Feasibility study for the analysis of coconut water using fluorescence spectroscopy coupled with PARAFAC and SVM methods

Gu, Haiyang; Liu, Kaiqi; Huang, Xingyi; Chen, Quansheng; Sun, Yanhui; Tan, Chin Ping

doi:10.1108/bfj-12-2019-0941

Cited by 8 publications

(5 citation statements)

References 22 publications

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“…Nevertheless, currently, many advanced and instrumental methods are being used for analyzing and evaluating the quality and authenticity of coconut water [ 39 , 69 , 70 ]. Coconut water also contains many relatively poorly investigated and unknown solutes with special biological effects.…”

Section: Resultsmentioning

confidence: 99%

Contemporary Developments and Emerging Trends in the Application of Spectroscopy Techniques: A Particular Reference to Coconut (Cocos nucifera L.)

et al. 2022

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The number of food frauds in coconut-based products is increasing due to higher consumer demands for these products. Rising health consciousness, public awareness and increased concerns about food safety and quality have made authorities and various other certifying agencies focus more on the authentication of coconut products. As the conventional techniques for determining the quality attributes of coconut are destructive and time-consuming, non-destructive testing methods which are accurate, rapid, and easy to perform with no detrimental sampling methods are currently gaining importance. Spectroscopic methods such as nuclear magnetic resonance (NMR), infrared (IR)spectroscopy, mid-infrared (MIR)spectroscopy, near-infrared (NIR) spectroscopy, ultraviolet-visible (UV-VIS) spectroscopy, fluorescence spectroscopy, Fourier-transform infrared spectroscopy (FTIR), and Raman spectroscopy (RS) are gaining in importance for determining the oxidative stability of coconut oil, the adulteration of oils, and the detection of harmful additives, pathogens, and toxins in coconut products and are also employed in deducing the interactions in food constituents, and microbial contaminations. The objective of this review is to provide a comprehensive analysis on the various spectroscopic techniques along with different chemometric approaches for the successful authentication and quality determination of coconut products. The manuscript was prepared by analyzing and compiling the articles that were collected from various databases such as PubMed, Google Scholar, Scopus and ScienceDirect. The spectroscopic techniques in combination with chemometrics were shown to be successful in the authentication of coconut products. RS and NMR spectroscopy techniques proved their utility and accuracy in assessing the changes in coconut oil’s chemical and viscosity profile. FTIR spectroscopy was successfully utilized to analyze the oxidation levels and determine the authenticity of coconut oils. An FT-NIR-based analysis of various coconut samples confirmed the acceptable levels of accuracy in prediction. These non-destructive methods of spectroscopy offer a broad spectrum of applications in food processing industries to detect adulterants. Moreover, the combined chemometrics and spectroscopy detection method is a versatile and accurate measurement for adulterant identification.

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Section: Resultsmentioning

confidence: 99%

Contemporary Developments and Emerging Trends in the Application of Spectroscopy Techniques: A Particular Reference to Coconut (Cocos nucifera L.)

et al. 2022

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“…In fact, the probability density function of the observed data is constant and satisfies p i1 (y) = p i2 (y) = … = p ik (y). The intensity waveform is updated with the number of iterations, so the probability density function of the observation data under the condition of additive white Gaussian noise can be defined as formula (32).…”

Section: Proposed Methodsmentioning

confidence: 99%

“…The main purpose of the analysis of this data type is to determine which chemicals are present in each sample and their relative concentrations. Reference [32] conducted a comparison between parallel factor analysis (PARA FAC) and support vector machine (SVM) to identify and distinguish the fluorescence spectrum of coconut water brands. The above results indicate that fluorescence spectroscopy combined with PARAFAC and SVM method has been proved to be a simple and rapid detection method for coconut water and other beverages.…”

Section: Introductionmentioning

confidence: 99%

Multi-source and multi-fault condition monitoring based on parallel factor analysis and sequential probability ratio test

Yang¹,

Chen

Ke³

et al. 2021

EURASIP J. Adv. Signal Process.

