A Machine Vision System For Estimation Of Theaflavins And Thearubigins In Orthodox Black Tea

Abstract

-Orthodox black tea quality depends upon the amount of certain organic compounds present and out of these, theaflavins (TF) and thearubigins (TR) are the most important ones While TF is responsible for attractive golden colour, increased brightness and astringency in tea liquor, TR is reddish brown, reduces the brightness of tea liquor and contribute mostly for the ashy taste of the liquor with minor improvement in astringency. The rapid estimation of TF and TR thus may resolve the problem of certain uncertainty or ambiguity that may arise during quality assessment of tea by the tea tasters. In this paper, a new method for rapid measurement of concentration of TF and TR is described using a machine vision system taking images of tea liquor and employing artificial neural networks (ANN). The results show good correlation of estimated values of TF and TR with the actual concentrations obtained using ultraviolet-visible spectrophotometer (UV-VIS).

An internet of things (IoT)-based optimum tea fermentation detection model using convolutional neural networks (CNNs) and majority voting techniques

“…Consequently, CNNs are now being applied in monitoring tea processing, including the detection of optimum fermentation of tea (Kimutai et al, 2020;Kamrul et al, 2020). Furthermore, a neural-network-based model for estimating the basic components of tea theaflavins (TF) and thearubigins (TR) is proposed (Akuli et al, 2016). Chen et al (2010) fused near-infrared spectroscopy with computer vision to detect optimum fermentation in tea.…”

“…reducing heart diseases, aiding in weight management, preventing strokes, lowering blood pressure, preventing bone loss, and boosting the immune system, among others. Historical evidence indicates that the tea plant was indigenous to China and Burma, among other countries (Akuli et al, 2016). Ta-ble 1 presents the current leading tea-producing countries.…”

Emerging Technologies Based on Artificial Intelligence to Assess the Quality and Consumer Preference of Beverages

“…On the other hand, Kumar et al [68] used a charge-coupled device camera to evaluate the color of tea liquor in the RGB scale and transformed it to CIELab, as this is considered as closer to human color perception. In a more recent study, Akuli et al [69] developed a method to assess color in tea liquor or infused tea using a black box with uniform illumination, and a low-cost camera positioned 30 cm above the sample, and thus they obtained color in both RBG and CIELab scales.…”

Application of Electronic Nose to Predict the Optimum Fermentation Time for Low-Country Sri Lankan Tea

“…e levels of TF increase during fermentation and reach a maximum point and then decrease while thearubigin is increasing [3,4] with time. e golden color of tea liquor corresponds to high TF content, while the dull color in tea liquor is a result of over fermentation [5]. If the tea particles are underfermented or overfermented, it leads to less tea quality.…”

“…Innovative technologies were developed by several research groups using the electronic eye method [5,11,[13][14][15][16][17][18], the electronic tongue method [19][20][21][22], and the electronic nose method [23][24][25][26][27][28][29][30][31][32][33][34][35] that aim at minimizing human intervention. At present, the electronic nose methods are often utilized to classify different types of tea or different tea grades [24,26,31,35].…”