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 as NIR values in one study. To improve 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/1 provided an average of 2.6 lb more milk per head daily compared to cows fed non-inoculated forages. In addition to an increase in milk production, these types of inoculants have shown 2% less forage dry matter loss and 0.5% increase in forage protein content. As forage protein increases, less supplemental protein is required. Table 3 provides an example of the economic benefit of improvements in milk production, silage dry matter preservation, and silage crude protein content derived from using a research-proven silage inoculant for a 200-head dairy herd.

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 and gdd can be beneficial in determining harvest date.