Monitoring and grading of tea by computer vision – A review

Gill, Gagandeep; Kumar, Amod; Agarwal, Ravinder

doi:10.1016/j.jfoodeng.2011.04.013

Cited by 59 publications

(41 citation statements)

References 51 publications

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“…Briefly, 0.5-1.0 g of the fresh, pre-treated leaves (before drying process) and powder were separately added with 0.1 g of CaCO 3 , followed by a pinch of purified acid sand and 20 ml of 80% acetone, then ground in a motor at ambient temperature for 5-10 min before taken to filter thought a Whatman No.1 filter paper. The residue was re-extracted with 5 ml of 80% acetone until tissue did not show any greenish color while solvent was colorless.…”

Section: Total Chlorophylls and Carotenoid Content Analysismentioning

confidence: 99%

Influence of hot water blanching process on phenolic profile and antioxidant activity of Cinnamomum porrectum herbal tea

Saetan

Usawakesmanee²,

Siripongvutikorn³

2016

FFHD

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Background: Cinnamomum porrectum leaves, one kind of Cinnamomum family, has recently been used to produce a locally herbal tea. Although C. porrectum essential oil and aqueous extract have been reported to have some biological activities, including antioxidant, antimicrobial, and anti-inflammatory activities, there is no scientific data using the blanching process for the production of herbal tea. Therefore, this experiment aimed to study the effect of hot water blanching before drying process on microstructure, nutrition content of the tea powder, TPC, TFC, antioxidant activities of infusion, as well as the phenolic profile of the extract.Objective: To determine effect of hot water blanching process on nutritional value, microstructure, phenolic profile, and antioxidant activity of the C. porrectum herbal tea.Methods: The C. porrectum leaves were divided into 2 groups; control (un-treated) and blanched before dried for herbal tea processing. The fresh leaves and the powders of control and blanched leaves were checked for proximate composition and chlorophyll contents, in addition to color value. The powders were determined microstructure by SEM. The infusions were determined to have color value and total extractable phenolic and flavonoid contents, as well as antioxidant activities. The hydrolyzed extracts of freeze dried infusion were subjected to identify phenolic profile by HPLC. Results: The blanched tea powder yielded a percentage of fat and protein contents higher than untreated due to easier extraction because of the bigger pore size found in microstructure. Chlorophyll content of blanched was decreased compared with the control sample. However, it was found that blanching could greater maintain green color of both powder and infusion.Additionally, blanching helped increased TPC, TFC extractability, and antioxidant activities in all assays except metal chelating property. Based on retention time and peak profile determined by using HPLC, it was found that both control and treated extracts consisted of similar main phenolic and flavonoid compounds however, only kaempferol was found in un-treated. Moreover, hydrolyzed blanched extract showed a higher intensity of 2 unknown compounds than un-treated. Though un-treated provided a higher intensity of pyrogallol, gallic acid, and cinnamic acid, the blanched exhibited a higher intensity of caffeic acid, protocatechuic acid, p-coumaric acid, and rutin. Conclusion:Blanching before drying expanded pore size of dried leaves, increased yield extractability, maintained color value, chlorophylls and increased TPC and TFC which related to antioxidant activities. Blanched extract provided higher intensity of some phenolic compounds than un-treated.

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Section: Total Chlorophylls and Carotenoid Content Analysismentioning

confidence: 99%

Influence of hot water blanching process on phenolic profile and antioxidant activity of Cinnamomum porrectum herbal tea

Saetan

Usawakesmanee²,

Siripongvutikorn³

2016

FFHD

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“…As shown in Figure 2, the concentrations of TF and TR as well as the desirable quality characteristics increase with fermentation time, reaching optimum levels and then degrading if the fermentation time is prolonged (Sanyal, 2011;Stodt et al, 2014). If fermentation time is extended, TF gradually degrade to TR, and the body of tea liquor becomes thick (Borah and Bhuyan, 2003;Gill et al, 2011). Over-fermented tea lacks many desirable qualities, although it has body.…”

