Update for Photosynthesis RIDES users

We have identified an error in the Photosynthesis RIDES macro, which is used to process the data from the Photosynthesis RIDES protocol. If you were using this protocol you may have noticed that your NPQt values were a bit higher than expected, or your PhiNO values were a bit lower than expected. This was due to an error in how we determined Foprime, which is key in calculating these parameters.

The good news is that the PhotosynQ platform is built to allow users to correct issues like this, and apply it to data that you have already collected!

We have now changed the macro to correct the error. So, the next time you go to one of your Photosynthesis RIDES projects, you will see the prompt below asking if you want to recalculate your parameters based on updates to the macro. If you choose yes, the updates will be applied to your data. If you choose no, your data will remain in its present form.project updates

User Page | PhotosynQ Website

User Page | Website Update

We are working on making your user page the central hub for all the information regarding your work with PhotosynQ.

We have found that one of the most useful features for any PhotosynQ project is the Dashboard, which allows you to quickly view important project results on one page.

We are currently using the same approach to allow users to have a personal dashboard that makes all of their PhotosynQ information (e.g. projects, protocols, macro’s etc) available in one place.

If you haven’t visited your user page recently, you should try it now, we think you’ll be pleasantly surprised! To get there, click on your name in the top right hand corner of the PhotosynQ webpage, this leads to your user page.

Over the past couple of months we have made a number of changes to this page that should really help you navigate through your PhotosynQ projects and collaborations.

user page image

Recent Activity

This change has been around for a while, but if you haven’t been checking in you may have missed it. We have now added your most recent projects, collaborations and comments to your user homepage. This should help you navigate quickly to your most active projects, instead of always going through the PhotosynQ search bar.

Side Menu

The side menu now contains a link to the instrument page (see below), your invitations, and the last two updates posted on PhotosynQ.

About – Contributions

We replaced the bar chart showing your contributions over the past year and doughnut chart with a calendar histogram. This view will provide more details about when and how many contributions you made over the last year.

Contributions over the last 12 months, shown as a calendar heat map.
Contributions over the last 12 months, shown as a calendar heat map.

Protocols & Macros

Do you make any of your own protocols and macros? If you do, now you can see all of your protocols and macros, sorted alphabetically and by their category, right from your user page.

Instruments

Now you can see all the instruments you have used in the past. It will show some basic information, based on the last measurement, including the firmware version, the total number of contributions (you and others, if you borrowed/lent the instrument) and the last time the instrument was seen (based on the latest submitted measurement).

Basic information panel for an instrument
Basic information panel for an instrument

If you have questions or need support, please check our forum or send us an email to support@photosynq.org.

New Data Selection & Plotting | Website Update

Data Selection & Plotting | Website Update

This is just a small update to the data viewing tool on https://photosynq.org, but we think, it will be very helpful for your data analysis.

Data Selection

Plots

With switching the plotting library to Plotly we introduced selecting a series by using the lasso tool or box selection tool to generate a new series, instead of using the filters (Goodbye Flot, Hello Plotly | Other Website Updates). Now you can also use the inverse of a selection as a new series or generate both at the same time. Just check the appropriate box in the dialog before you create a new series or download selection.

The new selection dialog allows you to not only select a range of markers as a new series, but also the inverse of your selection or even both as new series.
The new selection dialog allows you to not only select a range of markers as a new series, but also the inverse of your selection or even both as new series.

Map

Now you can also generate a new series by drawing a rectangle or a polygon around markers on the map. When viewing graphs you can use the selection tools to create new series of data selected, or the inverse.

Select a group of markers by dragging a rectangle or polygon to create a new series (buttons in the center top). Similar to the plot, the map as well allows you to use the selection, the inverse selection or both as new series.
Select a group of markers by dragging a rectangle or polygon to create a new series (buttons in the center top). Similar to the plot, the map allows you to use the selection, the inverse selection or both as new series.

Dashboard

A new panel is available, which lists all the Data Quality Issues, which were found in your project, listing each issue with a count of affected measurements. You can now generate a series containing these measurements for an easier screening and potential flagging.

Plotting

What’s in my selection?

