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Conveyor-Based High Throughput Plant Phenotyping Imaging System
PhenoScanalyzer HT
The high-throughput plant phenotyping imaging system-PhenoScanalyzer HTisafuly automated high-throughput syster plants frmseedingstomatue plants) It canbeptionaly configured with modules inclding RGBmaging,infrared ma visible light imaging,laserscaning and hyperspectral imaging toconduct coprehensive phenotypic analsisof plant
01
RGB Imaging Module
Equipped with a dedicated imaging chamber containing a top visible light imaging unit and a side visible light imaging unit (additional oblique 75° ， 60° or 45° cameras can be added upon request). The plant pot base features a rotation mechanism capable of 360° rotation, with adjustable angles controlled via software, enabling capture of visible light phenotypic parameters from multiple angles.
Pla Pheno Imag Mod
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Chlorophyll Fluorescence Imaging Module
Includes a dedicated imaging chamber housing a top chlorophyll fluorescence imaging unit. This module may optionally integrate dark adaptation/light adaptation channels for pre-treatment of plants during chlorophyll fluorescence measurements, ensuring precise dark adaptation and light induction protocols.
03
Infrared Imaging Module
Operates as a standalone top or side imaging unit, which may optionally be equipped with an imaging cabinet or deployed directly in cultivation areas without a chamber. It is capable of measuring plant surface temperature for stress studies such as drought and high-temperature conditions.
n designed for imaging large quantities of ing, chlorophyll fluorescence imaging, root
Laser 3D Imaging Module
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Utilizes 3D scanning to acquire plant point cloud data and reconstruct 3D plant architecture. The PhenoScanalyzer HT employs a 3D laser scanning system, delivering high-resolution point cloud data for precise structural analysis.
Hyperspectral Imaging Module
05
Covers spectral ranges of 400-1000 nm, 900-1700 nm, and 1000-2500 nm to extract intrinsic biochemical information from plants. Mounted on an automated robotic arm, this module performs dynamic scanning across plant surfaces. A stabilized halogen light source ensures enhanced precision in hyperspectral data acquisition.
Root Visible Light Imaging System
06
Utilizes rhizoboxes with specialized geometries to cultivate plants in soil-based in-situ conditions. The visible light imaging system captures and analyzes root architecture images through transparent observation panels.
Automated Transport System
The automated transport system transfers potted plants between cultivation zones and imaging modules, returning them post-imaging. Configurable transport mechanisms are available to accommodate varying sample weights. Throughput and system layout are customizable based on greenhouse size and operational demands, with load capacities ranging from 5-50~\mathsf{kg} . Designed with modularity, the system can be expanded post-installtion to increase throughput if required. A transport carts are equipped with RFID tags.When a cart passes through the loading area, the system automatically scans the tag, enabling alimaging data to be cataloged by tag ID and stored in a local database.
Server Storage
To accommodate the massive volume of plant phenotyping data, the system integrates dedicated server storage. All acquired phenotypic datasets are securely archived onlocal servers with climate-controlled stability. During analysis, raw data is retrieved directly from the server and processed results arelikewise stored locally, ensuring both security and operational reliability.
Software
The PhenoScanalyzer HT operates via integrated control and analytical software platforms
Control Software
Manages all hardware components, including device operation scheduling, protocol configuration, acquisition parameter adjustment, and camera calibration.
Analytical Software
Processes multi-sensor datasets to extract quantitative plant phenotypic traits, with customizable algorithms for phenotypic parameterization.
Application
Plant Color Classification
The color of plants is a key indicatol reflecting their health status. However, the human eye has low sensitivity to color and significant visual inaccuracies. The PhenoScanalyzer HT system addresses this limitation by capturing visible light images of plants and processing the color information through specialized software. This technological approach enables distinct differentiationofcolorvariations thatareotherwisedifficultto discern with the naked eye, thereby enhancing the precision of plant health assessments.
Plant skeleton and architecture information are quintessential phenotypic traits and a critical focus in agricultural informatics. For hybrid breeding, the PhenoScanalyzer HT system enables rapid phenotypic screening and facilitates the study of structural changes throughout a plant's entire life cycle, as well as under stress conditions.
Plant Morphological Analysis
After imaging, detailed three-dimensional morphological analysis of plants can be conducted usingspecializedsoftware and algorithms. For each captured image, multiple morphological parameters can be derived.
Forthisimage,datasuchasindividual leaflength, individualleafarea,averageleafwidth,stem length, stem width, stem volume, leaf curling index,leaforientation,andcolorclassificationof individualleavescanbeobtained.
This image is utilized for detailed analysis of plant orientation and angles.
By combining top-view imaging with multiple side-view images, three-dimensional (X, Y, Z) information of the plant can be acquired. Biomass is estimated using parameters such as leaf area, stem length, stem width, leaf length, and color across different orientations. Experimental results have demonstrated a strong linear correlationbetweentheestimated biomassandactualmeasured biomass.
Near-infrared (NIR) imaging provides a directvisualizationof watercontentvariationsacross plant tissues. By assigning color gradients torepresent different moisture levels through software processing, changes in water content under varying treatments can be intuitively observed.
In maize subjected to mild drought treatment (8 hours of withheld irrigation), NiR imaging clearly reveals water loss patterns
NIR Imaging Analysis of Water Content Dynamics in Wheat During Drying
This case study demonstrates how near-infrared (NIR) imaging visualizes and quantifies the temporal dynamics of water content in wheat under high-temperature treatment. Following 16 hours of exposure, NIR imaging captured progressive changes in the plant's hydration status. Quantitative analysisrevealed a gradual decline in wheat water content as the duration of high-temperature treatment increased, highlighting the system's capability to monitor dehydration processes in real time.
After pesticide application, non-transgenic plants (those not engineered with pesticide-resistant genes) can be identified through color-based analysis.
Morphological Applications in Individual Plants and Populations
The PhenoAlxpert HT imaging system enables the acquisition of extensive morphological parameters, with tailored metrics generated for different plant materials. Below are illustrative examples:
Panicle Imaging Parameters:
\bullet Panicle area
\bullet Panicle color
\bullet Panicle length Maximum panicle length Panicle architecture Panicle skeleton
Population Phenotyping Parameters:
Phenotypic Analysis Based on Complex Morphological Metrics
\bullet Growth status Plant height Compactness Leaf orientationbending index Density Symmetry Average plant widt per unit height
\bullet Structural orientation
\bullet Moment of inertia
\bullet Height Width Roundness Compactness