Section: Effect Of the Fermentation Process Parameters On The Qualitymentioning

confidence: 99%

“…Over-fermented tea lacks many desirable qualities, although it has body. A quality cup of tea requires maintaining an optimum ratio of TF and TR (1:10) (Gill et al, 2011). At a 20°C fermentation temperature, total TF, total TR, brightness, briskness, and total color reach their maximum levels at 90, 120, 60, 60, and 120 min of fermentation, respectively ).…”

Section: Effect Of the Fermentation Process Parameters On The Qualitymentioning

confidence: 99%

Fermentation: The Key Step in the Processing of Black Tea

Pou¹

2016

Journal of Biosystems Engineering

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Background: The same plant, Camellia sinensis, is used to produce all types of tea, and the differences among the various types arise from the different processing steps that are used. Based on the degree of fermentation, tea can be classified as black, green, white, or oolong tea. Of these, black tea is the most or fully fermented tea. The oxidized polyphenolic compounds such as theaflavins (TF) and thearubigins (TR) formed during fermentation are responsible for the color, taste, flavor, and aroma of black tea. Results: Research indicates that an optimum ratio of TF and TR (1:10) is required to ensure a quality cup of tea. The concentrations of TF and TR as well as desirable quality characteristics increase as fermentation time increases, reaching optimum levels and then degrading if the fermentation time is prolonged. It is also necessary to control the environment for oxidation. There are no established environment conditions that must be maintained during the fermentation of the ruptured tea leaves. However, in most cases, the process is performed at a temperature of 24-29°C for 2-4 h or 55-110 min for orthodox tea or crush, tear, and curl (CTC) black tea, respectively, under a high relative humidity of 95-98% with an adequate amount of oxygen. Conclusion: The polyphenolic compounds in black tea such as TF and TR as well as un-oxidized catechins are responsible for the health benefits of tea consumption. Tea is rich in natural antioxidant activities and is reported to have great potential for the management of various types of cancers, oral health problems, heart disease and stroke, and diabetes and to have other health benefits such as the ability to detoxify, improve urine and blood flow, stimulate, and improve the immune system.

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“…Laddi et al [23] suggested acquiring tea granule images using a 3-CCD camera in the illumination condition of dual ring light. Gill et al [24] overviewed various computer vision based algorithms for texture and color analysis with a special orientation towards monitoring and grading of made tea. Zhang et al [25] combined three different types of features (shape, color, and texture) to identify fruit images.…”

Section: Introductionmentioning

confidence: 99%

Tea Category Identification Using a Novel Fractional Fourier Entropy and Jaya Algorithm

Zhang

Yang

Cattani

et al. 2016

Entropy

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This work proposes a tea-category identification (TCI) system, which can automatically determine tea category from images captured by a 3 charge-coupled device (CCD) digital camera. Three-hundred tea images were acquired as the dataset. Apart from the 64 traditional color histogram features that were extracted, we also introduced a relatively new feature as fractional Fourier entropy (FRFE) and extracted 25 FRFE features from each tea image. Furthermore, the kernel principal component analysis (KPCA) was harnessed to reduce 64 + 25 = 89 features. The four reduced features were fed into a feedforward neural network (FNN). Its optimal weights were obtained by Jaya algorithm. The 10ˆ10-fold stratified cross-validation (SCV) showed that our TCI system obtains an overall average sensitivity rate of 97.9%, which was higher than seven existing approaches. In addition, we used only four features less than or equal to state-of-the-art approaches. Our proposed system is efficient in terms of tea-category identification.

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Monitoring and grading of tea by computer vision – A review

Cited by 59 publications

References 51 publications

Influence of hot water blanching process on phenolic profile and antioxidant activity of Cinnamomum porrectum herbal tea

Influence of hot water blanching process on phenolic profile and antioxidant activity of Cinnamomum porrectum herbal tea

Fermentation: The Key Step in the Processing of Black Tea

Tea Category Identification Using a Novel Fractional Fourier Entropy and Jaya Algorithm

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