Geographical origin discrimination of edible bird’s nests using smart handheld device based on colorimetric sensor array

Portable and miniature sensors in supply chain for food authentication: a review

Food fraud, a pervasive issue in the global food industry, poses significant challenges to consumer health, trust, and economic stability, costing an estimated $10-15 billion annually. Therefore, there is a rising demand for developing portable and miniature sensors that facilitate food authentication throughout the supply chain. This review explores the recent advancements and applications of portable and miniature sensors, including portable/miniature near-infrared (NIR) spectroscopy, e-nose and colorimetric sensors based on nanozyme for food authentication within the supply chain. After briefly presenting the architecture and mechanism, this review discusses the application of these portable and miniature sensors in food authentication, addressing the challenges and opportunities in integrating and deploying these sensors to ensure authenticity. This review reveals the enhanced utility of portable/miniature NIR spectroscopy, e-nose, and nanozyme-based colorimetric sensors in ensuring food authenticity and enabling informed decision-making throughout the food supply chain.

An investigation of heavy metals in edible bird's nest from Indonesia using inductively coupled plasma mass spectrometry

Background and Aim:

In 2020, Indonesia, which has the highest global production of edible bird’s nest (EBNs), exported up to 1312.5 tons of this product at a value of USD 540.4 million. Recently, food safety aspects related to EBNs, including contamination with heavy metals, have become a serious concern. However, data on the presence and concentration of heavy metals in EBNs in Indonesia are not yet available. This study aimed to determine and compare the presence and concentrations of arsenic (As), mercury (Hg), lead (Pb), cadmium (Cd), and tin (Sn) in EBNs originating from several primary Indonesian islands. The study also analyzed the effect of washing on the heavy metal content in EBNs.

Materials and Methods:

A study on 44 swiftlet farmhouses (SFHs) was conducted to determine the concentrations of heavy metals in EBNs. The number of samples from the SFHs was allocated proportionally to the main EBN-producing islands in Indonesia, that is, Kalimantan, Sumatera, Sulawesi, and Java (22, 13, 7, and 2, respectively). The concentrations of the above five elements in the samples before washing (raw–unclean EBNs) and after washing (raw–clean EBNs) were determined by inductively coupled plasma mass spectrometry. Washing was conducted according to the general procedures at an EBN processing plant.

Results:

The raw–unclean EBNs from the four islands contained As, Pb, Cd, and Sn at varying concentrations. However, Hg was not detected in the raw–unclean EBN samples from Sulawesi. The raw–unclean EBNs from Kalimantan had lower concentrations of Pb and Cd compared with the other islands. The concentrations of As, Pb, Cd, and Sn in the EBNs decreased significantly after washing with clean water.

Conclusion:

Heavy metals (As, Hg, Pb, Cd, and Sn) were detected at a low level in most of the raw–unclean EBNs originating from the main Indonesian island where they were produced. The concentrations of all the heavy metals reviewed in the raw–unclean EBNs samples decreased significantly after washing.

Why the importance of geo-origin tracing of edible bird nests is arising?

Edible bird's nest (EBN) swiftlet existed naturally 48,000 years ago in caves as their natural dwellings. Nowadays, edible bird's nest has become a very important industry due to its high nutritional, medicinal and economic value. Additionally, edible bird's nest has a long quality guarantee period. Obviously, the nutritional components and medicinal functions vary depending on geographical origins. Recently, the global demand for edible bird's nest has markedly increased, accompanied by the increasing attention of all key players of the global food trade system, i.e., producers, consumers, traders and the authorities to obtain safe and high-quality edible bird's nest. Hence, this target can be accomplished via the enforcement of an efficient and universal geo-tracing technique. Current methods of the geo-tracking of edible bird's nest, i.e., automation, physical and analytical techniques have several limitations and all of them fail to discriminate different quality grades of edible bird's nest. Meanwhile, in many studies and applications, polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) has proven to be a "cutting edge" technique for greatly enhance food traceability from field to fork through its ability in distinguishing the food products in terms of their quality and safety. This article provides an overview of (1) edible bird's nest as a multiuse strategic food product, (2) quality issues associated with edible bird's nest including implications that the site of acquisition of the edible bird's nest has food safety implications, (3) current regulations and geo-tracking approaches to ensure the safety and quality of edible bird's nest with the special focus on polymerase chain reaction-denaturing gradient gel electrophoresis technique as a vigorous and universal geo-tracing tool to be suggested for edible bird's nest geo-traceability.

