2013
DOI: 10.2298/apt1344279r
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Effect of temperature on acid hydrolysis of Jerusalem artichoke as raw material for ethanol production

Abstract: Jerusalem artichoke (JA) is a low-requirement crop, which does not interfere with food chain, and is a promising carbon source for industrial fermentation. Microbial conversion of such a renewable raw material to useful products, such as ethanol, is an important objective in industrial biotechnology. In this study, ethanol was efficiently produced from the hydrolyzates of JA obtained at different pH values (pH 2.5, pH 3.0 and pH 3.5), temperature (120, 130, 132 and 134?C) and hold time (30 an… Show more

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Cited by 1 publication
(4 citation statements)
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“…Samples for analysis were randomly taken from the available material and the small standard deviation indicates the compositional homogeneity of the tubers. The measured values are in agreement with values typically found for Jerusalem artichoke [12][13][14][15][16][17][18][19][20][21][22][23][24].…”
Section: Resultssupporting
confidence: 89%
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“…Samples for analysis were randomly taken from the available material and the small standard deviation indicates the compositional homogeneity of the tubers. The measured values are in agreement with values typically found for Jerusalem artichoke [12][13][14][15][16][17][18][19][20][21][22][23][24].…”
Section: Resultssupporting
confidence: 89%
“…c pH and time using H 3 PO 4 as catalyst artichoke tubers using different mineral acids and to compare the effectiveness of each acid on hydrolysis at optimal conditions. In a closely related study, the hydrolysis of Jerusalem artichoke tubers was carried out using HCl at a temperature of 120°C, pH of 2.5, for 60 min resulting in 68 % hydrolysis of inulin [17], which is lower than the results obtained in this study. It has been reported that the sugar yield, evaluated as fructose and glucose production, is very heat sensitive in acidic conditions as the products easily degrade at temperature higher than 97°C [19], as was the case for the work of Razmovski et al [20], resulting in a lower hydrolysis yield.…”
Section: Response Optimization and Model Validationcontrasting
confidence: 71%
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