Using Neural Network to Model the Relationship between Plant Surface Color and Its Pigment
Combining the intelligent algorithm such as BP neural network and support vector macbing (SVM) with traditional chemical method, this paper models the relationship between plant surface color and its pigment Using the neural network model constructed above, people can figure out the content of plant pigments by getting the corresponding plant surface color information. Compared with the traditional modeling methods, this method can significantly save time and experimental supplies. Furthermore, it is easy to implement because it neednt touch samples and doesnt cause any damage to samples. So this method provides a practical tool for non-destructive measurements of plant pigments and solutions to explore the mystery of plant color.
Chinese kale stems HSV mean plant pigment BP neural network Support vector machine(SVM)
Zeng Qingmao Zhang Tong Zhu Tonglin
Institution of Agricultural Multimedia Technology Guangzhou, China College of Science Guangzhou, Chi Institution of Agricultural Multimedia Technology Guangzhou, China College of Information South Chin
国际会议
深圳
英文
303-307
2011-03-28（万方平台首次上网日期，不代表论文的发表时间）