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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.
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篇名 Prediction Model of Nitrogen Content in Apple Leaves based on Ground Imaging Spectroscopy
来源期刊 遥感科学:中英文版 学科 工学
关键词 APPLE LEAVES SVM GROUND IMAGING SPECTROSCOPY
年,卷(期) 2018,(1) 所属期刊栏目
研究方向 页码范围 9-17
页数 9页 分类号 TP
字数 语种
DOI
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研究主题发展历程
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APPLE
LEAVES
SVM
GROUND
IMAGING
SPECTROSCOPY
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期刊影响力
遥感科学:中英文版
季刊
2329-8138
湖北省武汉市武昌区珞狮南路519号(中国
出版文献量(篇)
54
总下载数(次)
1
总被引数(次)
0
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