RFP for Dynamics of Coupled Natural and Human Systems (CNH)

The Dynamics of Coupled Natural and Human Systems (CNH) Program supports interdisciplinary research that examines human and natural system processes and the complex interactions among human and natural systems at diverse scales.  Research projects to be supported by CNH must include analyses of four different components:  (1) the dynamics of a natural system; (2) the dynamics of a human system; (3) the processes through which the natural system affects the human system; and (4) the processes through which the human system affects the natural system.  CNH also supports research coordination networks (CNH-RCNs) designed to facilitate activities that promote future research by broad research communities that will include all four components necessary for CNH funding.




Full Proposal Deadline Date:  November 17, 2015

Third Tuesday in November, Annually Thereafter

All CNH proposals must be submitted by 5:00 PM (local time of submitting organization) on the annual CNH proposal-submission deadline, which is the third Tuesday of November.


This program provides educational opportunities for  Undergraduate Students, Graduate Students, K-12 Educators . Individuals interested in applying for funding should see the program guidelines above.

Citizen Science 2015

Sandra Arango-Caro attended the inaugural conference of the Citizen Science Association (CSA), Citizen Science 2015.  She presented a poster on the Missouri Transect citizen science project, Missourians Doing Impact Research Together (MO DIRT), headed at the Danforth Center in St. Louis.  MO DIRT was the only project presented at the conference that focused on citizen-led measurements of soil health, signifying an important research gap that MO DIRT will fill.  You can read about her experience here.

Sandra Arango-Caro presenting on MO DIRT

Sandra Arango-Caro presenting on MO DIRT

Call for Papers

Machine Vision and Applications
Special Issue on Computer Vision and Image Analysis in Plant Phenotyping

Website: http://www.plant-phenotyping.org/CVPPP2014-Special-Issue/

Important Dates

Submission:         April 20 2015
First decisions:    June 20 2015
Revision deadline:  July 30 2015
Final decisions:    Aug 30 2015
Online publication: November 2015


Plant phenotyping is the identification of effects on the phenotype (i.e., the plant appearance and behavior) as a result of genotype differences (i.e., differences in the genetic code) and the environment. Previously, the process of taking phenotypic measurements has been manual, costly, and time consuming.  In recent years, non-invasive, imaging‐based methods have become more common. These images are recorded by a range of capture devices from small embedded camera systems to multi-million Euro smart-greenhouses, at scales ranging from microscopic images of cells, to entire fields captured by UAVs.

These images need to be analyzed in a high throughput, robust, and accurate manner. UN-FAO statistics show that according to current population predictions we will need to achieve a 70% increase in food productivity by 2050, simply to maintain current global nutrition levels. Phenomics -large-scale measurement of plant traits– is the bottleneck here, and machine vision is ideally placed to help. However, the occurring problems differ from usual tasks addressed by the computer vision community due to the requirements posed by this application scenario.
Dealing with these new problems has spawned new specialized workshops such as CVPPP (Computer Vision Problems in Plant Phenotyping) which was held for the first time in conjunction with ECCV 2014, and the stand-alone workshop IAMPS (Image Analysis Methods for the Plant Sciences) now in its fourth year.

The overriding goal of this special issue is to focus on submissions that propose interesting computer vision solutions, but also submissions that introduce challenging computer vision problems in plant phenotyping accompanied with benchmark datasets and suitable performance evaluation methods.

Specific topics of interest include, but are not limited to, the following:

  • problem statements accompanied by image data sets defining plant phenotyping challenges, complete with annotations if appropriate, and accompanied with benchmark methods wherever possible, and suitable evaluation methods
  • advances in segmentation, tracking, detection, reconstruction and identification methods that address unsolved plant phenotyping scenarios
  • open source implementation, comparison and discussion of existing methods


Authors are encouraged to submit original work that has not appeared in, nor is in consideration by, other journals. Previously published conference papers can be submitted in extended form (with additional supporting experiments and a more detailed technical description of the method). All papers will be subject to expert peer review.

Further information on the process (as well any special issue related updates) are available at: http://www.plant-phenotyping.org/CVPPP2014-Special-Issue/

The electronic copy of a complete manuscript (10-15 pages in the Machine Vision and Applications publication format) should be submitted through the journal manuscript tracking system at the web site: http://www.editorialmanager.com/mvap/ indicating that the contribution is for the special issue “Computer Vision and Image Analysis in Plant Phenotyping”.

Guest editors (alphabetical order)

Hannah Dee, Aberystwyth University, UK (hmd1@aber.ac.uk)
Andrew French, University of Nottingham, UK (Andrew.P.French@nottingham.ac.uk)
Hanno Scharr, Forschungszentrum Jülich, Germany (h.scharr@fz-juelich.de)
Sotirios Tsaftaris, IMT Lucca, Italy (s.tsaftaris@imtlucca.it)

Postdoctoral research combined with teaching opportunity at Washington University in St. Louis

A postdoctoral position is available, funded by the NIH, for research on the assembly of cytochrome proteins, using genetic engineering and protein biochemistry of membrane proteins (see research link below). This full-time position also provides an opportunity to teach a summer laboratory course on “DNA manipulation,” so the successful candidate will be partially supported for teaching. This course, Bio 437, is a three-week summer version of the Fall course taught by Prof Kranz (see course link below). Thus, the ideal candidate should already be able to carry out advanced DNA studies (eg. cloning, qRT-PCR, and/or DNA sequencing and analyses) but will learn how to design a course and investigation-type experiments, and how to implement these in a class setting. As one would expect, preparation time for teaching the course (with guidance) is essential. The NIH-supported research component will likely require that we train the candidate in the area’s of membrane protein biochemistry and/or cytochrome assembly, and/or the use of E.coli recombinant approaches for applied and basic studies in these fields. The ideal candidate is a published, motivated researcher, and has a sincere interest for future teaching and research at an advanced level (as an independent scientist.)