When you are working with a scatter plot and you are using a color gradient as a third dimension, it might be hard to tell, if for example, a certain crop variety is enriched in your selection. Now you can use the Enrichment feature to plot fractions of a category for each series.

Just select the bar-graph tab, check Enrichment and choose a category. The bar-graph will display the fractions as to the following selections:

  • category / series Will show the fraction of category appearances in each series compared to the total appearances in each series.
  • category / total Will show the fraction of category appearances in each series compared to the total appearances.

2D Heat-Map

The 2D Heat-Map will now adjust based on the selected series and not only show the map for all all series combined.


Spreadsheet

If you save photos along with your measurements, no matter if it is a project question or if you take them as notes, inside the spreadsheet you see a small image icon. When you hover over the icon, you will see the picture instead on top of your list of series. The same is true for long arrays of numbers. Instead of those, you now see a chart icon and hovering over it, will bring up a line graph.

Copying the data still works the same. You will get all the data or the link to the picture.

The “ID” and “Series” columns are now sticky and will stay visible when scrolling vertically in the table.

Statistics: Chi Square Test

We added another statistical test, the Chi Square test. This allows you to compare categorical data.

Dashboard

The functionality of the dashboard got extended a little bit. The graphs you save to the dashboard are now images, so you can simply save them to you hard-drive.

Hiding Advanced Parameters

As I am sure you’ve noticed by now, we at PhotosynQ like to provide you with a lot of data. Not just the primary parameters (e.g. Phi2, PhiNPQ, Light Intensity (PAR), time, etc) that you are interested in, but also many other parameters that may go into calculating those parameters. However, viewing all of this data in the plotting tool or spreadsheet view may be a bit much for some users.

We have now added a feature that allows users to decide whether or not they want to view the primary parameters and Project questions together with the Advanced parameters (e.g. absorbance_420, FvP_over_FmP, etc) or if they would prefer to hide the advanced parameters. The new default setting is to hide the advance parameters. If you want to view these parameters, select the settings icon near the Add Series and click the Show Advanced Parameters checkbox. Now all of the parameters output by the MultispeQ will be available in the Plot Data, Spreadsheet, Map and Statistics tabs.

Advanced data

If you have questions or need support, please check our forum or send us an email to support@photosynq.org.

 

PhotosynQ Website Update and New Features

We’ve updated the PhotosynQ website and added many new features to improve your user experience!

Some of the new features include: expanded plotting, mapping and graphing data options, improving the user page to help users better track their PhotosynQ projects, protocols and macros, and adding more content to the tutorials and help center.

We will be detailing these new features in blog posts over the next two weeks, but let me briefly explain a couple of the updates:

Tutorials

Two area’s where new PhotosynQ users seem to struggle are with creating robust projects and cleaning up their data prior to data analysis.

Project Creation

Since we began shipping the MultispeQ v1.0’s over 9 months ago we have seen a drastic increase in the number of PhotosynQ projects that are being created. Which is really exciting! Occasionally, we’ll check out new projects to figure out how people are doing with the platform and try to come up with ways to improve the PhotosynQ experience. We have noticed that setting up projects has been a problem for many users. The most common problems are choosing the wrong measurement protocol or not asking good project questions, which then makes filtering, analyzing and interpreting data difficult.

So we have added a Project creation tutorial to better guide users through the process.

Data Quality

Recently we published a blog post about how to Flag data to improve data quality. This is an important step in getting the most out of your PhotosynQ project. In our default Leaf Photosynthesis MultispeQ v1.0 and Photosynthesis RIDES protocols we add issue warnings that help identify measurements that may have technical issues, but many people are unfamiliar with what these mean. So we have also added a Data Quality tutorial to explain issue warnings and data flagging.

Help Center

If you have ever visited the help center you may have noticed a little poll at the bottom of each post asking if the article was helpful or not. Well, believe it or not, clicking those buttons actually matters! We have updated a number of help articles to be more helpful and have added numerous articles.

That’s it for today, but stay tuned! More details about new features will be coming soon!

 

Flagging Data to Improve Data Quality

Improve your PhotosynQ projects by getting rid of low quality measurements with the flagging data feature.

