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1106 PD: Variation in silage quality: Ways to evaluate the price

Floyd Hoisington Published on 10 November 2006

Forages are an integral component of the ration for dairy cows. The quality and consistency of the forage can have a significant impact on the production, profitability and health of the dairy cow. Forage quality can be extremely variable, based on hybrid or variety, area where grown, soil conditions, weather, harvesting, storage and feedout conditions.

To accurately assess variation and price (value), one must be able to measure the nutrient content and contribution from the forage. This then must be compared to the contribution of the forage under specific constraints and cost comparisons in the total ration.

For illustration purposes, corn silage will be used in the presentation of this [article]. The same principles may be used to compare or establish the value of any forage. I will be discussing establishing values based on the day-to-day aspects I use when consulting and balancing rations for my clients, rather than a research perspective. This is not the only way to determine value, and it may be different than other commonly accepted methods.

Forage quality
What is and what determines forage quality? Forage quality is the assessment, measurement and ability of a forage to supply specific nutrients under a given set of circumstances. This will vary from forage to forage, farm to farm and ration to ration. For ration balancing and evaluation purposes, forage quality is determined generally by laboratory analysis. The real proof of quality, of course, is the performance of the dairy cow.

Several quality parameters are important and need to be determined in the lab to allow us to accurately balance rations and assess the suitability of forage in a ration. First, one should make sure the feed is free of mold, noxious weeds and foreign matter and is suitable to be fed.

For this [article] we are going to look at dry matter (DM), crude protein (CP), fat, ash, acid detergent fiber (ADF), neutral detergent fiber (NDF), neutral detergent fiber digestibility (NDFD as a percentage of NDF), lignin, starch and calculated energy, both net energy for lactation (NEl) and total digestible nutrients (TDN). The minerals, other nutrients and fermentation profiles are also important and should be evaluated when balancing rations.

I randomly picked five samples of 2005 crop year corn silage from Washington and Idaho to use in this exercise (see Figure 1*).

These samples were all analyzed at Cargill Animal Nutrition’s lab in Elk River, Minnesota.

Tools to evaluate value
Several different methods have been used to evaluate, rank and price silages in the past. It is a fairly simple procedure to rank these silages based on individual nutrients. Based on energy, for example, one would choose sample 364058 from the Yakima Valley in Washington state as the top silage of the five. This gives us a comparison of quality based on the single nutrient (energy) to the other silages, but it tells us very little about the actual value to establish a price for that silage.

While not normally used for corn silage, relative feed value (RFV) or relative forage quality (RFQ), are often used to compare and buy forages. Again, this ranks forages from best to worst, based on the parameters used to determine the indices, but no actual value is established.

A common tool used in the Midwest is Milk2000. Milk2000 uses forage analyses (crude protein, NDF, in vitro NDF digestibility, starch and nonfiber carbohydrate) to estimate energy content using a modification of the 2001 NRC summative approach, and dry matter intake (DMI) calculated from NDF and in vitro NDF digestibility to predict milk production per ton of forage DM.

In Milk2000, the intake of energy from forage for a 1,350-pound lactating cow consuming a 30 percent NDF diet is calculated, and the cow’s maintenance energy requirement is then subtracted from the energy intake to provide an estimate of the energy available from the forage for conversion to milk (NRC, 1989). Forage DM yield is multiplied by the milk produced per ton of forage DM to provide an estimate of the milk produced per acre and combines yield and quality into a single term.

While this provides some excellent information, allowing you to rank silages from best to worst based on the quality parameters within the program, it does not result in a dollar value compared to other forages in the ration or geographical area. It also does not take into consideration interactions between forages or nutrients necessary to maintain a healthy functioning rumen.

Once you chose a price for one of the silages, you could calculate a price for the others based on the quality comparison and ranking. However, you do not know the value as compared to the current ration on that particular dairy or to other forages in the area.

N.R. St-Pierre has derived a maximum-likelihood method that uses the composition and prices of all feedstuffs traded in a given market to estimate unit costs of nutrients and break-even prices of feedstuffs. The method has been programmed into a Windows application named SESAME. This software can be used to identify feed ingredient purchasing opportunities and to benchmark feed costs from nutrient requirements and nutrient unit prices.

The developer of this application explains that this is very beneficial because it takes into account the entire marketplace. He feels that optimization programs suffer from being too case specific and may not deliver enough information on the unit costs of various nutrients.

