Prediction Model of Nitrogen Content in Apple Leaves based on Ground Imaging Spectroscopy

Prediction Model of Nitrogen Content in Apple Leaves based on Ground Imaging Spectroscopy

Baichao LI[1];Xicun ZHU[1,2];Ruiyang YU[1];Xiaoyan GUO[1];Shujing CAO[1];Huansan ZHAO[1];;

【期刊名称】《遥感科学：中英文版》 【年(卷),期】2018(006)001

【摘要】A prediction model of apple leaf nitrogen content based on ground imaging spectroscopy was established to rapidly and nondestructively detect nitrogen content in apple leaves.SOC710VP hyperspectral imager was used to obtain the imaging spectral information of apple leaves,and the average spectral curve of interest region was extracted.The study is to analyze the characteristics of imaging spectral curves of apple leaves with different nitrogen content.On the basis of the SG smoothing and first derivative pretreatment of the spectral curve,the maximum sensitive band with nitrogen content is screened and the spectral parameters are constructed.Three modeling methods of BP,SVM and RF were used to establish the prediction model of nitrogen content in apple leaves.The results showed that in the visible range,the nitrogen content of apple leaves was negatively correlated with the reflectance of the spectral curve,and was most obvious in the green range.The R2 of BP,SVM and RF of apple leaf nitrogen content prediction model were

0.7283,0.8128,0.9086,RMSE were 0.9359,0.7365,0.5368,the R2 of test model

were

0.6260,0.7294,0.6512,RMSE

were

0.9460,0.7350,0.9024.Comparing the prediction results of the three models,the optimal prediction model is SVM model,which can well predict the nitrogen content of apple leaves. 【总页数】9页(P.9-17)

【关键词】Apple Leaves;SVM;Ground Imaging Spectroscopy

【作者】Baichao LI[1];Xicun ZHU[1,2];Ruiyang YU[1];Xiaoyan GUO[1];Shujing CAO[1];Huansan ZHAO[1];;

【作者单位】[1]College of Resources and Environment,Shandong Agricultural University,Tai’an 271018,China;[1]College of Resources and Environment,Shandong 271018,China;[2]Key

Agricultural

of

Agricultural

University,Tai’an Ecology

and

Laboratory

Environment,Shandong Agricultural University,Tai’an

271018,China;[1]College of Resources and Environment,Shandong Agricultural University,Tai’an 271018,China;[1]College of Resources and Environment,Shandong

Agricultural

University,Tai’an

271018,China;[1]College of Resources and Environment,Shandong Agricultural University,Tai’an 271018,China;[1]College of Resources and Environment,Shandong Agricultural University,Tai’an 271018,China; 【正文语种】英文 【中图分类】TP

【文献来源】

https://www.zhangqiaokeyan.com/academic-journal-cn_remote-sensing-science-chinese-english_thesis/0201272347043.html 【相关文献】

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