BOARD OF DIRECTORS: Bryce Larson-President, Cleveland; Mike Mleziva-Vice President, New Franken; Dan Undersander-Exec Secretary-Treasurer, Madison; Ken Barnett Wausau; Bob Bosold Eau Claire; Mike Costello Malone; Robert Eder New London; Joe Holschbach Manitowoc; Bill Kautz Madison; Greg Kerr River Falls; Doug Mueller Fall Creek; Mahlon Peterson Altoona; Patrick Sturz Eau Claire; Ex-officio: Dennis Cosgrove River Falls and Keith Kelling Madison.

 

 

Volume 21, Number 3, September, 1997

 

reetings! Welcome to the Fall Forager. This summer has been an interesting one for forage production. Cool conditions delayed first crop, and while tonnage was high where rainfall was adequate, quality was lower than desired. Prolonged rains in much of the state made harvest of second crop a real challenge. This could once again lead to high hay prices this winter. Now is the time to consider your needs and move to purchase hay if need be.

 

Potato leafhoppers were a problem over much of the state this year. Despite leafhopper pressure nearly every year, less than two percent of our fields are treated for this insect pest. As leafhoppers can cause severe yield and quality losses, a good scouting program to help deter-

 

mine when, and if, spraying is needed may be a profitable investment. Potato leafhopper resistant alfalfa varieties are available now. Check the 1997 WFC Symposium Proceedings for more information and stayed tuned. The "second generation" leafhopper resistant alfalfas are showing even greater levels of resistance than those currently available. They may prove to be more economically favorable than the current varieties which have shown some yield decrease when compared to non-resistant, sprayed varieties.

 

Congratulations and thank you to all involved in the 1997 WFC Forage Expo. The event was very well organized and everything ran smoothly. There were over 600 people for the two-day event. Thanks to the Strebe and Eder family for hosting the Expo this year.

 

 

 

TABLE OF CONTENTS
Pages 2 & 3 The Impact Of Autotoxicity
Pages 3, 4, 5 & 6 Evolving Forage Quality Concepts
Pages 6 & 7 Forage Intake And Quality Needs Of Dairy Cows  

At Several Milk Production Levels On Pasture

Page 7 Hay Supplies And Haylistings
Page 8 1997 Proceedings Available
 

 

 

 
THE IMPACT OF AUTOTOXICITY

 

Over the past several years, many research projects, including some in Wisconsin have shown yield reductions associated with alfalfa autotoxicity. A frequently asked questions is "Do the yield reductions in the seeding year carryover into subsequent years?" Jerry Nelson from the University of Missouri presented a paper at the Central Alfalfa Improvement Conference held in Lacrosse in July. In that talk, he addressed this question. Part of his talk is reproduced here:

 

Introduction. Most autotoxicity research has focused on establishing alfalfa after alfalfa. The evidence from laboratory studies is clear that chemical substances extracted from alfalfa plant parts have a negative effect on seed germination and seedling growth. Reduced seedling growth is also seen as stunting in the field and has been researched in some short term studies. Now it is becoming apparent the effect may be long lasting.

 

Seedling Establishment. Stand failure is the main factor considered in autotoxicity, especially when trying to thicken a stand by interseeding or when reseeding an old stand that has been killed by tillage or a herbicide. Usually experiments are conducted by altering the time interval between killing an old alfalfa stand and reseeding the field. Generally, the field results show a clear time-dependence with the poorest stands resulting with the shortest interval between killing the old plants and reseeding. The length of time recommended before reseeding is not consistent from state to state. Factors to consider in explaining these differences are the amount of autotoxic chemicals in the soil, and its rate of leaching or microbial detoxification.

 

Alfalfa root growth is more sensitive to the autotoxic chemical than is seed germination. Many field studies evaluated seeding density and clearly showed an autotoxic effect, perhaps due to relatively high concentrations of the chemical. In cases with low concentrations, the plant density may appear adequate, i.e., at lower concentrations the germination and emergence are sufficient, but plants are stunted and yield is reduced. If the plants die later due to stress such as drought, it is too late to repeat a spring seeding. If the stand survives and is deemed acceptable, unless there is a control in the field, most farmers and some researchers do not notice the subtle effect of autotoxicity on yield. Thus, it is important that a proper check treatment be used in the experiment for comparison. This could be fallow or a crop such as corn or Kentucky Bluegrass that does not show allelopathy on alfalfa.

