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Detection of Acetamiprid in Fruits by Surface Enhanced Raman Spectroscopy

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  2015 ASABE Annual International Meeting  152189647.(doi:10.13031/aim.20152189647)
Authors:   Chen Zhai, Yongyu Li, Yankun Peng, Tianfeng Xu, Sagar Dhakal
Keywords:   Surface enhanced Raman spectroscopy, Fruit, Acetamiprid

Abstract. Acetamiprid, which belongs to the new neonicotinoid class insecticides, has been widely used to control sucking-type insects on fruits, leafy vegetables and tea trees. Although it is noted as relatively low acute and chronic mammalian toxicity, its accumulation in fruits and vegetables still cause potential risk to human health, owing to the frequent and extensive usage. Therefore, practical methods with rapid, non-destructive and highly sensitive characteristics for simple detection of acetamiprid residues are crucial for human health. In this research, a novel Surface Enhanced Raman Spectroscopy (SERS) method is developed using silver colloid and with a self-developed Raman system for the fast, sensitive and nondestructive detection of acetamiprid in fruits (apple, pear, orange and mango). The main advantages of using silver colloid for SERS measurement are the easy formation and manipulation for analytical study. The SERS spectra are obtained using 785 nm exciting radiation. The peaks of Raman spectra at 634 cm-1, 1111 cm-1 and 2172 cm-1 are used for the identification and the determination of acetamiprid. The lowest detectable level of acetamiprid in apple is 0.04 mg/kg, which is sensitive enough for identifying apple contaminated with acetamiprid above the maximum residue level. The quantitative curves indicate good linear relationship between the Raman intensity and the concentration of acetamiprid, with coefficients of determination more than 0.94. The silver colloid used for the detection of acetamiprid in different kinds of fruits shows excellent signal enhancement effect. The present study demonstrates a novel approach to detect acetamiprid in fruits with good performance, which shows great potential for the evaluation and identification of pesticide residues in agricultural products.

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