TY - GEN
T1 - Effect of process variables on the extrudate moisture content
AU - Shankar, Tumuluru Jaya
AU - Sokhansanj, Shahab
AU - Bandyopadhyay, Sukumar
AU - Bawa, A. S.
PY - 2009
Y1 - 2009
N2 - Fish and rice flour based coextrudates are gaining importance due to high nutritional value. Extrusion cooking is a versatile technique to develop new products using novel ingredients. The moisture content of the extrudate plays an important role in understanding the pellet physical properties. In the present study extrusion process variables like barrel temperature, x1 (100-200°C), screw speed, x2 (70-110 rpm), fish content of the feed, x3 (5-45 %) and feed moisture content, x4 (20-60 %) were used to understand the moisture content of the extrudate produced. Experiments were conducted based on rotatable experimental design for the various combinations of process variables and the extrudate moisture content was measured. Second order polynomial regression equation was developed for the extrudate moisture content in terms of the process variables under study. The ANOVA results indicated that x4 and x1 had strong effect and were significant at P<0.1 and whereas x3 and x2 had a marginal influence on the extrudate moisture content Based on response surface plots the trends of the process variables which can result in minimization of the extrudate moisture content were a x1 >100°C, x2 >70 rpm, x3 in between 25-35 % and x4 <60. Based on RSM analysis it was observed that barrel temperature and feed moisture content were the two interacting process variables. Further the regression equation was optimized using GA to understand the process variables which can result in maximum and minimum of the extrudate moisture content. The optimized process conditions to obtain maximum and minimum were x1=106.53, x2=102.25, x3=44.87 and x 4=59.95 and x1=199.86, x2=109.86, x 3=32.45 and x4=20 and the predicted moisture content values were 41.97 and 17.522. The precisely optimized GA results has corroborated with the trends of the RSM where x1 has influenced the most followed by x4 and x2 and x3 were found to have a marginal effect.
AB - Fish and rice flour based coextrudates are gaining importance due to high nutritional value. Extrusion cooking is a versatile technique to develop new products using novel ingredients. The moisture content of the extrudate plays an important role in understanding the pellet physical properties. In the present study extrusion process variables like barrel temperature, x1 (100-200°C), screw speed, x2 (70-110 rpm), fish content of the feed, x3 (5-45 %) and feed moisture content, x4 (20-60 %) were used to understand the moisture content of the extrudate produced. Experiments were conducted based on rotatable experimental design for the various combinations of process variables and the extrudate moisture content was measured. Second order polynomial regression equation was developed for the extrudate moisture content in terms of the process variables under study. The ANOVA results indicated that x4 and x1 had strong effect and were significant at P<0.1 and whereas x3 and x2 had a marginal influence on the extrudate moisture content Based on response surface plots the trends of the process variables which can result in minimization of the extrudate moisture content were a x1 >100°C, x2 >70 rpm, x3 in between 25-35 % and x4 <60. Based on RSM analysis it was observed that barrel temperature and feed moisture content were the two interacting process variables. Further the regression equation was optimized using GA to understand the process variables which can result in maximum and minimum of the extrudate moisture content. The optimized process conditions to obtain maximum and minimum were x1=106.53, x2=102.25, x3=44.87 and x 4=59.95 and x1=199.86, x2=109.86, x 3=32.45 and x4=20 and the predicted moisture content values were 41.97 and 17.522. The precisely optimized GA results has corroborated with the trends of the RSM where x1 has influenced the most followed by x4 and x2 and x3 were found to have a marginal effect.
KW - Extrusion cooking
KW - Genetic algorithm
KW - Moisture content
KW - Response surface methodology
UR - https://www.scopus.com/pages/publications/77649126628
M3 - Conference contribution
AN - SCOPUS:77649126628
SN - 9781615673629
T3 - American Society of Agricultural and Biological Engineers Annual International Meeting 2009, ASABE 2009
SP - 4489
EP - 4502
BT - American Society of Agricultural and Biological Engineers Annual International Meeting 2009, ASABE 2009
T2 - American Society of Agricultural and Biological Engineers Annual International Meeting 2009
Y2 - 21 June 2009 through 24 June 2009
ER -