PhenoWatch High-throughput plant phenotyping system

High-throughput plant phenotyping system


Mobile high-precision plant phenotype imaging system designed based on the Sensor to Plant concept


The PhenoWatch high-throughput plant phenotype analysis system deeply integrates multiple measurement units such as lidar, RGB imaging, multispectral imaging, infrared thermal imaging, hyperspectral imaging, etc., to generate three-dimensional images with multi-spectral information, and to perform single group planting. Plant identification, separation of stems and leaves of individual plants, accurate acquisition of phenotypic parameters such as plant height, plant width, leaf length, leaf width, leaf inclination, and leaf area, and calculation and analysis of spectral characteristics and vegetation index. Analysis, crop temperature and drought research, crop condition analysis, category identification, pest monitoring, water and fertilizer status monitoring, biochemical parameter detection and other analysis.


      The hardware of PhenoWatch high-throughput plant phenotype analysis system is mainly divided into 3D central imaging unit, greenhouse or field mobile platform.

     3D Central Imaging Unit

Ø  Point cloud module: Lidar. Scanning to obtain point cloud data of plants, for data sources under different platforms and different planting modes, calculation of population parameters and individual plant morphological parameters, so as to provide services for different research needs.

Ø  Multispectral module: Multispectral camera. The five-channel (Blue, Green, Red, NIR, RedEdge) spectral image is used as the data source, and the three-dimensional spatial point cloud is given spectral information through the matching and fusion of the image and the point cloud, and finally the three-dimensional vegetation index calculation is realized.

Ø  Color unit: RGB camera with high-definition resolution. Color image and point cloud matching and fusion to ensure that the true colors of plants are restored while obtaining high-precision three-dimensional images

Ø  Infrared thermal imaging module: adopts high-precision thermal infrared imaging CCD, which can accurately reflect the temperature of the measured object and the surface of the plant.

Ø  Hyperspectral imaging module: Each pixel in the image records the spectral characteristics of the chemical composition, quality, color and other information of the corresponding sample point, which is used for qualitative and quantitative analysis of the sample.

Mounting platform

The mounting platform is used to mount the 3D central imaging unit, which can be customized according to research needs and site conditions:

Ø  Platform Types:Crane, gantry, or customized design according to existing greenhouse or cultivation rack; Size: standard 4×4m (height×width), can be customized. The length of the guide rail can be longer than 1000 m;

Ø  Movement accuracy: X/Y/Z high-precision three-axis movement, guide rail movement (X axis, accuracy <50 mm), horizontal movement (Y axis, accuracy <5 mm), vertical movement (Z axis, accuracy <5 mm);
Ø  Switch function: It can switch between tracks of different plots. Migration function: It can be disassembled and moved to other installation locations.




The PhenoWatch software system uses advanced neural networks and deep learning algorithms, which can integrate the collected crop 3D point cloud data with multi-spectral and RGB image information, three-dimensional modeling and data extraction, and obtain canopy closure and canopy light transmission. Group parameters such as rate and vegetation index can automatically identify individual plants and stems and leaves, extract plant height, plant width, leaf length, leaf width, leaf inclination and leaf area, and provide strong support for plant phenotype research. The software has parallel processing and GPU acceleration functions, which can effectively increase the processing speed of massive point cloud data, and improve the accuracy of crop single plant segmentation and stem and leaf segmentation processing. We can also provide customized data processing module development services according to user needs to meet individual scientific research needs.


PhenoWatch software


Analysis and Extraction of Plant Skeleton


3. Parameters Acquired

ØPhenotypic parameters for population

lDEM: Digital elevation model, the digital expression of terrain surface form.

l DSM: Digital surface model, a ground elevation model that includes the heights of surface buildings, bridges, and vegetation.

lCHM: Canopy height model, subtracting the digital elevation model from the digital surface model

lCanopy Cover: The vertical projection of crops as a percentage of the field.



l Transmittance: It can reflect the light transmittance of the crop canopy from top to bottom, and understand the structural details of the 
canopy of light and ventilation.

l 3D point cloud vegetation index: 3D NDVI、3D TVI、3D RVI、3D DVI

l 2D vegetation index: 2D NDVI、2D TVI、2D RVI、2D DVI

l Vegetation index statistics: statistics of multi-spectral vegetation index, such as mean, maximum, minimum, etc.

l Greenness: custom threshold, reflecting the greenness of plants

l  Infrared thermal imaging analysis: image pixel temperature, plant canopy temperature (with thermal infrared imaging unit)Reports for
 statistical population phenotypic parameters: the height of each plant, crown width, projected area, crown height ratio and volume, etc.


Ø Phenotypic parameters for individuals:


Crown width

Projected area

Crown-to-height ratio


Leaf number

Total leaf area

Leaf length

Leaf width

Leaf angle

Leaf area

Stem width

ØReport of phenotypic parameters for individuals:


System Expandability

      The system can expand the optional imaging module according to different research needs to achieve more functions.

Optional module 1: Multispectral camera

      The wavelength range of 400-900nm, 5 bands, covering red, green, blue, near-infrared, red edge, can be calculated for various vegetation indexes such as NDVI, to meet the application of crop multispectral research.


Multispectral module can obtain chlorophyll distribution, NDVI, digital surface model, RGB image, etc.

Optional module 2: Infrared thermal imaging module

The infrared thermal imaging module has a builtin uncooled vanadium oxide (VoX) infrared detector, which can generate a 640 x 480 
pixel thermal image, making the thermal image more accurate; equipped with a highspeed infrared window option; clearly display a 
temperature difference of 50 mk; builtin 25° lens with electric focus and auto focus. It complies with GigE VISION™ standard to realize
 fast image transmission standard; supports GENICAM™ protocol, 16-bit temperature linear output, and supports non-contact temperature
 measurement in third-party software. It can stream 16-bit real-time images to the computer.


Fixed-point analysis

Isothermal analysis     Temperature analysis report

Optional module 3: Hyperspectral imaging module

    Equipped with hyperspectral imaging module, the hyperspectral imaging system combines visible light near infrared (VNIR or NIR)
 spectroscopy with high-resolution imaging, and uses pushbroom imaging technology for moving samples or static samples in motion.
 Collect and synchronouslygenerate images linebyline and fullband spectrum to obtain quantitative data of sample chemical composition
 and spatial distribution and other detailed information. Each pixel in the image records the spectral characteristics of the chemical 
composition, quality, color and other information of the corresponding sample point. Used for qualitative and quantitative analysis of samples.


Hyperspectral imaging and hyperspectral curve


Evaluation of Wheat Leaf Spot Blight by Hyperspectral


PhenoWatch on Site


Northwest Institute of Plateau Biology, Chinese Academy of Sciences

Institute of Soil Science, Chinese Academy of Sciences
China National Center for Vegetable Quality Standards 

Nanjing Agricultural University


LiDAR Specifications

Data Points Generated

97,600 points/sencond


±2 mm @ 25 m

Field of View


Angular Resolution


RGB Imaging Specifications


2448 x 2048 mm


24 bit RGB

Multispectral Imaging Specifications


0.35 cm/pixel (5m)

Field of View



475nm, 560nm, 668nm, 840nm, 717nm

Thermal Imaging Specifications


640 x 480 mm

Hyperspectral Imaging Specifications

Hyperspectral Wavelength

400 nm – 1000nm, 900nm – 1700 nm