2015
DOI: 10.1007/s12649-015-9395-y
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Optimization and Modelling of Process Conditions Using Response Surface Methodology (RSM) for Enzymatic Saccharification of Spent Tea Waste (STW)

Abstract: Spent tea waste (STW) is an important lignocellulosic waste as a cost-effective feedstock for ethanol production. The enzymatic hydrolysis of acid pretreated STW was investigated in this study. The effects of process parameters, including acid pretreatment time 26.4-93.6 min, b-glucosidase loading from 20 to 80 IU/g and cellulase loading from 11 to 45 IU/g on reducing sugar yield, were optimized by using central composite design of response surface methodology. The analysis of variance of data was examined by … Show more

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Cited by 21 publications
(5 citation statements)
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“…Tea is one of the most popular and inexpensive beverages in the world. According to FAO statistics, world tea production increased to about 568 million tons in 2018 [1]. China is the world's major producer and exporter of tea [2].…”
Section: Introductionmentioning
confidence: 99%
“…Tea is one of the most popular and inexpensive beverages in the world. According to FAO statistics, world tea production increased to about 568 million tons in 2018 [1]. China is the world's major producer and exporter of tea [2].…”
Section: Introductionmentioning
confidence: 99%
“…The classification tree model had an accuracy of 80%, which indicated that 44 of the 55 cases were correctly classified. Based on all obtained results and models, it appeared that our reducing sugar yield was applicable and promising among the literature studies conducted to rapeseed straw (yield: 19 g/L) (Karagöz et al, 2012), palm spent tea waste (yield: 29 g/L) (Yücel and Göycıncık, 2015), reed (yield: 8 g/L) (Li et al, 2009) under varying pretreated conditions with varying enzymes.…”
Section: Classification and Regression Tree Analysis In Enzymatic Hydrolysis Of Sbpmentioning
confidence: 60%
“…But still, our knowledge is limited regarding the complete use of hydrolases and hereby, appropriate enzyme combinations to maximize the saccharification has not been achieved, yet. At this point, Response surface methodology (RSM) could be proposed as a statistical approach for design of experiments, model building, evaluation of factor effects, optimization of responses and for the reduction of the required number of experiments (Yücel and Göycıncık, 2015;Astray et al, 2016).…”
Section: Introductionmentioning
confidence: 99%
“…The lack of fit of the model which is a vital criterion measuring the failure of the model for data representation was also found to be not significant (F value: 0.2797). A non-significant lack of fit is positive for the model and sufficient to estimate response in the presence of various variables (Yücel & Göycıncık 2015). Moreover, according to the model, all the criteria tested were found as significant (p<0.0001).…”
Section: Response Surface Methodologymentioning
confidence: 85%