Improving High-Throughput Phenotyping Using Fusion of Close-Range Hyperspectral Camera and Low-Cost Depth Sensor

被引:22
作者
Huang, Peikui [1 ]
Luo, Xiwen [1 ]
Jin, Jian [2 ]
Wang, Liangju [2 ]
Zhang, Libo [2 ]
Liu, Jie [3 ]
Zhang, Zhigang [1 ]
机构
[1] South China Agr Univ, Minist Educ, Key Lab Key Technol Agr Machine & Equipment, Guangzhou 510642, Guangdong, Peoples R China
[2] Purdue Univ, Dept Agr & Biol Engn, 225 S Univ St, W Lafayette, IN 47907 USA
[3] Huazhong Agr Univ, Coll Engn, Wuhan 430070, Hubei, Peoples R China
关键词
high-throughput phenotyping; close-range hyperspectral camera; low-cost depth sensor; fusion; plant 3D model; IMAGING-SYSTEM; PLANT; CALIBRATION; STRESS; GROWTH; MODEL; LIDAR;
D O I
10.3390/s18082711
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Hyperspectral sensors, especially the close-range hyperspectral camera, have been widely introduced to detect biological processes of plants in the high-throughput phenotyping platform, to support the identification of biotic and abiotic stress reactions at an early stage. However, the complex geometry of plants and their interaction with the illumination, severely affects the spectral information obtained. Furthermore, plant structure, leaf area, and leaf inclination distribution are critical indexes which have been widely used in multiple plant models. Therefore, the process of combination between hyperspectral images and 3D point clouds is a promising approach to solve these problems and improve the high-throughput phenotyping technique. We proposed a novel approach fusing a low-cost depth sensor and a close-range hyperspectral camera, which extended hyperspectral camera ability with 3D information as a potential tool for high-throughput phenotyping. An exemplary new calibration and analysis method was shown in soybean leaf experiments. The results showed that a 0.99 pixel resolution for the hyperspectral camera and a 3.3 millimeter accuracy for the depth sensor, could be achieved in a controlled environment using the method proposed in this paper. We also discussed the new capabilities gained using this new method, to quantify and model the effects of plant geometry and sensor configuration. The possibility of 3D reflectance models can be used to minimize the geometry-related effects in hyperspectral images, and to significantly improve high-throughput phenotyping. Overall results of this research, indicated that the proposed method provided more accurate spatial and spectral plant information, which helped to enhance the precision of biological processes in high-throughput phenotyping.
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页数:17
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共 42 条
[1]   A multi-sensor system for high throughput field phenotyping in soybean and wheat breeding [J].
Bai, Geng ;
Ge, Yufeng ;
Hussain, Waseem ;
Baenziger, P. Stephen ;
Graef, George .
COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2016, 128 :181-192
[2]   Low-weight and UAV-based Hyperspectral Full-frame Cameras for Monitoring Crops: Spectral Comparison with Portable Spectroradiometer Measurements [J].
Bareth, Georg ;
Aasen, Helge ;
Bendig, Juliane ;
Gnyp, Martin Leon ;
Bolten, Andreas ;
Jung, Andras ;
Michels, Rene ;
Soukkamaki, Jussi .
PHOTOGRAMMETRIE FERNERKUNDUNG GEOINFORMATION, 2015, (01) :69-79
[3]   Generation and application of hyperspectral 3D plant models: methods and challenges [J].
Behmann, Jan ;
Mahlein, Anne-Katrin ;
Paulus, Stefan ;
Dupuis, Jan ;
Kuhlmann, Heiner ;
Oerke, Erich-Christian ;
Pluemer, Lutz .
MACHINE VISION AND APPLICATIONS, 2016, 27 (05) :611-624
[4]   Calibration of hyperspectral close-range pushbroom cameras for plant phenotyping [J].
Behmann, Jan ;
Mahlein, Anne-Katrin ;
Paulus, Stefan ;
Kuhlmann, Heiner ;
Oerke, Erich-Christian ;
Pluemer, Lutz .
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2015, 106 :172-182
[5]   Computer Reconstruction of Plant Growth and Chlorophyll Fluorescence Emission in Three Spatial Dimensions [J].
Bellasio, Chandra ;
Olejnickova, Julie ;
Tesar, Radek ;
Sebela, David ;
Nedbal, Ladislav .
SENSORS, 2012, 12 (01) :1052-1071
[6]   A stereo imaging system for measuring structural parameters of plant canopies [J].
Biskup, Bernhard ;
Scharr, Hanno ;
Schurr, Ulrich ;
Rascher, Uwe .
PLANT CELL AND ENVIRONMENT, 2007, 30 (10) :1299-1308
[7]   Angular Dependency of Hyperspectral Measurements over Wheat Characterized by a Novel UAV Based Goniometer [J].
Burkart, Andreas ;
Aasen, Helge ;
Alonso, Luis ;
Menz, Gunter ;
Bareth, Georg ;
Rascher, Uwe .
REMOTE SENSING, 2015, 7 (01) :725-746
[8]   On the use of depth camera for 3D phenotyping of entire plants [J].
Chene, Yann ;
Rousseau, David ;
Lucidarme, Philippe ;
Bertheloot, Jessica ;
Caffier, Valerie ;
Morel, Philippe ;
Belin, Etienne ;
Chapeau-Blondeau, Francois .
COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2012, 82 :122-127
[9]   The spectral response of Buxus sempervirens to different types of environmental stress - A laboratory experiment [J].
de Jong, Steven M. ;
Addink, Elisabeth A. ;
Hoogenboom, Priscilla ;
Nijland, Wiebe .
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2012, 74 :56-65
[10]   Plane-Based Calibration for Linear Cameras [J].
Drareni, Jamil ;
Roy, Sebastien ;
Sturm, Peter .
INTERNATIONAL JOURNAL OF COMPUTER VISION, 2011, 91 (02) :146-156