Through surveying current development situations and existing problems of planting and processing of Ziziphus jujuba in south Xinjiang,this paper discussed planting,processing mode of Ziziphus Jujuba in south Xinjiang...Through surveying current development situations and existing problems of planting and processing of Ziziphus jujuba in south Xinjiang,this paper discussed planting,processing mode of Ziziphus Jujuba in south Xinjiang and development direction of enterprises in Ziziphus Jujuba production. It is expected to ensure and increase quality and sales volume of Ziziphus Jujuba and promote sound and sustainable development of Ziziphus Jujuba industrial chain in south Xinjiang.展开更多
The real-time monitoring and prediction system for quality attributes of jujube slices during the drying process was designed to solve the problem of destructive and inconvenient of the traditional quality detection m...The real-time monitoring and prediction system for quality attributes of jujube slices during the drying process was designed to solve the problem of destructive and inconvenient of the traditional quality detection method and realize quality online monitoring.Firstly,machine vision and automatic weighing were employed to monitor the color and moisture content changes of jujube slices in real-time.Secondly,correlation models between color parameter(a^(*)value)and nutritional quality attributes(vitamin C,reducing sugar)were established to predict vitamin C and reducing sugar content of jujube slices during the drying process.Finally,the upper computer monitoring software was integrated and designed based on LABVIEW virtual instrument,and the real-time monitoring system was tested and validated.Results showed that:the changing trends of color(L^(*),a^(*),and b^(*)values)monitored by the system were basically the same as the results detected by color difference meter,and the average errors of L^(*),a^(*),and b^(*)values were 0.93,0.52,and 0.73,respectively.The average relative error of moisture content between the system monitoring and manual static detection was 0.18%.The average error of vitamin C and reducing sugar content between the system prediction and manual detection were 50 mg/100 g in dry basis and 0.71g/100 g in dry basis,respectively.The current work can provide a useful reference for real-time monitoring of quality attributes of fruits and vegetables during the drying process.展开更多
基金Supported by Soft Science Research Plan of Xinjiang Production and Construction Corps(2012BB031)
文摘Through surveying current development situations and existing problems of planting and processing of Ziziphus jujuba in south Xinjiang,this paper discussed planting,processing mode of Ziziphus Jujuba in south Xinjiang and development direction of enterprises in Ziziphus Jujuba production. It is expected to ensure and increase quality and sales volume of Ziziphus Jujuba and promote sound and sustainable development of Ziziphus Jujuba industrial chain in south Xinjiang.
基金This work was financially supported by the Natural Science Fund of China(Grant No.31960488)the Shihezi University Achievement Transformation and Technology Promotion Project(Grant No.CGZH201808).
文摘The real-time monitoring and prediction system for quality attributes of jujube slices during the drying process was designed to solve the problem of destructive and inconvenient of the traditional quality detection method and realize quality online monitoring.Firstly,machine vision and automatic weighing were employed to monitor the color and moisture content changes of jujube slices in real-time.Secondly,correlation models between color parameter(a^(*)value)and nutritional quality attributes(vitamin C,reducing sugar)were established to predict vitamin C and reducing sugar content of jujube slices during the drying process.Finally,the upper computer monitoring software was integrated and designed based on LABVIEW virtual instrument,and the real-time monitoring system was tested and validated.Results showed that:the changing trends of color(L^(*),a^(*),and b^(*)values)monitored by the system were basically the same as the results detected by color difference meter,and the average errors of L^(*),a^(*),and b^(*)values were 0.93,0.52,and 0.73,respectively.The average relative error of moisture content between the system monitoring and manual static detection was 0.18%.The average error of vitamin C and reducing sugar content between the system prediction and manual detection were 50 mg/100 g in dry basis and 0.71g/100 g in dry basis,respectively.The current work can provide a useful reference for real-time monitoring of quality attributes of fruits and vegetables during the drying process.
