Two management decisions have been especially challenging. One challenge involves hybrid selection due to the numerous hybrid choices available to farmers. The other challenge involves timing of harvest to achieve the proper moisture to ensure adequate fermentation for preservation and storage. The interactions between forage yield and quality, genetics and environment make it difficult to properly time harvest.

Forage moisture cannot be visibly determined. Moisture measurement requires either time to dry the forage or the use of an NIR spectrophotometer. Prior to the 1970s, estimates of whole-plant moisture content in corn were frequently based on grain maturity. Grain moisture content varied with whole-plant moisture content in a predictable manner, so grain moisture content was suggested as an indicator of the proper stages of ensiling. In 1970, the Hybrid Corn Industrial Research Committee agreed upon black layer formation in the placentochalazal region of the corn kernel as the best indicator of physiological maturity in corn. The development of these dark layers is responsible for blocking the pathway of assimilate translocation into the kernel.

A common recommendation during the early 1970s was to harvest corn for silage when the black layer appears. However, grain moisture content varies from 30 to 42 percent at black layer appearance, and premature appearance of the black layer might occur due to cool weather. Kernel black layer has been reported to form at kernel moistures ranging from 15.4 to 75 percent. This large variation of whole-plant moisture content often means harvesting silage with a moisture content that is not optimal for proper ensiling. Another problem associated with using black layer is the inability to tell when it has formed.

Growing-degree days or calendar days accumulated after emergence or silking is another means of predicting date of maturity. Although the number of days from silking to maturity has been reported to be a constant time interval, hybrids vary as much as 25 days for the period. The growing-degree-day system does not take into account factors that influence plant growth and development such as soil moisture and mineral nutrition.

During the late 1980s, yield and quality of corn silage was found to be optimal between 0.5 to 0.25 kernel milk, and kernel milkline was suggested as a method for timing corn silage harvest. The milkline is a transitional layer, or boundary, between the solid and liquid matrices of the maturing endosperm. Kernel milkline position was demonstrated as a more reliable and useful visual indicator of grain maturity and proper moisture content for ensiling.

In Pennsylvania, however, corn plants were often drier than optimum for silage fermentation when corn reached the half milkline stage. They also stated that the milkline method was inconsistent for predicting forage moisture. By the late 1990s, the relationship between forage moisture and kernel milkline was highly variable among hybrids in different environments due to the ‘stay-green’ trait.

A visual indicator of crop development would enable rapid determination of maximum yield, quality or moisture content. Grain visual indicators of physiological maturity are used for corn, (Zea mays), sorghum, (Sorghum bicolor), pearl millet (Pennisetum americanum), soybean (Glycine max), oat (Avena sativa) and hard red spring wheat (Triticum aestivum). Other than kernel milkline monitoring, little work has been done to identify visual plant indicators for forage yield, quality and moisture.

It seems that kernel milkline and canopy monitoring should be useful for estimating the moisture status of corn for several reasons. First, disappearance of all kernel milk would represent kernel solidification and so translocation of liquid sucrose into a solid matrix would not be expected. Second, kernel milkline and canopy traits are visibly detectable, require no special instruments and no previous record keeping since the plant is integrating both genetic and environment into its dry-down pattern. Third, unlike black layer development, which is an endpoint, the movement of the milkline and the change in canopy green color and leaf inclination can be followed over a period of time. The objective of this article is to describe a system using visual plant indicators that reliably predict forage moisture for various ensiling structures.

Materials and methods
In the fall of 2003, a Wisconsin crop consultant, Steve Hoffman, suggested using both canopy (stover) and kernel development as a way to improve the prediction of forage moisture in a standing cornfield. In 2004 and 2005, every silage plot from all hybrid evaluation trials conducted by the Wisconsin Corn Agronomy program was rated for kernel and stover maturity. Experiments were conducted at Arlington, Chippewa Falls, Fond du Lac, Galesville, Lancaster, Marshfield, Rhinelander and Valders. A total of 232 hybrids were evaluated.

