基于多波段光谱探测仪的玉米冠层叶绿素含量诊断
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农业部引进国际先进农业科学技术计划(948计划)资助项目(2011-G32)、北京市科技计划资助项目(D151100004215002)和海外名师资助项目


Diagnosis of Chlorophyll Content in Corn Canopy Leaves Based on Multispectral Detector
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    摘要:

    为了快速无损地检测大田作物冠层叶绿素含量,使用便携式多波段光谱探测仪针对农大8号(G1)、郑单(G2)、先玉(G3)和京农科(G4)4种玉米作物品种,在拔节期采集550、650、766、850 nm波长处太阳光信号和作物冠层反射光信号,用于建立玉米冠层叶绿素含量诊断模型。首先,利用作物冠层650 nm和550 nm波长反射率之间的差值 T D 剔除了土壤背景数据点( T D >0)。然后,组合计算了NDVI、RVI和DVI共12个植被指数,分析各植被指数与叶绿素含量之间的相关关系,结果显示与G1~G4品种叶绿素含量相关性最优的参数分别为RVI(766,550)、 DVI(850,650)、 NDVI(850,550)和RVI(766,550),相关系数均达0.6以上。数据按一定间隔聚类后,相关性分析结果表明多波段光谱探测仪对玉米叶绿素含量检测最优分辨率为0.5 mg/L,且NDVI(850,550)、NDVI(766,550)和RVI(850,550)与叶绿素含量的相关系数分别为0.837 0、0.773 7和0.767 7,达到了强相关水平。最后,建立了多品种通用型玉米拔节期叶绿素含量诊断模型,可为大田玉米拔节期叶绿素含量诊断提供技术支持。

    Abstract:

    In order to rapidly detect the nutrition content of crop, a portable multispectral detector was developed. The detector was composed of a controller and an optical sensor node, which communicated with each other through the ZigBee protocol. The optical sensor node can measure both the intensity of solar light and crop reflective light at 550 nm, 766 nm, 650 nm and 850 nm wavebands, respectively. The control unit is a PDA, in which a ZigBee wireless communication module is embedded. As the coordinator of the whole wireless sensor network, the ZigBee wireless communication module is responsible for receiving, processing and displaying the spectral data transmitted by the measuring unit. The objective of the research was to assess the agronomic performance of the detector, i.e., the accuracy of chlorophyll content estimation when using the instrument in different arable crops. Field experiments were conducted on four varieties of corn (Nongda No. 8 (G1), Zhengdan (G2), Xianyu (G3) and Jingnongke (G4)). Crop canopy reflectance was measured by the detector at jointing stage. The chlorophyll contents of sampling leaves were measured by the spectrophotometer in the laboratory. According to the typical spectral characteristics of crop and soil, the differences of reflectance between 550 nm and 650 nm ( T D ) were used to remove the soil background data points ( T D >0). Furthermore, combinations of R nir and R r ((850, 550), (850, 650), (766, 550) and (766, 650)) were used to calculate vegetation indices, including DVI, NDVI and RVI. Relationship between each vegetation index and chlorophyll content of each variety was analyzed. The results showed that the optimal parameters of G1~G4 were RVI (766, 550), DVI (850, 650), NDVI (850, 550) and RVI (766, 550), respectively, and the correlation coefficients were above 0.6. The chlorophyll content of the four varieties was clustered respectively at intervals of 0.2 mg/L, 0.5 mg/L and 0.8 mg/L. The correlation analysis results showed that the optimal resolution of the multispectral detector for detecting chlorophyll content of corn was 0.5 mg/L. The correlation coefficients of NDVI (850, 550), NDVI (766, 550) and RVI (850, 550) and chlorophyll content were 0.837 0, 0.773 7 and 0.767 7, respectively. The NDVI (850, 550) and RVI (850, 550) were selected to establish the diagnosis model with R 2 C of 0.715 4 and R 2 V of 0.684 0. The research could provide theoretical and technical support for the diagnosis of chlorophyll content of corn at jointing stage.

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刘豪杰,赵毅,文瑶,孙红,李民赞,Zhang Qin.基于多波段光谱探测仪的玉米冠层叶绿素含量诊断[J].农业机械学报,2015,46(S1):228-233,245.

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  • 收稿日期:2015-10-28
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  • 在线发布日期: 2015-12-30
  • 出版日期: 2015-12-31