CAJ | 학술논문

为了有效的解决玉米苗期冠层叶片营养状态车载动态诊断过程中，土壤干扰信息无法剔除的问题，本文提出了一种动态测量用光谱指数MPRI，根据MPRI的构成和特点、论述了利用MPRI辨识土壤与冠层光谱信息的机理，构建了基于 MP R I的玉米苗期冠层叶片叶绿素含量的预测模型，通过车载式作物长势检测系统平台，运用模型对玉米苗期冠层叶片营养状态进行动态诊断与评估，取得良好的效果。研究表明：在车载动态条件下测量玉米苗期冠层叶片营养状态时，土壤的 MPRI 呈正值而玉米冠层的 MPRI 呈负值，因此使用光谱指数 MP R I能够有效识别土壤背景与冠层叶片光谱信息。设定固定的阈值，能够较为准确和便捷的去除土壤背景光谱信息。基于 MP R I构建的冠层叶片叶绿素含量的动态测量预测模型，能够准确的表征冠层叶片的叶绿素含量，模型决定系数R2达0．72，动态测量中对植株冠层的识别率达80％。与其他常用的指数相比，在车载动态测量环境下，光谱指数 MP R I具有土壤背景信息识别速度快、正确率高，模型预测精度良好等特点，为玉米苗期冠层营养状态的诊断提供了新的途径。
위료유효적해결옥미묘기관층협편영양상태차재동태진단과정중，토양간우신식무법척제적문제，본문제출료일충동태측량용광보지수MPRI，근거MPRI적구성화특점、논술료이용MPRI변식토양여관층광보신식적궤리，구건료기우 MP R I적옥미묘기관층협편협록소함량적예측모형，통과차재식작물장세검측계통평태，운용모형대옥미묘기관층협편영양상태진행동태진단여평고，취득량호적효과。연구표명：재차재동태조건하측량옥미묘기관층협편영양상태시，토양적 MPRI 정정치이옥미관층적 MPRI 정부치，인차사용광보지수 MP R I능구유효식별토양배경여관층협편광보신식。설정고정적역치，능구교위준학화편첩적거제토양배경광보신식。기우 MP R I구건적관층협편협록소함량적동태측량예측모형，능구준학적표정관층협편적협록소함량，모형결정계수R2체0．72，동태측량중대식주관층적식별솔체80％。여기타상용적지수상비，재차재동태측량배경하，광보지수 MP R I구유토양배경신식식별속도쾌、정학솔고，모형예측정도량호등특점，위옥미묘기관층영양상태적진단제공료신적도경。
Ground-based remote sensing system is a significant way to understand the growth of corn and provide accurate and scientific data for precision agriculture.The vehicle-borne system is one of the most important tools for corn canopy monitoring. However,the vehicle-borne growth monitoring system cannot maintain steady operations due to the row spacing of corn.The re-flectance of corn canopy,which was used to construct the model for the chlorophyll content,was disturbed by the reflectance of soil background.The background interference with the reflectance could not be removed effectively,which would result in a de-viation in the growth monitoring.In order to overcome this problem,a novel vegetation index named MPRI was developed in the present paper.The tests were carried out by the vehicle-borne system on the cornfield.The sensors which configured the vehi-cle-borne system had 4 bands,being respectively 550,650,766 and 850 nm.It would obtain the spectral data while the vehicle moved along the row direction.The sampling rate was about 1 point per second.The GPS receiver obtained the location informa-tion at the same rate.MPRI was made up by the reflectance ratio of 660 and 550 nm.It was very effective to analyze the infor-mation about the reflectance of the canopy.The results of experiments showed that the MPRI of soil was the positive value and the MPRI of canopy was the negative value.So it is easier to distinguish the spectral information about soil and corn canopy by MPRI.The results indicated that:it had satisfactory forecasting accuracy for the chlorophyll content by using the MPRI on the moving monitoring.The R2 of the prediction model was about 0. 72.The R2 of the model of NDVI,which was used to represent the chlorophyll content,was only 0. 24.It indicates that MPRI had good measurement results for the dynamic measurement process.It provided the novel measurement way to get the canopy reflectance spectra and the better vegetation index to construct the prediction model of the contents of chlorophyll.