Particle Size Distribution of High Grown Broken Orange Pekoe (Bop) Tea

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dc.contributor.author Shehani, M.G.D.
dc.date.accessioned 2021-10-08T04:53:34Z
dc.date.available 2021-10-08T04:53:34Z
dc.date.issued 2016
dc.identifier.other UWU/TEA/12/0024
dc.identifier.uri http://www.erepo.lib.uwu.ac.lk/bitstream/handle/123456789/7172/UWULD%20TEA%2012%200024-08052019094523.pdf?sequence=1&isAllowed=y
dc.description.abstract Tea grades are popularly described by various names according to their certain particle sizes. A knowledge of the particle size distribution of tea grades is important in testing them for conformity to specifications and in exercising control over manufacturing process. Particle size distribution of high grown Broken Orange Pekoe (BOP) has been successfully analyzed by sieve analysis technique and it has been shown that the BOP grades have been completely characterized by the mean (z) and standard deviation (s) of the particle size distribution based on a mathematical model (De Silva,1972). This particle size has been found to be distributed in a vast range, (lognormally distributed). High grown BOP processing technique has been changed with the current market requirement by reducing the particle size. In applying the mathematical model as proposed by De Silva (1972) the relationship between the probits of cumulative undersize and the corresponding fineness moduli of the particle size have been established for high grown BOP. The mean fineness moduli and the standard deviation of the particles of BOP have thus resulted in the particle size reduction of high grown BOP. Key Words: BOP, Particle Size Distribution, Sieve analysis, Fineness Moduli en_US
dc.language.iso en en_US
dc.publisher Uva Wellassa University of Sri Lanka en_US
dc.relation.ispartofseries ;UWU/TEA/12/0024
dc.subject Tea Technology and Value Addition Degree Programme ( TEA) en_US
dc.title Particle Size Distribution of High Grown Broken Orange Pekoe (Bop) Tea en_US
dc.title.alternative Research Article – TEA 2016 en_US
dc.type Thesis en_US


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