FROM THE FARM REPORT: WHY TAKING GOOD FEED SAMPLES IS IMPORTANT

Knowing what’s really in your feed is the first step to making good rations that meet the cows’ needs. That’s why taking and testing feed samples regularly is such an important tool — it helps to avoid nutrient shortages or waste. But the more tests we run, the more we see that feed values can vary a lot, especially in forages and by-products. For example, let’s say you tested corn silage every day for 14 days. The fiber (NDF) results are shown in the figure (just as a hypothetical example).

Some days were much different than others, like day 1 and day 9. If the ration was balanced for an average of 40% NDF, but the silage had 45% (day 1) or 30% (day 9), cows can usually handle short-term variations but they might face some ups and downs in intake and performance on days when the silage is higher or lower than that. But if the diet was balanced using only day 9 (30% NDF), the mismatch would be much greater, since the silage has more fiber than that — leaving the ration unbalanced and putting cows at greater risk of eating less and making less milk.

Corn silage NDF (% of dry matter) across 14 days.

That’s why it’s so important to understand not just the numbers on a feed test, but also where the variation comes from. Was day 9 really low? Or was it just a poor sample? Or maybe the lab test was off?

To figure this out, Dr. Normand St-Pierre and Dr. Bill Weiss ran two big studies.

Study 1 – Daily Sampling

They collected silage samples every day for 14 days on 11 farms in Ohio and Vermont. Each day they took two samples and tested each sample twice in the lab. This allowed them to separate the variation caused by the lab test itself, the sampling technique, and the real day-to-day changes in the silage.

Results: Sampling errors were the biggest reason test results changed (except for dry matter). In corn silage, 50.9% of NDF variation and 65.3% of starch variation came from sampling errors. In grass/legume silages, sampling caused 43.6% of NDF variation and 59.4% of crude protein variation. Lab testing explained only about 10–15% of the variation; the rest were true changes in the feed. These changes come from genetics, weather, harvest, storage, etc.

Study 2 – Monthly Sampling (More Like Real Farms)

Since most farmers don’t sample every day, the second study looked at monthly samples of feeds and TMR from 47 U.S. farms. They compared variation within farms (month to month) and across farms. As expected, the month-to-month forage variation was much higher than day-to-day. Sampling errors were still large: in corn silage, 36.6% of NDF variation came from sampling, 11.2% from lab tests, and 52.2% from true feed changes. With TMR samples errors were even worse: For NDF, crude protein, and ash, 60–69% of the variation came from sampling and lab work, not real ration differences.

Main Conclusions from the Studies

Feed values naturally change with weather, harvest, storage, or processing, and cows usually handle this normal “true variation” just fine as long as the ration is balanced around the right average. The bigger challenge often comes from sampling or testing errors, since a poor sample or lab mistake can make it look like the feed has changed when it really hasn’t, leading to unnecessary ration changes. To get the most accurate picture, it’s best to take duplicate, independent samples and average the results. Relying on just one feed test can be misleading, but using the average of several samples gives a much clearer idea of what the cows are actually eating.

What This Means on the Farm

Imagine your ration is set for 30% NDF. If you send just one TMR sample the result could read anywhere from 26.5% to 33.5% just because of sampling errors. That wide range makes it tough to spot real problems.

If you send two independent samples, the error drops and the range tightens (about 28–32%), making it much easier to see true changes.

Key Takeaways

How you sample matters a lot. Poor samples can hide real feed changes that affect cow performance.

Better sampling = better rations. Take more than one sample, average results, and be cautious with single tests.

— Daniel de Oliveira

doliveira@whminer.com