CropQuant: An automated and scalable field phenotyping platform for crop monitoring and trait measurements to facilitate breeding and digital agriculture
Ji Zhou, Daniel Reynolds, Thomas Le Cornu, Danny Websdale, Simon OrfordiD, Clare ListeriD, Oscar Gonzalez-Navarro, Stephen Laycock, Graham Finlayson, Tim Stitt, Matthew D. Clark, Michael W. Bevan, Simon GriffithsiD
Abstract
Automated phenotyping technologies are capable of providing continuous and precise measurements of traits that are key to todays crop research, breeding and agronomic practices. In additional to monitoring developmental changes, high-frequency and high-precision phenotypic analysis can enable both accurate delineation of the genotype-to-phenotype pathway and the identification of genetic variation influencing environmental adaptation and yield potential. Here, we present an automated and scalable field phenotyping platform called CropQuant, designed for easy and cost-effective deployment in different environments. To manage infield experiments and crop-climate data collection, we have also developed a web-based control system called CropMonitor to provide a unified graphical user interface (GUI) to enable realtime interactions between users and their experiments. Furthermore, we established a high-throughput trait analysis pipeline for phenotypic analyses so that lightweight machine-learning modelling can be executed on CropQuant workstations to study the dynamic interactions between genotypes (G), phenotypes (P), and environmental factors (E). We have used these technologies since 2015 and reported results generated in 2015 and 2016 field experiments, including developmental profiles of five wheat genotypes, performance-related traits analyses, and new biological insights emerged from the application of the CropQuant platform.
02 /Specification & Classification
Click any tag to browse matching papersReproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- CropSurveyor: a scalable open-source experiment management system for distributed plant phenotyping and IoT-based crop management
D. Reynolds, J. Ball, … J. Zhou·GigaSciencePeer-reviewed·Jan 31, 2019
- PhenoStream: A Cyberinfrastructure for Automated and AI-Based Crop Trait Extraction from Aerial Imagery
Sebastián Varela, Jeremy Ruhter, … Andrew D. B. Leakey·bioRxiv·Aug 30, 2026
- AGIcam: An open-source IoT-based camera system for automated in-field phenotyping and yield prediction
Worasit Sangjan, Nisit Pukrongta, … Sindhuja Sankaran·The Plant Phenome JournalPeer-reviewed·Jun 12, 2026
- A High Throughput Gravimetric Phenotyping Platform for Real Time Physiological Screening of Plant Environment Dynamic Responses
A. Dalal, I. Shenhar, … M. Moshelion·bioRxiv·Jan 30, 2020
- PhenoImage: an open-source GUI for plant image analysis
- Large-scale field phenotyping using backpack LiDAR and GUI-based CropQuant-3D to measure structural responses to different nitrogen treatments in wheat
Yulei Zhu, Gang Sun, … Ji Zhou·PLANT PHYSIOLOGYPeer-reviewed·Jul 14, 2021