2012
DOI: 10.1007/s13213-010-0067-7
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Erratum to: Cellulase production by solid state fermentation using bagasse with Penicillium decumbens L-06

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Cited by 7 publications
(8 citation statements)
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“…Different agricultural wastes (e.g. sugar cane bagasse, corn stover, elephant grass, fruit pomace and straw or bran from wheat, rice or corn) have been applied for enzyme production [28,[57][58][59][60][61][62][63]. These agricultural residues can also be used as potential biomass sources for biorefineries, and are therefore ideal for a CBP setup.…”
Section: Medium Composition For Enzyme Productionmentioning
confidence: 99%
“…Different agricultural wastes (e.g. sugar cane bagasse, corn stover, elephant grass, fruit pomace and straw or bran from wheat, rice or corn) have been applied for enzyme production [28,[57][58][59][60][61][62][63]. These agricultural residues can also be used as potential biomass sources for biorefineries, and are therefore ideal for a CBP setup.…”
Section: Medium Composition For Enzyme Productionmentioning
confidence: 99%
“…Even though some reports have commended that cellulases could be produced by Penicillium genera (Zynai et al 2009;Long et al 2009;Picart et al 2007), relatively little information of optimization of solid-state fermentation conditions of cellulases production by Penicillium chrysogenum using response surface methodology is available. Therefore, this work will provide a new reference in this field.…”
Section: Resultsmentioning
confidence: 99%
“…Most bacteria cannot utilize crystalline cellulose, which can be done by many filamentous fungi strains. Therefore, cellulolytic fungi such as Trichoderma (Rocky-Salimi and Hamidi-Esfahani 2010; Latifian et al 2007), Aspergillus (Soni et al 2010;Gao et al 2008), Penicillium (Long et al 2009), and Fusarium (Panagiotou et al 2003) genera are well known to secrete cellulases in large amounts.…”
Section: Introductionmentioning
confidence: 99%
“…However, this method cannot guarantee the determination of optimal conditions and is unable to study the interactions between the factors, thus probably leads to unreliable results and inaccurate conclusions. [13] Response surface methodology (RSM), the statistical optimization method, uses the data from a few sets of experiments to determine equations. This method can overcome the limitations of the classical method and has been proved to be a powerful tool for designing experiments, building models, evaluating the effects of factors and analysing optimal conditions of factors for desirable responses.…”
Section: Introductionmentioning
confidence: 99%