Artificial Neural Network to Predict Leaf Population Chlorophyll Content from Cotton Plant Images

文献类型： 外文期刊

第一作者： Li Shao-kun

作者： Li Shao-kun;Wang Ke-ru;Wang Chong-tao;Suo Xing-mei;Jiang Ying-tao;Yang Mei

作者机构：

关键词： artificial neural network;image processing;cotton plant;leaf population chlorophyll content;prediction

期刊名称：AGRICULTURAL SCIENCES IN CHINA （ 影响因子：0.82； 五年影响因子：0.997 ）

ISSN： 1671-2927

年卷期： 2010 年 9 卷 1 期

页码：

收录情况： SCI

摘要： Leaf population chlorophyll content in a population of crops, if obtained in a timely manner, served as a key indicator for growth management and diseases diagnosis. In this paper, a three-layer multilayer perceptron (MLP) artificial neural network (ANN) based prediction system was presented for predicting the leaf population chlorophyll content from the cotton plant images. As the training of this prediction system relied heavily on how well those leaf green pixels were separated from background noises in cotton plant images, a global thresholding algorithm. and an omnidirectional scan noise filtering coupled with the hue histogram statistic method were designed for leaf green pixel extraction. With the obtained leaf green pixels, the system training was carried out by applying a back propagation algorithm. The proposed system was tested to predict the chlorophyll content from the cotton plant images. The results using the proposed system were in sound agreement with those obtained by the destructive method. The average prediction relative error for the chlorophyll density (mu g cm(-2)) in the 17 testing images was 8.41%.

分类号：

  • 相关文献

[1]Functional analysis of nodulin-like promoter in transgenic cotton plants. Ren, MZ,Chen, QJ,Li, L,Zhang, R,Guo, SD. 2005

[2]Functional analysis of a reproductive organ predominant expressing promoter in cotton plants. Ren, MZ,Chen, QJ,Li, L,Zhang, R,Guo, SD.

[3]The Advances, Problems and Advices of Structural-Functional Modeling for Fruit Trees. Hong, Jianjun,Gan, Yangying,Yan, Minjie. 2011

[4]Plant Identification Based on Artificial Intelligence. Hou Chun Sheng,Zhou Ting. 2011

[5]Pedotransfer Functions for Estimating Soil Bulk Density: A Case Study in the Three-River Headwater Region of Qinghai Province, China. Yi Xiangsheng,Yi Xiangsheng,Li Guosheng,Yin Yanyu. 2016

[6]Application of Artificial Neural Network to the Assessment Environmental Quality of Urban wetland in Northeast China. Li Ji-guang,Ren Yi-bin,Ren Nan-qi,Li Ji-guang,Wang Qi-shuo,Tian Shuangqi,He Ji-wei,Wang He,Ren Nan-qi. 2012

[7]Spatio-temporal changes in rice area at the northern limits of the rice cropping system in China from 1984 to 2013. Long Yu-qiao,Tang Peng-qin,Li Zheng-guo,Wu Wen-bin,Hu Ya-nan,Yang Peng,Tan Jie-yang. 2017

[8]Research on Prediction Chemical Composition of Beef by Near Infrared Reflectance Spectroscopy. Sun Xiao-ming,Lu Ling,Zhang Song-shan,Sun Bao-zhong,Sun Xiao-ming,Zhang Jia-cheng. 2011

[9]Retrieval snow depth by artificial neural network methodology from integrated AMSR-E and in-situ data-A case study in Qinghai-Tibet Plateau. Cao Yungang,Yang Xiuchun,Zhu Xiaohua. 2008

[10]Improvement of specific growth rate of Pichia pastoris for effective porcine interferon-alpha production with an on-line model-based glycerol feeding strategy. Gao, Min-Jie,Zheng, Zhi-Yong,Wu, Jian-Rong,Jin, Hu,Zhan, Xiao-Bei,Lin, Chi-Chung,Dong, Shi-Juan,Li, Zhen. 2012

[11]Comparison of three methods to develop pedotransfer functions for the saturated water content and field water capacity in permafrost region. Yi, Xiangsheng,Li, Guosheng,Yin, Yanyu,Yi, Xiangsheng. 2013

[12]Evaluation of adsorption potential of bamboo biochar for metal-complex dye: equilibrium, kinetics and artificial neural network modeling. Yang, Y.,Wang, J.,Yang, Y.,Zhao, Y.,Lin, X.,Wei, B.. 2014

[13]Quantitative determination of nutrient content in poultry manure by near infrared spectroscopy based on artificial neural networks. Chen, L. J.,Han, L. J.,Xing, L.. 2009

[14]Sweetpotato vines hydrolysate promotes single cell oils production of Trichosporon fermentans in high-density molasses fermentation. Shen, Qi,Wang, Qun,Fan, Xiaoping,Zhao, Yuhua,Lin, Hui,Yang, Yuyi.

[15]Combining various wall materials for encapsulation of blueberry anthocyanin extracts: Optimization by artificial neural network and genetic algorithm and a comprehensive analysis of anthocyanin powder properties. Tao, Yang,Wang, Ping,Wang, Jiandong,Wu, Yue,Han, Yongbin,Zhou, Jianzhong.

[16]Estimation of subpixel land surface temperature using an endmember index based technique: A case examination on ASTER and MODIS temperature products over a heterogeneous area. Yang, Guijun,Yang, Guijun,Yang, Guijun,Zhao, Chunjiang,Huang, Wenjiang,Wang, Jihua,Pu, Ruiliang.

[17]Comparison of Four Chemometric Techniques for Estimating Leaf Nitrogen Concentrations in Winter Wheat (Triticum Aestivum) Based on Hyperspectral Features. Li, Zh.,Wei, Ch.,Wang, J.,Li, Zh.,Nie, Ch.,Xu, X.,Song, X.,Li, Zh.,Nie, Ch.,Xu, X.,Song, X.,Wang, J..

[18]Damage Mapping of Powdery Mildew in Winter Wheat with High-Resolution Satellite Image. Yuan, Lin,Zhang, Jingcheng,Nie, Chenwei,Wei, Liguang,Wang, Jihua,Zhang, Jingcheng,Wang, Jihua,Zhang, Jingcheng,Wang, Jihua,Yuan, Lin,Zhang, Jingcheng,Wang, Jihua,Shi, Yeyin. 2014

[19]Survey of Support Vector Machine in the Processing of Remote Sensing Image. Li, Su,Wang, Wenchao. 2013

[20]Quick image processing method of HJ satellites applied in agriculture monitoring. Yu Haiyang,Liu Yanmei,Yang Guijun,Yang Xiaodong,Yu Haiyang,Liu Yanmei,Yang Guijun,Yang Xiaodong. 2016

作者其他论文 更多>>

微信小程序