Journal of Food Science and Technology

, Volume 55, Issue 12, pp 4867–4876 | Cite as

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

  • Ajanto Kumar Hazarika
  • Somdeb ChandaEmail author
  • Santanu Sabhapondit
  • Sandip Sanyal
  • Pradip Tamuly
  • Sahnaz Tasrin
  • Dilip Sing
  • Bipan Tudu
  • Rajib Bandyopadhyay
Original Article


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.


Polyphenol Fine leaf count Near infrared reflectance (NIR) spectroscopy Folin Ciocalteu method Partial least squares (PLS) Preprocessing Root mean square error of cross-validation (RMSECV) 



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.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

13197_2018_3421_MOESM1_ESM.doc (39 mb)
Supplementary material 1 (DOC 39905 kb)


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Copyright information

© Association of Food Scientists & Technologists (India) 2018

Authors and Affiliations

  1. 1.Tocklai Tea Research InstituteJorhatIndia
  2. 2.Department of Instrumentation and Electronics EngineeringJadavpur UniversitySalt Lake, KolkataIndia
  3. 3.Laboratory of Artificial Sensory SystemsITMO UniversitySaint PetersburgRussia

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