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Quality assessment of fresh tea leaves by estimating total polyphenols using near infrared spectroscopy

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Abstract

This paper reports on the development of an integrated leaf quality inspecting system using near infrared reflectance (NIR) spectroscopy for quick and in situ estimation of total polyphenol (TP) content of fresh tea leaves, which is the most important quality indicator of tea. The integrated system consists of a heating system to dry the fresh tea leaves to the level of 3–4% moisture, a grinding and sieving system fitted with a 250 micron mesh sieve to make fine powder from the dried leaf. Samples thus prepared are transferred to the NIR beam and TP is measured instantaneously. The wavelength region, the number of partial least squares (PLS) component and the choice of preprocessing methods are optimized simultaneously by leave-one-sample out cross-validation during the model calibration. In order to measure polyphenol percentage in situ, the regression model is developed using PLS regression algorithm on NIR spectra of fifty-five samples. The efficacy of the model developed is evaluated by the root mean square error of cross-validation, root mean square error of prediction and correlation coefficient (R2) which are obtained as 0.1722, 0.5162 and 0.95, respectively.

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Acknowledgements

The research work has been carried out in collaboration with Tocklai Tea Research Institute (TTRI), Jorhat, Assam, India. The work has been financially supported by National Tea Research Foundation (NTRF), India.

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Authors and Affiliations

  1. Tocklai Tea Research Institute, Jorhat, Assam, India

    Ajanto Kumar Hazarika, Santanu Sabhapondit, Sandip Sanyal, Pradip Tamuly & Sahnaz Tasrin

  2. Department of Instrumentation and Electronics Engineering, Jadavpur University, Salt Lake Campus, Block LB, Sector III, Plot 8, Salt Lake, Kolkata, 700 098, India

    Somdeb Chanda, Dilip Sing, Bipan Tudu & Rajib Bandyopadhyay

  3. Laboratory of Artificial Sensory Systems, ITMO University, Saint Petersburg, Russia

    Rajib Bandyopadhyay

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  1. Ajanto Kumar Hazarika
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  2. Somdeb Chanda
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  3. Santanu Sabhapondit
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  4. Sandip Sanyal
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  5. Pradip Tamuly
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  7. Dilip Sing
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  8. Bipan Tudu
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  9. Rajib Bandyopadhyay
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Correspondence to Somdeb Chanda.

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Hazarika, A.K., Chanda, S., Sabhapondit, S. et al. Quality assessment of fresh tea leaves by estimating total polyphenols using near infrared spectroscopy. J Food Sci Technol 55, 4867–4876 (2018). https://doi.org/10.1007/s13197-018-3421-6

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  • DOI: https://doi.org/10.1007/s13197-018-3421-6

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