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The monitoring of mechanical equipment systems contains an increasing number of complex content, expanding from traditional time, and frequency information to three-dimensional data of the time, space, and frequency information, and even higher-dimensional data containing subjects, experimental conditions. For high-dimensional data analysis, traditional decomposition methods such as Hilbert transform, fast Fourier transformation, and Gabor transformation not only lose the integrity of the data, but also increase the amount of calculation and introduce a lot of redundant information. The phenomenon of feature coupling, aliasing, and redundancy between the mechanical multi-source data signals will cause the inaccuracy of the evaluation, diagnosis, and prediction of industrial production operation status. The analysis of the three-way tensor composed of channel, frequency, and time is called parallel factor analysis (PARAFAC). The properties between the parallel factor analysis results and the input signals are studied through simulation experiments. Parallel factor analysis is used to decompose the third-order tensor composed of channel-time-frequency after continuous wavelet transformation of vibration signal into channel, time, and frequency characteristics. Multi-scale parallel factor analysis successfully extracted non-linear multi-dimensional dynamic fault characteristics by generating the spatial, spectral, time-domain signal loading value and three-dimensional fault characteristic expression. In order to verify the effectiveness of the space, frequency, and time domain signal loading values of the fault characteristic factors generated by the centrifugal pump system after parallel factor analysis, the characteristic factors obtained after parallel factor analysis are used as the SPRT test sequence for identification and verification. The results indicate that the method proposed in this article improves the measurement accuracy and intelligence of mechanical fault detection.

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“…SVM algorithms are typically used for chemical concentration detection [17][18][19][20]. C. Robert [21] used both linear and non-linear SVM models to identify complete beef and lamb meats.…”

Section: Introductionmentioning

confidence: 99%

Research on the chemical oxygen demand spectral inversion model in water based on IPLS-GAN-SVM hybrid algorithm

Lu,

Zou,

et al. 2024

PLoS ONE

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Spectral collinearity and limited spectral datasets are the problems influencing Chemical Oxygen Demand (COD) modeling. To address the first problem and obtain optimal modeling range, the spectra are preprocessed using six methods including Standard Normal Variate, Savitzky-Golay Smoothing Filtering (SG) etc. Subsequently, the 190–350 nm spectral range is divided into 10 subintervals, and Interval Partial Least Squares (IPLS) is used to perform PLS modeling on each interval. The results indicate that it is best modeled in the 7th range (238~253 nm). The values of Mean Square Error (MSE), Mean Absolute Error (MAE) and R2score of the model without pretreatment are 1.6489, 1.0661, and 0.9942. After pretreatment, the SG is better than others, with MSE and MAE decreasing to 1.4727, 1.0318 and R2score improving to 0.9944. Using the optimal model, the predicted COD for three samples are 10.87 mg/L, 14.88 mg/L, and 19.29 mg/L. To address the problem of the small dataset, using Generative Adversarial Networks for data augmentation, three datasets are obtained for Support Vector Machine (SVM) modeling. The results indicate that, compared to the original dataset, the SVM’s MSE and MAE have decreased, while its accuracy has improved by 2.88%, 11.53%, and 11.53%, and the R2score has improved by 18.07%, 17.40%, and 18.74%.

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Feasibility study for the analysis of coconut water using fluorescence spectroscopy coupled with PARAFAC and SVM methods

Cited by 8 publications

References 22 publications

Contemporary Developments and Emerging Trends in the Application of Spectroscopy Techniques: A Particular Reference to Coconut (Cocos nucifera L.)

Contemporary Developments and Emerging Trends in the Application of Spectroscopy Techniques: A Particular Reference to Coconut (Cocos nucifera L.)

Multi-source and multi-fault condition monitoring based on parallel factor analysis and sequential probability ratio test

Research on the chemical oxygen demand spectral inversion model in water based on IPLS-GAN-SVM hybrid algorithm

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