As a typical disinfectant, the use of benzyl dodecyl dimethyl ammonium bromide (BDAB) has dramatically increased since the emergence of SARS-CoV-2, posing a threat to environmental balance and human health. Screening BDAB co-metabolic degrading bacteria is required for efficient microbial degradation. Conventional methods for screening co-metabolic degrading bacteria are laborious and time-consuming, especially when the number of strains is large. This study aimed to develop a novel method for the rapid screening of BDAB co-metabolic degrading bacteria from the cultured solid medium using near-infrared hyperspectral imaging (NIR-HSI) technology. Based on NIR spectra, the concentration of BDAB in the solid medium can be well predicted by partial least squares regression (PLSR) models, non-destructively and rapidly, with R_c² > 0.872 and R_cv² > 0.870. The results show that the predicted BDAB concentrations decrease after degrading bacteria utilization, comparing with the regions where no degrading bacteria grew. The proposed method was applied to directly identify the BDAB co-metabolic degrading bacteria cultured on the solid medium, and two kinds of co-metabolic degrading bacteria RQR-1 and BDAB-1 were correctly identified. This method provides a high-efficiency method for screening BDAB co-metabolic degrading bacteria from a large number of bacteria.

作为一种典型的消毒剂，自 SARS-CoV-2 出现以来，苄基十二烷基二甲基溴化铵 (BDAB) 的使用量急剧增加，对环境平衡和人类健康构成威胁。筛选 BDAB 共代谢降解细菌是有效微生物降解所必需的。筛选共代谢降解细菌的常规方法既费力又费时，尤其是当菌株数量很大时。本研究旨在开发一种利用近红外高光谱成像 (NIR-HSI) 技术从培养的固体培养基中快速筛选 BDAB 共代谢降解菌的新方法。基于 NIR 光谱，BDAB 在固体介质中的浓度可以通过偏最小二乘回归 (PLSR) 模型非破坏性且快速地很好地预测，其中 R _c² > 0.872 和 R _cv ² > 0.870。结果表明，与没有降解细菌生长的区域相比，降解细菌利用后预测的 BDAB 浓度降低。应用该方法对固体培养基上培养的BDAB共代谢降解菌进行直接鉴定，正确鉴定出2种共代谢降解菌RQR-1和BDAB-1。该方法为从大量细菌中筛选BDAB共代谢降解菌提供了一种高效方法。