摘要
近年来,我国水产养殖业发展迅速,采用投饲机代替人工投饲是发展趋势。为了确定影响投饲机投饲精准性的因素及其影响程度,以QC-TR-15型投饲机为试验对象,利用Box-Behnken的响应曲面设计方法,研究风机风速、投饲间隔时间、投饲量和料筒装料量对投饲精准性的影响,并利用Design Expert 8.0.6软件进行试验设计与数据分析,获得关于投饲精准性的回归模型。结果表明:在研究的4个因素中,风机风速对投饲精准性的影响极显著(P<0.000 1),其他因素影响不显著;各个因素对投饲精准性的影响程度排序为风机风速>投饲量>间隔时间>料筒装料量。本研究结果可以为该类型投饲机的优化和应用提供参考。
In recent years, China’s aquaculture has developed rapidly, so it is a necessary trend that the use of feeding machine will replace the artificial feeding. In order to determine the factors that affect the precision of the feeding machine and their influence degree, we took the QC-TR-15 feeding machine as the experimental object,and 29 sets of tests were designed by using Box-Behnken response surface design method, and in accordance with the order of experimental numbers to start the test, the effects of wind speed, feeding time interval, feeding amount and cylinder capacity on the feeding accuracy were studied. Then the Design Expert 8.0.6 software was used for data analysis, and a quadratic regression model for the feeding accuracy was obtained. The results of variance analysis showed that the wind speed had extremely significant effect on the feeding accuracy(P<0.000 1)in the four factors, and other factors had no significant effect. The results of the single factor analysis and interaction analysis showed that the influence degree of each factor on the feeding accuracy was as follows: wind speed>feed amount>feeding time interval>cylinder capacity. The above results can provide a reference for optimization and application of the type of feeding machine.
作者
张丰登
朱松明
张佩琦
季柏民
王珂宇
文彦慈
叶章颖
ZHANG Fengdeng;ZHU Songming;ZHANG Peiqi;JI Baimin;WANG Keyu;WEN Yanci;YE Zhangying(Agricultural Bio-Environment Engineering Institute,College of Biosystems Engineering and Food Science,Zhejiang University,Hangzhou 310058,China)
出处
《浙江大学学报（农业与生命科学版）》
CAS
CSCD
北大核心
2018年第6期755-764,共10页
Journal of Zhejiang University:Agriculture and Life Sciences
基金
国家自然科学基金(31772900)
浙江省重点研发计划重点农业项目(2015C02010)
关键词
投饲机
精准性
响应曲面设计
回归模型
试验
feeding machine
precision
response surface design
regression model
experiment
