Understanding and Improving Forage Quality (B 1425) University of Georgia Extension The goal of this publication is to guide the user to a better understanding of basic forage quality terms and to recommend management changes that will improve forage quality. To that end, our objectives are to explain how forage quality is measured, describe how to interpret a forage analysis, present the effects of management on forage quality, and list the key management strategies that can increase the nutritive value of forage crops. 2017-03-28 14:33:22.483 2014-01-21 14:14:29.0 Understanding and Improving Forage Quality | Publications | UGA Extension Skip to content

Understanding and Improving Forage Quality (B 1425)

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Dennis W. Hancock, Extension Forage Agronomist, Department of Crop and Soil Sciences
Uttam Saha, Program Coordinator, UGA CAES Feed and Environmental Water Lab
R. Lawton Stewart, Jr., Extension Beef Nutritionist, Department of Animal and Dairy Science
John K. Bernard, Extension Dairy Nutritionist, Department of Animal and Dairy Science
Robert C. Smith, III, Ag & Natural Resources Program, Development Coordinator, NE District
Jennifer M. Johnson, Extension Forage Specialist, Auburn University

The nutritive value of a specific lot of forage is defined by the amount of nutrition that can be derived from it and the presence/concentration of any toxic compounds that could reduce animal performance or threaten animal health. In combining the nutritive value of the forage with assumptions/predictions of how much of the forage an animal could eat, one can determine if the forage?s quality is sufficient. It is important to understand the quality of the forage being used so as to develop a least-cost ration for the animals being fed. Estimates of protein, mineral, and vitamin content can be made relatively easily. However, the majority of the available energy in a forage crop is in a fibrous form. Several analytical procedures have been developed to provide estimates of fiber content and digestibility. These estimates have also been calibrated to predict animal nutrition and performance.

The goal of this publication is to guide the user to a better understanding of basic forage quality terms and to recommend management changes that will improve forage quality. To that end, our objectives are to explain how forage quality is measured, describe how to interpret a forage analysis, present the effects of management on forage quality, and list the key management strategies that can increase the nutritive value of forage crops. This publication is written with the understanding that the reader either knows or can quickly find the definition of key forage quality terms. The reader is encouraged to refer to the glossary of UGA Extension Bulletin 1367, “Common Terms Used in Animal Feeding and Nutrition,” for unfamiliar terms used in this publication.

Forage Quality Has Value

Commodity and by-product feeds are relatively expensive. Certainly, providing high-quality forage (either as pasture, hay, baleage/haylage, or silage) is not inexpensive, either. With recent feed prices, however, high-quality forage is cheaper than most supplements that are typically fed. Forage that is lower in digestibility will not meet the nutrient requirements of the animal requiring supplementation, which increases the cost of production. As a result, more and more supplement is needed to meet the requirements of the animal (Table 1).


Table 1. The effect of bermudagrass and tall fescue maturity on hay quality, supplementation rate, and cost of supplementing a lactating beef cow.1


Crop Maturity Crude Protein
(CP)
Total Digestible
Nutrients (TDN)
Supplement
Req. for a Lact.
Beef Cow
Cost to Supplement
  ---- % ---- ---- % ---- lbs/hd/day $/hd/day
Bermudagrass 4 weeks 10-12 58-62 0 $0
6 weeks 8-10 51-55 2.3 – 4.8 $0.23 – 0.48
8 weeks 6-8 45-50 5.3 – 7.5 $0.53 – 0.75
Tall Fescue Late boot 14-16 66-70 0 $0
Early head 11-13 60-63 0 $0
Dough (seed) 8-10 50-54 3.0 - 5.3 $0.30 – 0.53
1 Assumptions: 1,200 lb beef cow, average to above-average milking ability, first three months postpartum, 6.0 lbs of TDN required daily, and supplement that provides 85% TDN and costs $200/ton ($0.10/lb).

