title: Use of artificial neural network (ANN) for the development of bioprocess using Pinus roxburghii fallen foliages for the release of polyphenols and reducing sugars.
abstract: In present study, different parameters, i.e., percentage of NaOH, loading volume, microwave power (watt) and volume of water during pretreatment were optimized by ANN for release of polyphenols and sugars from pine fallen foliage. ANN used was feed forward back propagation type with 72 input, 72 output and 10 hidden layers coupled with Lvenberg-Marquardt (LM) training algorithms. The predicted optimal values by generated neural network for alkali pretreatment were 6 ml (0.5% NaOH)/g of substrate, soaking time of 10 min followed by 1 min of 100 W microwave. Pretreated sample on enzymatic hydrolysis at 50°C for 20 h with cocktail of cellulase, xylanase and laccase produced by locally isolated consortia released 668.9 mg/g of total sugar and 265.06 mg/g of total polyphenols. Optimization by ANN showed good yield, therefore, indicating its suitability for bioprocess modeling and control for release of reducing sugars and polyphenols from pine foliage.
authors.affiliation: Department of Biotechnology, Motilal Nehru National Institute of Technology, Allahabad 211 004, India.
authors.forename: Siddharth
authors.initials: S
authors.lastname: Vats
authors.forename: Sangeeta
authors.initials: S
authors.lastname: Negi
mesh_terms: D000468:Alkalies / Q000494:pharmacology; D001709:Biotechnology / Q000379:methods*; D002241:Carbohydrates / Q000737:chemistry*; D008872:Microwaves; D016571:Neural Networks, Computer; D010084:Oxidation-Reduction / Q000187:drug effects; D028223:Pinus / Q000737:chemistry* / Q000187:drug effects; D018515:Plant Leaves / Q000737:chemistry* / Q000187:drug effects; D059808:Polyphenols / Q000737:chemistry*; D012044:Regression Analysis; D012972:Sodium Hydroxide / Q000494:pharmacology; D012996:Solutions
chemical_list: D000468:Alkalies; D002241:Carbohydrates; D059808:Polyphenols; D012996:Solutions; D012972:Sodium Hydroxide