Agricultural engineering |
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Design and analysis of parameter optimization on development of corn straw fiber composition by ultrasound with alkalization pretreatment |
SHEN Weizheng, QU Tengyu, WEI Xiaoli*, MU Yingxin |
College of Electrical and Information Engineering, Northeast Agricultural University, Harbin 150030, China |
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Abstract Focusing on the defects in fiber structure of corn stalk feed, we proposed a novel production method of ruminant animal fodder by co-treatment with ultrasound and alkalization. By using central composite design with four factors at five levels and response surface analysis, we investigated the effects of ultrasonic power, ultrasonic time, liquid-to-solid ratio and ultrasonic power density in the container on extraction of cellulose and removal of hemicellulose and lignin in corn stalk. In addition, the two-phase regression model was established by taking the contents of lignin, cellulose, and hemicellulose as response values, respectively. The model explained the factor contribution rate of ultrasonic factors to response value and the significant influence on response surface model by the interaction between ultrasonic power, ultrasonic time, liquid-to-solid and ultrasonic power density in the container. The results showed that the determination coefficients of lignin, cellulose and hemicellulose models were 0.69, 0.79 and 0.73, respectively. The process parameters were optimized by the response surface model, and the optimal working parameters of each ultrasonic factor were obtained as ultrasonic power 99 W, ultrasonic time 20 min, liquid-to-solid ratio 7.8:1, and ultrasonic power density in the container 2.05 W/mL. The relative errors of actual values and predicted values were less than 13%, 12% and 14%, respectively. It is indicated that reasonable matching of ultrasonic parameters is helpful to reduce the content of lignin and cellulose of corn stalk feed and increase livestock digestibility, and provides scientific basis for the design of ultrasonic alkalization device and selection of working parameters.
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Received: 06 April 2017
Published: 10 July 2017
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Corresponding Authors:
neauwxl@sina.cn
E-mail: neauwxl@sina.cn
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超声碱化改善玉米秸秆纤维结构参数优化设计与分析
针对玉米秸秆制作饲料在纤维结构上的缺陷,提出超声碱化处理玉米秸秆制作反刍动物粗饲料的方法,利用4因素5水平的中心组合设计与响应面分析方法,研究超声功率、超声时间、液固比与容器内声功率密度对玉米秸秆木质素脱除与纤维素、半纤维素提取的影响,并以超声碱化玉米秸秆后木质素、纤维素、半纤维素含量为响应值分别建立二次回归模型。模型揭示超声因素对各响应值影响的因子贡献率及各因素之间的交互作用对响应面模型具有显著性影响。木质素、纤维素和半纤维素二次回归模型的决定系数分别为0.69、0.79、0.73;利用响应面模型进行工艺参数优化,得到各超声因素的最优工作参数为超声功率99 W、超声时间20 min、液固比7.8:1、容器内声功率密度2.05 W/mL。各响应参数实际值与预测值的相对误差分别小于13%、12%、14%。本研究表明,合理匹配超声参数有利于降低玉米秸秆饲料中的木质素含量,为超声碱化装置的设计及工作参数的选择提供了科学依据。
关键词:
模型,
响应面,
纤维结构,
超声碱化,
因子贡献率
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