The Need for Forage Testing

There is no technique for assessing the nutritional value of the forage in a pasture or lot of hay or silage strictly on the basis of feel, texture, smell, or appearance. In fact, attempting to do so has frequently caused producers to buy or use forage that has lower nutritional value and is often uneconomical or counterproductive (Figure 1). The nutritional value of the forage can only be evaluated by obtaining a representative sample of the forage and subjecting that sample to analysis in a qualified laboratory.

Figure 1. Though different in appearance, lots 1 and 2
are essentially the same quality. Figure 1. Though different in appearance, lots 1 and 2 are essentially the same quality.
figure2. Sampling for forage quality can aid decisions,
such as storage priority. Figure 2. Sampling for forage quality can aid decisions, such as storage priority.

The results of a forage test can be used for a number of purposes. One of the most important uses is to formulate cost-effective rations. Forage testing is also used to establish the nutritive and, therefore, market value of the lot. Though hay, silage, and other conserved forages have not typically been marketed in the Southeast on the basis of nutritive quality, savvy producers are increasingly insisting upon having a forage quality analysis for any lots that they may be purchasing. Another purpose for sampling forage is to prioritize the lots that one may have in inventory for timely use (Figure 2). For example, a beef cow-calf producer with limited hay storage space may want to store their low-quality forage outside while storing the higher quality lots under cover so as to better protect the more valuable forage.

Obtaining a Representative Forage Sample

Figure 3. Sampling a lot of hay bales using a Colorado
hay probe. Figure 3. Sampling a lot of hay bales using a Colorado hay probe.

Obtaining a representative forage sample is critical. The first step is to identify a single lot (forage taken from the same farm, field, and cut under uniform conditions within a 48-hour time period). Once a lot is defined, sub-samples should be obtained from at least 20 different bales (hay, baleage) or areas (silage) that are selected at random. Detailed procedures for sampling forage are provided by the National Forage Testing Association (http://www.foragetesting. org/). Avoid taking grab samples from the bale or stack, as this may cause leaf loss and result in a sample that is not a fair representation of the lot. It is best to use a clean, sharp, forage probe (Figure 3). For information on selecting and purchasing forage probes, see the frequently asked question page titled “What hay probe do you recommend and where can I get one?” (http://www.caes.uga. edu/commodities/fieldcrops/forages/questions/hayprobes.html) on the University of Georgia?s Forage Extension website (www.georgiaforages.com).

Measures of Forage Quality

Certainly, the ultimate evaluation of forage quality is animal performance. But, it is obviously not practical to do feeding trials to estimate the quality of each lot of forage crop. Thus, predictions of forage digestibility and rate of intake have been developed that allow one to better estimate the forage crop?s nutritive value.

Predictions of forage digestibility and intake rate are based on the fibrous part of the forage. Since a forage crop is essentially a collection of many plant cells, a simplified example of a single plant cell can help to illustrate the various fractions and components (Figure 4).

Figure 4. The easily digestible components of a cell and the fibrous
components (NDF) of the cell wall. Figure 4. The easily digestible components of a cell and the fibrous components (NDF) of the cell wall.

A plant cell is made up of a cell wall and cell contents (i.e., material inside the cell). Essentially, all of the cell contents are easily digestible. However, the cell wall is fibrous and less digestible. This fibrous fraction can be measured and divided into components using a stepwise laboratory procedure. This procedure involves the extraction of the cell components in a progressive manner, starting with the most easily removed components (cell contents and pectins). The soluble cell contents and the pectin within the cell wall are removed by boiling the sample in a neutral detergent. The whole fibrous fraction that remains is known by the first step in the chemical analysis, neutral detergent fiber (NDF) analysis. This NDF fraction consists of hemicellulose, cellulose, lignin, and silica/minerals. The next step involves boiling the NDF fraction in an acid detergent, which dissolves and washes away the hemicellulose component. This leaves the acid detergent fiber (ADF) fraction, which consists of cellulose, lignin, and silica/minerals. Next, the ADF fraction is further treated with a stronger acid to dissolve the cellulose to leave just the lignin and silica/mineral components. Finally, the remaining fraction is burned in a 500° C furnace, leaving just the silica/mineral components in the ash.

