Analyzing Silage Crops for Quality: What Is Most Important?

Animal productivity depends on the nutrient composition of the ration presented to the animal as well as on the quality of feed ingredients. In assessing animal productivity the nutritionist must determine if ration composition is the factor limiting productive potential. In order to do this one must have an accurate assessment of feed quality and delivery. Having as complete a set of information as possible on the feeds and delivered ration will assist the nutritionist in making this determination and allow for the identification of limiting factors. With advances in the use of Near Infrared Reflectance Spectroscopy (NIRS) thirty or more items of nutrient information can be provided with minimal cost. Various evaluations beyond the scope of NIR are available as well. This volume of information can often overwhelm the nutritional diagnostician and make it more difficult to focus on critical indexes of forage quality. With so many analyses available which characterize different aspects of feed quality, where does one start in order to critically assess feed quality in silages? Defining Objectives Obviously, the first step in determining what analytical approach to use in forage evaluation is to define the objectives of testing which dictates what evaluations should be performed. Testing objectives can be summarized within the following four categories:  Diagnostic Evaluation  Providing nutritional inputs for ration balancing  Marketing  Process control It is the author’s observation that often these objectives are not used in defining the scope of testing and as a result either more is spent on testing than necessary, or sufficient data is not generated to meet the objective. It is granted that there is significant overlap in what is potentially tested to meet goals of each of these objectives. Traditionally, emphasis has been placed on nutritional forage evaluation for meeting the objectives of each of these categories. These values are quantitative in nature and are more easily defined and measured than items that are more qualitative evaluations. However, the qualitative evaluations often relate more significantly to animal performance. These evaluations comment more significantly on forage management, harvesting, and storage than nutritional measures. This paper will spend much time discussing the use of qualitative evaluations in meeting the above objectives. 1 Ward, R. T. ([email protected]), President, Cumberland Valley Analytical Services. 14515 Industry Drive, Hagerstown, MD 21783; In: Proceedings, 2011 Western Alfalfa and Forage Conference, Las Vegas, NV, 11 – 13 December, 2011. UC Cooperative Extension, Plant Sciences Department, University of California, Davis, CA 95616. (See http://alfalfa.ucdavis.edu for this and other alfalfa conference Proceedings.) Qualitative versus Quantitative Evaluation of Feeds It is easy to become overly focused on key quantitative evaluations such as the amount of protein or NDF in a feed material. While these nutrients are important for balancing rations, they often are not the most important when initially assessing forage or feed quality factors related to conservation or acceptability by the animal. Animal productivity is significantly dependent on animal acceptance of the feed and resulting dry matter intake. Those factors of forage quality associated with high and consistent dry matter intake should be come of the first factors to evaluate. These same factors are often associated with higher levels of dry matter conservation during the storage and feed-out processes. Losses of dry matter from field to feed bunk run 10% to 15% under optimum conditions and can be 20% to 40% where management is poor (Table 1). This represents serious economic loss of feed nutrients apart from impaired animal performance. Those qualitative factors that are important to consider are dry matter, fermentation acid levels, ammonia, ADF-CP (bound protein), fiber digestibility, molds, yeasts, ash, forage particle size and corn silage starch processing. This paper will focus briefly on the listed items related to qualitative evaluation. Each of these evaluative criteria of themselves would provide opportunity for lengthy discussions. Forage laboratories should be able to provide most of these qualitative evaluation services for their clients along with traditional quantitative evaluations. Requirement for Reference Statistics In order for forage or feed evaluation to have value, the data or index generated from the analysis must be compared against some standard or distribution of results consistent with the feed class that is being evaluated. It does little good for us to know that the 30 hour in vitro NDF digestibility of corn silage is 55.3% unless we know how that relates to the population of analyses for corn silage. Table 2 provides an example of averages and standard deviations for various forage classes. Figure 7 provides more extensive information about the distribution of 30 hour in vitro NDF digestibility in corn silages specific to a given laboratory. It is important to refer to reference statistics from the laboratory that is generating the analyses for a given forage sample. Procedures can be different among various commercial and research laboratories with widely varying averages and distributions for some nutrients. Measures such as in vitro starch and NDF digestibility would be a good example where significant lab differences may exist. This paper provides a number of examples of references statistics (Figures and Tables) generated from commercial laboratory data of Cumberland Valley Analytical Services (CVAS) that can be used to interpret specific laboratory values. Table 4 provides an example of “goal” values for fermentation profiles. Qualitative Evaluation of Forage Use of Fermentation Analysis Some argue that while the fermentation analysis is interesting, it is of little value, because it provides no information that can be used directly in the ration balancing process. However, this challenge avoids the true value of fermentation evaluation that is meant to provide a comparative evaluation that allows the user to better characterize the silage, and to lend insight into possible dry matter intake and performance problems. A silage at 30% DM that has 1.5% butyric acid and 18% ammonia nitrogen as a percentage of total nitrogen will be utilized differently than a silage at the same DM level that has no butyric acid and 