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</header><div class="mh-section mh-group"> <div id="main-content" class="mh-content"><article id="post-3666" class="post-3666 post type-post status-publish format-standard hentry category-v10n4"> <header class="entry-header clearfix"> <h1 class="entry-title">Modeling and Optimization of the Osmotic Dehydration of Cantaloupe</h1> </header> <p class="entry-meta"> </p> <div class="entry-content clearfix"> <div class="italics"><i>Hamid Bakhshabadi, Mohammad Ganje, Masoumeh Moghimi, Alireza Ghodsvali, Toktam Mohammadi-Moghaddam, Elham Taghavi and Afsaneh Morshedi</i></div> <p><strong>Abstract</strong></p> <p style="text-align: justify;">In current research, the optimization of osmotic dehydration of cantaloupe pieces aimed to maximize water loss (WL) and minimize moisture reabsorption using artificial neural network (ANN). The effects of three parameters were studied: osmotic solution temperature (40 – 60 <sup>掳</sup>C), immersion time (40 – 240 min), and solution concentration (40 – 60 <sup>掳</sup>Brix), employing central composite design (CCD). Various parameters including WL, solid gain (SG), reduction in WL to SG ratio, and reduction in sample weight were analyzed. The results indicated that the optimal conditions for osmotic dehydration were achieved with a solution temperature of 60 <sup>掳</sup>C, immersion time of 85.71 min, and solution concentration of 40% sucrose (sugar). Under these conditions, the following parameters were observed: WL of 3.79%, SG of 43.74%, WL to SG ratio of 14.48, and sample weight reduction of 47.71%. Furthermore, results from the ANN revealed that a network structure with one hidden layer comprising 5 nodes (3-5-4 network with 3 inputs, 5 nodes in the hidden layer, and 4 outputs) provided the most accurate predictions. This network achieved correlation coefficients (R2) of 0.999 and root mean squared error (RMSE) of 0.000039, demonstrating high reliability and precision in predicting the selected responses.</p> <div><strong>Published on:</strong> October 09, 2024<br/> <strong>doi:</strong> 10.17756/jfcn.2024-192<br/> <strong>Citation: </strong>Bakhshabadi H, Ganje M, Moghimi M, Ghodsvali A, Mohammadi-Moghaddam T, et al. 2024. Modeling and Optimization of the Osmotic Dehydration of Cantaloupe. <i>J Food Chem Nanotechnol </i>10(4): 192-199.</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=3667" class="sdm_download green" title="jfcn-192-masoumeh-moghimi.pdf" target="_self">PDF (Download Full text)</a></div></div> <div><div class="sdm_download_count"><span class="sdm_count_number"><strong>127</strong></span><br/><span class="sdm_count_string"> Downloads</span></div><span class="postviews_eachpost"><div class="post-views post-3666 entry-meta"> <span class="post-views-label">Views </span> <span class="post-views-count">360</span> </div></span></div> <script 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