The concentration of NDF and the ratios of the subcomponents of NDF in relation to one another have direct effects on the digestibility of the forage. Cellulose (a long chain of glucose molecules linked end to end) and hemicellulose (a branched polymer of glucose, xylose, galactose, and other carbohydrates) can be broken down by enzymatic action of bacteria and other microbes in the animal?s digestive tract, though their digestion is markedly slower than the digestion of sugars, starches, and other freely available non-structural carbohydrates. In contrast, lignin is not carbohydrate-based but is a phenolic compound. As such, lignin is not digestible. Moreover, the very presence of lignin acts as a physical barrier to the microbial enzymes that break down cellulose and hemicellulose. As a result, the amount of NDF and proportion of the NDF that is hemicellulose, cellulose, lignin, and silica/mineral are known to influence and can be used to estimate other aspects of forage quality. It is those components that are used to calculate metrics like total digestible nutrients (TDN), metabolizable energy (ME), and net energy for maintenance (NEm), gain (NEg), and lactation (NEl)1. These variables, along with a measure of crude protein (CP) and mineral content, can then be used to develop a balanced ration that meets the nutritional needs of the animal type/class.

1 It is important to note that the estimates of TDN, ME, NEm, NEg, and NEl are made using predictions specific to the animal species and class that is being fed.

In addition to ration balancing, the results of a forage analysis can be helpful to identify nutritional problems or toxin-related disorders. Frequently, a ration may be balanced for CP but not supply enough energy or mineral content. Furthermore, some measures of forage quality can be used to estimate dry matter (DM) intake by the livestock class being fed. An overview of the important uses of the forage quality metrics specified on reports from the University of Georgia?s Feed and Environmental Water Laboratory are presented in Table 2.


Table 2. Summary of the primary uses of the forage quality metrics specified on reports from the University of Georgia?s Feed and Environmental Water Laboratory.


  Important Uses
Metric Abbrev. Units Analytical
Method
Ration
Balancing
Nutritional
Diagnostics
Energy
Estimates
Involved in
Estimating
DM Intake
Standard Procedures
Relative Forage Quality2 RFQ -- NIR        
Crude Protein CP % NIR, WC x x   x
Crude Fiber3 CF % NIR        
Neutral Detergent Fiber NDF % NIR, WC x x x x
Acid Detergent Fiber ADF % NIR, WC x   x x
Lignin   % NIR, WC     x  
Total Digestible Nutrients TDN % NIR x x x x
Net Energy of Lactation NEl Mcal/lb NIR x x x  
Net Energy of Maintenance NEm Mcal/lb NIR x x x  
Net Energy of Gain NEg Mcal/lb NIR x x x  
Metabolizable Energy ME kcal/lb NIR x x x  
Moisture   % Oven        
Dry Matter4 DM % Oven x      
Mineral Analyses
Phosphorus P % WC, ICP x x    
Potassium K % WC, ICP x x    
Calcium Ca % WC, ICP x x    
Magnesium Mg % WC, ICP x x    
Manganese Mn PPM WC, ICP x x    
Iron Fe PPM WC, ICP x x    
Aluminum Al PPM WC, ICP x x    
Copper Cu PPM WC, ICP x x    
Zinc Zn PPM WC, ICP x x    
Sodum Na PPM WC, ICP x x    
Other Analyses
Total Fat   % WC x x    
Nitrates5 NO3-N PPM WC x x    
Ash   % Oven x      
Sulfur S % WC, ICP x x    
Arsenic As PPM WC, ICP   x    
Selenium Se PPM WC, ICP x x    
Bound Protein   % NIR   x    
pH   unitless WC   x    
Salt   % WC   x    
Total Aflatoxin4   ppb WC x x    
2 An index (unitless) most commonly used for forage categorization and marketing.
3 A term that is now obsolete, with the exception that many states still mandate its listing on the label of commercial feedstuffs.
4 When comparing forage lots, feed tags, and/or labels, balancing rations, or conducting cost assessments of forages and all feedstuffs, it is important to use values corrected for moisture (i.e., on a DM basis).
5 Anti-quality factor assessed when conditions for toxic concentrations of the compound are suspected.

