GDM Solutions, Inc.

GDM Solutions, Inc. GDM creates, markets, and supports ARM software for managing and summarizing agriculture research experiments.

Today we're featuring the Quick Filters Panel of the Study List:-Define preset filters with a single click.-Specify a ra...
06/11/2026

Today we're featuring the Quick Filters Panel of the Study List:

-Define preset filters with a single click.
-Specify a range of values with the 'Filter For' field.
-Review the current filter applied to the study grid.
-View filters currently applied and number of studies visible with 'Active Filter' feature.

Other filter options:
-Whole Field: show studies that exactly match entered text.
-Start of Field: show studies that begin with entered text.
-Empty (Blank) Fields: show studies where selected field is blank.
-Everything Except: performs in inverse filter.
-Contains: show studies where selected field contains entered text.

Today we're featuring the Filters Section and Filter Navigation Bar of the Study List. Filters Section: -Define one or m...
06/10/2026

Today we're featuring the Filters Section and Filter Navigation Bar of the Study List.

Filters Section:
-Define one or more filters to display only studies that match or exclude specified items.
Example: Enter "2021" in the Trial Year field and press Enter to see only studies from that year.

-Use the * (asterisk) wildcard to act as a placeholder for any number of characters.
Example: a search for b* will return all field values beginning with b. To display only studies containing "wheat" in the title, enter the following into the Title field and press enter: *wheat*

-Use the ? (question mark) wildcard to act as a placeholder for a single character.
Example: a search for ATD_??HERB in the Study ID field would return all studies following the ATD_xxHERB pattern, where xx is the trial year.

-Click the yellow filter icon beside an information field to show the unique items for all currently displayed studies. Select one or more items from the filter list and choose include or exclude to narrow your search.

Filter Navigation Bar: quickly navigate through the groups of filters on the Filters Section.

Today we're featuring the Study Grid and Selected Study Panel sections of the Study List! The Study Grid is the actual ...
06/09/2026

Today we're featuring the Study Grid and Selected Study Panel sections of the Study List!

The Study Grid is the actual list of ARM studies.
-Use the Selected Column (far left) to select one or more studies to open.
-Study ID = main identification of a study and should be unique.
-ARM sorts the grid by Last Opened (default setting).

Tips & Tricks:
-Click and drag the columns to order them the way you want them.
-Don't use a column? Right-click and select Hide Current Field to hide it!
-Quickly sort individual columns (ascending or descending) by clicking the column headings.

Use the Selected Study Panel to quickly review indexed information of a selected study.

GDM Solutions is excited to take part in the 2026 Research Equipment Field Day! Research technicians are invited to join...
06/08/2026

GDM Solutions is excited to take part in the 2026 Research Equipment Field Day! Research technicians are invited to join us for hands-on demonstrations of the latest innovations in planting and harvesting.

See flyer below for details on date and location.

Register by emailing: [email protected].

This week will focus on the Study List: learn tips about this often overlooked but very powerful tool! Fast facts: -The ...
06/08/2026

This week will focus on the Study List: learn tips about this often overlooked but very powerful tool!

Fast facts:
-The Study List is an indexed list of ARM studies that you are working with.
-ARM builds a list of studies as you open or create them.
-ARM will track your studies and remember the study path of where the file is located.
-ARM does not store data; the study list only accesses it.

Each day we will highlight different features of the Study List. Check back to expand your ARM knowledge!

That’s a wrap on this week’s ARM featured topic: subsamples.Throughout the week, we explored how subsampling can improve...
06/05/2026

That’s a wrap on this week’s ARM featured topic: subsamples.

Throughout the week, we explored how subsampling can improve data accuracy when assessments show variability within a plot. We covered:
▪ Key assessment header fields used to define subsamples
▪ Basic subsampling techniques and sample size setup
▪ Adding structure and consistency with collection basis methods
▪ Using reporting basis fields to normalize data across trial locations

Whether sampling fruit from multiple branches or standardizing nematode counts from different soil volumes, properly documenting subsampling methods helps create more accurate, consistent, and meaningful research data.

Thank you for following along with this week’s ARM feature series. Stay tuned for more tips and tutorials designed to help simplify agricultural research data collection and management.

Subsample Post #4: Using Reporting Basis to normalize data Sometimes sampling must be completed using non-standard meth...
06/04/2026

Subsample Post #4: Using Reporting Basis to normalize data

Sometimes sampling must be completed using non-standard methods, or the sampling process may vary depending on the equipment available at each trial location. In these situations, the Reporting Basis can be used to normalize data as it is entered into ARM.

For example, suppose researchers are recording the number of nematodes per 500 cm³ of soil. At Trial Site A, samples are collected using 250 cm³ of soil, while Trial Site B uses 200 cm³ samples. Even though the sample sizes differ, both trialists can normalize their data to the same reporting basis of 500 cm³ when entering values into ARM.
▪ Trialist A multiplies raw values by 2 (250 × 2 = 500)
▪ Trialist B multiplies raw values by 2.5 (200 × 2.5 = 500)

Using a consistent reporting basis helps standardize data across locations, making comparisons and analysis more accurate and meaningful.

Subsample Post #3: Adding detail on subsampling techniques In yesterday’s example, we counted 20 fruit per tree without...
06/03/2026

Subsample Post #3: Adding detail on subsampling techniques

In yesterday’s example, we counted 20 fruit per tree without explaining how the fruit were selected. Maybe the fruit were chosen randomly from different parts of the tree during the assessment.

But what if the sampling method was more structured? For example, we could select 4 different branches per tree and then randomly sample 5 fruit from each branch. In this case:
▪ Sample Size = 5 fruit
▪ Collection Basis = 4 branch
▪ Number of Subsamples = 20

This still results in 20 subsample values per plot, but the sampling method is now clearly defined and provides consistency across multiple trials and notetakers.

A simple way to think about it is:
“We are sampling [Sample Size, Unit] per [Collection Basis Unit], and doing that [Collection Basis] times.”

Follow along as we break down subsampling techniques and show how to properly document them in ARM.

Subsample Post #2: Basic subsamplingExample: You need to rate the % disease on the fruit's surface. Instead of inspecti...
06/02/2026

Subsample Post #2: Basic subsampling

Example: You need to rate the % disease on the fruit's surface. Instead of inspecting only one fruit from the entire plot, you plan to sample 20 fruits in each plot.

In this case, the sample size is “20 fruit,” creating 20 subsample values per plot.

Check back tomorrow for information on adding detail for subsampling techniques.

Subsample Post #1This week's ARM featured topic is subsamples. When assessments show substantial variability within a p...
06/01/2026

Subsample Post #1

This week's ARM featured topic is subsamples. When assessments show substantial variability within a plot, recording multiple values per plot can provide more accurate and meaningful data.

Setting up subsamples correctly involves a few key assessment header fields, including:
▪ Sample Size and Unit
▪ Collection Basis and Unit
▪ Reporting Basis and Unit
▪ Number of Subsamples

Not every field is required for every subsampling technique, so understanding how they work together is essential.

When no subsampling occurs, the Sample Size field can be entered as “1 PLOT” or whatever the experimental unit is for your trial. You can also leave it blank to indicate that no subsampling was performed. The only required field is Number of Subsamples, which should be set to 1. An example is counting the total number of fruit for each experimental unit, such as a single tree.

This week, we’ll walk through different assessment examples and show how to properly describe them using the key header fields.

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