Since conventional quantification techniques like liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS) methods are expensive and have many drawbacks, sensing platforms with various transduction systems have become an efficient alternative tool for quantifying various target molecules in a wide variety of food samples.
GANG BEASTS CONTROLS PDA PORTABLE
Hence, in the wake of such food and public health safety efforts, there is a rising demand for economic, rapid, and portable detection and quantification methods for these contaminants. FDA) and European Union Commission regulations have disseminated various acrylamide mitigation strategies in food processing practices. These results indicate that using the developed PDA sensor, a simple naked eye detection for dissolved ammonia is possible with higher accuracy and on-site detection enabled by the smartphone and machine learning processes.Īcrylamide, a food processing contaminant with demonstrated genotoxicity, carcinogenicity, and reproductive toxicity, is largely present in numerous prominent and commonly consumed food products that are produced by thermal processing methods. Using a support vector machine for the machine learning model, the classification of ammonia concentration was possible with a high accuracy of 100 and 95.1% using color RGB images captured by a scanner and a smartphone, respectively. Furthermore, the quantitative on-site monitoring of dissolved ammonia was investigated using colorimetric images with machine learning classifiers. Also, the PDA sensor could be stably operated for up to 60 days by storing in a refrigerator. The fabricated PDA sensor exhibited a detection limit of ammonia below 10 ppm with a response time of 20 min. The quantitative color change was studied by UV-vis spectroscopy, and it was found that the absorption peak at 640 nm gradually decreased, and the absorption peak at 540 nm increased with increasing ammonia concentration. PDA vesicles were assembled from diacetylene monomers through a facile green chemical synthesis which exhibited a blue-to-red color transition upon exposure to dissolved ammonia and was detectable by the naked eye. This work demonstrates quantitative naked eye detection of dissolved ammonia based on polydiacetylene (PDA) sensors with machine learning classifiers. These nanofibers are suitable for real-time and in situ monitoring and assessment of meat deterioration and freshness.Įasy-to-use and on-site detection of dissolved ammonia are essential for managing aquatic ecosystems and aquaculture products since low levels of ammonia can cause serious health risks and harm aquatic life. Overall, our forcespun PDA nanofibers demonstrated promising colorimetric detection of meat spoilage based on the released amine vapors during the food degradation.
An effective colorimetric response was also obtained when evaluating the sensing ability of the nanofibers to BA vapors from actual spoiling meat products including chicken, beef, fish and pork.
The PDA nanofibers made from 5,7-eicosadienoic acid (ECDA) demonstrate higher performance and can determine amine vapor concentration with a detection limit of ˜7 ppm in a few minutes. PDA nanofibers were prepared from two different monomers and their amine sensing properties are evaluated and compared.
GANG BEASTS CONTROLS PDA PLUS
Specifically, the PDA nanofibers produce a color transition from blue-to-red plus an enhancement of its fluorescence. These PDA nanofibers demonstrate optical sensing of BAs owing to their strong electrostatic interaction with carboxylate ions of the PDA and amine ions in the BA molecules.
In this study, we have developed silica-reinforced polydiacetylene (PDA) nanofiber mats by a novel Forcespinning® technique. Therefore, the sensitive detection of the released BAs is crucial to the assessment of the safety and quality of meat products during storage, transportation and consumption. Ammonia and biogenic amines (BAs), such as trimethylamine, putrescine and cadaverine, are released during the decomposition of meat protein. Due to health and economic concerns, increasing attention has been attracted to the safety and quality control of food, particularly meat and seafood.
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