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Optimizing the preparation of seaweed-based edible cones with response surface methodology


Affiliations
1 Department of Fish Processing Technology, Fisheries College and Research Institute, Tamil Nadu Dr J. Jayalalithaa Fisheries University, Thoothukudi 628 008, India
2 Fisheries College and Research Institute, Tamil Nadu Dr J. Jayalalithaa Fisheries University, Thalainayar 609 201, India
3 Department of Fish Processing Technology, Fisheries College and Research Institute, Tamil Nadu Dr J. Jayalalithaa Fisheries University, Ponneri 601 204, India
4 Department of Aquatic Animal Health, Fisheries College and Research Institute, Tamil Nadu Dr J. Jayalalithaa Fisheries University, Thoothukudi 628 008, India
5 Department of Fish Processing Technology, College of Fishery Science, Andhra Pradesh Fisheries University, Muthukur 524 344, India

In the present study, we have prepared seaweed-based nutritious edible cones through per cent optimization of composite flour level using Box–Behnken design for response surface methodology. The three independent variables of the statistical design were pearl millet, wheat and seaweed powder from Ulva lactuca and Gracilaria edulis, and overall acceptability (OAA) and retention time (RT) were considered responses. A second-order quadratic polynomial equation was applied to the dataset of all responses to make predictions. U. lactuca-incorporated cones showed that the overall desirability function fits with the quadratic model at 99.77% significance level at a combination of 27.75% for pearl millet, 7.38% of wheat and 0.986% for U. lactuca with a predicted OAA of 8.2 and RT of 23.93 min, whereas in G. edulis cone, at 99.34% level of significance, the point prediction was at 27.94%, 7.95% and 1.006% for pearl millet, wheat and G. edulis with a predicted OAA of 8.331 and RT of 24.6 min

Keywords

Composite flour, edible cones, Gracilaria edulis, response surface methodology, Ulva lactuca
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  • Optimizing the preparation of seaweed-based edible cones with response surface methodology

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Authors

K. Sravani
Department of Fish Processing Technology, Fisheries College and Research Institute, Tamil Nadu Dr J. Jayalalithaa Fisheries University, Thoothukudi 628 008, India
P. Ganesan
Department of Fish Processing Technology, Fisheries College and Research Institute, Tamil Nadu Dr J. Jayalalithaa Fisheries University, Thoothukudi 628 008, India
S. Balasundari
Fisheries College and Research Institute, Tamil Nadu Dr J. Jayalalithaa Fisheries University, Thalainayar 609 201, India
N. Muralidharan
Department of Fish Processing Technology, Fisheries College and Research Institute, Tamil Nadu Dr J. Jayalalithaa Fisheries University, Ponneri 601 204, India
B. Chrisolite
Department of Aquatic Animal Health, Fisheries College and Research Institute, Tamil Nadu Dr J. Jayalalithaa Fisheries University, Thoothukudi 628 008, India
K. Dhanapal
Department of Fish Processing Technology, College of Fishery Science, Andhra Pradesh Fisheries University, Muthukur 524 344, India

Abstract


In the present study, we have prepared seaweed-based nutritious edible cones through per cent optimization of composite flour level using Box–Behnken design for response surface methodology. The three independent variables of the statistical design were pearl millet, wheat and seaweed powder from Ulva lactuca and Gracilaria edulis, and overall acceptability (OAA) and retention time (RT) were considered responses. A second-order quadratic polynomial equation was applied to the dataset of all responses to make predictions. U. lactuca-incorporated cones showed that the overall desirability function fits with the quadratic model at 99.77% significance level at a combination of 27.75% for pearl millet, 7.38% of wheat and 0.986% for U. lactuca with a predicted OAA of 8.2 and RT of 23.93 min, whereas in G. edulis cone, at 99.34% level of significance, the point prediction was at 27.94%, 7.95% and 1.006% for pearl millet, wheat and G. edulis with a predicted OAA of 8.331 and RT of 24.6 min

Keywords


Composite flour, edible cones, Gracilaria edulis, response surface methodology, Ulva lactuca



DOI: https://doi.org/10.18520/cs%2Fv125%2Fi12%2F1381-1387