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基于光譜學原理的便攜式土壤有機質(zhì)檢測儀設(shè)計與實驗
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浙江省重點研發(fā)計劃項目(2021C02023)


Design and Experiment of Portable Soil Organic Matter Detector Based on Spectroscopy Principle
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    摘要:

    為快速無損獲取土壤有機質(zhì)含量信息,基于光譜學原理設(shè)計了一款便攜式土壤有機質(zhì)含量檢測儀。檢測儀主要由機械部分、光路系統(tǒng)和控制部分組成,其中機械部分為檢測儀提供平臺支撐,光路部分由光源、藍寶石玻璃、濾光片和光電探測器組成,控制系統(tǒng)實現(xiàn)對土壤測量信號的采集和處理。便攜式土壤有機質(zhì)檢測儀工作時,光源發(fā)出光照射到待測土壤表面,漫反射光經(jīng)過濾光片濾波后由光電轉(zhuǎn)換器實現(xiàn)光信號轉(zhuǎn)換成電信號,再經(jīng)信號處理單元計算出各個敏感波長處的反射率,通過測量光譜反射率檢測土壤有機質(zhì)含量。采集了北京市中國農(nóng)業(yè)大學上莊實驗站土壤的光譜數(shù)據(jù)和土壤有機質(zhì)含量實測值,經(jīng)過光譜數(shù)據(jù)預(yù)處理后,對比了CARS、MCUVE、MWPLS和隨機蛙跳4種波長篩選算法對土壤光譜的處理結(jié)果,建立了土壤有機質(zhì)含量的偏最小二乘和隨機森林預(yù)測模型。結(jié)果表明,基于CARS算法挑選出的4個特征波長建立的隨機森林模型預(yù)測精度最好,建模集R 2為0.923,預(yù)測集R 2為0.888。將CARS-RF模型嵌入有機質(zhì)檢測儀系統(tǒng),實驗結(jié)果表明檢測儀測量值與標準值的相關(guān)系數(shù)達到0.891。開發(fā)的檢測儀精度較高,可以實現(xiàn)快速檢測土壤有機質(zhì)含量。

    Abstract:

    In order to obtain the information of soil organic matter content quickly and non-destructively, a portable instrument for measuring soil organic matter content was designed based on spectroscopy principle. The detector was mainly composed of mechanical part, optical path system and control part, in which the mechanical part provided platform support for the detector, while the optical path part consisted of light source, sapphire glass, filter and photoelectric detector, and the control system realized the collection and processing of soil measurement signals. When the portable soil organic matter detector worked, the light emitted by the light source irradiated the surface of the soil to be detected, the diffuse reflection light was filtered by the optical filter, and then converted into an electrical signal by the photoelectric converter, and then the reflectivity at each sensitive wavelength was calculated by the signal processing unit, and the content of soil organic matter was detected by measuring the spectral reflectivity. The spectral data of soil and the measured values of soil organic matter content in Beijing Shangzhuang Experimental Station were collected. After preprocessing the spectral data, the processing results of four wavelength screening algorithms, CARS, MCUVE, MWPLS and Random Frog Leaping, were compared, and the partial least squares and random forest prediction models of soil organic matter content were established. The results showed that the random forest model based on four characteristic wavelengths selected by CARS algorithm had the best prediction accuracy, with the modeling set R2 being 0.923 and the prediction set R2 being 0.888. The CARS-RF model was embedded into the organic matter detector system. The experimental results showed that the correlation coefficient between the measured value and the standard value of the detector reached 0.891. The developed detector had high precision and can quickly detect the content of soil organic matter.

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崔玉露,楊 瑋,王煒超,王 懂,孟 超,李民贊.基于光譜學原理的便攜式土壤有機質(zhì)檢測儀設(shè)計與實驗[J].農(nóng)業(yè)機械學報,2021,52(S0):323-328,350. CUI Yulu, YANG Wei, WANG Weichao, WANG Dong, MENG Chao, LI Minzan. Design and Experiment of Portable Soil Organic Matter Detector Based on Spectroscopy Principle[J]. Transactions of the Chinese Society for Agricultural Machinery,2021,52(S0):323-328,350.

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  • 收稿日期:2021-07-15
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  • 在線發(fā)布日期: 2021-11-10
  • 出版日期: 2021-12-10