Deep fat frying of yam slices: optimization of processing conditions using response surface methodology
The deep-fat frying of yam slices was investigated with the aim of optimizing the processing conditions. During frying, frying temperature, initial dry matter and frying time have a significant effect on moisture loss and oil uptake. Response surface methodology central composite rotatable design was used to study the effects of the independent variables on quality attributes of yam chips. Breaking force, oil content, moisture content and color parameters were determined. Statistical analysis with response surface regression showed that breaking force, oil and moisture contents and color parameters (L* and a*) were significantly (P < 0.05) correlated with frying temperature, initial dry matter and frying time. The optimum conditions were a frying temperature of 175–180C, using tubers of initial dry matter of 0.179–0.214 kg/kg with a frying time of 4–5 min. It was suggested that the regression equation can be used to estimate the dependent variables for fried yam chips except b* (yellowness) parameter.
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Format: | Journal Article biblioteca |
Language: | English |
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2008
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Subjects: | frying temperature, tubers, yam chips, color parameters, oil and moisture contents, |
Online Access: | https://hdl.handle.net/10568/90770 |
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dig-cgspace-10568-907702023-06-12T08:37:43Z Deep fat frying of yam slices: optimization of processing conditions using response surface methodology Sobukola, O.P. Awonorin, S.O. Sanni, Lateef O. Bamiro, F.O frying temperature tubers yam chips color parameters oil and moisture contents The deep-fat frying of yam slices was investigated with the aim of optimizing the processing conditions. During frying, frying temperature, initial dry matter and frying time have a significant effect on moisture loss and oil uptake. Response surface methodology central composite rotatable design was used to study the effects of the independent variables on quality attributes of yam chips. Breaking force, oil content, moisture content and color parameters were determined. Statistical analysis with response surface regression showed that breaking force, oil and moisture contents and color parameters (L* and a*) were significantly (P < 0.05) correlated with frying temperature, initial dry matter and frying time. The optimum conditions were a frying temperature of 175–180C, using tubers of initial dry matter of 0.179–0.214 kg/kg with a frying time of 4–5 min. It was suggested that the regression equation can be used to estimate the dependent variables for fried yam chips except b* (yellowness) parameter. 2008 2018-02-06T12:14:40Z 2018-02-06T12:14:40Z Journal Article Sobukola, O.P., Awonorin, S.O., Sanni, L.O. & Bamiro, F.O. (2008). Deep‐fat frying of yam slices: optimization of processing conditions using response surface methodology. Journal of Food Processing and Preservation, 32(3), 343-360. 0145-8892 https://hdl.handle.net/10568/90770 en Limited Access p. 343-360 |
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frying temperature tubers yam chips color parameters oil and moisture contents frying temperature tubers yam chips color parameters oil and moisture contents |
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frying temperature tubers yam chips color parameters oil and moisture contents frying temperature tubers yam chips color parameters oil and moisture contents Sobukola, O.P. Awonorin, S.O. Sanni, Lateef O. Bamiro, F.O Deep fat frying of yam slices: optimization of processing conditions using response surface methodology |
description |
The deep-fat frying of yam slices was investigated with the aim of optimizing
the processing conditions. During frying, frying temperature, initial
dry matter and frying time have a significant effect on moisture loss and oil
uptake. Response surface methodology central composite rotatable design was
used to study the effects of the independent variables on quality attributes of
yam chips. Breaking force, oil content, moisture content and color parameters
were determined. Statistical analysis with response surface regression showed
that breaking force, oil and moisture contents and color parameters (L* and
a*) were significantly (P < 0.05) correlated with frying temperature, initial dry
matter and frying time. The optimum conditions were a frying temperature of
175–180C, using tubers of initial dry matter of 0.179–0.214 kg/kg with a
frying time of 4–5 min. It was suggested that the regression equation can be
used to estimate the dependent variables for fried yam chips except b*
(yellowness) parameter. |
format |
Journal Article |
topic_facet |
frying temperature tubers yam chips color parameters oil and moisture contents |
author |
Sobukola, O.P. Awonorin, S.O. Sanni, Lateef O. Bamiro, F.O |
author_facet |
Sobukola, O.P. Awonorin, S.O. Sanni, Lateef O. Bamiro, F.O |
author_sort |
Sobukola, O.P. |
title |
Deep fat frying of yam slices: optimization of processing conditions using response surface methodology |
title_short |
Deep fat frying of yam slices: optimization of processing conditions using response surface methodology |
title_full |
Deep fat frying of yam slices: optimization of processing conditions using response surface methodology |
title_fullStr |
Deep fat frying of yam slices: optimization of processing conditions using response surface methodology |
title_full_unstemmed |
Deep fat frying of yam slices: optimization of processing conditions using response surface methodology |
title_sort |
deep fat frying of yam slices: optimization of processing conditions using response surface methodology |
publishDate |
2008 |
url |
https://hdl.handle.net/10568/90770 |
work_keys_str_mv |
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_version_ |
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