04/21/2021
How are you screwing up your customers ultrasound data? (Read this as a bit of tough love as intended. We all need a kick in the butt sometimes.)
1. Taking IMF images that are basically the same image 4 or 5 times: This doesn't sample the muscle. The longissimus dorsi isn't marbled exactly the same in every area. So, the idea is to sample in some different areas. While you may have limitations on depth, it is still critical to take images that are different.
2. Blurring IMF images: This is simple to explain. First, you are wasting our time and yours by collecting a blurred image. We have to remove them from the set of 4 or 5 which reduces the values used to create the average. Plus, we need 3 to make an average. Blur 2 in a set of 4, or 3 in a set of 5, and your breeder gets no data. With The EVO, ExaGo, Ibex, and Aquila, you can scroll back to an unblurred image. Sorry Aloka users, you have to start over. So STOP TAKING BLURRED IMAGES!
3. Taking ribeye images that are marginal or rejected: This one is obvious as rejected images are of no value and we report only the fat thickness if we can make it out. Marginal images that are close to a rib, reduce the size of the ribeye. When a producer has some marginal and some acceptable images in their data, the marginals will have a slight bias small, thus affecting ratios and EPDs. This is your responsibility to find out why you are getting marginals or rejections. Give us a call so we can help you get more clarity on what you are doing wrong. Then, improve. We can help anyone improve.
4. Competency Bias: If you think you are one if the best technicians for image quality, you probably aren't. Just like a year or so back when I was exposed to this idea of competency bias, I thought I was an above average driver. Feedback told me otherwise. (A ticket and a dumb accident were my feedback to tell me I wasn't as good as i thought i was.) If you are the tech that thinks you doing okay but can still improve, it is actually more likely that you are one of the best technicians. Use your image quality reports like I had to use my driving record to geound myself. Now i am fsr improved. If you think it doesn't apply to you, then you are likely a victim of competency bias.
5. You are using an Aloka, Classic, or Aquila: The data is in and it is very convincing. We have zero doubts. The new systems: ExaGo, Ibex, and Evo are superior in performance when it comes to IMF. They all have more spread, better correlation, and improved accuracy. Every single person who has switched to the ExaGo from Aloka has remarked about ribeye images being easier to see and collect. From the lab side, we agree. Everyone who switched, ExaGo in particular, has improved their image quality. And, their customers have seen much more accurate IMF data with values that have opened their eyes to new lows and highs. That is a WIN-WIN!
Take this info to heart. We know some of you can't or won't be able to upgrade and that's okay for now. However, your competition has or soon will. The word is getting out that the old systems and models are not as accurate. Ultimately it is your choice.
Below is a graph if IMF values before and after a technology switch. The higher average of IMF values is NOT the message. Look at the standard deviation of the heifer data. STDEV. Look at the high value in the heifer group. We are seeing so many more values on heifers higher than ever before. That is due to the new technology.