We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
Complementarity of portable and benchtop near-infrared spectrometers for microplastic predictive detection in whole camel milk powder
AI summary Read the abstract
Scientists tested whether a light-based scanning technology (near-infrared spectroscopy) could detect tiny plastic particles hiding in camel milk powder, using both expensive lab equipment and a smaller, portable version you could use on-site. The portable device wasn't quite as accurate on its own, but when researchers combined data from both devices and applied a correction technique, they got much better results, suggesting this could become a practical, field-ready tool for catching microplastic contamination in food before it reaches consumers.
This study systematically investigated the complementarity and transferability of benchtop and portable Near Infrared Spectroscopy regarding the detection of common microplastic contamination in camel milk powder (CMP).Both devices achieved superior results in the Support Vector Machine (SVM) discrimination of microplastic contamination types and demonstrated complementarity in the precise identification of pure CMP and its PET contaminated samples.A data level fusion strategy combined with SVM discriminant analysis reduced the classification error of PE, PET, and PS contaminated CMP samples to 0. Benchtop spectrometers were significantly superior to portable devices in the quantitative analysis of microplastic contamination levels, with cross validation coefficients of determination ranging from 0.789 to 0.899 and 0.526-0.717,respectively.Furthermore, the Slope Bias Correction method successfully implemented model transfer; the prediction accuracy of the portable device for PP contaminated samples after correction (R 2 = 0.796) was improved by 51.10% compared with the original model (R 2 = 0.526).This study provides a theoretical basis and technical pathway for the rapid onsite screening of microplastic contamination in CMP.
More Papers Like This
Comparison of Benchtop and Portable Near-Infrared Instruments to Predict the Type of Microplastic Added to High-Moisture Food Samples
AI summary Read the abstract
Researchers compared benchtop and portable near-infrared (NIR) spectroscopy instruments for classifying microplastics added to high-moisture food samples such as vegetables and fruit, evaluating whether portable instruments could match benchtop performance for rapid, non-destructive detection.
Evaluation of near infrared spectroscopy for direct detection of common microplastics contamination in camel Milk powder
AI summary Read the abstract
Researchers evaluated near infrared spectroscopy as a rapid, non-destructive method for detecting common microplastic contamination in camel milk powder. The technique successfully distinguished between uncontaminated and contaminated samples spiked with polyethylene, polypropylene, polystyrene, and PET at concentrations as low as 0.01% by weight. The findings suggest NIR spectroscopy could serve as a practical quality control tool for screening microplastic contamination in premium dairy products.
Near-infrared (NIR) spectroscopy for quantitative modelling of quaternary microplastic mixtures and the effect of interferents
AI summary Read the abstract
Scientists tested a portable scanning device that uses infrared light to quickly identify and measure different types of plastic pollution (like the kind found in food packaging and synthetic fabrics) even when mixed with real-world debris like dirt, sand, and plant matter. The tool worked well, meaning researchers could soon have a faster, cheaper way to track how much plastic is contaminating our environment. Since microplastics have been found in human blood, organs, and food, better detection tools like this are an important step toward understanding, and eventually reducing, our exposure to them.
Qualitative and Quantitative Detection of Microplastics in Chicken Feed Using Portable Near-Infrared Spectroscopy
AI summary Read the abstract
Scientists tested a portable scanning tool that uses infrared light to detect tiny plastic particles hidden in chicken feed, and it correctly identified the type of plastic about 96% of the time. This matters because microplastics in animal feed could end up in the meat and eggs we eat, and this faster, non-destructive testing method could eventually help catch contaminated feed before it enters the food supply, though it still needs more testing in real-world conditions with mixed plastic types.
Improved Microplastic Identification from Simultaneously Collected Photothermal Infrared and Raman Spectra Using Multiview Conformal Prediction
AI summary Read the abstract
Scientists have developed a more reliable way to identify tiny plastic particles (microplastics) by combining two different light-based detection methods and using statistics to double-check the results, rather than relying on just one test with an arbitrary cutoff. This matters because accurately spotting microplastics in air, water, and our environment is the first step to understanding how much of this potentially harmful material we're actually exposed to—and this new method proved better at correctly flagging real plastic particles while avoiding false alarms on non-plastic debris.
Research digests by email
When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.