Send a CV, including names and contact info of two recs, to:
Robert Kranz
Department of Biology
E-mail : kranz@wustl.edu

Other information:

Kranz research website is at http://wubio.wustl.edu/kranz

For info on the Fall, Bio 437 course, including syllabus and overview, go to http://www.nslc.wustl.edu/courses/Bio437/bio437.html


What’s Happening in the Plant Phenotyping World

High-Throughput Phenotyping Workshop in May 2015

The Plant Imaging Consortium is hosting the Plant High-Throughput Phenotyping Workshop May 18-22, 2015 at the Arkansas Biosciences Institute at Arkansas State University, Jonesboro, AR.

Plant High-Throughput Phenotyping Workshop
Phenomics: How Next-Generation Phenotyping is Revolutionizing Plant Breeding

This book represents a pioneer initiative to describe the new technologies available for next-generation phenotyping and applied to plant breeding. Over the last several years plant breeding has experienced a true revolution. Phenomics, i.e., high-throughput phenotyping using automation, robotics and remote data collection, is changing the way cultivars are developed. Written in an easy to understand style, this book offers an indispensable reference work for all students, instructors and scientists who are interested in the latest innovative technologies applied to plant breeding.

Publisher: Springer; 2015 edition (January 13, 2015)
Language: English ASIN: B00S7L0DDI

New Plant Phenotyping Image processing  Applications notes see here

Application Note – Analysing Turfgrass Images
Application Note – Biocide screening
Application Note – Color Analysis using LemnaGrid

more details can be found here

PhenoDays 2015 in Munich, Germany

PhenoDays 2015: October 28 – 30, 2015 at Marriott Hotel Freising, near Munich Airport, Germany

Registration is open now.  All speakers should submit an abstract by September 1, 2015.

University of Nebraska-Lincoln’s greenhouse phenotyping platform is coming together at innovation campus in Lincoln

Searching for a Job?

Field Phenotyping Image Analysis & Data Handler position at Rothamsted Research.  If interested, please visit http://www.rothamsted.ac.uk/jobs/1392

This post requires expertise in image processing and analysis, software and database development, preferably with a plant/agricultural science background, and will involve data extraction and large scale high throughput data handling. The appointee will liaise with other team members and facility users to ensure high throughput automated pipelines are in place to facilitate data flow from the experiments to the experimentalists.

CI-WATER Education Resources

Model Earth is a set of interactive and other resources to help educators to bring water science into the classroom. Developed by the University of Utah’s Genetic Science Learning Center for the CI-WATER and iUTAH Projects.

To see CI-Water Education modules, tools and resources, visit their Education & Outreach page.

What is CI-Water?

What is a model?

2015 Big Data Analytics Summer Experience at MU Computer Science Department

Big Data is transforming science, engineering, medicine, healthcare, finance, business, and ultimately society itself. The Computer Science Department at the University of Missouri-Columbia will offer Big Data Analytics Summer Experience 2015, from July 6 through July 24, 2015. This program will introduce key Big Data processing and analytics technologies and teach practical skills and practices. This program is open to undergraduate students, graduate students, and professionals.

Application deadline is April 10, 2015.

Visit the MU Engineering announcement for details and application instructions.

Undergraduate Research in Consumer Networking Technologies

The REU (Research Experiences for Undergraduates) Site is in the area of Consumer Networking Technologies and will investigate some important issues related to software-defined networking, social media computing, social health networking for eldercare, body-area sensing and emotion recognition, and network performance optimization. The REU Site is supported by NSF, MU Office of Research, MU Office of Undergraduate Research, the College of Engineering, and the Department of Computer Science.

In this REU Site, students will participate and develop new skills in ongoing funded research projects of the faculty mentors by investigating, implementing, and testing viable solutions to technical challenges in consumer networking technologies. This research activity will allow the students to obtain a better understanding of the technical issues, performance, and trade-offs in consumer networking. Exposing the students to collaborative research environments, fostering their enthusiasm for science and engineering, and developing skills needed for pursuing advanced degrees in research is a goal of this program.

The REU site will support typically 10 undergraduate students every summer. The participants will engage in a 10-week summer school at the University of Missouri (MU). The participants will take a 1-week short course, one to two lectures per week in the remaining weeks, work with other undergraduate and graduate students and a faculty mentor to carry out a research project, present their progress weekly throughout the summer, and write project reports and give final presentations. In addition, the undergraduate participants will present their work at their home institutions during the following semester.

The Program runs from May 25 through July 31 in 2015. The undergraduate participants will get a stipend of $5,000, room (if needed) and meal allowance, plus support for travel to/from the Site, and potentially travel support to present their work at a conference.

Application is due by March 16

For more information, visit the REU Site website.