sample in the lab. Then it was analysed for amino acids composition. After that OPLS-DA multivariate model was used to discriminate the unclean and cleaned EBN on 18 types of amino acids composition. The model was robust with classification and predictive ability of 76.1 and 64.5 respectively. The model was further validated with sample blind test and 100 of the sample was accurately fall into their respective cluster unclean and cleaned EBN. The findings suggest that three major amino acids with the highest VIP value were Aspartic acid Methionine and Glutamic acid and proposed as the marker for discriminating the unclean and cleaned EBN.

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Item Type:	Article
AGROVOC Term:	Bird nests
AGROVOC Term:	Chemical analysis (results)
AGROVOC Term:	Statistical analysis
AGROVOC Term:	Cleaning
AGROVOC Term:	Chemical composition
AGROVOC Term:	Amino acids
AGROVOC Term:	Aspartic acid
AGROVOC Term:	Methionine
AGROVOC Term:	Glutamic acid
AGROVOC Term:	Product quality
Depositing User:	Mr. AFANDI ABDUL MALEK
Last Modified:	24 Apr 2025 00:55
URI:	http://webagris.upm.edu.my/id/eprint/9526

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