花生仁光电色选工艺条件的研究
|
摘要
以花生仁为对象,CF7+色选机为色选设备,研究色选机振动频率、病斑值、灵敏度等工作参数对色选机选净率、带出比的影响,以及色选工序前后花生仁纯质率、霉变率的变化。由正交试验得到花生仁色选的最优工艺条件为振动频率50 Hz、灵敏度10、病斑值120,在此条件下选净率达到99. 84%、带出比为41。通过色选,花生仁的纯质率由94. 22%提高至97. 99%,霉变率由0. 85%大幅度降低至0. 04%,大大提高了花生仁的品质和食用安全性。
Taking peanut kernel as the object,the effects of vibration frequency,disease spot value and sensitivity of CF7 + electro-optical sorter on the sorting net rate and error-sorting rate of sorter,and the pure rate and mildew rate of selected peanut kernel before and after the electro-optical sorting procedure were studied. The optimal conditions of sorter for peanut kernel were obtained by orthogonal experiment as follows: vibration frequency 50 Hz,sensitivity 10 and disease spot value 120. Under these conditions,the sorting net rate and error-sorting rate were 99. 84% and 41,respectively. Through electro-optical sorting procedure,the pure rate of peanut kernel increased from 94. 22% to 97. 99%,and the mildew rate sharply reduced from 0. 85% to 0. 04%,which greatly improved the quality and safety of peanut kernel.
Taking peanut kernel as the object,the effects of vibration frequency,disease spot value and sensitivity of CF7 + electro-optical sorter on the sorting net rate and error-sorting rate of sorter,and the pure rate and mildew rate of selected peanut kernel before and after the electro-optical sorting procedure were studied. The optimal conditions of sorter for peanut kernel were obtained by orthogonal experiment as follows: vibration frequency 50 Hz,sensitivity 10 and disease spot value 120. Under these conditions,the sorting net rate and error-sorting rate were 99. 84% and 41,respectively. Through electro-optical sorting procedure,the pure rate of peanut kernel increased from 94. 22% to 97. 99%,and the mildew rate sharply reduced from 0. 85% to 0. 04%,which greatly improved the quality and safety of peanut kernel.
引文
[1]谢焕雄,彭宝良,张会娟,等.我国花生加工利用概况与发展思考[J].中国农机化学报,2010(5):46-49.
[2]徐珊珊.中国花生产品国际竞争力分析[J].世界农业,2015(12):154-156.
[3]姚惠源,方辉.色选技术在粮食和农产品精加工领域的应用及发展趋势[J].粮食与食品工业,2011,18(2):4-6.
[4]陈红,丁幼春,熊利荣.无损检测技术在花生品质检测中的应用[J].粮油加工与食品机械,2005(2):53-55.
[5]李雅丽,刘阳.霉变花生光电分选技术应用现状及发展趋势[J].农业机械,2012(12):50-53.
[6]韩仲志,赵友刚.基于计算机视觉的花生品质分级检测研究[J].中国农业科学,2010,43(18):3882-3891.
[7]韩仲志,刘竟,杨锦忠.花生籽仁感官品质鉴定中的计算机色选机制研究[J].花生学报,2009,38(2):15-19.
[8]韩仲志,赵友刚.花生外观品质品种图像分析与系统仿真[J].中国粮油学报,2010,25(11):114-118.
[9]赵龙.基于TCS230颜色传感器的花生色选机设计[D].山东青岛:青岛科技大学,2010.
[10]乔艳芳,李馨,孙鹏.食品光电色选技术装备设计及应用[J].农机化研究,2005(2):118-119.
[11]张德高,谢焕雄,胡志超,等.花生色选机工作参数优化与试验[J].江苏农业科学,2017,45(18):218-222.
[12]闫泽民,王志山,陈留记.影响玉米色选机工艺效果的因素分析[J].河南农业,2017(23):46-47.
[2]徐珊珊.中国花生产品国际竞争力分析[J].世界农业,2015(12):154-156.
[3]姚惠源,方辉.色选技术在粮食和农产品精加工领域的应用及发展趋势[J].粮食与食品工业,2011,18(2):4-6.
[4]陈红,丁幼春,熊利荣.无损检测技术在花生品质检测中的应用[J].粮油加工与食品机械,2005(2):53-55.
[5]李雅丽,刘阳.霉变花生光电分选技术应用现状及发展趋势[J].农业机械,2012(12):50-53.
[6]韩仲志,赵友刚.基于计算机视觉的花生品质分级检测研究[J].中国农业科学,2010,43(18):3882-3891.
[7]韩仲志,刘竟,杨锦忠.花生籽仁感官品质鉴定中的计算机色选机制研究[J].花生学报,2009,38(2):15-19.
[8]韩仲志,赵友刚.花生外观品质品种图像分析与系统仿真[J].中国粮油学报,2010,25(11):114-118.
[9]赵龙.基于TCS230颜色传感器的花生色选机设计[D].山东青岛:青岛科技大学,2010.
[10]乔艳芳,李馨,孙鹏.食品光电色选技术装备设计及应用[J].农机化研究,2005(2):118-119.
[11]张德高,谢焕雄,胡志超,等.花生色选机工作参数优化与试验[J].江苏农业科学,2017,45(18):218-222.
[12]闫泽民,王志山,陈留记.影响玉米色选机工艺效果的因素分析[J].河南农业,2017(23):46-47.