In recent years, growing food safety and quality concerns have emerged and created an urgent need for the development of rapid and reliable food control technologies. This study proposes a novel surface-enhanced Raman spectroscopy (SERS) substrate printing technology that utilizes commercial filter paper functionalized by silver nanoparticles. We modified the Automatic TLC Sampler using a two-dimensional (2D) printer. The modification allows for various sampling modes which can be applied to 2D printing. The shape and size of nano silver on the substrate were determined, and the substrate sensitivity, uniformity, and stability were evaluated. As demonstrated by the experimental outcomes, the proposed technology is highly sensitive and reproducible, that is, the limit of quantitation was 10 −5 mg/kg, and the spot-to-spot and block-to-block Raman intensity variations were below 4.2%. We also successfully applied the technology to pears and apples for thiram recognition, yielding outstanding detectability down to 2.5 × 10 −6 and 3.9 × 10 −7 mg/mL (equal to 2.5 × 10 −3 and 3.9 × 10 −4 mg/kg), respectively. These were well below the maximum residue limit (7 mg/kg). More importantly, the linear relationships between thiram levels and the SERS intensity allow for sensitive monitoring of minute variations in agricultural insecticide residues. This proposed detection method can realize in situ detection with a strong signal fingerprint.

In this paper, a two-level algorithm is proposed to solve the distribution network reconfiguration with an objective of minimum power loss. In the first level reconfiguration, switches of maximum power loss reduction are disconnected by the branch exchange (BE) algorithm. Based on the results, neighbourhoods of disconnected switches are constructed by the deterministic transform method in the second level. The variable neighbourhood search (VNS) algorithm keeps searching the neighbourhoods to obtain a better solution with a lower power loss. Simulations are carried out on IEEE33 and PG&69 distribution networks to verify the superiority of the proposed algorithm. The obtained results are compared with the other methods available in the paper. It can be concluded that the presented method has both high stability and rapidity.

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