Statistical analysis

Taking the kinks out of curves

In a recent paper, researchers have developed a methodology suitable for analyzing the growth curves of a large number of plants from multiple families. The corrected curves accurately account for the spatial and temporal variations among plants that are inherent to high-throughput experiments.

13007_2017_165_Fig2_HTML

An example of curve registration.  a The salinity sensitivity (SS) curves of the 16 functions from an arbitrary family, b SS curves after the curve registration, and c the corresponding time-warping functions. The salinity sensitivity on the y-axis of a and b refers to the derivative of the relative decrease in plant biomass

 

Advanced high-throughput technologies and equipment allow the collection of large and reliable data sets related to plant growth. These data sets allow us to explore salt tolerance in plants with sophisticated statistical tools.

As agricultural soils become more saline, analysis of salinity tolerance in plants is necessary for our understanding of plant growth and crop productivity under saline conditions. Generally, high salinity has a negative effect on plant growth, causing decreases in productivity.  The response of plants to soil salinity is dynamic, therefore requiring the analysis of growth over time to identify lines with beneficial traits.

In this paper the researchers, led by KAUST and including Dr Bettina Berger and Dr Chris Brien from the Australian Plant Phenomics Facility (APPF), use a functional data analysis approach to study the effects of salinity on growth patterns of barley grown in the high-throughput phenotyping platform at the APPF. The method presented is suitable to reduce the noise in large-scale data sets and thereby increases the precision with which salinity tolerance can be measured.

Read the full paper, “Growth curve registration for evaluating salinity tolerance in barley” (DOI: 10.1186/s13007-017-0165-7) here.

Find out how the Australian Plant Phenomics Facility can support your plant science research here.

TPA_KAUSTproject

High-throughput phenotyping in the Smarthouse™ at the Adelaide node of the APPF

NW 24-7-15 (2)

Barley plants growing in the Smarthouse™

 

 

Last chance to secure an internship – apps close tomorrow!

This is your chance to investigate your plant science questions with the support of the highly skilled Australian Plant Phenomics Facility (APPF) team and the incredible technology and infrastructure we have available.

Internships are offered at the APPF in Adelaide and Canberra for enthusiastic, highly motivated postgraduate students with a real interest in our research and technology. Current postgraduate students in the following areas are encouraged to apply:

  • Agriculture
  • Bioinformatics
  • Biology
  • Biotechnology
  • Computer Science
  • Genetics
  • Mathematics
  • Plant physiology
  • Science
  • Software engineering
  • Statistics

Interstate students are strongly encouraged to apply!

We offer postgraduate internship grants which, in general, comprise:

  • $1,500 maximum towards accommodation in Adelaide or Canberra, if required
  • $500 maximum towards travel / airfare, if required
  • $10,000 maximum toward infrastructure use

The APPF has identified a number of priority research areas, each reflecting a global challenge and the role that advances in plant biology can play in providing a solution:

  • Tolerance to abiotic stress
  • Improving resource use efficiency in plants
  • Statistics and biometry
  • Application of mechatronic engineering to plant phenotyping
  • Application of image analysis techniques to understanding plant form and function

Students proposing other topics will also be considered.

APPF postgraduate internship grants involve access to the facility’s phenotyping capabilities to undertake collaborative projects and to work as an intern with the APPF team to learn about experimental design, image and data analysis in plant phenomics.

Selection is based on merit. Applications are assessed on the basis of academic record, research experience and appropriateness of the proposed research topic. Interviews may be conducted.

Postgraduate students are encouraged to contact APPF staff prior to submitting their application to discuss possible projects.

APPLICATIONS CLOSE:  31 March 2017. For further information click here.

 

Why apply for an internship with the APPF?

Well, aside from the fact we are a pretty nice bunch…

PhD student Rohan Riley, from Western Sydney University, undertook his research at APPF’s Adelaide node (The Plant Accelerator®) after being awarded a Postgraduate Student Internship Grant with us in 2015.

His research attempted to explain the unpredictability of plant growth responses in terms of resource limitation by introducing fungal communities to plants which are isolated from soils containing high or low levels of salinity and analysing the effects on plant stress at the phenotypic level.

This is what he had to say about his experience:

”Using daily phenotyping following the application of salt stress and controlled watering-to-weight in The Plant Accelerator® allowed for an unprecedented resolution and range of plant genetic changes in response to combinations of nutrient level, salinity and two different fungal communities that would not otherwise be achievable in a regular greenhouse,” said Rohan.

rohan_brachy

”As a PhD student with limited experience in greenhouse experiments, the highly controlled growth conditions, large-scale automation, digital imaging and software technology (high-throughput phenotyping) at The Plant Accelerator® provided me with the work-space, expertise and technical support to make a complicated experiment possible.”

“It has been an amazing experience to conduct this experiment at The Plant Accelerator®. I am walking away from the facility with a big smile on my face, an incredible dataset for my PhD research and invaluable experience in greenhouse based plant research.”

To find out more about Rohan’s research:  https://www.researchgate.net/profile/Rohan_Riley

A better way to tackle environmental variation in your greenhouse research

Statistics prove the smart way to deal with variation in your controlled environment greenhouse.

Plant phenomics allows the measurement of plant growth with unprecedented precision. As a result, the question of how to account for the influence of environmental variation across the greenhouse has gained attention.

Controlled environment greenhouses offer plant scientists the ability to better understand the genetic elements of specific plant traits by reducing the environmental variances in the interaction between genetics and environment.

But controlled environments aren’t as controlled as they seem – variation does exist. For example, some days are cloudy, some are not. The sun, as it crosses the sky, casts shadows differently on plants, depending on their position within the greenhouse. In fact, a recent study by colleagues at INRA in Montpellier showed significant light gradients within a greenhouse and provided sophisticated tools for understanding how much light each plant receives.

One practice for dealing with variation has been to rearrange the position of the plants around the greenhouse during the experiment, however, there is a better way.

img_1128

Rice plants growing in The Plant Accelerator® at the Australian Plant Phenomics Facility’s Adelaide node

The automated high-throughput phenotyping greenhouses at The Plant Accelerator® are controlled environment facilities which use sensor networks to identify and quantify environmental gradients (light, temperature, humidity) in the greenhouses. To further tackle environmental variation, Chris Brien, Senior Statistician at The Plant Accelerator®, led a study that showed good statistical design and analysis was key to accounting for the impact of environmental gradients on plant growth. It was argued that rearranging the plants during the experiment makes it impossible to adjust for the effect of gradients and should be avoided.

The study involved a two-phase wheat experiment involving four tactics in a conventional greenhouse and a controlled environment greenhouse at The Plant Accelerator® to investigate these issues by measuring the effect of the variation on plant growth.

To learn more about Chris’s study read the full paper here.

To discuss the benefits of good statistical design contact Chris Brien.

To access The Plant Accelerator® for your research:  The Plant Accelerator® at the Australian Plant Phenomics Facility (APPF) is available to all publicly or commercially funded researchers. We have a full team of specialists including statisticians, horticulturalists and plant scientists who can provide expert advice to you when preparing your research plans.