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NEW YORK STATE CORN SILAGE HYBRID TRIALS – 2016

Joseph Lawrence1, Thomas Overton1, Margaret Smith2, Michael Van Amburgh1, Allison Lawton1, Sherrie Norman2, Keith Payne2, Dan Fisher2
1
Department of Animal Science, PRO-DAIRY; 2Plant Breeding and Genetics

In 2016, we were pleased to be able to reinstate the corn silage hybrid testing program at Cornell. The reinstatement of the New York trials was made possible with support from dairy producers, participating seed companies, Cornell University, the New York Farm Viability Institute, and the Cornell University Agricultural Experiment Station.

Twenty-nine corn silage hybrids (ranging from 84 day to 107 day relative maturity [RM]) were tested at two locations in NY in 2016. Hybrids were planted at the Musgrave Research Farm in Aurora (Cayuga Co.) and at Greenwood Farms in Madrid (St. Lawrence Co.). Seed companies were invited to submit hybrids for both sites for a fee. The purpose of this trial is to provide unbiased, local data to aid in producers’ decision making and consultants’ recommendations.  Detailed results can be found in the full report at (https://scs.cals.cornell.edu/extension-outreach/field-crop-production/variety-trials#corn-silage). Here we will discuss the main points of the 2016 trials.

All hybrids were planted at 34,000 plants/acre. The Aurora site was planted on May 12th and the Madrid site was planted on May 17th. Hybrids were planted in a randomized complete block design, with 4 replications, by 5-day maturity groups.

The Aurora site was harvested on three dates, according to maturity group. Early (90-95 day) corn was harvested on August 29th, medium (96-100 day) corn was harvested on September 1st, and late (101-105 day) corn was harvested on September 7th. At the Madrid location, all maturity groups were harvested on September 13th. The goal was to harvest all hybrids at about 65% (±3%) moisture.

Overall growing degree day accumulation was above average across the state while rainfall was extremely variable.  Both locations in this trial were below average in total rainfall (Table 1) but the patterns in the rain events made significant differences in the crop’s performance.

A significant change to the program in 2016 was the way in which hybrids were evaluated for forage quality.  For each hybrid, the forage analysis results (four replicates) were applied to a typical New York higher corn silage-based diet utilizing the Cornell Net Carbohydrate and Protein System (CNCPS v. 6.5.5; Cornell University, Ithaca, NY) biology and dynamic model and were averaged by site. The diet was developed for a second lactation dairy cow to produce 100 pounds of milk per day with forage at ~60% of diet dry matter (DM) and corn silage ~70% of forage DM in a software platform (NDS Professional version 3.9.2.03, RUM&N Sas, Reggio Emilia, Italy), which utilizes the CNCPS biology.

This novel approach to hybrid evaluation allowed us to account for differences in dry matter intake (DMI) potential of the total ration based upon hybrid selection and is a more biologically robust representation compared to evaluating hybrids on a constant DMI basis.  The predictions made by the CNCPS biology were used to evaluate differences in intake potential and subsequent metabolizable energy (ME) and metabolizable protein (MP) allowable milk yield based upon the nutrient and digestibility characteristics of each hybrid. Only the ME allowable milk yield is reported as it was more limiting than MP allowable milk yield for all hybrids.

A season such as this provides an opportunity to evaluate hybrid performance under variable growing conditions. While more locations are always beneficial, the difference in growing conditions and performance at these two locations provided some valuable insight into hybrid performance.  Figures 1 and 2 identify hybrids that performed above average in both crop yield and milk yield (top right quadrant) at each location. The hybrids performing above average at both locations are more likely to maintain a high level of performance across varying growing conditions.

Due to very different growing conditions experienced at the two sites, there was a large difference in the undigested neutral detergent fiber (uNDF) overall mean values, which translated into large differences in the predicted milk yield when corrected for uNDF at the 240 hour time point (uNDF240). The predicted ME allowable milk yield on a DMI equivalent was not as variable as the predicted ME allowable milk yield on an uNDF240 equivalent. This would be expected when DMI of the total ration is allowed to vary to meet a constant uNDF240 intake. We also need to acknowledge that while this approach offers a sound method for comparing relative hybrid performance, the absolute differences in predicted milk yield are predicted values from the model and are likely greater than the actual differences in milk yield expected in a herd of cows.

