Non-destructive estimation of rice plant nitrogen status with Crop Circle multispectral active canopy sensor

被引:174
作者
Cao, Qiang [1 ]
Miao, Yuxin [1 ]
Wang, Hongye [1 ]
Huang, Shanyu [1 ,2 ]
Cheng, Shanshan [1 ]
Khosla, R. [1 ,3 ]
Jiang, Rongfeng [1 ]
机构
[1] China Agr Univ, Ctr Resources Environm & Food Secur, Coll Resources & Environm Sci, Int Ctr Agroinformat & Sustainable Dev ICASD, Beijing 100193, Peoples R China
[2] Univ Cologne, Inst Geog, D-50923 Cologne, Germany
[3] Colorado State Univ, Dept Soil & Crop Sci, Ft Collins, CO 80523 USA
关键词
Precision nitrogen management; Nitrogen status; Nitrogen nutrition index; Red edge vegetation index; Active crop sensor; Nitrogen status diagnosis; Precision agriculture; HYPERSPECTRAL VEGETATION INDEXES; LEAF-AREA INDEX; NUTRITION INDEX; CHLOROPHYLL CONTENT; USE EFFICIENCY; GRAIN-YIELD; N STATUS; CORN; REFLECTANCE; MANAGEMENT;
D O I
10.1016/j.fcr.2013.08.005
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Crop Circle is an active multispectral canopy sensor developed to support precision crop management. The Crop Circle ACS-470 model is user configurable, with a choice of six wavebands covering blue, green, red, red edge and near infrared spectral regions. The objectives of this study were to determine how well nitrogen (N) status of rice (Oryza sativa L) can be estimated with the Crop Circle ACS-470 active sensor using green, red edge and near infrared (NIR) bands at key growth stages and identify important vegetation indices for estimating rice N status indicators. Six field experiments involving different N rates and two varieties were conducted in Sanjiang Plain in Heilongjiang Province, China during 2011 and 2012. Crop sensor data and plant samples were also collected from five farmers' fields to further evaluate the sensor and selected vegetation indices. The results of the study indicated that among 43 different vegetation indices evaluated, modified chlorophyll absorption reflectance index 1 (MCARI1) had consistent correlations with rice aboveground biomass (R-2=0.79) and plant N uptake (R-2=0.83) across growth stages. Four red edge-based indices, red edge soil adjusted vegetation index (RESAVI), modified RESAVI (MRESAVI), red edge difference vegetation index (REDVI) and red edge re-normalized difference vegetation index (RERDVI), performed equally well for estimating N nutrition index (NNI) across growth stages (R-2=0.76). For rice plant N concentration, the highest R-2 was 0.33, and none of the indices performed satisfactorily with validation using farmers' field data. We conclude that the Crop Circle ACS-470 active canopy sensor allows users the flexibility to select suitable bands and calculate different vegetation indices and has a great potential for in-season non-destructive estimation of rice biomass, plant N uptake and NNI. (C) 2013 Elsevier B.V. All rights reserved.
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页码:133 / 144
页数:12
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