The Integrated Analysis Platform for high-throughput plant image analysis

This project is maintained by OpenImageAnalysisGroup

IAP - The Integrated Analysis Platform

Developed from 2010-2015 at IPK Gatersleben by the Group Image Analysis, from 2015-2016 by J.-M. Pape @ IPK and C. Klukas

Software design and main development: C. Klukas (head of group)

Pipeline development: J.-M. Pape

Post-processing: D. Chen


The Integrated Analysis Platform (IAP) has been designed and developed to support the analysis of large-scale image data sets of different camera systems. It aims in bridging different data domains and in integrating different approaches to data analysis and post-processing.

If you have any question, feel free to the designer and developer of IAP by E-Mail.

Documentation and further Informations

Documentations and releases (up to version 2.0.2) are available on sourceforge: IAP on Sourceforge


The latest executable release is available from the release section: Download Latest Release

Example Data Set

An example high throughput plant phenotyping data set including 33 maize plants is available here: Download Maize Example

Reference Information

Klukas, C., Chen, D., Pape, J.M.: Integrated analysis platform: An open-source information system for high-throughput plant phenotyping. Plant physiology 165(2), 506-518 (2014) (link).

Post-Processing High-Throughput Phenotyping Data

Our approach for post-processing phenotyping data has been published in The Plant Cell. Please click here, for further information and resources.

Outgoing Links

Acknowledgements for funding

This work was supported by IPK institute funds, and with grants supporting collaborations and business trips from the National Natural Science Foundation of China (NSFC, 31050110121), the Robert Bosch Stiftung (32.5.8003.0116.0), the Federal Agency for Agriculture and Food (BEL, 15/12-13, 530-06.01-BiKo CHN) and project funding of the Federal Ministry of Education and Research (BMBF) (OPTIMAL: 0315958A, DPPN: 031A053B), and the EU funded project EPPN (Grant Agreement No. 284443).