Non-destructive discrimination of Chinese bayberry varieties using Vis/NIR spectroscopy

Liu, Yuanyuan; He, Yong; Fang, Hui

doi:10.1016/j.jfoodeng.2006.10.033

Cited by 83 publications

(41 citation statements)

References 15 publications

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“…Vis/NIR spectroscopy has shown potential usage in various agricultural and food products for freshness discrimination due to its non-destruction, no pollution, easy operation, capability of on-line analysis, [9] variety classification, [10] bruise identification, [11] and adulteration analysis. [12] Also, this method has been reported for aquatic products quality analysis.…”

Section: Study Of Golden Pompano (Trachinotusmentioning

confidence: 99%

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Study of golden pompano (Trachinotus ovatus) freshness forecasting method by utilising Vis/NIR spectroscopy combined with electronic nose

Zhang

Zhou

Chang

et al. 2018

International Journal of Food Properties

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Golden pompano (Trachinotus ovatus) quality forecasting method utilising Vis/ NIR spectroscopy combined with electronic nose (EN) was investigated in this article. Responses of Vis/NIR spectroscopy and EN to pompanos stored at 4°C were measured for 6 days. Physical/chemical indexes including texture, total volatile basic nitrogen, pH, total viable counts, and human sensory evaluation were synchronously examined as quality references. Chemometric methods including principal component analysis (PCA) and stochastic resonance (SR) were employed for spectroscopic and EN data analysis. Physicochemical examination demonstrated that fish quality decreased rapidly during storage. PCA qualitatively classified freshness degree of pompano samples, while SR signalto-noise ratio (SNR) spectrum using SNR maximum quantitatively characterised quality for all samples. Golden pompano quality predictive models were developed based on spectroscopy, EN, and spectroscopy combined with EN, respectively. Results demonstrated that the model developed based on spectroscopy combined with EN presented a forecasting accuracy of 93.3%. ARTICLE HISTORY

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Section: Study Of Golden Pompano (Trachinotusmentioning

confidence: 99%

“…Table 1 displays the sensory evaluation details. Voting number is set at k, k∈ (1,10). The quality of pompano is divided into m levels, and the score of a specific level is set at h j , j∈(1,m).…”

Section: Total Viable Countsmentioning

confidence: 99%

Study of golden pompano (Trachinotus ovatus) freshness forecasting method by utilising Vis/NIR spectroscopy combined with electronic nose

Zhang

Zhou

Chang

et al. 2018

International Journal of Food Properties

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“…The latter was found to be the better one: the classifying correctness was 91.2% in fruit's stem-calyx axis horizontal. Three defective pears and one sound pear (correctness 89.2%) were misclassified during calibration Interactance Eating quality [92] Grape N/A Acidity [39] Olive Reflectance Oil content, moisture, fatty acids [93] Chinese bayberry Reflectance Variety [94] Mangosteen Transmittance Translucent flesh disorder [95] process and for validation, no defective pear was predicted incorrectly and only one sound pear was predicted as defect (correctness 95%). Discriminant analysis with Mahalanobis Distance (MD) analysis can discriminate between brown core and normal pears and grade the brown core pears to three classes, based on NIR region of 651-1282 nm wavelengths.…”

Section: Defect Determinationmentioning

confidence: 99%

Theory and application of near infrared spectroscopy in assessment of fruit quality: a review

Lin

Ying

2009

Sens. & Instrumen. Food Qual.

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Fruits provide nutrients for human body and are able to prevent sorts of non-communicable diseases. The fruit quality test is an area that both technology and market section concern about. Near infrared spectroscopy (NIR) is a rapid, precise, and non-destructive technique which can be well utilized in determination of fruit quality. This review paper summarizes the theory of NIR analysis, and the fundamental structure of instruments based on NIR for fruit quality assessment. Chemometrics for NIR spectroscopy involving analysis methods of data pre-processing, calibration, model transfer and evaluation, is also included. In recent 11 years, significant progresses were achieved in fruit quality assessment via NIR spectroscopy, which is the main focus in this review. Furthermore, urgent problems in this research field are discussed, expecting to be solved in the near future.

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“…Establishing a rapid and non-destructive method for discrimination origins and species of agricultural food is of important interest. There are also examples of the use of spectroscopy especially the near infrared (NIR) spectroscopy (Liu et al, 2010;Li et al, 2007;Ritthiruangdej and Suwonsichon, 2007;Christy et al, 2004). Raman spectroscopy (Abbas et al, 2009;Bicanic et al, 2010;de Veij et al, 2008) is also a method of choice for determination and quantification in food products.…”

Section: Introductionmentioning

confidence: 99%

Rapid Classification of Citrus Fruits Based on Raman Spectroscopy and Pattern Recognition Techniques

Feng

Zhang

Zhu

2013

FSTR

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Citrus fruits are major agricultural products of China and they are rich sources of health beneficial substances. In this study, Raman spectroscopy as a rapid and non-destructive tool was employed to classify eight different citrus fruits. Baseline drift caused by fluorescence of organic compounds in the citrus samples interferes with the Raman signals. A polynomial fitting based method was adopted for baseline correction, which is a key factor both for Raman peaks assignment and subsequent pattern recognition. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were the two selected pattern recognition techniques. PCA showed the distribution of sweet oranges and mandarins, and HCA was a useful guide for detailed relationship between various citrus samples. The results demonstrated that Raman spectroscopy combined with pattern recognition techniques has substantial potential for discriminating varieties of citrus fruits.

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Non-destructive discrimination of Chinese bayberry varieties using Vis/NIR spectroscopy

Cited by 83 publications

References 15 publications

Study of golden pompano (Trachinotus ovatus) freshness forecasting method by utilising Vis/NIR spectroscopy combined with electronic nose

Study of golden pompano (Trachinotus ovatus) freshness forecasting method by utilising Vis/NIR spectroscopy combined with electronic nose

Theory and application of near infrared spectroscopy in assessment of fruit quality: a review

Rapid Classification of Citrus Fruits Based on Raman Spectroscopy and Pattern Recognition Techniques

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