 

Whether you are taking measurements in the field or in the lab, it is not uncommon for a handful of measurements to be returned to you with an issue warning. There are a variety of warnings you might receive, red issue warnings suggest that a measurement might be bad, while yellow and blue issue messages simply provide information about the measurement. You may find it is necessary to remove the measurements with red issue warnings from a project before you can properly analyze your data.

WHY

Bad measures can happen for many reasons, maybe someone had shaky hands or the leaf was dead. Or maybe the leaf was not totally covering the light guide, many  of these things can be attended to and fixed if you follow our Best Measurement Practices. It could be our fault, your fault, or maybe natures. All of these will return issue warnings that something went wrong during your measurement. You always have the choice to discard and redo the measurement in the field, however this can be easy to overlook. If you go through your experiment, accept everything and later realize you may have made some mistakes, we allow you to flag this data later in the Data Explorer. Flagging data DOES NOT delete the measurements from the website, but rather hides them. Flagged data can always be viewed by clicking the “Include flagged datasets” box in the Add Series tab, so don’t worry!

FlagDataBlogpic2Including flagged data in your data series

HOW

Flagging your data could not be any easier in the Data Viewer at photosynq.org. All you will have to do is select a single suspect point (1), either from a scatter plot or the table. Look at the data point in the single data view, and see if there were any issue warnings (2). If you determine this point is no good and you’d like to flag it, under the name of the person who submitted the data point, you will see a tab for Issues. Click here, write up your issue in the Reason for Flagging dialog box and click Submit to quickly flag a data point (3). It is important to remember that when you flag a data point you are hiding it from your analysis, NOT deleting it entirely, don’t worry, we never delete your data.

CIRCLEBADBADBAD(1) This measurement’s SPAD (relative chlorophyll content) is very low, we can take a closer look at it by clicking on the data point

BADTRACE

(2) Here we can see that the macro output an issue warning when the measurement was taken. Even if there is no issue warning, you may spot a problem with the measurement by examining the measurement trace. In this case it appears that someone failed to completely cover their entire light guide!

GOODTRACE

For reference, this is a good, average trace for the Leaf Photosynthesis MultispeQ V1.0

owowoww

(3)Flagging data requires a reason, this helps everyone involved be on the same page

The Difference Flagging Makes

When you a flag a data point, you are essentially putting them aside, not to be considered when you run analysis, so it is easy to see how your outcomes might be different depending on if you flagged your data or not.

phi2AVGwflag.png

First, let’s look at data for a project that includes every data point. This is what you might see in your project after a day in the field and no work done to your data yet. You can see for the Phi2 parameter that the standard error is very large, even reaching into the negatives. Since plants can’t have a negative Phi2, it indicates some work on the data needs to be done before we can be confident in the results. If you went through and flagged bad measurements, you will end up with a better graph like the one below.

phi2AVGnoflag

After flagging all of the measurements that either had issue warnings or had obvious problems, by looking at the measurement traces, we get a very different graph. Even after flagging the poor quality measurements we still see large standard error bars. Remember, photosynthetic parameters are highly dependent on ambient conditions such as light intensity, time of day and temperature. We recommend using multivariate analysis to account for these factors, for more tips on data analysis, check out our tutorials here.

Issue warnings can occur on exceptional leaves, such as ones with a very dark deep green colour, and still be fine, so it is important to examine them, rather than just flag whole chunks. Flagging your data where appropriate will make your data tighter and more true to what was observed in your experiment. This is useful when interpreting your results because you are not being bogged down by faulty measurements, which in turn should make statistical analysis of your results much better!

