Rapid and Green Classification Method of Bacteria Using Machine Learning and NIR Spectroscopy.

Green Chemistry is a vital and crucial instrument in achieving pollution control, and it plays an important role in helping society reach the Sustainable Development Goals (SDGs). NIR (near-infrared spectroscopy) has been utilized as an alternate technique for molecular identification, making the process faster and less expensive. Near-infrared diffuse reflectance spectroscopy and Machine Learning (ML) algorithms were utilized in this study to construct identification and classification models of bacteria such as Escherichia coli, Salmonella enteritidis, Enterococcus faecalis and Listeria monocytogenes. Furthermore, divide these bacteria into Gram-negative and Gram-positive groups. The green and quick approach was created by combining NIR spectroscopy with a diffuse reflectance accessory. Using infrared spectral data and ML techniques such as principal component analysis (PCA), hierarchical cluster analysis (HCA) and K-Nearest Neighbor (KNN), It was feasible to accomplish the identification and classification of four bacteria and classify these bacteria into two groups: Gram-positive and Gram-negative, with 100% accuracy. We may conclude that our study has a high potential for bacterial identification and classification, as well as being consistent with global policies of sustainable development and green analytical chemistry.

Production of feather hydrolysates with antioxidant, angiotensin-I converting enzyme- and dipeptidyl peptidase-IV-inhibitory activities.

The antioxidant and antihypertensive activities of feather hydrolysates obtained with the bacterium Chryseobacterium sp. kr6 were investigated. Keratin hydrolysates were produced with different concentrations of thermally denatured feathers (10-75 g l(-1)) and initial pH values (6.0-9.0). Soluble proteins accumulated in high amounts in media with 50 and 75 g l(-1) of feathers, reaching values of 18.5 and 22 mg ml(-1), respectively, after 48 hours of cultivation. In media with 50 g l(-1) of feathers, initial pH had minimal effect after 48 hours. Maximal protease production was observed after 24 hours of cultivation, and feather concentration and initial pH values showed no significant effect on enzyme yields at this time. Feather hydrolysates displayed in vitro antioxidant properties, and optimal antioxidant activities were observed in cultures with 50 g l(-1) feathers, at initial pH 8.0, after 48 hours growth at 30°C. Also, feather hydrolysates were demonstrated to inhibit the angiotesin I-converting enzyme by 65% and dipeptidyl peptidase-IV by 44%. The bioconversion of an abundant agroindustrial waste such as chicken feathers can be utilized as a strategy to obtain hydrolysates with antioxidant and antihypertensive activities. Feather hydrolysates might be employed as supplements in animal feed, and also as a potential source of bioactive molecules for feed, food and drug development.