Pesticides are essential in modern agricultural practices. Detection of pesticides is an essential step in regulating and monitoring the levels of pesticides in the environment. Even though GC/LC-MS is often the gold standard method for pesticide detection, recent technological advancements has promoted the creation of alternative techniques, such as Surface Enhanced Raman Spectroscopy (SERS), that provide added advantages such as ultrasensitive detection, 24 faster turnover, simpler protocols, in situ sampling, on-site capability and reduced cost. In this review, a comprehensive report of recent advances in SERS detection of synthetic chemical pesticides is given. The development and applications of the SERS technique for pesticide detection in both simple and complex matrices are discussed. The main advantages of using SERS for pesticide detection are highlighted, together with its limitations. Lastly, promising future trends and applications of SERS for pesticides detection are also discussed.

The objective of this study was to develop a simple and rapid method that could detect and discriminate four specific pesticides (isocarbophos, omethoate, phorate, and profenofos) using a single aptamer-based capture procedure followed by Surface Enhanced Raman Spectroscopy (SERS). The aptamer is a single stranded DNA sequence that is specific to capture these four pesticides. The thiolated aptamer was conjugated onto silver (Ag) dendrites, a nanostructure that can enhance the Raman fingerprint of pesticides, through Ag-thiol bonds. It was then backfilled with 6-mercaptohexanol (MH) to prevent nonspecific binding. The modified SERS platform [Ag-(Ap + MH)] was then mixed with each pesticide solution (P) for 20 min. After capturing the pesticides, the Ag-(Ap + MH)-P complex was analyzed under a DXR Raman microscope and TQ Analyst software. The results show that the four pesticides can be captured and detected using principal component analysis based on their distinct fingerprint Raman peaks. The limits of detection (LODs) of isocarbophos, omethoate, phorate, and profenofos were 3.4 μM (1 ppm), 24 μM (5 ppm), 0.4 μM (0.1 ppm), and 14 μM (5 ppm) respectively. This method was also validated successfully in apple juice. These results demonstrated the super capacity of aptamer-based SERS in rapid detection and discrimination of multi-pesticides. This technique can be extended to detect a wide range of pesticides using specific aptamers.

Acetamiprid is a neonicotinoid pesticide that is commonly used in modern farming. Acetamiprid residue in food commodities can be a potential harm to human and has been implicated in the honey bee hive die off crisis. In this study, we developed rapid, simple, and sensitive methods to detect acetamiprid in apple juice and on apple surfaces using surface-enhanced Raman spectroscopy (SERS). No pretreatment of apple juice sample was performed. A simple surface swab method was used to recover acetamiprid from the apple surface. Samples were incubated with silver dendrites for several minutes and SERS spectra were taken directly from the silver surface. Detection of a set of 5 apple juice samples can be done within 10 min. The swab-SERS method took 15 min for a set of 5 samples. Resulting spectral data were analyzed using principal component analysis. The highest acetamiprid peak at 634 cm(-1) was used to detect and quantify the amount of acetamiprid spiked in 1:1 water-methanol solvent, apple juice, and on apple surface. The SERS method was able to successfully detect acetamiprid at 0.5 μg/mL (0.5 ppm) in solvent, 3 μg/mL (3 ppm) in apple juice, and 0.125 μg/cm(2) on apple surfaces. The SERS methods provide simple, rapid, and sensitive ways to detect acetamiprid in beverages and on the surfaces of thick skinned fruits and vegetables.

Here we presented a simple, rapid and label-free surface-enhanced Raman spectroscopy (SERS) based mapping method for the detection and discrimination of Salmonella enterica and Escherichia coli on silver dendrites. The sample preparation was first optimized to maximize sensitivity. The mapping method was then used to scan through the bacterial cells adsorbed on the surface of silver dendrites. The intrinsic and distinct SERS signals of bacterial cells were used as the basis for label-free detection and discrimination. The results show the developed method is able to detect single bacterial cells adsorbed on the silver dendrites with a limit of detection as low as 10(4) CFU mL(-1), which is two orders of magnitude lower than the traditional SERS method under the same experimental condition. The time needed for collecting a 225 points map was approximately 24 minutes. Moreover, the developed SERS mapping method can realize simultaneous detection and identification of Salmonella enterica subsp. enterica BAA1045 and Escherichia coli BL21 from a mixture sample using principle component analysis. Our results demonstrate the great potential of the label-free SERS mapping method to detect, identify and quantify bacteria and bacterial mixtures simultaneously.