Read More »

New PhotosynQ Related Publication

Check out the new publication in the American Journal of Plant Sciences, using the MultispeQ and PhotosynQ Platform (10.4236/ajps.2017.84050)

Response of Cowpea Genotypes to Drought Stress in Uganda

Saul Eric Mwale, Mildred Ochwo-Ssemakula, Kassim Sadik, Esther Achola, Valentor Okul, Paul Gibson, Richard Edema, Wales Singini, Patrick Rubaihayo

Moisture stress is a challenge to cowpea production in the drought prone areas of eastern and north eastern Uganda, with yield losses of up to 50% reported. Genotypes grown by farmers are not drought tolerant. This study was therefore, undertaken at Makerere University Agricultural Research Institute Kabanyolo to identify cowpea genotypes tolerant to drought. Thirty cowpea accessions comprising of Ugandan landraces and released varieties, Brazilian lines, Makerere University breeding lines, elite IITA germplasm and seven IITA drought tolerant lines as checks were screened for drought tolerance at vegetative and reproductive stages. The experiment was designed as a 2 × 37 factorial and laid out in a split-plot arrangement, 37 genotypes of cowpea at two soil moisture stress levels (T1, no stress and T2, severe stress) with all factorial combinations replicated two times in a screen house. The genotypes showed considerable variability in tolerance to drought. Genotypes were significantly different for chlorophyll content (P ≤ 0.01), efficiency of photosystem II (P ≤ 0.05), non-photochemical quenching (P ≤ 0.05), recovery (P ≤ 0.01), delayed leaf senescence (P ≤ 0.01), grain yield (P ≤ 0.01), 100 seed weight (P ≤ 0.05), number of pods per plant and number of seeds per pod (P ≤ 0.001). There was a highly significant positive correlation between chlorophyll content and efficiency of photosystem II (r = 0.75, P ≤ 0.001) implying that chlorophyll content and efficiency of photosystem II could be used as efficient reference indicators in the selection of drought tolerant genotypes. Genotypes SECOW 5T, SECOW 3B, SECOW 4W, WC 30 and MU 24 C gave relatively high yields under stress and no stress conditions, maintained above mean chlorophyll content, efficiency of photosystem II and had good recovery scores from stress and thus were tolerant to drought stress induced at both vegetative and reproductive stages.


More PhotosynQ related publications are available here

Building Strong Research Collaborations

If you have ever visited the PhotosynQ webpage (you’re reading the PhotosynQ blog, so I’ll assume you have), you know that the banner across our homepage reads “Truly Collaborative Plant Research.”

We have always aspired to making PhotosynQ a flexible platform to accommodate many forms of collaboration. For example, we hope the open nature of PhotosynQ data combined with built-in discussion tools will foster communication and collaboration between researchers across the globe.

I recently returned from Uganda, where I conducted some training workshops and (hopefully) established a long-term collaboration between PhotosynQ and the Makerere University Regional Centre for Crop Improvement (MaRCCI). Before my trip, MaRCCI had a few MultispeQ devices, a few students had used PhotosynQ, and they have even published a few papers. However, until now, there has been little direct communication between MaRCCI and PhotosynQ.

After spending 2 days together, learning how to create robust projects and collect, analyze and interpret quality photosynthesis data, we hope to develop a much stronger collaboration.

MaRCCI pic for blog

What does ‘stronger’ collaboration mean?

MaRCCI already has access to PhotosynQ’s low-cost, cutting edge phenotyping technologies and platform for data storage, visualization and management. Building a stronger collaboration means giving MaRCCI students and faculty the opportunity to work directly with the PhotosynQ team to analyze the links between complex photosynthesis phenotypes and crop outcomes (this requires sharing of outcome data such as yield, disease resistance, etc). It also brings MaRCCI into the PhotosynQ development workflow. So, as we continue to work on automating advanced analytical tools like multivariate analysis, prediction and QTL mapping we will work closely with MaRCCI students and faculty to make sure that what we are developing will solve their problems.

On the flip side, collaboration with MaRCCI offers PhotosynQ some great benefits. MaRCCI recently received support from the World Bank as an “African Higher Education Centre of Excellence” in plant breeding and related activities. This means that they are positioned to be a hub of plant breeding training for breeding programs throughout sub-Saharan Africa. They receive Masters and PhD students from 20 different countries, and while I was there I met students from Benin, Burundi and Tanzania, just to name a few. Such a diverse group of students allows us to disseminate PhotosynQ technology over a wide geographical area, and have much greater impact.

The end result, we hope, will be a long-term partnership that improves the education and capacity of young plant breeders across Africa and helps PhotosynQ continue to evolve as an advanced phenotyping platform.

Personally, I look forward to continuing the work with a great institution with enthusiastic students and faculty.