Au@Ag nanoflowers based SERS coupled chemometric algorithms for determination of organochlorine pesticides in milk. (October 2021) - Zhu, Afang
Abstract: In this study, SERS coupled with chemometric algorithms like PLS (partial least square), Si-PLS (synergy interval-PLS), GA-PLS (genetic algorithm-PLS) and UVE-PLS (uninformative variable elimination-PLS) were applied for the detection of 2, 4-D and imidacloprid in milk. The fabricated gold and silver core-shell nanoflowers (Au@Ag NFs) were used as SERS nanosensor which exhibited strong signal over the concentration range of 1.0 × 10 −3 to 1.0 × 10 2 ng/mL. Performances of the models were evaluated based on the attained correlation coefficients of the prediction ( R p ) and calibration ( R c ), root mean square error in calibration ( RMSECV ) and prediction ( RMSEP ), and the ratio of sample standard deviation to RMSEP ( RPD ). The models exhibited improved results in the order of PLS < Si-PLS < GA-PLS < UVE-PLS. The UVE-PLS model showed superior performance, yielded R c = 0.9801 and R p = 0.9878 with RPD = 6.32 for 2, 4-D, and R c = 0.9732 and R p = 0.9726 with RPD = 4.30 for imidacloprid. The strategy could be employed for safety and quality monitoring of milk. Highlights: Hollow Au@Ag NFs were synthesized and served as active SERS substrates. The SERS nanosensor exhibited strong signal at 1.0 × 10 −3 to 1.0 × 10 2 ng/mL. PLS, Si-PLS, GA-PLS, UVE-PLS were applied for the 2, 4-D and imidacloprid detection. The models exhibited improved results in the order of PLS < Si-PLS < GA-PLS < UVE-PLS.