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ISSN: 2157-7110

Journal of Food Processing & Technology
Open Access

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Research Article

Milling Study of Multiple Pulses Using CIAE Dhal Mill for Optimal Responses

Central Institute of Agricultural Engineering, Nabibagh, Berasia Road, Bhopal, M.P., India
Corresponding Author : Dr. S. Mangaraj
Central Institute of Agricultural Engineering
Nabibagh, Berasia Road
Bhopal, M.P., India
E-mail: [email protected]
Received February 07, 2011; Accepted March 15, 2011; Published March 17, 2011
Citation: Mangaraj S, Singh KP (2011) Milling Study of Multiple Pulses Using Ciae Dhal Mill For Optimal Responses. J Food Process Technol 2:110. doi:10.4172/2157-7110.1000110
Copyright: © 2011 Mangaraj S, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Generally many numbers of experimental trials are under taken for milling study of various pulses for getting optimum responses. However, optimization of machine parameters greatly over come the numbers of trials apart from maximizing the out put of the system. The independent milling parameters of CIAE (Central Institute of Agricultural Engineering Bhopal, India) dhal mill were roller speed, emery grit size and feed rates. These parameters were optimized for pigeon pea, chickpea and green gram dehulling using response surface methodology (RSM) and Central Composite Rotable design (CCRD). The roller peripheral speed of 10m/s, emery grit size 0.3mm and feed rate 101.60kg/h were found optimal. The maximum pulse recovery on the optimized independent parameters was found for pigeon pea (76.36% against 77.04% predicted) followed by chickpea (73.80% against 73.06% predicted) and green gram (71.25% against 69.82% predicted). The maximum milling efficiency on optimal machine parameters was observed in pigeon pea (83.0% against 82.79% predicted) followed by chickpea (74.8% against 75.53% predicted) and green gram (78% against 78.24% predicted).


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