{"title":"增强近红外光谱快速灵敏检测牛奶中的三聚氰胺:一种新的方法方法","authors":"Wenliang Qi, Qingqing Jiang","doi":"10.1186/s40538-025-00863-2","DOIUrl":null,"url":null,"abstract":"<div><p>The detection of melamine in milk has consistently been a crucial issue in food safety. Near-infrared spectroscopy is widely used for rapid, non-destructive quantitative analysis and adulteration detection in dairy products, as evidenced by its application in detecting components, such as moisture, fat, and protein, and identifying adulterants, such as water and starch. Despite advancements in qualitative and quantitative models using near-infrared spectroscopy for melamine detection in milk, such as those employing discriminant analysis and partial least squares methods, the technique still faces challenges due to its inherent low sensitivity and high detection limits. This paper proposes a novel method for the detection of melamine in milk based on surface-enhanced near-infrared absorption (SENIRA) spectroscopy with gold nanoparticles. Gold nanospheres were successfully fabricated as substrates for enhancing near-infrared spectroscopy signals, leveraging their unique quantum confinement effects and interactions with light. Utilizing a wavelength range of 900 ~ 1700 nm and various chemometric methods, the concentration of melamine in milk, ranging from 0.0001 to 0.1 mg/mL, was quantified. The modelling effects were found to be favourable, with a calibration correlation coefficient (R<sub>c</sub><sup>2</sup>) of 0.9853, a prediction correlation coefficient (R<sub>p</sub><sup>2</sup>) of 0.9837, and a root mean square error of calibration (RMSEC) of 0.0059, the root mean square error of prediction (RMSEP) was 0.0066, the relative prediction deviation (RPD) was 5.3940, and the average recovery rate was calculated to be 117%. The combination of a high correlation coefficient a low prediction error, a high RPD value, and acceptable recovery rates suggests that the established model is robust and has competent predictive performance. Furthermore, experiments have demonstrated the feasibility of using SENIRA in conjunction with chemometrics for the determination of melamine content in milk, a process that aligns with the successful application of HPLC and NIR spectroscopy techniques as detailed in recent studies.</p><h3>Graphical Abstract</h3>\n<div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":512,"journal":{"name":"Chemical and Biological Technologies in Agriculture","volume":"12 1","pages":""},"PeriodicalIF":5.2000,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://chembioagro.springeropen.com/counter/pdf/10.1186/s40538-025-00863-2","citationCount":"0","resultStr":"{\"title\":\"Enhanced near-infrared spectroscopy for rapid and sensitive detection of melamine in milk: a novel methodological approach\",\"authors\":\"Wenliang Qi, Qingqing Jiang\",\"doi\":\"10.1186/s40538-025-00863-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The detection of melamine in milk has consistently been a crucial issue in food safety. Near-infrared spectroscopy is widely used for rapid, non-destructive quantitative analysis and adulteration detection in dairy products, as evidenced by its application in detecting components, such as moisture, fat, and protein, and identifying adulterants, such as water and starch. Despite advancements in qualitative and quantitative models using near-infrared spectroscopy for melamine detection in milk, such as those employing discriminant analysis and partial least squares methods, the technique still faces challenges due to its inherent low sensitivity and high detection limits. This paper proposes a novel method for the detection of melamine in milk based on surface-enhanced near-infrared absorption (SENIRA) spectroscopy with gold nanoparticles. Gold nanospheres were successfully fabricated as substrates for enhancing near-infrared spectroscopy signals, leveraging their unique quantum confinement effects and interactions with light. Utilizing a wavelength range of 900 ~ 1700 nm and various chemometric methods, the concentration of melamine in milk, ranging from 0.0001 to 0.1 mg/mL, was quantified. The modelling effects were found to be favourable, with a calibration correlation coefficient (R<sub>c</sub><sup>2</sup>) of 0.9853, a prediction correlation coefficient (R<sub>p</sub><sup>2</sup>) of 0.9837, and a root mean square error of calibration (RMSEC) of 0.0059, the root mean square error of prediction (RMSEP) was 0.0066, the relative prediction deviation (RPD) was 5.3940, and the average recovery rate was calculated to be 117%. The combination of a high correlation coefficient a low prediction error, a high RPD value, and acceptable recovery rates suggests that the established model is robust and has competent predictive performance. Furthermore, experiments have demonstrated the feasibility of using SENIRA in conjunction with chemometrics for the determination of melamine content in milk, a process that aligns with the successful application of HPLC and NIR spectroscopy techniques as detailed in recent studies.