Machine Learning-Based Analytical Systems: Food Forensics

An Encyclopedic Compendium on Chemosensing Supramolecular Metal-Organic Gels

Chemosensing, an interdisciplinary scientific domain, plays a pivotal role ranging from environmental monitoring to healthcare diagnostics and (inter)national security. Metal-organic gels (MOGs) are recognized for their stability, selectivity, and responsiveness, making them valuable for chemosensing applications. Researchers have explored the development of MOGs based on different metal ions and ligands, allowing for tailored properties and sensitivities, and have even demonstrated their applications as portable sensors such as paper-based test strips for practical use. Herein, several studies related to MOGs development and their applications in the chemosensing field via UV-visible or luminance along with electrochemical approach are presented. These papers explored MOGs as versatile materials with their use in sensing bio or environmental analytes. This review provides a foundational understanding of key concepts, methodologies, and recent advancements in this field, fostering the scientific community.

Development of chemometric-assisted supercritical fluid extraction of effective and natural tyrosinase inhibitor from Syzygium aqueum leaves

Tyrosinase is a key enzyme in enzymatic browning, causing quality losses in food through the oxidation process. Thus, the discovery of an effective and natural tyrosinase inhibitor via green technology is of great interest to the global food market due to food security and climate change issues. In this study, Syzygium aqueum (S. aqueum) leaves, which are known to be rich in phenolic compounds (PC), were chosen as a natural source of tyrosinase inhibitor, and the effect of the sustainable, supercritical fluid extraction (SFE) process was evaluated. Response surface methodology-assisted supercritical fluid extraction (RSM-assisted SFE) was utilized to optimize the PCs extracted from S. aqueum. The highest amount of PC was obtained at the optimum conditions (55 °C, 3350 psi, and 70 min). The IC50 (661.815 μg/mL) of the optimized extract was evaluated, and its antioxidant activity (96.8 %) was determined. Gas chromatography-mass spectrometry (GC-MS) results reveal that 2',6'-dihydroxy-4'-methoxychalcone (2,6-D4MC) (82.65 %) was the major PC in S. aqueum. Chemometric analysis indicated that 2,6-D4MC has similar chemical properties to the tyrosinase inhibitor control (kaempferol). The toxicity and physiochemical properties of the novel 2,6-D4MC from S. aqueum revealed that the 2,6-D4MC is safer than kaempferol as predicted via absorption, distribution, metabolism, and excretion (ADME) evaluation. Enzyme kinetic analysis shows that the type of inhibition of the optimized extract is non-competitive inhibition with Km = 1.55 mM and Vmax = 0.017 μM/s. High-performance liquid chromatography (HPLC) analysis shows the effectiveness of S. aqueum as a tyrosinase inhibitor. The mechanistic insight of the tyrosinase inhibition using 2,6-D4MC was successfully calculated using density functional theory (DFT) and molecular docking approaches. The findings could have a significant impact on food security development by devising a sustainable and effective tyrosinase inhibitor from waste by-products that is aligned with the United Nation's SDG 2, zero hunger.

Identification of Radix Bupleuri From Different Geographic Origins Using Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry and Support Vector Machine Algorithm

BACKGROUND

The geographic origin of Radix bupleuri is an important factor affecting its efficacy, which needs to be effectively identified.

OBJECTIVE

The goal is to enrich and develop the intelligent recognition technology applicable to the identification of the origin of traditional Chinese medicine.

METHOD

This article establishes an identification method of Radix bupleuri geographic origin based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and support vector machine (SVM) algorithm. The Euclidean distance method is used to measure the similarity between Radix bupleuri samples, and the quality control chart method is applied to quantitatively describe their quality fluctuation.

RESULTS

It is found that the samples from the same origin are relatively similar and mainly fluctuate within the control limit, but the fluctuation range is large, and it is impossible to distinguish the samples from different origins. The SVM algorithm can effectively eliminate the impact of intensity fluctuations and huge data dimensions by combining the normalization of MALDI-TOF MS data and the dimensionality reduction of principal components, and finally achieve efficient identification of the origin of Radix bupleuri, with an average recognition rate of 98.5%.

CONCLUSIONS

This newly established approach for identification of the geographic origin of Radix bupleuri has been realized, and it has the advantages of objectivity and intelligence, which can be used as a reference for other medical and food-related research.

HIGHLIGHTS

A new intelligent recognition method of medicinal material origin based on MALDI-TOF MS and SVM has been established.