Development of a bead-based immunoassay for detection of triazophos and application validation

A "turn-on" fluorescent sensor for herbicide quizalofop-p-ethyl based on cyanostilbene-pyridine macrocycle

Quizalofop-p-ethyl is a widely used herbicide that also poses a risk to human health and environmental safety. However, there is still a lack of simple and in-situ detecting method for quizalofop-p-ethyl so far. In this work, the fluorescent sensor was firstly developed on detection of quizalofop-p-ethyl based on cyanostilbene-pyridine macrocycle (CPM). CPM was prepared by the "1 + 1" condensation of pyridine-substituted cyanostilbene derivative with 4,4'-Bis(chloromethyl)biphenyl in 68 % yield. The weak fluorescence of CPM in aqueous media transferred to strong orange fluorescence after sensing quizalofop-p-ethyl. This sensing behavior exhibited high selectivity among 28 kinds of herbicides and ions. The limitation of detection (LOD) was 2.98 × 10-8 M and the limitation of quantification (LOQ) was 9.94 × 10-8 M (λex = 390 nm, λem = the maximum emission between 512 nm and 535 nm) with a dynamic range of 0.01-0.9 eq. The binding constant (Ka) of quizalofop-p-ethyl to the sensor CPM was 3.2 × 106 M-1. The 1:1 sensing mechanism was confirmed as that quizalofop-p-ethyl was located in the cavity of CPM, which enhanced aggregating effect and reduced the intramolecular rotation of aromatic groups for better AIE effect. The sensing ability of CPM for quizalofop-p-ethyl had been efficiently applied in test paper experiments, agricultural product tests and real water samples, revealing that CPM has good application prospect for simple and in-situ detection of quizalofop-p-ethyl in real environment.

A non-competitive surface plasmon resonance immunosensor for rapid detection of triazophos residue in environmental and agricultural samples

The wide application of an organophosphate pesticide triazophos raises concern on the environmental pollution and the potential risk to human health. Thus, it is crucial to regularly monitor triazophos residue in the environment and agro-products. Herein we described a non-competitive immunoassay for trace detection of triazophos using a direct surface plasmon resonance (SPR) biosensor. Two anti-triazophos monoclonal antibodies (mAbs) were immobilized on the sensor chip and characterized by SPR-based kinetic analysis. The mAb with relatively slow dissociation rate was used for direct immunosensing of triazophos. The biosensor assay showed a high specificity and a low detection limit of 0.096ngmL^-1 to triazophos, with the linear detection range of 0.98-8.29ngmL^-1. Under the optimal condition, the sensor chip could be regenerated for 160cycles at least. Moreover, the sensitive method was applied to determine triazophos in the spiked environmental water and agricultural products, as well as in unknown real-life samples (including Chinese cabbage, cucumber, and apple). Desirable results demonstrated that the newly-developed immunosensor could be used as a rapid, convenient, and reliable tool to regularly monitor triazophos and meet the detection requirement of its maximum residue limits.

The Rapid Screening of Triazophos Residues in Agricultural Products by Chemiluminescent Enzyme Immunoassay

A highly sensitive chemiluminescent enzyme immunoassay (CLEIA) method was developed in this study for efficient screening of triazophos residues in a large number of samples. Based on the maximum residue limits (MRLs) set by China and CAC for triazophos in different agro-products, the representative apple, orange, cabbage, zucchini, and rice samples were selected as spiked samples, and the triazophos at the concentrations of the MRL values were spiked to blank samples. Subsequently, the five samples with the spiked triazophos standard were measured by CLEIA 100 times, and the detection results indicated that the correction factors of the apple, orange, cabbage, zucchini, and rice were determined as 0.79, 0.66, 0.85, 0.76, and 0.91, respectively. In this experiment, 1500 real samples were detected by both the CLEIA and the GC-MS methods. With the GC-MS method, 1462 samples were identified as negative samples and 38 samples as positive samples. Based on the correction factors, the false positive rate of the CLEIA method was 0.13%, and false negative rate was 0. The results showed that the established CLEIA method could be used to screen a large number of real samples.