Measurement of the Ratio of Tea Polyphenols to Amino Acids in Green Tea Infusion Based on near Infrared Spectroscopy

This study attempted the feasibility to determine the ratio of tea polyphenols to amino acids in green tea infusion using near infrared (NIR) spectroscopy combined with synergy interval PLS (siPLS) algorithms. First, SNV was used to preprocess the original spectra of tea infusion; then, siPLS was used to select the efficient spectra regions from the preprocessed spectra. Experimental results showed that the spectra regions [7 8 18] were selected, which were out of the strong absorption of H2O. The optimal PLS model was developed with the selected regions when 6 PCs components were contained. The RMSEP value was equal to 0.316 and the correlation coefficient (R) was equal to 0.8727 in prediction set. The results demonstrated that NIR can be successfully used to determinate the ration of tea polyphenols to amino acids in green tea infusion.

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Analysis of degree maturation of edam cheese by FT Near Infrared Spectroscopy

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis ◽

10.11118/actaun200856010221 ◽

2008 ◽

Vol 56 (1) ◽

pp. 221-228

Author(s):

Květoslava Šustová ◽

Jana Růžičková

Keyword(s):

Infrared Spectroscopy ◽

Correlation Coefficient ◽

Near Infrared Spectroscopy ◽

Dry Matter ◽

Near Infrared ◽

Nir Spectroscopy ◽

Optical Probe ◽

Raw Material ◽

Soluble Nitrogen ◽

Processed Cheese

This work deals with use of FT NIR spectroscopy to speedy analysis of maturation of edam cheese. Maturation of cheese was study with the measure of soluble nitrogen, tyrosine and tryptophane. This method can be able to make optimal making raw material to production of processed cheese. Samples of edam cheese (45% fat in dry matter) were analysed with time of ripening 7 to 99 days. Soluble nitrogen, tyrosine and tryptophane were analysed on UV–VisSpectrometer (270 and 290 nm). Sequentially samples were analysed on FT NIR spectrometer of two methods: 1) slice of cheese was analysed help with optical probe, 2) grated cheese was analysed on the integration sphere. The values of correlation coefficient of calibration on the integration sphere were as follows: soluble nitrogen 0.922, tyrosine 0.911 and tryptophane 0.852. The values of correlation coefficient of calibration with optical probe were as follows: soluble nitrogen 0.996, tyrosine 0.958 and tryptophane 0.922.

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Textile Recognition and Sorting for Recycling at an Automated Line Using Near Infrared Spectroscopy

Recycling ◽

10.3390/recycling6010011 ◽

2021 ◽

Vol 6 (1) ◽

pp. 11

Author(s):

Kirsti Cura ◽

Niko Rintala ◽

Taina Kamppuri ◽

Eetta Saarimäki ◽

Pirjo Heikkilä

Keyword(s):

Infrared Spectroscopy ◽

Near Infrared Spectroscopy ◽

Near Infrared ◽

Nir Spectroscopy ◽

Automated Recognition ◽

Textile Materials ◽

Input Material ◽

Adequate Quality ◽

Automated Line

In order to add value to recycled textile material and to guarantee that the input material for recycling processes is of adequate quality, it is essential to be able to accurately recognise and sort items according to their material content. Therefore, there is a need for an economically viable and effective way to recognise and sort textile materials. Automated recognition and sorting lines provide a method for ensuring better quality of the fractions being recycled and thus enhance the availability of such fractions for recycling. The aim of this study was to deepen the understanding of NIR spectroscopy technology in the recognition of textile materials by studying the effects of structural fabric properties on the recognition. The identified properties of fabrics that led non-matching recognition were coating and finishing that lead different recognition of the material depending on the side facing the NIR analyser. In addition, very thin fabrics allowed NIRS to penetrate through the fabric and resulted in the non-matching recognition. Additionally, ageing was found to cause such chemical changes, especially in the spectra of cotton, that hampered the recognition.

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Intelligent evaluation of taste constituents and polyphenols-to-amino acids ratio in matcha tea powder using near infrared spectroscopy

Food Chemistry ◽

10.1016/j.foodchem.2021.129372 ◽

2021 ◽

Vol 353 ◽

pp. 129372

Author(s):

Zhiming Guo ◽

Alberta Osei Barimah ◽

Limei Yin ◽

Quansheng Chen ◽

Jiyong Shi ◽

...

Keyword(s):

Amino Acids ◽

Infrared Spectroscopy ◽

Near Infrared Spectroscopy ◽

Near Infrared

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Quality Control of Japanese Green Tea by Near Infrared Spectroscopy.