The experimental design was a randomized complete block with three replications at each location. All plots were measured for forage moisture by subsampling approximately 500 grams of corn forage after the plot was chopped, placing the forage in a cotton muslin bag and drying to uniform moisture at 140°F for seven days.

Kernel maturity rating is defined as the proportion of kernel milk remaining in the kernel:

Kernel maturity rating (range from 5 to 0) KMR = Kernel milk X 0.05

Stover maturity rating was calculated from a modified scale used for scoring lodging in small grains:

Stover maturity rating (range from 5 to 0) SMR = intensity score X area score X 0.1

An intensity (proportion of leaves inclined) score of 5 equals 100 percent of leaves inclined, 4 equals 75 percent of leaves inclined and ear leaf inclined, 3 equals 50 percent of leaves inclined and ear leaf declined, 2 equals 25 percent of leaves inclined and ear leaf declined and 1 equals 0 percent of leaves inclined (all leaves declined); area score is the proportion of green stalk and leaf tissue in a cross section of the crop canopy.

Combining both kernel and stover maturity ratings results in a visual maturity rating:

Visual maturity rating (range from 0 to 10) VMR = KMR + SMR

Treatment means were calculated from replicate data and analyzed using traditional regression techniques where forage moisture was regressed on kernel maturity rating, intensity score, green area score, stover maturity rating or visual maturity rating. The analysis was conducted using PROC MIXED. Location was considered a fixed effect.

Results and discussion
The relationship between forage moisture and kernel maturity rating was typical of what has been measured in the past. In this study, at 50 percent kernel milk (KMR = 2.5), forage moisture ranged from approximately 55 to 72 percent moisture. The trend line predicts 61 percent forage moisture when KMR = 2.5. The variability in this relationship is not acceptable, and kernel milkline should not be used by itself to time forage harvest.

The relationship between forage moisture and stover maturity rating was more variable than the relationship for kernel maturity rating. One group of data points was observed at forage moistures between 65 to 75 percent and stover maturity ratings between 1 and 0. No data points were observed between stover maturity ratings of 5 and 4 where the canopy is 80 to 100 percent green and most of the leaves are inclined. The trend line predicts forage moisture of 65 percent at a stover maturity rating of 2.5. The variability in this relationship is not acceptable and stover maturity rating should not be used by itself to time forage harvest.

Combining kernel and stover maturity ratings to calculate a visual maturity rating improved the relationship to forage moisture. A visual maturity rating of 5 predicted forage moisture of 63 percent, and the range was between 60 to 70 percent moisture. A visual maturity rating of 5 can be obtained when kernel milk has not moved (100 percent kernel milk) and the stover is brown or when the kernels are at black layer (0 percent kernel milk) and the stover is completely green with all leaves inclined.

The frequency of a correct harvest timing decision depended upon the silo structure. Structures with wider recommended moisture contents had a greater frequency of correct decisions (i.e., bag = 78 percent correct, oxygen-limiting = 85 percent correct). The system would correctly predict the appropriate moisture for all silo structures with a frequency of 56 percent.

Conclusion
Using the Wisconsin visual maturity rating system for corn silage improves the success of timing harvest at the proper moisture, but there is still a high frequency of wrong decisions. A correct decision would be made 68 to 85 percent of the time depending upon the silo structure. Taking the time to harvest a few plants, then chopping and drying a subsample, is still the best method for determining forage moisture and timing harvest for the silo structure. This visual maturity rating system might be best used as a trigger to begin moisture sampling the field. Visual maturity ratings may be useful in assessing overall field moisture variability. The rating can be quickly made and would supplement actual moisture measurements.  PD

References omitted due to space but are available upon request.

—From 2006 Silage for Dairy Farms Conference Proceedings

Joe Lauer, Professor, Department of Agronomy, University of Wisconsin

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