Qualitative Analysis of Lambda-Cyhalothrin on Chinese Cabbage Using Mid-Infrared Spectroscopy Combined with Fuzzy Feature Extraction Algorithms

Shen, Yanjun; Wu, Xiaohong; Wu, Bin; Tan, Yi; Liu, Jinmao

doi:10.3390/agriculture11030275

Cited by 12 publications

(8 citation statements)

References 29 publications

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“…Weight index

m

is a significant factor when FDUT is used for feature extraction, which has a profound influence on the classification results of milk (Shen, Wu, Wu, Tan, & Liu, 2021). If

m

is too small, FUDT could not process the overlapped data points efficiently.…”

Section: Resultsmentioning

confidence: 99%

Rapid authentication of the geographical origin of milk using portable near‐infrared spectrometer and fuzzy uncorrelated discriminant transformation

Zhang

et al. 2022

J Food Process Engineering

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The quality of milk is related to its geographical origin. In addition, the geographical origin of milk plays an important role in its commercial value. Therefore, this research aimed to design an identification system including a portable near‐infrared (NIR) spectrometer and feature extraction algorithms to authenticate the geographical origin of milk. In order to improve the classification accuracy, fuzzy uncorrelated discriminant transformation (FUDT) was used to deal with the NIR spectra of milk collected by a portable NIR spectrometer. In this system, Savitzky–Golay (SG) algorithm and principal component analysis (PCA) were used to remove noise and reduce dimensionality, respectively. Then, three feature extraction algorithms, linear discriminant analysis (LDA), uncorrelated discriminant transformation (UDT), and FUDT were applied to separate the NIR spectra. Finally, K‐nearest neighbor (KNN) classifier was utilized to assess the performance of this identification system. The results showed that the maximum classification accuracies of FUDT, UDT, and LDA were 98.67%, 97.33%, and 93.33%, respectively. The results confirmed the great potential for authenticating the geographical origin of milk by the combination of the portable NIR spectrometer and FUDT. Practical Applications The geographical origin of milk is vitally important to evaluate the milk quality in dairy market. Compared with traditional detection methods, NIR spectroscopy is considered to be a fast, accurate, and nondestructive detection method, so it is widely used in the field of food detection. In this article, FUDT with portable NIR spectrometer can be used to detect the adulteration of geographical origin in milk correctly and rapidly. The experimental result indicated that application potential in identifying the geographical origin of milk.

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“…Weight index

m

is a significant factor when FDUT is used for feature extraction, which has a profound influence on the classification results of milk (Shen, Wu, Wu, Tan, & Liu, 2021). If

m

is too small, FUDT could not process the overlapped data points efficiently.…”

Section: Resultsmentioning

confidence: 99%

Rapid authentication of the geographical origin of milk using portable near‐infrared spectrometer and fuzzy uncorrelated discriminant transformation

Zhang

et al. 2022

J Food Process Engineering

Self Cite

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show abstract

“…The original spectra were easily influenced by the physical properties of the samples. The data shown in Figure 1 not only had the required sample characteristics but also were mixed with unnecessary information and noise [ 38 ]. Therefore, it was necessary to preprocess the spectra to achieve the purpose of enhancing the stability of the model [ 39 ].…”

Section: Methodsmentioning

confidence: 99%

Discrimination of the Red Jujube Varieties Using a Portable NIR Spectrometer and Fuzzy Improved Linear Discriminant Analysis

Yang

et al. 2022

Foods

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In order to quickly, nondestructively, and effectively distinguish red jujube varieties, based on the combination of fuzzy theory and improved LDA (iLDA), fuzzy improved linear discriminant analysis (FiLDA) algorithm was proposed to classify near-infrared reflectance (NIR) spectra of red jujube samples. FiLDA shows performs better than iLDA in dealing with NIR spectra containing noise. Firstly, the portable NIR spectrometer was employed to gather the NIR spectra of five kinds of red jujube, and the initial NIR spectra were pretreated by standard normal variate transformation (SNV), multiplicative scatter correction (MSC), Savitzky-Golay smoothing (S-G smoothing), mean centering (MC) and Savitzky-Golay filter (S-G filter). Secondly, the high-dimensional spectra were processed for dimension reduction by principal component analysis (PCA). Then, linear discriminant analysis (LDA), iLDA and FiLDA were applied to extract features from the NIR spectra, respectively. Finally, K nearest neighbor (KNN) served as a classifier for the classification of red jujube samples. The highest classification accuracy of this identification system for red jujube, by using FiLDA and KNN, was 94.4%. These results indicated that FiLDA combined with NIR spectroscopy was an available method for identifying the red jujube varieties and this method has wide application prospects.

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“…In this experiment, fresh Chinese cabbage ( Brassica rapa , Chinese group) were purchased from the same supermarket. 42 In total, 120 Chinese cabbage leaf samples were collected under similar growth conditions. All the samples were washed adequately with water (45 °C), which removed pesticide residues on the surface of the samples effectively.…”

Section: Methodsmentioning

confidence: 99%

Rapid determination of lambda-cyhalothrin residues on Chinese cabbage based on MIR spectroscopy and a Gustafson–Kessel noise clustering algorithm

et al. 2022

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Qualitative Analysis of Lambda-Cyhalothrin on Chinese Cabbage Using Mid-Infrared Spectroscopy Combined with Fuzzy Feature Extraction Algorithms

Cited by 12 publications

References 29 publications

Rapid authentication of the geographical origin of milk using portable near‐infrared spectrometer and fuzzy uncorrelated discriminant transformation

Rapid authentication of the geographical origin of milk using portable near‐infrared spectrometer and fuzzy uncorrelated discriminant transformation

Discrimination of the Red Jujube Varieties Using a Portable NIR Spectrometer and Fuzzy Improved Linear Discriminant Analysis

Rapid determination of lambda-cyhalothrin residues on Chinese cabbage based on MIR spectroscopy and a Gustafson–Kessel noise clustering algorithm

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