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

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 (R 2 ) which are obtained as 0.1722, 0.5162 and 0.95, respectively.Keywords Polyphenol Á Fine leaf count Á Near infrared reflectance (NIR) spectroscopy Á Folin Ciocalteu method Á Partial least squares (PLS) Á Preprocessing Á Root mean square error of cross-validation (RMSECV)

Rapid and Nondestructive Discrimination of Geographical Origins of Longjing Tea using Hyperspectral Imaging at Two Spectral Ranges Coupled with Machine Learning Methods

“…Visible/near-infrared spectroscopy (VNIRS) is widely used as a rapid and non-destructive technique for tea classification [6][7][8] and tea composition determination [9][10][11]. Hyperspectral imaging (HSI) is a technique integrating both spectroscopic techniques and imaging techniques, acquiring spectral and spatial information simultaneously.…”

“…In general, a certain amount of tea samples (contains tens or more tea leaves in a sample) is used for VINRS and HSI analysis and overlap of tea leaves occurs in this situation [6][7][8][9][10][17][18][19]. Thus it is difficult to identify adulterations in this amount of tea when some amounts of adulterations are mixed into the normal sample.…”

Estimation of Andrographolides and Gradation of Andrographis paniculata Leaves Using Near Infrared Spectroscopy Together With Support Vector Machine

“…Even when sample extracts are used, NIR spectroscopy obviates the use of further costly chemicals, equipment and time that are required in standard techniques like HPLC. NIR spectroscopy has been successfully used in several areas, like, in the tea leaf quality assessment ( Hazarika et al, 2018 ), in food safety assessment ( Cen and He, 2007 ; Lee and Herrman, 2016 ; Kusumaningrum et al, 2018 ) environmental chemistry, microfluidics, biomolecules ( Cho et al, 2009 ), cancer diagnostic agents, and forensic science ( Muehlethaler et al, 2016 ) as well as explosive detection.…”

Fresh Tea Sprouts Detection via Image Enhancement and Fusion SSD

“…Tang et al [4] proposed a Local Binary Pattern (LBP) and Gray-Level Co-Occurrence-Matrix-(GLCM-) based method for green tea leaves classification. A fresh tea leaves quantity assignment method by estimating total polyphenols using near infrared spectroscopy is introduced in [5]. Unfortunately, most existing studies focused on tea classification and quantity assignment [6,7], and the imaging condition is limited to indoor or laboratory [8].…”