Predication of Dry Rubber Content in Hevea Latex based on SPSS Multiple Regression Model

2019 International Conference on Advanced Electronic Materials, Computers and Materials Engineering

无线电电子学;计算机科学;材料科学

Zhang, Fan^1 ; Liao, Lusheng^1 ; Huang, Hui^1 ; Zhang, Fuquan^1 ; Wang, Bingbing^1 ; Long, Huaqian^1

Key Laboratory of Tropical Crop Products Processing, Ministry of Agriculture and Rural Affairs, Agricultural Products Processing Research Institute, Chinese Academy of Tropical Agricultural Sciences, Zhanjiang, Guangdong

524001, China^1

关键词: Average relative error;    Dry rubber content;    Influence degree;    Multiple regression model;    Natural rubber latex;    Predication model;    Producing areas;    Regression equation;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/563/2/022030/pdf
DOI  :  10.1088/1757-899X/563/2/022030

来源: IOP

【 摘 要 】

The Dry Rubber content (DRC) in hevea latex is affected by a great many of factors, including producing area, strains, tree age, cutting system, origins and so on. Each factor was discussed and evaluated to confirm the influence degree. A predication model based on SPSS multiple regression models was constructed to analyse the factors influencing the DRC, and the regression equation was used to forecast the DRC in natural rubber latex. The results show that the predication model has a good achievement and the average relative error was 7.4%