 

We conducted experiments at three separate locations with alfalfa being no-till spring seeded after rotation intervals of fallow of up to 18 months after the old stand was killed. We found plant density was reduced for the two-week and three-week rotation interval, but not for longer intervals. In all cases, the stand appeared acceptable and would not have been replaced. But, yields over the next three years showed a different pattern as yields were lower than the 18-month control for treatments where the time interval was six months or less.

 

Yield Reduction. There is some disparity in results, but most studies show a reduction in yield during the seeding year due to autotoxicity that is closely associated with reduced plant density. Miller also showed the reduction carried over to the second year. We evaluated the response over three years and found the reduction is not overcome. Similarly, the decrease in plant density over time remained rank ordered according to the initial seedling density. Most seeding rate studies indicate that alfalfa yields are not dependent on plant density above a minimum density, with the implication that crowns of plants at low densities produce more shoots to keep shoot density high. Thus, many studies imply that the reduced stands resulting from autotoxicity will grow out of the problem. This may not be the case.

 

Our observations suggest that seedlings that persist through autotoxic growth reduction develop a "systematic memory" that continues into the production years. This is visually most noticeable during early regrowth after cutting where plants regrow more slowly in treatments with short intervals between killing the old stand and reseeding. After three years, when we excavated plants from short- and long-rotation intervals, we found plants affected by the autotoxic chemicals were more branch-rooted. Our hypothesis is that during early exposure of these plants to the autotoxic chemicals the reduced root growth was associated with alteration or death of the root apex, but the plants survived by developing branch roots. Branch-rooted plants, especially when a stress caused the branching, may not be as productive as tap-rooted plants thus allowing the morphological change to serve as a "permanent memory" for the damaged plants.

Stand Persistence. We could find virtually no data on the effect of autotoxicity on long-term stand persistence. Research has indicated reduced stands in the short term. In our studies, we found the ranking for plant density of treatments remained similar through both the short-term and long-term thinning stages. Ironically, it appeared both the early rapid thinning and the later slow thinning were largely independent from autotoxicity as the short-rotation treatment consistently lost plants at the same basic rate as the longest rotation treatment. This indicates the length of stand life may also be shortened by autotoxicity due to the reduced initial plant density, a further consideration when calculating the long-term economic loss due to autotoxicity.

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EVOLVING FORAGE QUALITY CONCEPTS

 

As we begin our discussion of forage quality concepts, we should remember why we are measuring forage quality in feedstuffs.

 

The first reason for measuring forage quality is to balance rations to optimize animal growth, or production of meat or milk. This generally means estimating two parameters: a) estimates of available (digestible) energy or nutrient, and b) estimates of intake. Here we must be aware that the world is changing and what was good enough 20 years ago is not good enough today. As production levels of milk, in particular, have risen, properly balanced rations have become more important than ever before. These higher production levels also mean that we are pushing the milking dairy cow to the edge where factors, not previously of great concern, can now cause the cow to develop health problems and result in lost production. Thus, when balancing rations, we are not only attempting to optimize animal production, but also to avoid animal health problems by such considerations as feeding adequate fiber and avoiding excess soluble protein.

 

The second reason for forage analysis is to develop least cost rations for the animals we are feeding. The more accurately we can characterize the availability of energy, minerals and other metabolites in the forage, the better we can match forage to the appropriate animal category, and the more we can match least cost grain and other supplements to the forage being fed.

 

The third reason for forage analysis is to determine the value of hay for marketing. There is value in hay quality when being fed, and there is cost to the production of quality hay; therefore, the seller should share in the value of quality hay. This value of quality is reflected in many hay markets. However, it is important that the basis of quality pricing have a foundation in animal feeding. There is the tendency in marketing to think that more is better, i.e. 27 percent crude protein alfalfa is better than 24 percent crude protein, which is not always the case as far as the animal is concerned. Pricing considerations for hay quality should be based on animal responses.

