{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T15:57:42Z","timestamp":1790006262265,"version":"4.0.1"},"reference-count":0,"publisher":"S. Karger AG","issue":"4","license":[{"start":{"date-parts":[[2015,1,1]],"date-time":"2015-01-01T00:00:00Z","timestamp":1420070400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.karger.com\/Services\/SiteLicenses"},{"start":{"date-parts":[[2015,1,1]],"date-time":"2015-01-01T00:00:00Z","timestamp":1420070400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.karger.com\/Services\/SiteLicenses"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Microb Physiol"],"published-print":{"date-parts":[[2015]]},"abstract":"<jats:p>&lt;b&gt;&lt;i&gt;Background:&lt;\/i&gt;&lt;\/b&gt; Spinosyns, products of secondary metabolic pathway of &lt;i&gt;Saccharopolyspora spinosa&lt;\/i&gt;, show high insecticidal activity, but difficulty in enhancing the spinosad yield affects wide application. The fermentation process is a key factor in this case. &lt;b&gt;&lt;i&gt;Methods:&lt;\/i&gt;&lt;\/b&gt; The response surface methodology (RMS) and artificial neural network (ANN) modeling were applied to optimize medium components for spinosad production using &lt;i&gt;S. spinosa &lt;\/i&gt;strain CGMCC4.1365. Experiments were performed using a rotatable central composite design, and the data obtained were used to construct an ANN model and an RSM model. Using a genetic algorithm (GA), the input space of the ANN model was optimized to obtain optimal values of medium component concentrations. &lt;b&gt;&lt;i&gt;Results:&lt;\/i&gt;&lt;\/b&gt; The regression coefficients (R&lt;sup&gt;2&lt;\/sup&gt;) for the ANN and RSM models were 0.9866 and 0.9458, respectively, indicating that the fitness of the ANN model was higher. The maximal spinosad yield (401.26 mg\/l) was obtained using ANN\/GA-optimized concentrations. &lt;b&gt;&lt;i&gt;Conclusion:&lt;\/i&gt;&lt;\/b&gt; The hybrid ANN\/GA approach provides a viable alternative to the conventional RSM approach for the modeling and optimization of fermentation processes.<\/jats:p>","DOI":"10.1159\/000381312","type":"journal-article","created":{"date-parts":[[2015,6,29]],"date-time":"2015-06-29T21:06:42Z","timestamp":1435612002000},"page":"253-261","source":"Crossref","is-referenced-by-count":14,"title":["Optimization of Culture Medium for Maximal Production of Spinosad Using an Artificial Neural Network - Genetic Algorithm Modeling"],"prefix":"10.1159","volume":"25","author":[{"given":"Zhou","family":"Lan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chen","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weiqun","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiong","family":"Guan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaolin","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"127","published-online":{"date-parts":[[2015,6,30]]},"container-title":["Microbial Physiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.karger.com\/Article\/Pdf\/381312","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.karger.com\/Article\/Pdf\/381312","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,23]],"date-time":"2025-04-23T17:52:52Z","timestamp":1745430772000},"score":1,"resource":{"primary":{"URL":"https:\/\/karger.com\/article\/doi\/10.1159\/000381312"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015]]},"references-count":0,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2015,9,1]]}},"URL":"https:\/\/doi.org\/10.1159\/000381312","archive":["Portico"],"relation":{},"ISSN":["2673-1665","2673-1673"],"issn-type":[{"value":"2673-1665","type":"print"},{"value":"2673-1673","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015]]}}}