Based on the overall mean for predicted milk yield on an uNDF240 equivalent, corn silages performed exceptionally better at the Aurora site than at the Madrid site. However, the overall mean corn silage yield, when adjusted to 65% moisture, was drastically lower at Aurora than at Madrid. Due to higher fiber digestibility content in the hybrids grown at Aurora, it is predicted that dairy cows will consume more feed compared to the feed produced at Madrid, as reflected in the adjusted total mixed ration (TMR) DMI. With lower yields and higher predicted DMI at Aurora, dairy farmers feeding corn silages grown under these environmental conditions are more likely to be constrained by inventory for the following year compared to farmers feeding corn silages grown at Madrid.

The locations of our trials underlined the highly variable rainfall patterns experienced across NY state in 2016 and highlighted how critical timing of rainfall can be, rather than solely total rainfall.

In general, the eastern part of NY state experienced adequate rainfall with amounts diminishing as you moved west across the state, though there were large variations within regions. Producers in areas with adequate rainfall reported average to well above average yields, while other areas ranged from below average yields to complete crop failure. As was the case at our Aurora location, August rains in some locations helped save the crop from complete failure, though it was clearly still below average.

The impact of weather patterns and growing conditions on key factors, notably fiber digestibility and starch, influencing forage quality and milk producing potential on these hybrids was very evident when comparing the differences in crop yield and predicted milk yield across the two trial locations (Figures 1 and 2).

Figure 1. Relationship between silage yield and milk production potential at Madrid, NY. Hybrids located in the top right quadrant were above the overall mean for both crop yield and milk production potential and are considered good performers. Hybrids located in the bottom left quadrant were below the mean for yield and milk production potential. Hybrids in the top left quadrant were below the mean for yield and above the mean for milk production potential and hybrids in the bottom right quadrant were above the mean for yield and below the mean for milk production potential. Hybrids that were above average for crop and milk yield at both locations are marked and noted in the legend.

Figure 2. Relationship between silage yield and milk production potential at Aurora, NY. Hybrids located in the top right quadrant were above the overall mean for crop yield and milk production potential and are considered good performers. Hybrids in the bottom left quadrant were below the mean for yield and milk production potential. Hybrids located in the top left quadrant were below the mean for yield and above the mean for milk production potential and hybrids located in the bottom right quadrant were above the mean for yield and below the mean for milk production potential. Hybrids that were above average for crop and milk yield at both locations are marked and noted in the legend.

Predicting milk yield with the use of the CNCPS model provides dairy farmers and dairy nutritionists in NY with a more applicable approach for evaluating different corn silage hybrids. The predicted ME allowable milk yield on an uNDF240 equivalent reflects how much DMI the cow might be able to consume based on rumen fill and passage rate. These results demonstrate how crucial it is to adjust rations based on the predicted DMI rather than replacing corn silages on a DM equivalent basis.

ACKNOWLEDGEMENTS

We thank the seed companies that participated in 2016 for their collaboration. We urge all seed companies to participate in our corn silage testing program in 2017 so we can provide the best information under New York growing conditions to our New York dairy producers.

We thank Greenwood Dairy for their ongoing collaboration and support of the program; Paul Stachowski and Jeff Stayton at the Cornell Musgrave Research Farm, Aurora for their efforts during field operations; Greg Godwin, Kitty O’Neill, and Mike Hunter for assistance at harvest and Buzz Burhans and Ermanno Melli for providing us with the NDS software and technical assistance. We appreciate the guidance of Dr. Bill Cox, Dr. Jerry Cherney, Phil Atkins, and Ken Paddock in implementing the 2016 trials.

Additional financial support was provided by New York Farm Viability Institute and the Cornell University Agricultural Experiment Station.

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