Nondestructive identification of tea (Camellia sinensis L.) varieties using FT-NIR spectroscopy and pattern recognition

Chen, Quansheng; Zhao, Jiewen; MuHua, Liu; Cai, Jun

doi:10.17221/1125-cjfs

Cited by 27 publications

(15 citation statements)

References 24 publications

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“…2), which indicated linear response of the instrument along with sample concentrations within the range of study. Similar spectral responses were obtained for determining the sweetness of orange juice in terms of total soluble solids [12] for determination of curcuminoids from turmeric powder [13] and for quality of sugarcane juice using FT-NIR [14].…”

Section: Nir Spectrummentioning

confidence: 59%

Sugarcane/Sugarcane Juice Quality Evaluation by FT-NIR Spectrometer

Tripathi¹,

Singh²,

Mali³

et al. 2017

Int.J.Curr.Microbiol.App.Sci

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Section: Nir Spectrummentioning

confidence: 59%

Sugarcane/Sugarcane Juice Quality Evaluation by FT-NIR Spectrometer

Tripathi¹,

Singh²,

Mali³

et al. 2017

Int.J.Curr.Microbiol.App.Sci

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“…PCA is a data reconstruction and dimension reduction method, which projects the maximum variance and minimum correlation in the data set and indicates the data trend in a visualizing dimension space by principal component (PC) scores (Chen et al . ; Bhattacharyya et al . ).…”

Section: Resultsmentioning

confidence: 99%

“…Moreover, organoleptic assessments are often influenced by physiological, psychological and environmental factors, which gives rise to inconsistent and unreliable evaluations (Chen et al . ) and could not satisfy an urgent requirement of quality appraisals of large amounts of samples (Pang et al . ).…”

Section: Introductionmentioning

confidence: 99%

Analysis on Quality Indicators of Taste and Infusion Color and Discrimination of Famous and Superior Green Tea with Different Appearances in Fujian Province, PR China

Guo

Lai

2015

Journal of Food Processing and Preservation

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Compared to traditional sensory quality evaluation, chemical components and color values in CIE-Lab space are looked as indicators to assess tea quality objectively. This study spectrophotometrically analyzed quality indicators of famous and superior green tea (FSGT) with three appearance types in the Fujian Province, PR China and applied chemometrics methods to discriminate them. By factor analysis, all indicators were classified into four factors, evaluating FSGT quality in (1) lightness, yellowness and saturation of infusion color and astringency and bitterness of taste; (2) umami and mellowness; (3) greenness; and (4) body. By the principal component (PC) analysis, three appearance types were separated from each other with the cumulative variance contribution rate of 88.35% for the first three PCs based on indicators of taste and 90.30% for the first two PCs based on indicators of infusion color, respectively. By Bayes discrimination analysis, three decision functions were established to effectively discriminate three appearance types of FSGT. PRACTICAL APPLICATIONSFujian is one of the popular provinces producing green tea in China and has a long history of processing famous and superior green tea (FSGT), which have the best quality and are usually known for their distinctive appearances and flavors. FGST qualities among different appearances or within the same appearance originating from different areas or using different cultivars often have distinctive qualities and maybe have similar qualities. Traditionally, FGST qualities are appraised and discriminated by the sensory evaluation, which is subjective and difficult to describe qualities quantitatively. Chemometrics methods use chemical components as indicators, which are objective and achieve quantified qualities. Therefore, they could be used as advantageous complements or references for traditional sensory evaluation.

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“…Determination coefficient (R 2 ) indicated a strong relationship between predicted value and actual value of curcuminoid content. This technique has been standardized for the determination of various parameters including tetracycline in milk (Sivakesava and Irudayaraj 2002), identification of tea varieties (Chen et al 2008), sweetness of orange juice (Jha 2007) and lignin content in Acacia. spp.…”

Section: Resultsmentioning

confidence: 99%

Nondestructive determination of curcuminoids from turmeric powder using FT-NIR

2010

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Nondestructive method of measuring curcuminoid content of turmeric powder was developed by fourier transform near infrared (FT-NIR) spectrometer. Also, the calibration models describing the relationship between curcuminoid content and the NIR spectra of the turmeric powder were developed and evaluated. To develop the model, NIR reflectance spectra were acquired for each turmeric powder sample. Spectra were pre-processed by applying different spectra correction algorithms. The relationship between spectrometric curcuminoid content and FT-NIR spectra of turmeric powder was examined through partial least square (PLS) regression method in the wave number range of 6102 to 4246 cm(-1). The root mean square error of cross-validation and test set validation were 0.104 and 0.201 whereas the determination coefficient (R(2)) for both the validations were 97.64 and 87.53, respectively. A low value of root mean square error and high value of R(2) indicates a high correlation between the concentration and spectral data. Thus the FT-NIR offers a viable alternative to spectroscopic procedures as well as the method is time and cost effective for determination of curcuminoid content of turmeric.

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Nondestructive identification of tea (Camellia sinensis L.) varieties using FT-NIR spectroscopy and pattern recognition

Cited by 27 publications

References 24 publications

Sugarcane/Sugarcane Juice Quality Evaluation by FT-NIR Spectrometer

Sugarcane/Sugarcane Juice Quality Evaluation by FT-NIR Spectrometer

Analysis on Quality Indicators of Taste and Infusion Color and Discrimination of Famous and Superior Green Tea with Different Appearances in Fujian Province, PR China

Nondestructive determination of curcuminoids from turmeric powder using FT-NIR

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