 

In the past, and still in some regions of the U.S., hay was/is evaluated visually. Farmers look for green color, leafiness and texture. This evaluation can certainly separate hay into rough categories of good, average and bad. But, it certainly is not adequate for determining the feeding value of the hay. While surveys have indicated that the single most important characteristic for rejection of hay lots on delivery is color, all nutritionists agree that color has no relationship to the nutritional value of the hay beyond determination of spoilage. First, green color appears differently to different individuals. Second, the greenness of a hay depends on the light under which the hay is viewed, i.e., the color would appear different on a cloudy day than on a sunny day or in a barn vs. outside. The color relates to the chlorophyll content, which does not relate to any animal performance parameter.

 

Visual rating of leafiness too can be an indication of quality hay, but this too can be misleading because under the best conditions, around 50 percent of alfalfa is stem, and stem digestibility can vary greatly and then affect the overall nutritional value of the hay.

 

Texture is usually a secondary ‘visual’ characteristic. It certainly has some effect on the percentage of refusal in the feed bunk; though this becomes questionable if the hay is mixed in a Total Mixed Ration. Texture has little relationship to nutritional quality of the forage. Thus none of the visual characteristics have a significant relationship to the value of the hay to the animal being fed.

 

The best way to determine the value of a forage is to do a feeding trial where over a period of three to four weeks forage is weighed and fed to several animals of the desired class (i.e. milking cow, stocker or growing animal), and manure and urine are collected and weighted. The dry weight of the manure divided by the dry weight of the forage fed is the apparent digestibility of the forage. Obviously, this is too time consuming and expensive for determining nutritive value of individual forages. However, it is important to remember that all other forage analysis values we use are an attempt to estimate values derived from such feeding trials.

 

Among the first estimate of forage nutritive value was the crude fiber system developed in the 1890’s as an attempt to separate fiber from more readily digestible portions of the forage. The problem with this system, and the modified crude fiber system, is that varying amounts of fiber fractions were dissolved out in the non-fiber fraction. Thus, there was no structural or biochemical relationship to the crude fiber value. Since each cell wall fraction digests in the rumen at a different rate and to a different extent, the crude fiber might correlate well with digestibility of a similar sample type and from a range of environmental conditions, but would not predict animal performance accurately from samples outside the range of conditions used to develop the relationship.

 

The next advance in fiber analysis was the development of the detergent fiber system by Goering and Van Soest in the 1970’s. This system estimated two fiber fractions in forage. Neutral detergent fiber (NDF) was related to the total cell wall and included hemicellulose, cellulose, lignin and ash. The term has been used to estimate how much an animal will consume (intake). The second fraction, acid detergent fiber (ADF), contained all of the above fractions except hemicellulose. Hemicellulose is rapidly digestible in the rumen. Therefore, the fiber fractions remaining in ADF are often correlated with digestibility and used to calculate total digestible nutrients (TDN). This relationship assumes that all cell walls digest at the same rate. While the correlation has historically been reasonably good within a forage species, the relationship changes as forage changes, and as we are finding with higher producing herds, the relationship also varies among years indicating an environmental effect on digestibility of the cell wall.

 

TDN and net energy of lactation (NEL) are simply calculated values that are derived from regressions of the fiber analysis with animal performance data. Thus, each researcher with a different data set gets a slightly different equation. The different TDN equations mean that the same forage would have different TDN values depending on which state/regional equation was used to calculate TDN.

 

A number of researchers have used rumen microbes to determine digestibility as an estimate of forage quality. The advantage of this is that rumen microbes are actually digesting the forage. Digestibility may be determined by adding forage and rumen microbe to a test tube which is incubated for a fixed time period (in vitro), or putting the forage in a nylon bag and suspending the bag in the rumen of a cow for a fixed time (in situ or in sachu). Results of this system have higher correlations with animal performance than fiber analysis because it detects variations in fiber digestion that fiber analysis does not detect. However, this system is seldom used outside of research because of the expense and problems with run to run, (and therefore, laboratory) variation in results. There is an additional problem in that digestibility is related to the rumen retention time. Animals at higher feed levels, such as milking cows, have shorter rumen retention times than animals at lower feed levels, such as growing heifers. Thus, digestibility would be different for a milking cow than a growing heifer.

