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Forage Quality and Its Effect
on Profitability...
It's More Than
You May Think |
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The key to optimum milk production and higher
profitability can be found in forage quality. Most dairy producers
realize, to some extent, the impact that forage quality has on
milk production and income over feed cost. Unfortunately, dairy
producers do not set a goal of harvesting and storing high-quality
forage often enough. In most cases, forage crop growers are forced
to make a decision between yield and quality and the incorrect
assumption is that higher yields per cutting provide more profit.
Actually, higher yields of forage usually equate to more mature
forage.
Mature forages always contain more fiber and less energy. Energy
is inversely related to the amount of ADF in the forage.
Additionally, mature forages contain more neutral detergent fiber
(NDF), which is inversely related to dry matter intake. As forages
mature, cows consume less dry matter because of rumen fill. Not
only are mature forages lower in energy, consumption of mature
forages is also lower. Consequently, energy intake is much lower
compared to feeding less mature forages. As milk production levels
rise, forage energy level becomes more critical because the
levels of starch and fat that can be added to the ration are
limited. When forage quality is poor, more grain (concentrate) is
fed. This practice is expensive for two reasons.
• Feeding more grain costs more than feeding
high-quality forage.
• Cows on high-grain rations are more susceptible to
acidosis, laminitis,
reduced milk fat, reduced intake,
and, ultimately, reduced production.
The income over feed cost of high starch rations (>42% NFC) is
low. Besides reducing milk protein percentage, feeding fat levels
over 6% of the ration dry matter can significantly reduce fiber
digestibility and rumen health. The bottom line is feeding extra
grain with high levels of fat or starch cannot overcome poor
forage quality.
When to Cut Forage for Maximum
Profitability
Optimal forage quality is best predicted by using NDF. For
alfalfa, 40% NDF for dry hay and 45% NDF for haylage is generally
considered ideal. Some recent research has shown that forage
quality can be predicted from plant height and maximum stage of
maturity. Growing degree days (gdd) can also be used to predict
the time in spring when forage will reach 40% or 45% NDF. Two
recent reports have shown that to achieve 40% NDF, 700 gdd are
required in the spring. In these studies, gdd were counted after
the ambient temperature reached 41 °F for five consecutive days.
Predicting ADF and NDF
A procedure for predicting ADF and NDF using the PEAQ (predictive
equations for alfalfa quality) method (see
Table 1) can be useful when making a judgment on forage
quality in the field. Validation of these equations using NIR and
chemical values in Wisconsin have been positive. In fact, the
values were shown to be as accurate the accuracy of this
technique, at least five samples should be taken and ADF and NDF
calculated and then averaged. Although PEAQ were designed to
predict fiber levels in predominately pure alfalfa stands, the
same concept applies to all forages.
Effect on Profitability
Next, the actual loss in profitability due to
delayed harvest (when dry hay is greater than 40% NDF and haylage
is greater than 45% NDF) can be approximated. Predicting milk
production loss from poorer quality forage can be accomplished by
estimating dry matter intake (DMI). One must assume that forage
DMI (as a percent of body weight) can be calculated using 120/NDF%.
The expected increase in total ration pounds of DM could be
approximated using:
[3.0* - (calculated forage DMI)] x (% this forage represents in
ration DM/100) x (body weight/100) = pounds of DM expected
increase in DMI.
*3.0 % of body weight intake assumed with good-quality forage.
The expected increase in milk production from cutting less mature
hay or haylage can then be approximated by assuming that for each
pound increase in DM, cows will increase milk production by two
lb. The potential loss in milk income from feeding poorer quality
forage can also be calculated and is illustrated in
Table 2.
How Silage Inoculants can
Improve Profitability
While harvesting high-quality forages is a primary goal, the use
of a research-proven inoculant can enhance forage value. In 1998,
Kung summarized 14 research trials and found cows fed forages
treated with silage inoculants containing Lactobacillus
plantarum MTD/l provided more milk per head daily
compared to cows fed non-inoculated forages.
Improving Forage Digestibility with Feed
Additives
Feed additives have also been used to improve the
digestibility of forage fiber. Cobalt glucoheptanate has shown
varying results, but seems to improve fiber digestibility by
impacting the microbial population in the rumen. Because cobalt is
a necessary nutrient for rumen microbes and glucoheptanate makes
the mineral compound more soluble in the rumen, cellulolytic
bacteria can be increased. Some studies have shown a 15 to 20%
improvement in fiber digestibility with cobalt glucoheptanate.
Research with rumen stable enzymes has also shown some benefits by
improving fiber digestion in the rumen. These enzymes increase the
number of cellulolytic bacteria which improves forage
digestibility. The key to using enzymes to increase fiber
digestibility is that they are not degraded in the rumen. Enzymes
such as cellulase and hemicellulase derived from fungal extracts
seemed to have had the best rumen stability in these trials.
Summary Forage quality has a major impact on milk production and
income over feed costs. Taking full advantage of forage quality
and fiber digestibility can have a major impact on farm
profitability. The ability to predict when forage should be
harvested for maximum profitability would be extremely beneficial
to a producer. PEAQ equations to predict fiber levels in alfalfa
can be beneficial in determining harvest date.
Table 1
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Procedure for Predicting ADF and OF using PEAQ |
1.
Five samples are taken for every 30 acres to be cut for alfalfa
hay or haylage.
Each sample should contain 100 stems.
2. The length of the tallest stems in each sample is measured
to the tip (inches).
3. For the most mature stem in each sample, a maturity index (1
to 7) is assigned:
1 = stems less than 6 inches in length, no buds or
flowers.
2 = stems 6-12 inches in
length, no buds or flowers.
3 = stems greater than 12 inches in length, no
buds or flowers.
4 = stems with 1-2 nodes with visible buds, no
flowers.
5 = stems with more than 2 nodes with visible
buds, no open flowers.
6 = stems with 1 node, at least 1 open flower.
7 = stems with 2 or more nodes, at least 1 open
flower.
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4. ADF and NDF are calculated
using the following equations:
• NDF = 16.89 +
(0.69 x height) + (0.81 x maturity index).
• ADF = 11.57 +
(0.53 x height) + (0.79 x maturity index).
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Table
2
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Effect of Haylage Quality on Profitability: An Example |
Haylage has an NDF
either analyzed or predicted from the PEAQ (predictive equations
for alfalfa quality) equations of 50% on a dry matter basis. This
forage is 30% of the ration dry matter and average cow body weight
is 1350 lb.
120/(50) = 2.4%
of body weight forage DMI
(3.0 - 2.4) x
(30/100) x (1350/100) = 2.43 lb of milk lost from a difference of
five percentage
units in NDF.
Therefore, at a milk price of $0.14/Ib, the loss is $0.34 per
cow per day. For a 200-cow herd where the haylage is 30% of the
ration dry matter, the loss in milk income is approximately
$25,000 per year. These calculations do not take into account
losses from feeding energy from added concentrate or from the cost
of losing 3rd or 4th cutting forages.
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