Screening Malaysian edible bird’s nests for structural adulterants and geographical origin using Mid-Infrared – Attenuated Total Reflectance (MIR-ATR) spectroscopy combined with chemometric analysis by Data-Driven – Soft Independent Modelling of Class Analogy (DD-SIMCA)

Machine learning applications for multi-source data of edible crops: A review of current trends and future prospects

The quality and safety of edible crops are key links inseparable from human health and nutrition. In the era of rapid development of artificial intelligence, using it to mine multi-source information on edible crops provides new opportunities for industrial development and market supervision of edible crops. This review comprehensively summarized the applications of multi-source data combined with machine learning in the quality evaluation of edible crops. Multi-source data can provide more comprehensive and rich information from a single data source, as it can integrate different data information. Supervised and unsupervised machine learning is applied to data analysis to achieve different requirements for the quality evaluation of edible crops. Emphasized the advantages and disadvantages of techniques and analysis methods, the problems that need to be overcome, and promising development directions were proposed. To monitor the market in real-time, the quality evaluation methods of edible crops must be innovated.

Rapid and nondestructive identification of adulterate capsules by NIR spectroscopy combined with chemometrics

This study aims to develop a rapid and non-destructive method to identify counterfeit and substandard drugs, addressing the critical need for better quality control in drug production. According to the reasons for counterfeit products in actual production, the commonly used solid preparation excipients such as HPMC, MCC, Mg-St and Pregelatinized Starch, as well as three chemical drugs with similar efficacy to Guizhi-Fuling (GZFL) Capsule as adulterants, including Aspirin, Ibuprofen and Sinomenine Hydrochloride were selected and designed as adulteration samples with different levels of adulteration. NIR spectra were collected in a non-invasive mode and analyzed by one-class classification methods. The feasibility of using Near-infrared (NIR) spectroscopy as a detection method to qualitatively identify adulterated samples was explored at three packaging levels of powder, intact capsules and capsules in PVC. The differences between the samples were analyzed by NIR spectra comparison, cluster analysis and principal component analysis. The performance of SVM, OCPLS and DD-SIMCA models in dealing with the authentication of genuine and counterfeit products was established and compared. The results show that the spectra contain sample information and the adulterated samples could be discriminated correctly by established models. Moreover, applying appropriate spectral preprocessing methods can further improve the model's performance. In addition, a PLS regression model was developed to predict the adulteration levels of the three packing level samples, which yielded satisfactory results. This study highlights the potential of NIR spectroscopy combined with Chemometrics as a rapid and non-destructive testing analysis method to accurately identify counterfeit and substandard drugs, thereby ensuring drug quality.

Investigation of Structural Characteristics and Solubility Mechanism of Edible Bird Nest: A Mucin Glycoprotein

In this study, the possible solubility properties and water-holding capacity mechanism of edible bird nest (EBN) were investigated through a structural analysis of soluble and insoluble fractions. The protein solubility and the water-holding swelling multiple increased from 2.55% to 31.52% and 3.83 to 14.00, respectively, with the heat temperature increase from 40 °C to 100 °C. It was observed that the solubility of high-Mw protein increased through heat treatment; meanwhile, part of the low-Mw fragments was estimated to aggregate to high-Mw protein with the hydrophobic interactions and disulfide bonds. The increased crystallinity of the insoluble fraction from 39.50% to 47.81% also contributed to the higher solubility and stronger water-holding capacity. Furthermore, the hydrophobic interactions, hydrogen bonds, and disulfide bonds in EBN were analyzed and the results showed that hydrogen bonds with burial polar group made a favorable contribution to the protein solubility. Therefore, the crystallization area degradation under high temperature with hydrogen bonds and disulfide bonds may be the main reasons underlying the solubility properties and water-holding capacity of EBN.

Adulteration Detection of Edible Bird’s Nests Using Rapid Spectroscopic Techniques Coupled with Multi-Class Discriminant Analysis

Edible bird’s nests (EBNs) are vulnerable to adulteration due to their huge demand for traditional medicine and high market price. Presently, there are pressing needs to explore field-deployable rapid screening techniques to detect adulteration of EBNs. The objective of this study is to explore the feasibility of using a handheld near-infrared (VIS/SW-NIR) spectroscopic device for the determination of EBN authenticity against the benchmark performance of a benchtop mid-infrared (MIR) spectrometer. Forty-nine authentic EBNs from the different states in Malaysia and 13 different adulterants (five types) were obtained and used to simulate the adulteration of EBNs at 1, 5 and 10% adulteration by mass (a total of 15 adulterated samples). The VIS/SW-NIR and MIR spectra collated were subsequently processed, modelled and classified using multi-class discriminant analysis. The VIS/SW-NIR results showed 100% correct classification for the collagen and nutrient agar classes in authenticity classification, while for the other classes, the lowest correct classification rate was 96.3%. For MIR analysis, only the karaya gum class had 100% correct classification whilst for the other four classes, the lowest rate of correct classification was at 94.4%. In conclusion, the combination of spectroscopic analysis with chemometrics can be a powerful screening tool to detect EBN adulteration.

One-class classification of special agroforestry Brazilian coffee using NIR spectrometry and chemometric tools

The near-infrared spectrometry combined with the one-class classification method was applied as quality control of the agroforestry-grown specialty coffee. A total of 34 samples were analyzed in this study. Spectral data were obtained using a NIR portable and different pre-treatment strategies for baseline correction were evaluated. Unsupervised pattern recognition (PCA and HCA) techniques were performed. The construction of the classification model was carried out using the dd-SIMCA algorithm with 19 samples acquired directly from producers that are recognized for the best quality control of the specialty type coffee. In order to test the model, 15 samples of non-specialty type, obtained in local markets, were evaluated. The classification model with the highest correct classification rate (CCR) scored 100% and 87% in the validation and test groups, respectively. The results demonstrated that the application of this strategy was successful in verifying the authenticity of specialty type agroforestry-grown coffee samples.

A comprehensive review of edible bird's nest

Edible bird's nest (EBN) is built by seven species of Aerodramus and Collocalia (Apodidae), using salivary gland secretion mixed with feathers or grass during the breeding. Its rich nutritional values such as anti-aging activity, immunomodulatory and antioxidant activity make consumers flock to it. Consumers' pursuit, on the one hand, aroused the arrogance of counterfeiters, which eventually leads to food safety problems. On the other hand, it promotes the in-depth studies of EBN in all aspects, such as compositions, biological activities, authenticity identification, quality control, and so on. This paper presented the origins and classifications of EBN and the current situation of EBN industry in detail; reviewed the nutritional compositions, pharmacological actions, identification, inspection and content determination of EBN comprehensively; and prospected the future research directions to provide suggestions for the further study.