 

Now the potential exists to solve most of these problems through use of near infrared reflectance spectroscopy (NIRS). Near infrared reflectance spectroscopy reads organic bonds very accurately. Thus, chemical components, such as protein, starch, cellulose, etc., can be determined with greater than 98 percent agreement with wet chemistry. It is widely used in the grain industry to determine moisture and protein at grain terminals so that sellers can have an analysis at point and time of sale. This technology is also very applicable to forage analysis, though such applications are more difficult because we are generally looking at multiple chemical constituents, i.e. fiber, rather than a single component, such as protein or starch. The second problem is that early NIRS instruments and versions of software caused instrument to instrument variation in prediction from the same sample with the same equations. This problem has been solved by standardization of instruments for those laboratories with newer NIRS instruments. Near infrared reflectance spectroscopy can estimate digestibility of a forage. Thus, for laboratories with standardized instruments and common equations, we can now estimate digestibility accurately, repeatably and cost effectively.

 

The second problem of different rumen retention times and resulting different digestions can now be addressed by considering the rate of forage digestion. Different forages digest at different rates. When combining the different forage digestion rates with different animal retention (digestion) times, we find that the same forage may not be the best for all categories of animals. For example, as shown in figure 1, one forage (A) might be most digestible to a milking dairy cow (rumen retention time of 30 hours), while forage B might be most digestible to a growing heifer or beef steer (rumen retention time of 48 hours). This problem can now also be solved by measuring rate of digestion. By knowing the rate of digestion, along with the A fraction (total digestible), B fraction (particularly and slowly digestible) and C fraction (undigestible), we can calculate digestibility for any time period. This means that a dairy cows digestibility can be determined as well as one for heifers and dry cows. Again the expense of doing this in vitro or in situ is great, but such parameters can now be estimated by NIRS and will become available to producers.

 

Our discussion of forage analysis began with the age-old visual estimate of forage quality, went through fiber analysis, and ended with state-of-the-art determination of digestibility by NIRS. What future forage analysis do we see down the road? Of the nearly 30 parameters used in ration balancing, we currently only measure four (dry matter, ADF, NDF and crude protein) in standard forage analysis. Most of the other parameters could be measured. Many individuals are now working on some of these analyses. Additionally, we could potentially directly predict animal intake rather than estimating an estimator, and we could relate digestion directly to animal class/performance. These future changes in forage analysis will be necessary to balance rations for future high performing dairy animals.

 

Dan Undersander, UW-Forage Agronomist

 
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FORAGE INTAKE AND QUALITY NEEDS OF DAIRY COWS
AT SEVERAL MILK PRODUCTION LEVELS ON PASTURE

The following table gives some parameters from balanced rations of dairy cows at several levels of milk production. We have calculated the annual energy requirement of a cow at each level of milk production. Then we calculated three levels of grain fed per day of lactation to meet the energy requirement, along with the forage intake per year and day. The forage NDF column includes the maximum forage NDF content that would allow the grazing animal to meet its intake needs. The comments column tells whether or not the ration is possible. ‘FQ not limit’ indicates that the ration is possible, and that forage quality is not a limiting factor as indicated by the maximum forage NDF allowable in the ration. These comments are based on the NDF of the ration that would be required to allow adequate animal intake of forage to meet the energy need above grain (if it is fed), and the NDF intake as a percent of body weight required to maintain desired animal performance.

 

The table shows that until we get above 15,000 lbs milk, forage quality is not a major limitation in milk production, and even at this point, we only need to maintain an average NDF of 43 percent or less to allow adequate forage intake (13,200 lbs) to meet the animal needs. This means, that for 15,000 lbs of milk or less, grain is not required for cattle on pasture. Grain simply reduces the animal forage intake and substitutes for energy in the forage. Grain supplementation of milk cows producing less than 15,000 milk should be done carefully, or it can actually reduce milk production as cows go off forage. However, grain can be used to stretch the pasture in times of forage shortage such as drought.

