Submitting Field Trial Plots

The form for submitting or editing existing Plots is available at https://grassroots.tools/private/service/field_trial-submit_plots

Firstly, select the study that you wish to add the plots for from the drop down menu. The table and form on the page below will load the existing plot information from the database.

The form for submitting field trial plots

Then drag and drop the excel file that constains the plot observations. This will populate the table with the data that will be submitted.

The form for submitting field trial plots

The file should be in the format described below.

Types of Plots

A Study can contain different categories of plots which are used for a variety of purposes. We currently support the following different types of plots:

Plot details

For all of these different types, there a number of fields some of which are required and some that are optional. These are described below.

Common Values

Grassroots uses a system where each plot has a unique identifier There are a set of common values that are required for all plots regardless of their type and these are:

As well as the required values listed above, there are a number of optional fields which can be applied to all plots and these are listed below.

Standard Plots

For standard plots, the following fields are also required:

As well the required fields listed above

* denotes the required values for each row in the spreadsheet.

Treatment Factors

Treatment Factors are metadata that specify pieces of information such as the level of Nitrogen fertilizer used on a given plot and these can be added as extra columns within the spreadsheet. To specify the Treatment Factors to add search for the terms you want on the Search Treatment Factors page. The column headers that you need to put in the spreadsheet are the Treatment Ontology values from there.

For example, if you wanted to add Nitrogen fertilizer exposure as a Treatment Factor to the spreadsheet, you would search at the above page and get a similar view to the screenshot below

Search for a Treatment

Copy the value from the Treatment Ontology column, which in this example is PECO:0007102 and add this as a column header to the plots spreadsheet

Measured Variables

Measured Variables are the terms used to describe phenotypic experimental values that have been measured on a given plot. Similar to the approach of adding Treatment Factors described above these can be added as extra columns as follows:

Add Measured Variables dialogue

To add data, make sure to add the Measured Variables first. They can be found from the page in the link above.

The first value in any of the column headers that you add must be the name of the Measured Variable. You can then add extra text to these headers to specify a date that the observation applies too and whether the values in this column are corrected, rather than raw, values. If the value was measured on a single date, then you can add a date here. Likewise if the measurements were taken over a range of days, you can specify both a start and an end date. These dates can be in one of two formats: one for a day and one for a specfic time on a day.

For dates that refer to a day the format is YYYY-MM-DD, where YYYY is the 4-digit year, MM is the 2-digit month and DD is the 2-digit day of the month. If you wish to specify a time as well then the format is YYYY-MM-DDThh:mm:ss where hh is the 2-digit hour, mm is the 2-digit minute and ss is the 2-digit second.

As well as adding dates you can also specify whether the values in the given column are raw or corrected values. By default, the values within a column are assumed to be raw values. You can change these to corrected values by adding corrected (all lower case) within the column header.

You can also store multiple data points for a given trait in a given plot, for example plant heights from 5 different points within a plot. This is done by adding sample_n within the column header where n is a number starting starting from 1 and going on to 2, 3, 4, etc. as needed. When this is omitted, samples have a default index of 1.

Some examples are given below:

Column Description
PH_M_cm Plant height on unspecified date
PH_M_cm 2020-12-01 Plant height measured on 01 Dec 2020
PH_M_cm 2020-12-01 2020-12-03 Plant height measured on 01 Dec 2020 to 03 Dec 202
PH_M_cm corrected Plant height corrected value on unspecified date
PH_M_cm 2020-12-01T09:30:00 Plant height measured on at 9:30 AM on 01 Dec 2020
PH_M_cm 2020-12-01T09:30:00 2020-12-03T12:15:30 Plant height measured from 9:30 AM 01 Dec 2020 to 12:15:30 PM on 03 Dec 2020
PH_M_cm 2020-12-01T09:30:00 corrected Corrected plant height measured on at 9:30 AM on 01 Dec 2020
PH_M_cm 2020-12-01T09:30:00 2020-12-03T12:15:30 corrected Corrected plant height measured from 9:30 AM 01 Dec 2020 to 12:15:30 PM on 03 Dec 2020
PH_M_cm 2020-12-01T09:30:00 sample_1 A sample Plant height measured on at 9:30 AM on 01 Dec 2020 to be stored with an index of 1
PH_M_cm 2020-12-01T09:30:00 sample_2 A sample Plant height measured on at 9:30 AM on 01 Dec 2020 to be stored with an index of 2