Discrimination of rice varieties using smartphone-based colorimetric sensor arrays and gas chromatography techniques

A smartphone-based colorimetric sensor array system was established for discrimination of rice varieties having different geographical origins. Purposely, aroma profiling of nine rice varieties was performed using solid-phase microextraction gas chromatography-mass spectrometry. Alcohols, aldehydes, alkanes, ketones, heterocyclic compounds, and organic acids represent the abundant compounds. Colorimetric sensor array system produced a characteristic color difference map upon its exposure to volatile compounds of rice. Discrimination of rice varieties was subsequently achieved using principal component analysis, hierarchical clustering analysis, and k-nearest neighbors. Rice varieties from same geographical source were clustered together in the scatter plot of principal component analysis and hierarchical clustering analysis dendrogram. The k-nearest neighbors algorithm delivered optimal results with discrimination rate of 100% for both calibration and prediction sets using sensor array system. The smartphone-based colorimetric sensor array system and gas chromatography technique were able to effectively differentiate rice varieties with the advantage of being simple, rapid, and low-cost.

Review of sialic acid's biochemistry, sources, extraction and functions with special reference to edible bird's nest

Sialic acids are a group of nine-carbon α-keto acids. Sialic acid exists in more than 50 forms, with the natural types discovered as N-acetylneuraminic acid (Neu5Ac), deaminoneuraminic acid (2-keto-3-deoxy-nonulononic acid or Kdn), and N-glycolylneuraminic acid (Neu5Gc). Sialic acid level varies depending on the source, where edible bird's nest (EBN), predominantly Neu5Ac, is among the major sources of sialic acid. Due to its high nutritive value and complexity, sialic acid has been studied extensively through acid, aqueous, and enzymatic extraction. Although detection by chromatographic methods or mass spectrometry is common, the isolation and recovery work remained limited. Sialic acid is well-recognised for its bioactivities, including brain and cognition development, immune-enhancing, anti-hypertensive, anticancer, and skin whitening properties. Therefore, sialic acid can be used as a functional ingredient in the various industries. This paper reviews the current trend in the biochemistry, sources, extraction, and functions of sialic acids with special reference to EBN.

Geographical Factor Influences the Metabolite Distribution of House Edible Bird's Nests in Malaysia

Background: Edible Bird's Nest (EBN) is famously consumed as a food tonic for its high nutritional values with numerous recuperative and therapeutic properties. EBN is majority exploited from swiftlet houses but the differences in terms of metabolite distribution between the production site of house EBN is not yet fully understood. Therefore, this study was designed to identify the metabolite distribution and to determine the relationship pattern for the metabolite distribution of house EBNs from different locations in Malaysia. Methods: The differences of metabolite distribution in house EBN were studied by collecting the samples from 13 states in Malaysia. An extraction method of eHMG was acquired to extract the metabolites of EBN and was subjected to non-targeted metabolite profiling via liquid chromatography-mass spectrometry (LC-MS). Unsupervised multivariate analysis and Venn diagram were used to explore the relationship pattern among the house EBNs in Malaysia. The geographical distribution surrounded the swiftlet house was investigated to understand its influences on the metabolite distribution. Results: The hierarchical clustering analysis (HCA) combined with correlation coefficient revealed the differences between the house EBNs in Malaysia with four main clusters formation. The metabolites distribution among these clusters was unique with their varied combination of geographical distribution. Cluster 1 grouped EBNs from Selangor, Melaka, Negeri Sembilan, Terengganu which geographically distributed with major oil palm field in township; Cluster 2 included Perak and Sarawak with high distribution of oil palm in higher altitude; Cluster 3 included Perlis, Kelantan, Kedah, Penang from lowland of paddy field in village mostly and Cluster 4 grouped Sabah, Pahang, Johor which are majorly distributed with undeveloped hills. The metabolites which drove each cluster formation have happened in a group instead of individual key metabolite. The major metabolites that characterised Cluster 1 were fatty acids, while the rest of the clusters were peptides and secondary metabolites. Conclusion: The metabolite profiling conducted in this study was able to discriminate the Malaysian house EBNs based on metabolites distribution. The factor that most inferences the differences of house EBNs were the geographical distribution, in which geographical distribution affects the distribution of insect and the diet of swiftlet.