Evaluate Forage on More than Just Crude Protein

Most of the classes of livestock that are being fed in the Southeast have relatively low requirements for CP. For example, the CP requirement for beef cows peaks during early lactation at 12% CP and declines to about 7% CP for dry cows. Most of the forages produced in the Southeast can meet these requirements (see inset, “Forage Quality of Major Southern Forages: Summary Statistics”).

Unfortunately, there is a false perception that protein is the most limiting nutrient in the animal?s diet. The reality is that the energy value of the forage is usually the most limiting factor in meeting a livestock class?s requirements. As a result, many mistakenly believe that CP is the ultimate measure of a forage crop?s quality.

Using CP as the sole measure of forage quality can be deceiving. Crude protein, as the name implies, is a crude method for measuring protein. In fact, CP is merely an estimate of nitrogen content (N, % x 6.25 = CP, %) and must be considered in context of plant maturity, species, fertilization rate, and many other characteristics. For example, a high nitrate concentration in the forage would be measured in the total N fraction, but nitrates are non-protein N.

Certainly, CP is an important indicator of the protein content of a forage crop. However, focusing on CP may cause one to fail to place enough emphasis on meeting energy requirements. Instead of focusing on CP, one should focus first on the amount of digestible energy in the forage.

Near Infrared Spectroscopy

The multiple steps and chemicals involved in the stepwise, “wet chemistry” extraction procedures are dangerous to laboratory workers, time consuming, and expensive. Consequently, forage researchers and nutritionists have developed alternative analysis techniques to mitigate these issues. In the early 1980s, scientists began measuring near infrared reflectance of known forage samples and found good relationships between the reflectance data and many of the forage quality metrics. Near infrared light in the 1100 to 2500 nm wavelength bands reflects in a known and repeatable way when it contacts compounds that contain hydrogen bonds to carbon, nitrogen, and oxygen. Consequently, complex carbon- and nitrogen-containing compounds (e.g., NDF, ADF, lignin, CP, etc.) can be accurately and precisely estimated by measuring the near infrared reflectance spectra. Using these relationships, researchers and engineers developed near infrared reflectance spectroscopy (NIRS) equipment and software that provide a safe, time-efficient, and cost-effective alternative to wet chemistry extraction methods (Figure 5).

Figure 5. Analyses that once took numerous hours in the laboratory can now be performed in seconds using near infrared
(NIR) spectroscopy. Though wet chemistry methods are still performed to check the calibration of the NIR system, the
main forage quality measurements can now be accurately made at relatively low cost. Figure 5. Analyses that once took numerous hours in the laboratory can now be performed in seconds using near infrared (NIR) spectroscopy. Though wet chemistry methods are still performed to check the calibration of the NIR system, the main forage quality measurements can now be accurately made at relatively low cost.

Additionally, the NIRS technology does not cause a sample to be destroyed. This enables researchers at multiple laboratories to analyze the exact same sample. Consequently, researchers can develop, refine, and verify calibration equations for new forage species or new metrics of nutritive value. For example, the NIRS system enables laboratory technicians to identify outliers (samples that do not fit the calibration well), which can be analyzed with wet chemistry and included in the calibration equation to make the equation more robust. In this same way, the NIRS Forage and Feed Testing Consortium continually refines a number of standardized equations and provides them to forage and feed testing laboratories. The non-destructive nature of NIRS also allows laboratories to use standard samples to conduct quality assurance procedures, which ensures accuracy and precision in their results. The National Forage Testing Association (NFTA) coordinates a certification process that conducts random tests of their member laboratorie

Status and Revision History
Published on Jan 21, 2014
Reviewed on Mar 28, 2017