9% ammonia nitrogen. The extent of an adverse fermentation can be determined better by the fermentation analysis than by visual and olfactory observation, or by the use of a simple pH measurement. A second and perhaps more important application of the fermentation report is as a “report card” on the management of the silage making process. Fermentation end-products the result of all conditions that affected the silage making process, including plant maturity, plant moisture, sugar content, epiphytic (indigenous) bacteria activity, additive use, ambient temperature, packing, and face management (Kung and Shaver, 2001). Significant breakdowns in the management of the silage making process will show up as silage with less desirable fermentation characteristics. The farm adviser can use the information gained from the fermentation analysis to document the quality of the silage and to challenge a farmer to improve silage making practices. Quality forage is the basis of profitable animal production. The type and degree of fermentation will significantly affect the amount of DM recovery from the silage making process. Significance of Moisture to Fermentation Outcome Forage that is ensiled properly exhibits rapid pH drop where homo-fermentative bacteria predominate. Lactic acid should be a significant end-product of these fermentations. Fermentations that yield more lactic acid typically result in the lowest dry matter losses. Silages that have high levels of acetic, propionic, butyric or iso-butyric indicate conditions where DM recovery from the silage making process may be poor. Generally, in well-preserved silage, 60% -70% of the total acid will be lactic acid or 4-7% lactic acid (%DM). Acceptable silages generally contain <3% acetic acid, <0.1% butyric acid, and <0.5% propionic acid. Table 4 provides an example of goals for fermentation profiles of corn silage and high moisture corn. The significance of level of moisture in providing opportune conditions for various epiphytic organisms that are active during ensiling cannot be overstated. Fermentation end products are significantly related to moisture level because of the epiphytes favored at those moisture levels. Figure 1 shows fermentation data for legume silage broken out by dry matter range across thousands of samples evaluated at CVAS (2008 – 2011). Most evaluations vary significantly by DM of the plant material. Highly Fermented High Moisture Silages High levels of silage acids indicate that an extensive fermentation occurred in the silo. Many feeding situations utilize silages with high acid content with no apparent problems. Although higher lactic acid levels are usually considered to be better for silage preservation, lactic acid may be a problem in silages where it exceeds ten percent of DM. This rarely happens in North America but is more common in Europe. When wet grasses (<30% DM) with a high amount of sugar are ensiled, perhaps as direct-cut silage, they can undergo an extensive silo fermentation and can contain high levels of lactic acid. In one study with direct-cut ryegrass silage, it had a pH of 3.8 and 17.5% lactic acid (McDonald, 1991 as cited by Harrison et al., 1994). Wet silages that have undergone a long fermentation often contain higher levels of acetic acid (>3% DM) (Figure 1). Ammoniated silages also often have higher levels of acetic acid because of their longer fermentation (Kung and Shaver, 2001). Very high levels of acetic acid (>5% DM) have been suggested to cause intake problems, however research has not consistently found this to be true and the mechanism by which acetic acid might compromise intake is not understood (Seglar and Mahanna, 2001). The acetic acid itself may not be a problem, but may be an indicator of less desirable fermentation. Poorly Fermented High-Moisture Silages Clostridial Fermentations Forages ensiled at less than 32% DM have a greater risk for clostridial growth. Clostridia bacteria are one of the most common undesirable bacteria that may persist in unstable silage that has no oxygen. They produce butyric acid and break down protein. Clostridia usually are associated with hay-crop silage that has a pH of 5.0-5.5. With a clostridial fermentation, there will be higher silage dry matter losses, poor silage palatability, and a higher level of ammonia nitrogen. It is suspected that the protein breakdown products, such as ammonia, amines, and amides, may be responsible for limiting intake. Butyric acid itself may not significantly impact intake, but may be a marker for protein degradation products. Soluble protein has been used to evaluate retention of protein quality in fermented silage. Forage evaluation data compiled by CVAS indicates that there is significant variation in the quality of protein in the soluble fraction. In Figure 2, one can observe a very strong relationship between moisture level of legume forage and the ammonia nitrogen as a percentage of total nitrogen. This would be expected as there are more clostridial and proteolytic organisms active at higher moisture levels. However, there is little correlation between soluble protein and moisture level (Figure 2) indicating that the soluble protein test is not sensitive to the quality of the protein in the soluble fraction. It would not be a good predictor of ammonia or proteolytic activity during the forage wilting and fermentation process. Unavailable Protein (ADF-CP) The ADF-CP is measured by boiling feed or forage in an acid detergent solution and determining the protein content of the residue. This protein fraction is assumed to be of little use to the cow. Excessive heating of forages leads to what is known as the Maillard reaction where sugars are condensed with amino acids and become insoluble like the lignin complex. Van Soest (1982) makes the statement concerning the evaluation of heat damage: “Its assay as a guide to quality of processed feeds cannot be underestimated nor overlooked.” This process of heat damage may severely reduce the availability of protein and digestible carbohydrate in a feed. ADF bound protein (%DM) values above 2% (Figure 3) in legume silage indicate a potential problem with excessive heating. Ensiling at higher dry matter levels and poor bunk face management which exposes more silage surface area to air can increase ADF bound protein in silage (Ruppell et al., 1995). Fiber digestibility in hay-crop forages as determined by a 30 hour invitro NDF assay is negatively impacted by heating and creation of ADF-Protein (Figure 5, CVAS 2011).