[Spectrum analysis of crop and weeds at seedling].
The infestation information on field weeds is the basis of variable spraying herbicides. It was found that the method using the spectral characteristics of plant is superior in real-time respect. The Fourier transform infrared spectrum technique was applied to measure the reflectance of wheat and weeds in the range from 700 to 1100 nm. The discrimination analysis was done using the SPSS software. Firstly, the source spectrum data were compressed and normalized. Secondly, the characteristic wavelengths were selected by using stepwise method. Thirdly, the discrimination model was set up to use the selected wavelengths as the variables for detecting wheat and weeds. It was shown by the result of discrimination analysis that the correct classification rate of wheat and weeds detection with the selected wavelength points achieved 97%. In addition, the selected wavelength points were marked in the "red edge" of reflectance within some range, and the rate of correct classification increased with the increase in the numbers of the selected wavelength points. According to the selected wavelength points, the proper filters were chosen to perform the multi-spectral images captured and processed with the machine vision system.
Mao
Wen-hua
WH
College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China.
Wang
Yue-qing
YQ
Wang
Yi-ming
YM
Zhang
Xiao-chao
XC
D029687:Capsella / Q000737:chemistry; D027462:Chenopodium / Q000737:chemistry; D016002:Discriminant Analysis; D019684:Magnoliopsida / Q000737:chemistry* / Q000145:classification; D018515:Plant Leaves / Q000737:chemistry; D036226:Seedlings / Q000737:chemistry*; D031184:Sonchus / Q000737:chemistry; D013050:Spectrometry, Fluorescence; D017550:Spectroscopy, Fourier Transform Infrared; D013057:Spectrum Analysis; D014908:Triticum / Q000737:chemistry