Chagyo Kenkyu Hokoku (Tea Research Journal) ◽

10.5979/cha.1996.29 ◽

1996 ◽

pp. 29-34 ◽

Cited By ~ 1

Author(s):

Toshio HARA

Keyword(s):

Quality Control ◽

Infrared Spectroscopy ◽

Green Tea ◽

Near Infrared Spectroscopy ◽

Near Infrared

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Determination of Tea Polyphenols Content in Puerh Tea Using Near-Infrared Spectroscopy Combined with Extreme Learning Machine and GA-PLS Algorithm

Laser & Optoelectronics Progress ◽

10.3788/lop50.043001 ◽

2013 ◽

Vol 50 (4) ◽

pp. 043001

Author(s):

张海东 Zhang Haidong ◽

李贵荣 Li Guirong ◽

李若诚 Li Ruocheng ◽

许文方 Xu Wenfang ◽

华英杰 Hua Yingjie

Keyword(s):

Infrared Spectroscopy ◽

Extreme Learning Machine ◽

Near Infrared Spectroscopy ◽

Near Infrared ◽

Tea Polyphenols ◽

Learning Machine

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Near infrared spectroscopy as an alternative method for rapid determination of the solidification point of 2,4,6-trinitrotoluene in production

Journal of Near Infrared Spectroscopy ◽

10.1177/0967033519845080 ◽

2019 ◽

Vol 27 (4) ◽

pp. 286-292

Author(s):

Chongchong She ◽

Min Li ◽

Yunhui Hou ◽

Lizhen Chen ◽

Jianlong Wang ◽

...

Keyword(s):

Infrared Spectroscopy ◽

Near Infrared Spectroscopy ◽

Near Infrared ◽

Rapid Determination ◽

Nir Spectroscopy ◽

Principal Component ◽

Quality Parameter ◽

Solidification Point ◽

Fast Analysis ◽

Online Application

The solidification point is a key quality parameter for 2,4,6-trinitrotoluene (TNT). The traditional solidification point measurement method of TNT is complicated, dangerous, not environmentally friendly and time-consuming. Near infrared spectroscopy (NIR) analysis technology has been applied successfully in the chemical, petroleum, food, and agriculture sectors owing to its characteristics of fast analysis, no damage to the sample and online application. The purpose of this study was to study near infrared spectroscopy combined with chemometric methods to develop a fast and accurate quantitative analysis method for the solidification point of TNT. The model constructed using PLS regression was successful in predicting the solidification point of TNT ([Formula: see text] = 0.999, RMSECV = 0.19, RPDCa = 33.5, [Formula: see text] = 0.19, [Formula: see text] = 0.999). Principal component analysis shows that the model could identify samples from different reactors. The results clearly demonstrate that the solidification point can be measured in a short time by NIR spectroscopy without any pretreatment for the sample and skilled laboratory personnel.

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The Kinetic Model of the Peel Brittleness of Stored Cucumis Melons Based on Visible/Near-Infrared Spectroscopy

Journal of Spectroscopy ◽

10.1155/2020/1402965 ◽

2020 ◽

Vol 2020 ◽

pp. 1-7

Author(s):

Defang Xu ◽

Huamin Zhao ◽

Shujuan Zhang ◽

Chengji Li ◽

Fei Zhao

Keyword(s):

Infrared Spectroscopy ◽

Kinetic Model ◽

Correlation Coefficient ◽

Root Mean Square ◽

Near Infrared Spectroscopy ◽

Storage Time ◽

Near Infrared ◽

Mean Square ◽

Zero Order Reaction ◽

Variation Tendency

A kinetic model based on visible/near-infrared spectroscopy of the peel brittleness of “Xintian-125” Cucumis melons, the research object, stored under room temperature, was established in order to realize real-time monitoring of the peel brittleness of Cucumis melons and for prediction of storage time. The NIR and peel brittleness of melons stored for 1, 4, and 7 days were collected and measured. SG was confirmed to be the best pretreatment by comparing the PLS models established with 4 pretreatment methods, and the differences of the prediction set determination coefficient and root-mean-square were 0.818 and 23.755, respectively. CARS and SPA were adopted to extract the feature wavelengths and establish the peel brittleness of PLS prediction model. The model’s prediction accuracy was 0.919, and the prediction root-mean-square was 25.413, indicating that NIR is able to realize the prediction of the peel brittleness of Cucumis melons. As a result, a NIR-based peel brittleness kinetic model was created. The P value of the regression model was less than 0.001, and the model’s correlation coefficient was 0.8503, showing that the model is of extreme significance and high precision. The zero-order reaction equation was overfitted according to the variation tendency of the average peel brittleness of stored melons. The model’s correlation coefficient was 0.981, the standard error was 4.624, and the linear relation between the stored period and NIR was established based on it. The research proves that the NIR-based technology is able to realize quick and loss-free inspection of melons’ peel brittleness and prediction of the stored period.

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Seeing the light: NIR at the coalface (the inaugural Blakeney Address)

NIR news ◽

10.1177/0960336018782034 ◽

2018 ◽

Vol 29 (5) ◽

pp. 7-11

Author(s):

Peter Flinn

Keyword(s):

Infrared Spectroscopy ◽

Near Infrared Spectroscopy ◽

Near Infrared ◽

Nir Spectroscopy ◽

Scientific Development ◽

Unique Contribution ◽

Learned Societies ◽

To Receive ◽

Highly Cited

Anthony Bernard (Tony) Blakeney (1948–2015) made a unique contribution to near infrared (NIR) spectroscopy in Australia and to the development of the Australian Near Infrared Spectroscopy Group (ANISG). An eminent and highly cited grain scientist and carbohydrate chemist, in the 1980s he recognised that NIR-based analyses could aid the production of more and higher quality cereals. Tony was ANISG Treasurer from its inception in 1988 until 2015 and was recognised as a champion of learned societies and their importance in scientific development. This presentation is in honour of Tony’s achievements, and it is a great honour to receive the inaugural award in his name.

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