The 2018 RFC survey is designed to understand the amount of variation in soil and food quality, as per the testing methods used, in the North East and Midwest US.  In addition, we will be looking for connections between soil health, food quality, and farm practice.  Farm practice is broadly defined as organic, regenerative, and conventional and in some cases includes specific definition of practices like no till, no spray, consistent irrigation, etc.  Finally, the survey is a learning experience for the RFC to better understand testing costs and throughput for future surveys, and to build a community around the survey and testing process.  The survey was performed from June 2018 to November 2018.


Data collected in the field (sample intake data)

Crop: carrot, spinach

Sampling location: supermarket, farmers market, farm

Management: conventional, Organic, regenerative ag

In addition to the above, data is also collected about the samples:

Brand or grower (for supermarket/farmers market samples)

Field and/or variety (for farm samples)

Within the crop/sampling location/management/brand/field bucket, 3 samples are taken.

Data collected in the lab

You can find the exact soil and food lab methods used on the Testing page.


I go to the store, and identify 2 brands of organic carrots.  I collect 3 carrots from each brand.

I go to a farm, and identify 2 fields of carrots planted with the same variety.  I collect 3 carrots from each field

I go to a farm and identify a field with 2 varieties.  I collect 3 carrots from each variety.

Collection Process

Once samples are collected, data is shipped  using standard USPS Priority Express padded envelopes (ships 1 – 2 days guaranteed), designed to contain 6 samples (one sample includes both food and soil at 0 – 6” and 6 – 12”) each.  Those boxes are shipped to data collectors with pre-addressed return labels, and samples are expected to be returned to the lab the same day they were collected.  This minimizes reduction in quality like antioxidents and other compounds which are known to decrease quickly after harvest.

Samples will also have a survey attached to them, either written in paper in the box, or filled out through the Our Sci survey app (link, currently in beta).  When samples arrive in the lab they are processed, and lab data is recorded using a separate set of surveys.

All surveys are built using the ODK Build (build.opendatakit.org, or open using OpenOffice or Excel), and resulting data uploaded to app.our-sci.net.  The surveys are occasionally updated, and below are links to the most recent versions.

Link to all surveys

  • Intake survey (filled out by data collectors)
  • Carrot quality survey (in lab)
  • Spinach quality survey (in lab)
  • Soil quality survey (in lab)
  • Calibration survey (in lab, used to run standards for antioxidents, polyphenols, and proteins)

To see detailed descriptions of the testing methods, see the Testing Page.

Data Collectors

Data Partners (BFA Chapters and other RFC partners) collect the data from the North East and Midwest.  In 2018, we have 7 data partners with expectations of collecting 12 – 18 samples per week from 2 – 3 unique sampling locations.  Data Partners are part time volunteers, and therefore the exact data collection schema varies for each.  However, in general, the target data collection schema for each Data Partner is as follows (for example crop carrots).  Data Partners is told to collect the widest possible range of samples within each bucket (so if you go to Meijers this week for carrots, go to Busch’s next week).

Once a schema is developed for each sample partner, a weekly schedule is created for that partner by randomizing the collection events which occur within each time period (early, early-middle, middle, late-mid, late).  Those time periods are defined based on the Data Partner’s availability and their normal season for that crop.  An example completed weekly schema for a Data Partner is shown below.

For more information about the Data Partners, see the invitation letter and non-binding agreement for data partners.

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