 

The table also indicates that 20,000 lbs of milk is possible on a moderate quality pasture diet with 11.2 lbs grain daily. It is not feasible to produce this level of milk with less grain because the NDF intake would have to exceed 1.4 percent of body weight. Increasing grain above 11.2 lbs/day at the same forage fiber level simply reduces the forage intake. This level of milk production on pasture can be a very cost effect and manageable system as grain is relatively inexpensive compared to milk prices. Up to 7.5 lbs grain can be fed at one time with little fear of acidosis or other animal health problems. This means that many dairymen can easily feed 12 to 15 lbs per day with a grain feeding at each milking.

 

It is also possible to produce up to 25,000 lbs of milk on pasture with 26.3 lbs grain fed daily. This does not require a particularly high quality pasture. In fact, the fiber must remain high to give the animal adequate fiber with its high grain intake. Some Wisconsin farmers have approached this level of milk production on pasture.

 

In general, the table indicates that a milking dairy cow should have a forage intake of approximately 5 to 5.5 tons annually with the appropriate grain to obtain the desired herd performance. It also indicates that moderate quality forage is preferred to provide adequate fiber for animals receiving some grain.

 
 
Table 1. Effect of grain level on forage intake and quality needs of dairy cows at several milk production levels.
Milk, lb/lact Mcal  

energy/yr

Grain level % lact NEI grain/day lb/d of lact lb forage/yr lb forage /day Forage NDF Comments
10,000
7194
0
0.0
10737
31
54
FQ not limit
10,000
7194
30
7.4
7870
22
73
FQ not limit
10,000
7194
60
14.8
5002
13
120
FQ not limit
15,000
8844
0
0.0
13200
39
43
Possible
15,000
8844
30
9.3
9594
28
57
FQ not limit
15,000
8844
60
18.6
5987
16
92
FQ not limit
20,000
10494
0
0.0
15663
47
35
Not feasible
20,000
10494
30
11.2
11318
33
46
Possible
20,000
10494
60
22.5
6973
19
74
FQ not limit
25,000
12144
0
0.0
18125
56
30
Not feasible
25,000
12144
30
13.1
13041
39
39
Not feasible
25,000
12144
60
26.3
7958
22
61
Possible
30,000
13794
0
0.0
20588
64
26
Not feasible
30,000
13794
30
15.0
14765
45
34
Not feasible
30,000
13794
60
30.1
8943
25
52 Possible
 

Dr. Dan Undersander and Dr. Dave Combs, University of Wisconsin

Forage Quality is not likely to be limiting as the ration requires high NDF.

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HAY SUPPLIES AND HAYLISTINGS
 

Wisconsin is going to have marginal hay and haylage supplies this year due to record low carryover from last year and poor growth conditions this year. First cutting alfalfa was down about 40 percent because of the cool, dry spring. Second cutting was rained on in much of the state. Western Minnesota, northwestern Wisconsin and Pennsylvania are having a drought. Nebraska had significant winterkill, and South Dakota had flooding that wiped out stands (if they weren't killed by ice sheeting). I think hay will be very short this year and high priced.

 

I suggest two alternatives for farmers short on hay: first, consider harvesting any grass acreage available (30 to 40 lb nitrogen around August 1 to 15 would have greatly increased yield); second, harvest corn for silage and buy corn grain. It appears that corn grain will be less expensive than forage.

For those who need to buy hay, the Great Lakes Haylist is no longer operating. It was just too expensive to maintain for the number of farmers that were using it. Minnesota has a haylist at http://www.mes.umn.edu/Haylist/hay_srch.html?userid=0 that we will be supporting. I would encourage you to check this site either to buy or sell hay.

 

Dan Undersander - UW-Madison

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1997 PROCEEDINGS AVAILABLE

 

The 1997 Proceedings from our Annual Meeting in January are now available to members at a reduced cost of $6.00 which includes shipping and handling. If you are interested in receiving a copy of the Proceedings, please send your name and address along with a check for $6.00 to:

 

Wisconsin Forage Council
813 W. Lexington Pkwy
DeForest, WI 53532

 

 
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