PhenoSight

PhenoSight is anloT-enabled phenotyping plaform designed forsimlicity and versatity acrosdiverse environments.Th modeling tomanage and process platform-generated data, enabling comprehensive explorationof dynamic genotype-phe

PhenoSight operates optimall in partitioned field plots with recommended mx2m units, comprising servers and teminal temperatureumidityetectors, soilparametesensors, chlorophyforesence sensors,hyperspectral measuring sens be equipped initThis multi-sensor integration enablessimultaneus phenotyping datacollection and environmental facto plant develpment underspecificenironental condiionsoffring crtical insights foragricuturaldecisionmaingld

Tomeasur plant canpyperature, laf mperature, and temperaturevariations acro diferent pant parts to sup

A state-ofthe-art diagnsticsystemleveraging pectral parameter extraction technlgyforcrops, thismodule synergie real-tien-fid crpvitaltyassessentyquantifyingcanp spetral refetance, thdevice elives instantane index(LAl), biomasallocation, chlorophla profling, and ntrient status dagnstics.This invationcircumvents conve precision agriculture analytics.

system integrates automated field control, high-throughput trait analysis algorithms, and machine learning-based notype-environment interactions.

Inits. PhenoSight servers equips a RGB sensor as a standard option, and it can equip other sensors including s, and multispectral maging sensors. PhenoSight terminal unit equips a RGB sensor and there are nomore sensors can incorporation into growth models. eyond quantifying phenotypic parameters,the systemachieves predictive analysis of ta can be transmitted to cloud platforms for centralized processing and analysis.

stress-related experiments.

multisensor integration, automated measurement protocols, inteligent control systems, and l connectivity to enable n-invasive detectionof keyagronomic ndicators: foliar nitrogenconcentration, nitrgen assimilationcapacity,laf area ional workflows reliant ondestructive sampling and post-hoc laboratory procesng, establishing a paradigm shift in

General Function

Real-Time Crop Phenotyping Monitoring

Utilizes low-cost field terminal units to enable automated, real-time continuous monitoring of crop growth and development.

Comprehensive Field Meteorological Monitoring

Records a suite of meteorological parameters, including photosynthetically active radiation (PAR), air temperature and humidity, soil temperature, humidity and conductivity, and leaf canopy temperature.

High-Throughput Analysis Pipeline

Processes and quantifies crop growth models and adaptive performance through hyperspectral measurements of field plots, enabling analysis of key constituentlevels.

Plant Stomatal Phenotyping Measurement

Built on modern loT technology, the system integrates multi-location stomatal monitoring terminals and deep learning-based image analysis algorithms to achieve large-scale, multi-species cluster deployment of stomatal monitoring devices.

RiceFloweringTemporal Pattern Analysis Plant Phenotyping Measurement

Conducts temporal analysis of rice flowering stages.

Performs RGB data-based phenotyping analysis for plants within field plots.

Chlorophyll Fluorescence Imaging

Fo, Fm, F, Fo' , Fv/Fm, Y(ll), qP, qL, qN, NPQ, Y(NPQ), Y(NO), ETR, PAR

Leaf Canopy Temperature Measurement

To measure plant canopy temperature, leaf temperature, and temperature variations across different plant parts to support stress-related experiments.

Hypspectral Measurement

A state-of-the-art diagnostic system leveraging spectral parameter extraction technology for crops, this module synergizesmultisensor integration, automated measurement protocols, inteligent control systems, and loT connectivity to enable real-timein-field crop vitalitly assessment. By quantifying canopy spectral reflectance, the device delivers instantaneous, non-invasivedetection of kev agronomic indicators. foliar nitrogen concentration, nitrogen assimilation capacity, leaf area index (LAl, biomassallocation, chlorophylla profling, and nutrient status diagnostics. This innovation circumvents conventional workflows reliant ondestructive sampling and post-hoc laboratory processing, establishing a paradigm shift in precision agriculture analytics.

Stomatal Measurement

The stomata measuring modulecanbeusedto measure stomata of wheat,rice, corn, cotton, rape, ginkgo.phoenix tree, peach tree and otherplants

Plot-Scale Plant Parameter Quantification

Measurement of plant architecture, plant height, canopy parameters (including canopy density), leaf color, and leaf dimensions within experimental plots.

Monitoring of Flowering Progression Across GrowthStages

Continuous tracking of flowering dynamics throughout plant developmental phases.

Plant Growth Dynamics Analysis

Investigation of dynamic growth patterns and growth rate variations during plant development.

02

Plant Environmental Response Studies (requires development)

Physiological investigations under controlled environmental stressors such as drought, irrigation, and fertilization.

Scalable Machine Learning-Based Phenotyping Analytics

Implementation of extensible phenotyping analysis frameworks driven by machine learning algorithms.

Integration of GxE (Genotype-byEnvironment)Interactions

Incorporation of genotype-environment interplay analysis to decode phenotypic plasticity.

ZealquestAl NetherlandsB.V. Sir Winston Churchillaan299a,2288DC,Rijswijk,TheNetherlands

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sales@zealquest.com

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