New Silage App Designed to Improve Corn Silage Quality

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To check corn kernel processor accuracy, producers usually take a few handfuls of silage, toss it on their tailgate, have a look and say, “Yep, good enough.” The other option is sending a sample off to a lab for analysis after harvest, and it comes back a week later with a kernel processing score. Dr. Brian Luck, assistant professor and extension specialist in biological systems engineering at the University of Wisconsin-Madison, in collaboration with Dr. Rebecca Willett, associate professor in electrical and computer engineering, also at UW-Madison, decided it was time for a better option.

“I’d seen image analysis used for particle size assessment and thought it would be a good fit to assess kernel processors,” Luck says. “Our goal was to try to match the results you could get from laboratory analysis. We don’t mean to replace lab analysis, but within about one minute, we wanted to provide an accurate in-field kernel processing assessment that allows producers to make adjustments prior to the crop being harvested.”

How SilageSnap Works

The SilageSnap app can be opened on your cell phone or tablet. With the app, all that is needed to Silage Snapget results of the particle size assessment is a single photo. Because phones have several different cameras, the app uses one of four U.S. coins (or two Euro coins) to establish standardized image measurement. Prior to taking a photo, the producer needs to separate the corn kernels from plant material using the following process, called water separation:

  1. Fill a bucket with water
  2. Put your silage sample in and swirl it around
  3. Skim the plant material off the top 
  4. Pour the water off and gather the corn kernels

Place the corn kernels on a matte black background and take a picture. The SilageSnap app will come back with results, including average particle diameter and two-dimensional surface area of every kernel in the image.

“What’s really nice is you have the option to look at the image and see what the image analysis came up with as particles within the image. IfParticles you see a circle that’s larger than the coin, it may be picking up glare or dust,” Luck says. “Once you get your picture corrected, you can trust the results and make adjustments as needed that will ultimately impact your silage quality.” 

Rather than photographing every corn kernel from your sample, another option is to pick the 10 largest kernels from the water-separated sample and only use those in the photo. 

“It’s the larger kernels that we’re really concerned with, so by cherry-picking the largest particles and confirming that those are below the 4.75 mm threshold, you’ll know if you need to make adjustments to the processor,” notes Luck.

 To create the best image:

  • Use a dark, solid-color, smooth background.
  • Glare can be an issue if it’s sunny outside, so try to pick a shady spot.
  • If it’s dark or cloudy outside, consider using the flash on your phone camera to get a higher contrast.
  • Any fine particles in the image will be counted as particles, so use a clean, smooth surface.

SilageSnap will offer a “Share” option for producers to share their information with the University of Wisconsin Extension team. If enough data comes in, general trends of the kernel particle size can be posted online without publishing any confidential or identifiable data.

“Being able to provide real-time trending data to producers could be very helpful – if parts of the country are wetter or drier, we might be able to go out and diagnose problems or offer guidance on processor adjustments that may need to be made in an area before harvest,” Luck says.

App Availability

SilageSnap will be available on Android and Apple/iOS cell phones and tablets. The app will be undergoing beta testing in June 2018; release is expected early July 2018. It will be available in the Google Play Store and on iTunes. Upon release, Luck will post it on his university website, wimachineryextension.bse.wisc.edu, and will be “shouting from the rooftops” on Twitter @BadgerLuck.

 

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