Rapid Detection of Heavy Metal Contaminated <i>Tegillarca granosa</i> by Temperature-dependent Near-infrared Spectroscopy

ZHOU Qiwei; SONG Yanru; ZHANG Zhanshuo; YUAN Leiming; SUN Yiye

doi:10.13386/j.issn1002-0306.2021120125

Volume 43 Issue 19

Sep. 2022

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Science and Technology of Food Industry > 2022 > 43(19): 326-330. > DOI: 10.13386/j.issn1002-0306.2021120125

ZHOU Qiwei, SONG Yanru, ZHANG Zhanshuo, et al. Rapid Detection of Heavy Metal Contaminated Tegillarca granosa by Temperature-dependent Near-infrared Spectroscopy[J]. Science and Technology of Food Industry, 2022, 43(19): 326−330. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2021120125.

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Rapid Detection of Heavy Metal Contaminated Tegillarca granosa by Temperature-dependent Near-infrared Spectroscopy

College of Electrical & Electronic Engineering, Wenzhou University, Wenzhou 325035, China

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Received Date: December 12, 2021
Available Online: August 02, 2022

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Abstract

Objective: To explore a rapid determination method of heavy metal contaminated shellfish based on enzymatic hydrolysis and temperature-dependent near infrared spectroscopy. Methods: Shellfish of Tegillarca granosa was reared artificially and used in this paper. Three heavy metals, including copper (Cu), cadmium (Cd) and lead (Pb), were used to contaminate Tegillarca granosa. The full protein supernatant samples of heavy metal-contaminated and healthy Tegillarca granosa were extracted by enzymolysis and centrifugation pretreatments. Fourier transform near-infrared spectroscopy (FT-NIR) was employed to collect spectra of each sample under the process of elevating temperature with each 5 ℃ interval in the range of 25~60 ℃, and a discriminant model was constructed to distinguish these samples contaminated with heavy metals. Results: Partial least square-discrimination analysis (PLS-DA) was used to identify the heavy metals contaminated Tegillarca granosa under each temperature. The accuracy rate was influenced by the temperature first increasing and then decreasing with raising the temperature. When the temperature of sample was kept at 40 ℃, the accuracy of discriminant model was 92%, and it can be improved up to 98% by the optimized parameters through variable selection methods. Conclusion: With the help of chemo-metrics, near infrared spectroscopy and enzymatic hydrolysis, the heavy metals-contaminated Tegillarca granosa can be quickly identified and the detection methods of heavy metal pollution of shellfish can be enriched.

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