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In this study, aimed at designing an industrial- scale process for extracting oil from sesame seeds, we investigated three cooking temperatures (75 °C, 90 °C, and 105 °C) and three different moisture contents of the seeds leaving the cooking pot (4.5%, 5.5%, and 6.5%)."/> <meta property="og:url" content="https://foodchemistryjournal.com/2024/10/01/application-of-artificial-neural-networks-for-predicting-cooking-dynamics-in-industrial-sesame-seed-oil-extraction/"/> <meta property="og:site_name" content="Journal of Food Chemistry & Nanotechnology"/> <meta property="article:section" content="Volume 10 Issue 4"/> <meta property="article:published_time" content="2024-10-01T11:09:24+00:00"/> <meta property="article:modified_time" content="2024-09-23T11:15:02+00:00"/> <meta property="og:updated_time" content="2024-09-23T11:15:02+00:00"/> <meta property="og:image" content="http://jnanoworld.com/wp-content/uploads/2017/04/pdf-icon-24-e1509106685135-1.png"/> <meta name="twitter:card" content="summary"/> <meta name="twitter:description" content="Hamid Bakhshabadi, Alireza Ghodsvali, Abolfazl Bojmehrani, Mohammad Ganje, Toktam Mohammadi-Moghaddam, Elham Taghavi and Afsaneh Morshedi Sesame seeds are a significant source of vegetable oil and were among the earliest grains used for oil extraction. In this study, aimed at designing an industrial- scale process for extracting oil from sesame seeds, we investigated three cooking temperatures (75 °C, 90 °C, and 105 °C) and three different moisture contents of the seeds leaving the cooking pot (4.5%, 5.5%, and 6.5%). 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menu-item-68"><a href="https://foodchemistryjournal.com/contact/">Contact</a></li> </ul></div> </nav> </div> </header><div class="mh-section mh-group"> <div id="main-content" class="mh-content"><article id="post-3620" class="post-3620 post type-post status-publish format-standard hentry category-v10n4"> <header class="entry-header clearfix"> <h1 class="entry-title">Application of Artificial Neural Networks for Predicting Cooking Dynamics in Industrial Sesame Seed Oil Extraction</h1> </header> <p class="entry-meta"> </p> <div class="entry-content clearfix"> <div class="italics"><i>Hamid Bakhshabadi, Alireza Ghodsvali, Abolfazl Bojmehrani, Mohammad Ganje, Toktam Mohammadi-Moghaddam, Elham Taghavi and Afsaneh Morshedi</i></div> <p><strong>Abstract</strong></p> <p style="text-align: justify;">Sesame seeds are a significant source of vegetable oil and were among the earliest grains used for oil extraction. In this study, aimed at designing an industrial- scale process for extracting oil from sesame seeds, we investigated three cooking temperatures (75 <sup>°</sup>C, 90 <sup>°</sup>C, and 105 <sup>°</sup>C) and three different moisture contents of the seeds leaving the cooking pot (4.5%, 5.5%, and 6.5%). The study focused on several responses: the oil content of the pressed cake, the quantity of extracted oil, the protein and moisture contents of the resulting meal, and the percentage of insoluble fine particles in the extracted oil. To predict these responses, an artificial neural network (ANN) model was employed. Among the various backpropagation feedforward networks with different topologies studied, the configuration with 2 input nodes, 5 hidden nodes in one layer, and 5 output nodes was selected based on its high correlation coefficient (R<sup>2</sup> = 0.997) and low mean squared error (MSE = 0.0002). The sigmoid hyperbolic tangent activation function was used, and the Levenberg-Marquardt learning algorithm with 1000 learning cycles was identified as the optimal neural model. The selected optimized models demonstrated high R<sup>2</sup> ≥ 0.97 during the evaluation of their results.</p> <div><strong>Published on:</strong> October 01, 2024<br/> <strong>doi:</strong> 10.17756/jfcn.2024-188<br/> <strong>Citation: </strong>Bakhshabadi H, Ghodsvali A, Bojmehrani A, Ganje M, Mohammadi-Moghaddam T, et al. 2024. Application of Artificial Neural Networks for Predicting Cooking Dynamics in Industrial Sesame Seed Oil Extraction. <i>J Food Chem Nanotechnol </i>10(4): 159-165.</div> <div class="pdfdownloadlink"><img class="alignleft size-full wp-image-507" style="margin: 4px -5px 4px 5px;" src="http://jnanoworld.com/wp-content/uploads/2017/04/pdf-icon-24-e1509106685135-1.png" alt="" width="16" height="16"/><div class="sdm_download_link"><a href="https://foodchemistryjournal.com/?smd_process_download=1&download_id=3621" class="sdm_download green" title="jfcn-188-hamid-bakhshabadi.pdf" target="_self">PDF (Download Full text)</a></div></div> <div><div class="sdm_download_count"><span class="sdm_count_number"><strong>111</strong></span><br/><span class="sdm_count_string"> Downloads</span></div><span class="postviews_eachpost"><div class="post-views post-3620 entry-meta"> <span class="post-views-label">Views </span> <span class="post-views-count">236</span> </div></span></div> <script 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published</th> <th>Articles rejected</th> <th>% Acceptance</th> </tr> <tr class="even"> <td>2023</td> <td>63</td> <td>24</td> <td>39</td> <td>38</td> </tr> </tbody> </table> </div> </div><div id="multi-image-slider-widget-id-3" class="sb-widget clearfix widget_multi-image-slider-widget-id"><h4 class="widget-title"><span>Author Services</span></h4> <style type="text/css">.misw-slider-multi-image-slider-widget-id-3{display:none}</style> <script type="text/javascript">(function($){"use strict";$(window).load(function(){$('.misw-slider-multi-image-slider-widget-id-3').show().sliderPro({loop:false,autoplay:true,autoplayDelay:5000,buttons:true,arrows:true,autoHeight:true,fullScreen:false,shuffle:false,fade:false,fadeDuration:500});});})(jQuery);</script> <div class="misw-slider-container"> <div class="slider-pro misw-slider-multi-image-slider-widget-id-3"> <div class="sp-slides"> <div class="sp-slide"> <div class="misw-slider-image"> <a 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