{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T23:45:33Z","timestamp":1792194333652,"version":"4.4.0"},"reference-count":50,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2024,5,21]],"date-time":"2024-05-21T00:00:00Z","timestamp":1716249600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Microbiol."],"abstract":"<jats:p>Shiitake (<jats:italic>Lentinula edodes<\/jats:italic>) is one of the most widely grown and consumed mushroom species worldwide. They are a potential source of food and medicine because they are rich in nutrients and contain various minerals, vitamins, essential macro- and micronutrients, and bioactive compounds. The reuse of agricultural and industrial residues is crucial from an ecological and economic perspective. In this study, the running length (RL) of <jats:italic>L. edodes<\/jats:italic> cultured on 64 substrate compositions obtained from different ratios of bagasse (B), wheat bran (WB), and beech sawdust (BS) was recorded at intervals of 5\u2009days after cultivation until the 40<jats:sup>th<\/jats:sup> day. Multilayer perceptron-genetic algorithm (MLP-GA), multiple linear regression, stepwise regression, principal component regression, ordinary least squares regression, and partial least squares regression were used to predict and optimize the RL and running rate (RR) of <jats:italic>L. edodes<\/jats:italic>. The statistical values showed higher prediction accuracies of the MLP-GA models (92% and 97%, respectively) compared with those of the regression models (52% and 71%, respectively) for RL and RR. The high degree of fit between the forecasted and actual values of the RL and RR of <jats:italic>L. edodes<\/jats:italic> confirmed the superior performance of the developed MLP-GA models. An optimization analysis on the established MLP-GA models showed that a substrate containing 15.1% B, 45.1% WB, and 10.16% BS and a running time of 28 days and 10\u2009h could result in the maximum <jats:italic>L. edodes<\/jats:italic> RL (10.69\u2009cm). Moreover, the highest RR of <jats:italic>L. edodes<\/jats:italic> (0.44\u2009cm d<jats:sup>\u22121<\/jats:sup>) could be obtained by a substrate containing 30.7% B, 90.4% WB, and 0.0% BS. MLP-GA was observed to be an effective method for predicting and consequently selecting the best substrate composition for the maximal RL and RR of <jats:italic>L. edodes<\/jats:italic>.<\/jats:p>","DOI":"10.3389\/fmicb.2024.1366264","type":"journal-article","created":{"date-parts":[[2024,5,21]],"date-time":"2024-05-21T05:01:15Z","timestamp":1716267675000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Lentinula edodes substrate formulation using multilayer perceptron-genetic algorithm: a critical production checkpoint"],"prefix":"10.3389","volume":"15","author":[{"given":"Naser","family":"Safaie","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mina","family":"Salehi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siamak","family":"Farhadi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ali","family":"Aligholizadeh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Valiollah","family":"Mahdizadeh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2024,5,21]]},"reference":[{"key":"ref1","volume-title":"Genetic algorithm and direct search toolbox user\u2019s guide","author":"Abramson","year":"2007"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"717","DOI":"10.1016\/S0731-7085(99)00272-1","article-title":"Basic concepts of artificial neural network (ANN) modeling and its application in pharmaceutical research","volume":"22","author":"Agatonovic-Kustrin","year":"2000","journal-title":"J. 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