St-Pierre also feels that the information provided from optimization programs is very limited in providing aggregate unit costs of nutrients and break-even prices of feedstuffs based on the trading of all feed commodities in a given market. He feels the information supplied by optimization programs is applicable to one group of animals in one herd.

His points are valid and correct, depending on what you want to accomplish. Our job as a consulting nutritionist is to maximize the profitability of each client we work with. In this case, I generally want to be looking at each herd on an individual basis rather than a wider swath that will occur from establishing prices on the entire market as far as forages are concerned. However, there may be times and circumstances where this is not the case, and I will establish prices based on the area market.

A given price may be a good buy based on the entire market, but it may not be a good buy based on a specific cost set and set of nutrient constraints for an individual client. You have to decide which approach is going to be best in the circumstance you are trying to evaluate.

Establishing price or value
You want to buy or sell one of the silages from the group of five. What is it really worth? To some extent, this depends on whether you are selling or buying. If selling, you want to get the most possible. If buying, you want to pay the least possible. Many times, prices are established without having any nutrient analyses and are based on RFV, RFQ or DM. This is playing forage roulette.

To establish actual values, I utilize ration-balancing software to run a parametric analysis. This allows me to establish the price on a feed ingredient that will not change the price of the ration. If you have to pay more for the feed than that price determined through parametrics, then your ration cost will increase. If you can get it for less than that price, your ration cost will decrease.

I enter the forage analysis into a specific farm file or set up a farm file that is representative of the area. I establish nutrient constraints based on desired production and health parameters. Other ingredients in the ration are priced based off actual purchase price or current market prices. I then solve for an optimized solution, and through the parametrics, I am able to establish an actual dollar value of the forage in a real-life situation.

This method looks at many different interactions, depending on the limiting nutrients in the ration. If one simply looks at energy, but digestible fiber is the limiting nutrient, the value of a forage could be much different. Without taking into consideration the interactions of the fiber fractions, amino acids and fatty acids in the entire ration, one could end up with a forage priced on another set of values that may not fit well into their ration.

Using the above method, I established values for the five silages. I used one of my existing clients with the parameters set for a high-producing ration. All silages were allowed or forced into the ration at 10 pounds of DM from the silage. The rations were solved and a value was generated, thus giving an opportunity cost or value based on the constraints, costs and ingredients offered for this specific ration (see Figure 2*).

The prices in the as-fed column are shown based on the actual DM of the silage. Since the DM is variable, two other prices are calculated for comparison. To be able to compare between silages with different Dm values, the 100 percent DM price is calculated.

To give a standardized comparison on an as-fed basis, a 30 percent DM price was calculated. This value is valid only for this specific ration, and it is a moving number, depending on the dynamics of the ration. If the costs or nutrient composition for other ingredients change, the value of the silage may change.

With the five silages, there is a dramatic difference in the value of the different silages, ranging from a low of $78.32 per ton DM to a high of $115.98 per ton DM. The numbers obtained through this method may vary between software applications, depending on the algorithms used and the dynamics of nutrition modeling. The extent of which the application looks at interactions of nutrients and balances for amino acids can have an impact on the price or value generated.

The value determined in this manner may not have any correlation to actual production costs of that forage. If one is growing the forage, and you cannot grow it for less than the value it fits in the ration, then you should probably look at other forage options in the future that may be more profitable. If you are purchasing the silage and the asking price is greater than the value, you should also look for other options.

With the actual dollar value established, we can rank the silages based on value. The ranking based on value is compared to the ranking of the silages based on some of the other methods and tools discussed earlier (see Figure 3*).

Note than none of the other four methods used agreed with the rankings by dollar value. It is not surprising that the energy ranking and Milk2000 are identical, since both are based on energy. RFQ and RFV will be very similar on corn silage, but they will show much more variation when using forages that have higher levels and more variation in protein, NDFD and lignin levels.

Conclusion
There are many different methods to evaluate silage quality variation and determine value. First, you must analyze the forage to check nutrient and quality parameters to see if it is something that you are willing to use.

If so, then a value can be determined (based off actual analysis and interaction in your ration) using several different methods. There is not just one correct procedure. You must choose the method that best fits your needs.  PD

References omitted due to space but are available upon request.

Figures omitted but are available upon request to .

—From 2006 Intermountain Nutrition Conference Proceedings

Floyd Hoisington, Dairy Nutritionist, Ferndale Grain

See more articles like this at www.progressivedairy.com

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