A novel on‐chip solution enabling rapid analysis of melamine and chloramphenicol in milk by smartphones

Metrological traceability in process analytical technologies and point-of-need technologies for food safety and quality control: not a straightforward issue

Traditional techniques for food analysis are based on off-line laboratory methods that are expensive and time-consuming and often require qualified personnel. Despite the high standards of accuracy and metrological traceability, these well-established methods do not facilitate real-time process monitoring and timely on-site decision-making as required for food safety and quality control. The future of food testing includes rapid, cost-effective, portable, and simple methods for both qualitative screening and quantification of food contaminants, as well as continuous, real-time measurement in production lines. Process automatization through process analytical technologies (PAT) is an increasing trend in the food industry as a way to achieve improved product quality, safety, and consistency, reduced production cycle times, minimal product waste or reworks, and the possibility for real-time product release. Novel methods of analysis for point-of-need (PON) screening could greatly improve food testing by allowing non-experts, such as consumers, to test in situ food products using portable instruments, smartphones, or even visual naked-eye inspections, or farmers and small producers to monitor products in the field. This requires the attention of the research community and devices manufacturers to ensure reliability of measurement results from PAT strategy and PON tests through the demonstration and critical evaluation of performance characteristics. The fitness for purpose of methods in real-life conditions is a priority that should not be overlooked in order to maintain an effective and harmonized food safety policy.

Microfluidic Paper-Based Analytical Devices for the Determination of Food Contaminants: Developments and Applications

Food safety is an issue that cannot be ignored at any time because of the great impact of food contaminants on people's daily life, social production, and the economy. Because of the extensive demand for high-quality food, it is necessary to develop rapid, reliable, and efficient devices for food contaminant detection. Microfluidic paper-based analytical devices (μPADs) have been applied in a variety of detection fields owing to the advantages of low-cost, ease of handling, and portability. This review systematically discusses the latest progress of μPADs, including the fundamentals of fabrication as well as applications in the detection of chemical and biological hazards in foods, hoping to provide suitable screening strategies for contaminants in foods and accelerating the technology transformation of μPADs from the lab into the field.

Handheld Spectral Sensing Devices Should Not Mislead Consumers as Far as Non-Authentic Food Is Concerned: A Case Study with Adulteration of Milk Powder

With the rising trend of consumers being offered by start-up companies portable devices and applications for checking quality of purchased products, it appears of paramount importance to assess the reliability of miniaturized sensors embedded in such devices. Here, eight sensors were assessed for food fraud applications in skimmed milk powder. The performance was evaluated with dry- and wet-blended powders mimicking adulterated materials by addition of either ammonium sulfate, semicarbazide, or cornstarch in the range 0.5-10% of profit. The quality of the spectra was assessed for an adequate identification of the outliers prior to a deep assessment of performance for both non-targeted (soft independent modelling of class analogy, SIMCA) and targeted analyses (partial least square regression with orthogonal signal correction, OPLS). Here, we show that the sensors have generally difficulties in detecting adulterants at ca. 5% supplementation, and often fail in achieving adequate specificity and detection capability. This is a concern as they may mislead future users, particularly consumers, if they are intended to be developed for handheld devices available publicly in smartphone-based applications.

Fully Automatic Multi-Class Multi-Residue Analysis of Veterinary Drugs Simultaneously in an Integrated Chip-MS Platform

Microfluidic chip analysis has great potential advantages such as high integration, fast speed analysis, and automatic operation and is widely used not only in biological fields but also in many other analytical areas such as agriculture and food safety. Herein, a fully automatic multi-class multi-residue analysis of veterinary drugs simultaneously in an integrated chip-mass spectrometry (chip-MS) platform was developed. The developed microfluidic chip platform integrated three modules including the extraction and filtration module, "pass-through" clean-up module, and online evaporation module. The resulting chip has been coupled to a MS detector successfully, in which 23 kinds of residues in five classes were simultaneously qualitatively and quantitatively detected without chromatographic separation, obtaining the limits of detection of the spiked milk sample in the range of 0.23-4.13 ng/mL and the recovery rate in the range from 71.7 to 118.0% under optimized conditions. The microfluidic chip system developed in this study provided a new idea for the development of detection chips and exhibited considerable potential in the point-of-care testing in milk.

Pesticide Residues Identification by Optical Spectrum in the Time-Sequence of Enzyme Inhibitors Performed on Microfluidic Paper-Based Analytical Devices (µPADs)

Pesticides vary in the level of poisonousness, while a conventional rapid test card only provides a general “absence or not” solution, which cannot identify the various genera of pesticides. In order to solve this problem, we proposed a seven-layer paper-based microfluidic chip, integrating the enzyme acetylcholinesterase (AChE) and chromogenic reaction. It enables on-chip pesticide identification via a reflected light intensity spectrum in time-sequence according to the different reaction efficiencies of pesticide molecules and assures the optimum temperature for enzyme activity. After pretreatment of figures of reflected light intensity during the 15 min period, the figures mainly focused on the reflected light variations aroused by the enzyme inhibition assay, and thus, the linear discriminant analysis showed satisfying discrimination of imidacloprid (Y = −1.6525X − 139.7500), phorate (Y = −3.9689X − 483.0526), and avermectin (Y = −2.3617X − 28.3082). The correlation coefficients for these linearity curves were 0.9635, 0.8093, and 0.9094, respectively, with a 95% limit of agreement. Then, the avermectin class chemicals and real-world samples (i.e., lettuce and rice) were tested, which all showed feasible graphic results to distinguish all the chemicals. Therefore, it is feasible to distinguish the three tested kinds of pesticides by the changes in the reflected light spectrum in each min (15 min) via the proposed chip with a high level of automation and integration.