</p><h3>Graphical Abstract</h3>\\n<div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>\",\"PeriodicalId\":512,\"journal\":{\"name\":\"Chemical and Biological Technologies in Agriculture\",\"volume\":\"12 1\",\"pages\":\"\"},\"PeriodicalIF\":5.2000,\"publicationDate\":\"2025-09-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://chembioagro.springeropen.com/counter/pdf/10.1186/s40538-025-00863-2\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Chemical and Biological Technologies in Agriculture\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://link.springer.com/article/10.1186/s40538-025-00863-2\",\"RegionNum\":2,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AGRICULTURE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chemical and Biological Technologies in Agriculture","FirstCategoryId":"97","ListUrlMain":"https://link.springer.com/article/10.1186/s40538-025-00863-2","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURE, MULTIDISCIPLINARY","Score":null,"Total":0}
Enhanced near-infrared spectroscopy for rapid and sensitive detection of melamine in milk: a novel methodological approach
The detection of melamine in milk has consistently been a crucial issue in food safety. Near-infrared spectroscopy is widely used for rapid, non-destructive quantitative analysis and adulteration detection in dairy products, as evidenced by its application in detecting components, such as moisture, fat, and protein, and identifying adulterants, such as water and starch. Despite advancements in qualitative and quantitative models using near-infrared spectroscopy for melamine detection in milk, such as those employing discriminant analysis and partial least squares methods, the technique still faces challenges due to its inherent low sensitivity and high detection limits. This paper proposes a novel method for the detection of melamine in milk based on surface-enhanced near-infrared absorption (SENIRA) spectroscopy with gold nanoparticles. Gold nanospheres were successfully fabricated as substrates for enhancing near-infrared spectroscopy signals, leveraging their unique quantum confinement effects and interactions with light. Utilizing a wavelength range of 900 ~ 1700 nm and various chemometric methods, the concentration of melamine in milk, ranging from 0.0001 to 0.1 mg/mL, was quantified. The modelling effects were found to be favourable, with a calibration correlation coefficient (Rc2) of 0.9853, a prediction correlation coefficient (Rp2) of 0.9837, and a root mean square error of calibration (RMSEC) of 0.0059, the root mean square error of prediction (RMSEP) was 0.0066, the relative prediction deviation (RPD) was 5.3940, and the average recovery rate was calculated to be 117%. The combination of a high correlation coefficient a low prediction error, a high RPD value, and acceptable recovery rates suggests that the established model is robust and has competent predictive performance. Furthermore, experiments have demonstrated the feasibility of using SENIRA in conjunction with chemometrics for the determination of melamine content in milk, a process that aligns with the successful application of HPLC and NIR spectroscopy techniques as detailed in recent studies.
期刊介绍:
Chemical and Biological Technologies in Agriculture is an international, interdisciplinary, peer-reviewed forum for the advancement and application to all fields of agriculture of modern chemical, biochemical and molecular technologies. The scope of this journal includes chemical and biochemical processes aimed to increase sustainable agricultural and food production, the evaluation of quality and origin of raw primary products and their transformation into foods and chemicals, as well as environmental monitoring and remediation. Of special interest are the effects of chemical and biochemical technologies, also at the nano and supramolecular scale, on the relationships between soil, plants, microorganisms and their environment, with the help of modern bioinformatics. Another special focus is the use of modern bioorganic and biological chemistry to develop new technologies for plant nutrition and bio-stimulation, advancement of biorefineries from biomasses, safe and traceable food products, carbon storage in soil and plants and restoration of contaminated soils to agriculture.
This journal presents the first opportunity to bring together researchers from a wide number of disciplines within the agricultural chemical and biological sciences, from both industry and academia. The principle aim of Chemical and Biological Technologies in Agriculture is to allow the exchange of the most advanced chemical and biochemical knowledge to develop technologies which address one of the most pressing challenges of our times - sustaining a growing world population.
Chemical and Biological Technologies in Agriculture publishes original research articles, short letters and invited reviews. Articles from scientists in industry, academia as well as private research institutes, non-governmental and environmental organizations are encouraged.