Sampling during feedout for determination of silage nutrient composition at commercial feed analysis laboratories, and the use of these analyses for ration reformulation had traditionally been done once monthly. However, this sampling protocol is inadequate on today’s larger dairy farms. Researchers at The Ohio State University recommend different silage sampling protocols depending upon herd size. An analysis was performed using their software program.
The optimum sampling schedule for a 50-cow herd was the same as what has been done traditionally. As herd size grew at increments from 50 to more than 1,500 cows, the sampling frequency greatly intensified to an interval between samples of only four days. In other words, the large herds needed to be sampling about seven times per month. Full adoption of on-farm near-infrared system (NIRS) technology could allow this level of analytical frequency, or even sampling/analysis done daily or by feeding within the day, in the future. Lack of accuracy and precision for NIRS equation calibrations for key nutrients beyond dry matter (DM) and in-line sensor challenges, however, have thus far limited farm-level application for nutrient composition.
Another approach
Because it has less variation in nutrient composition than haycrop silage, corn silage can usually be sampled less frequently. This may not be the case, however, in years when crop growing and harvest conditions result in larger variations in corn silage starch and neutral detergent fiber (NDF) within and across silos.
Frequent sampling and analysis does not dictate that rations need to be reformulated each time. Frequent silage sampling protocols are for detecting changes in nutrient composition early or during a period of change. Ration reformulation is needed only when differences in nutrient composition appear significant. If differences are small between samples, then reformulation of rations may not be necessary. When ration reformulation is performed it should be based on a rolling average of three samples rather than on an individual sample; this avoids random sampling or analytical errors greatly influencing the consistency of the feeding program.
Get a good sample
It is critical that representative samples be collected for subsequent nutrient analysis. Because corn silage is a mixture of grain and stover fractions, special care must be taken to obtain a homogeneous sample to send to the testing lab. Don’t take a grab sample from a bunker silo face as it is unsafe and does not result in accurate or precise determination of DM content or nutrient composition. Wisconsin Extension workers provide detailed protocols for sampling silages from bunker silos, silo bags, and tower silos that are available to readers on the internet (bit.ly/HFG-sample).
On-farm determinations of silage DM content are typically done using either a microwave oven, Koster tester, or food dehydrator drying methods as described by Wisconsin Extension (bit.ly/HFG-moisture). As costs for equipment and equation calibration updates decline and accuracy and precision of DM determinations improve, the on-farm use of NIRS continues to climb.
The major analyses for nutrient composition performed at commercial feed testing labs include crude protein (CP), NDF, starch, crude fat (ether extract), total ash, and individual macrominerals. A calculated value for nonfiber carbohydrates (NFC; 100 percent minus CP percent minus NDF percent minus Fat percent minus Ash) along with analytical values for acid detergent fiber (ADF), NDF- and ADF-insoluble CP, lignin, water-soluble carbohydrates (sugars), and soluble-CP concentrations are also typically reported.
Wet chemistry procedures and results serve as the basis for NIRS equation development and calibration and for troubleshooting outlier results from NIRS analysis. Compared to wet chemistry, the NIRS analyses are lower cost and can be performed much more quickly, thereby resulting in a faster turnaround time for nutritionists using the results for ration reformulation.
Although some nutrient analyses may be less precise with NIRS than wet chemistry, this can be partially offset by more frequent sampling and analyses with NIRS made possible by the lower cost. For standard corn silage analyses where the NIRS equation calibrations have been improved over many years, DM, CP, soluble-CP, NDF, ADF, and starch, the laboratory NIRS results are generally thought to be very acceptable. These are the same nutrients being explored for on-farm NIRS determinations, with DM being the most commonly accepted determination thus far.
Feedstuff energy values provided on laboratory analysis reports are calculated from nutrition composition results. Typically, the summative energy equation, which was originally developed by The Ohio State University researchers, is used to calculate total digestible nutrients at a maintenance level of intake (TDN1x) using CP, NDF, NFC, and crude fat or fatty acid concentrations along with either assumed or assayed digestibility values for those nutrients (Dairy NRC, 2001).
From TDN1x, net energy values are calculated for lactation (NEL; adjusted for a productive level intake [for example, three times maintenance energy intake or NEL-3x]), gain (NEG), and maintenance (NEM). Comparative forage indexes, such as milk per ton for corn silage and relative forage quality (RFQ) for haycrop silages, are also calculated values that utilize nutrient composition results along with NDFD measurements.
Beyond the basics
For evaluation of starch digestibility, a 7-hour feedstuff incubation, either in vitro in rumen fluid or in situ (Dacron bags inserted in rumen-cannulated cows) is the most common assay. Although this test can be performed on both corn silage and high-moisture corn samples, the sample’s particle size and length of time ensiled prior to analysis confounds any relationship that might exist between kernel endosperm properties and the results obtained from the assay.
Finally, a fermentation profile can be requested from commercial testing labs to assess silage quality. For sample benchmarking, see accompanying graphs. These data are summarized over a six-year period for a commercial testing lab based on the relationship between the DM content of corn and alfalfa silages (from Kung and co-workers, 2018, Journal of Dairy Science).
This article appeared in the November 2018 issue of Grower on pages 18 and 19.
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