Identification of aminoglycoside antibiotics in milk matrix with a colorimetric sensor array and pattern recognition methods

Shang, Yan; Lai, Xiaoxia; Du, Guorong; Xiang, Yuhong

doi:10.1016/j.aca.2018.06.004

Cited by 54 publications

(27 citation statements)

References 35 publications

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“…Some methods have also been developed to detect antibiotics abused in animal husbandry, that could be found as residues in animal-derived food. These methods, both based on AuNP aggregation, have been developed to determinate aminoglycoside antibiotics [35] and ceftriaxone [36] in animal-origin foods, such as milk, eggs and meat. The spectral changes induced by AuNP aggregation were analysed with a pattern recognition technique (i.e., Cluster Analysis) for aminoglycoside antibiotics and with spectrophotometric surface plasmon resonance (SPR) band shift for ceftriaxone.…”

Section: Contaminants Determinationmentioning

confidence: 99%

Noble Metal Nanoparticles Applications: Recent Trends in Food Control

Vinci

Rapa

2019

Bioengineering

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Scientific research in the nanomaterials field is constantly evolving, making it possible to develop new materials and above all to find new applications. Therefore, nanoparticles (NPs) are suitable for different applications: nanomedicine, drug delivery, sensors, optoelectronics and food control. This review explores the recent trend in food control of using noble metallic nanoparticles as determination tools. Two major uses of NPs in food control have been found: the determination of contaminants and bioactive compounds. Applications were found for the determination of mycotoxins, pesticides, drug residues, allergens, probable carcinogenic compounds, bacteria, amino acids, gluten and antioxidants. The new developed methods are competitive for their use in food control, demonstrated by their validation and application to real samples.

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Section: Contaminants Determinationmentioning

confidence: 99%

Noble Metal Nanoparticles Applications: Recent Trends in Food Control

Vinci

Rapa

2019

Bioengineering

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“…Variable selection methods can improve the prediction performance, make the calibration reliable and provide simpler interpretation [28,29]. Principal component analysis (PCA) [14,30,31] and Fisher linear discriminant analysis (FLD) [32,33] are used for the establishment of identification model, while partial least-regression (PLS) and related robust techniques [17,30] are used for the quantitative analysis.…”

Section: Introductionmentioning

confidence: 99%

A Rapid and Nondestructive Approach for the Classification of Different-Age Citri Reticulatae Pericarpium Using Portable Near Infrared Spectroscopy

Zhang

et al. 2020

Sensors

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Citri Reticulatae Pericarpium (CRP), has been used in China for hundreds of years as a functional food and medicine. However, some short-age CRPs are disguised as long-age CRPs by unscrupulous businessmen in order to obtain higher profits. In this paper, a rapid and nondestructive method for the classification of different-age CRPs was established using portable near infrared spectroscopy (NIRS) in diffuse reflectance mode combination with appropriate chemometric methods. The spectra of outer skin and inner capsule of CRPs at different storage ages were obtained directly without destroying the samples. Principal component analysis (PCA) with single and combined spectral pretreatment methods was used for the classification of different-age CRPs. Furthermore, the data were pretreated with the PCA method, and Fisher linear discriminant analysis (FLD) with optimized pretreatment methods was discussed for improving the accuracy of classification. Data pretreatment methods can be used to eliminate the noise and background interference. The classification accuracy of inner capsule is better than that of outer skin data. Furthermore, the best results with 100% prediction accuracy can be obtained with FLD method, even without pretreatment.

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“…To solve the problem, the combination pretreatment methods are often used to eliminate various interferences in the spectra (Bian et al., 2020). PCA (Li et al., 2012), soft independent modeling of class analogy (SIMCA) (Szabó et al., 2018), and Fisher's linear discriminant analysis (FLD) (Witjes et al., 2003; Yan et al., 2018) have been applied for the classification, while partial least squares (PLS), boosting partial least squares (Shao et al., 2010), and related robust techniques (Li et al., 2018; Li et al., 2020; Ma, Liu, et al., 2020; Ma, Pang, et al., 2020; Melssen et al., 2007) were used for the quantitative analysis. Multiple sets of data provide more useful and complementary information than a single set.…”

Section: Introductionmentioning

confidence: 99%

A novel method for the nondestructive classification of different‐age Citri Reticulatae Pericarpium based on data combination technique

Zhang

et al. 2020

Food Science & Nutrition

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The quality of Citri Reticulatae Pericarpium (CRP) is closely correlated with the aging time. However, CRPs in different storage ages are similar in appearance, and the young CRP may be labeled as the aged one to obtain the excess profit by some unscrupulous traders. Most traditional analysis methods are laborious and time‐consuming, and they can hardly realize the nondestructive classification. In this paper, a novel method based on near‐infrared diffuse reflectance spectroscopy (NIRDRS) and data combination technique for the nondestructive classification of different‐age CRPs was proposed. The CRPs in different storage ages (5, 10, 15, 20, and 25 years) were measured. The near‐infrared spectra of outer skin and inner capsule were obtained. Principal component analysis (PCA), soft independent modeling of class analogy (SIMCA), and Fisher's linear discriminant analysis (FLD), with different data pretreatment methods, were used for the classification analysis. Data combination of the outer skin and inner capsule spectra was discussed for further improving the classification results. The results show that multiple sensors provide more useful and complementary information than a single sensor does for improving the prediction accuracy. With the help of data combination strategy, 100% prediction accuracy can be obtained with both second‐order derivative–FLD and continuous wavelet transform–multiplicative scatter correction–FLD methods.

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Identification of aminoglycoside antibiotics in milk matrix with a colorimetric sensor array and pattern recognition methods

Cited by 54 publications

References 35 publications

Noble Metal Nanoparticles Applications: Recent Trends in Food Control

Noble Metal Nanoparticles Applications: Recent Trends in Food Control

A Rapid and Nondestructive Approach for the Classification of Different-Age Citri Reticulatae Pericarpium Using Portable Near Infrared Spectroscopy

A novel method for the nondestructive classification of different‐age Citri Reticulatae Pericarpium based on data combination technique

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