Final Report for LNE12-321
The Penn State Extension dairy team worked with 143 dairy operations consistently in the past five years to develop cash flow plans, monitor income over feed costs and cost of production. From this group, 50 farms were selected to test corn silage quality, fecal starch and milk urea nitrogen and evaluate its impact on farm profitability. Forty-four farms completed their actual cash flow plan for 2013 and sampled their corn silage in the fall of 2013 and spring of 2014. Producers responded to questions related to corn hybrids planted and feeding management practices.
Additional farms were added for 2014-2015, so thetotal number of farms completing the project was 56. Farms utilized between 1 to 13 different corn hybrids and the process for selection ranged from the cheapest seed to crop yields. Quality parameters such as neutral detergent fiber and starch digestibility did not routinely factor into the decision process.
Farms incorporating best feeding and cropping management practices showed a 5.8 pound milk increase versus their counterparts. Over the two-year period, milk urea nitrogen and fecal starch levels consistently fell within recommended parameters and there was no association to forage quality or feeding management practices. Average changes in seven-hour starch digestibility fall to spring tended to increase for farms that had the same corn hybrid and same structure during the seasonal sampling period (M=6.5 SD=5.01), which is expected and illustrated in controlled research studies. However, this trend was not observed for farms that had either hybrid blends or that changed hybrid and or structure during the sampling period (M=1.8 SD=4.85). They had more varied changes in starch digestibility and were different than the same farms F(1,50) = 7.135, p=0.01.
Forage quality and quantity are the foundation for developing successful and profitable rations. Producers benefit from advisors that understand cropping, feeding and economics to help them make smarter decisions. There are opportunities for producers to examine more closely hybrid selection decisions and evaluate how quality parameters affect animal production and cash surplus.
According to the 2012 Census, Pennsylvania is home to 7,829 dairy operations with 6,122 farms ranging between 20 to 199 lactating cows. Based on USDA’s NASS report for 2014, 410,000 acres were planted for corn silage producing 8.2 million tons compared to haylage grown on 450,000 acres producing 2.8 million tons. Assuming these farms are on limited land base, producing and feeding forage of consistent quality and quantity is paramount. The extension dairy team has been working with several hundred herds for the past five years doing cash flow plans or income over feed cost analyses, and the majority of herds are feeding a high corn silage based ration. The assumption made by consultants and producers is that corn silage quality is very consistent compared to other crops like alfalfa and grass, which can change in quality throughout the growing season.
The two main objectives of this project were to:
- Build a participatory motivated, new capacity for farm-level economic analysis of feed best management practices by extending a cash flow planning tool and year end income statements to provide net cash flow break-even and cost of production effects of each best management practice.
- Develop a case study to support development and demonstration of the extended tools based on a best management practices focused on management of fecal starch and milk urea nitrogen as the barometers of how nutrients were being utilized by the cow.
Performance target: 20 dairy farm operators will use the eEtool to support evaluation, monitoring, and analysis of BMPs on their farms. This will lead to adjustment in conservation and nutrient management plans covering close to 2000 acres of field crops, 2000 cows annually yielding 1.5 million lbs of raw milk per year.
In 2010-2011 the extension dairy team conducted focus group discussions across all regions in Pennsylvania with large farms (>200 milk cows) and small farms (<200) to evaluate the issues most important to them. The major themes identified for education were business management, nutrient management and managing forages/crops.
In 2008-2009 Pennsylvania’s Center for Dairy Excellence conducted a dairy farm survey that resulted in a 22% response rate. Of the total, 65.9% of the respondents reported milking less than 80 cows. Nutrition was one of their top priority areas. In August 2014, 140 people attended a twilight meeting in the second largest dairy county in Pennsylvania and were surveyed on the topics of greatest interest; double cropping, forage and feed based education and business management ranked the highest. During the past five years similar themes still rank at the top for additional education.
Initial work focused on assessment of current status of use of feed management BMPs. The project first interviewed a small set of key informant farm managers to identfy vocabulary and practices. Based on these interviews, a survey instrument was developed and implemented for the participants in cash flow planning.
The project proceeded under the premise that consultants and managers that can evaluate the whole farm system are empowered to make decisions that can enhance profitability on farms. Results from earlier Penn State Extension dairy team work revealed substantial opportunities to improve decisions based on cropping, feeding and financials. The dairies with the lowest fiber digestibility (46.97% of neutral detergent fiber) on their corn silage fed the highest amounts, utilized the most small grain silage and adjusted rations to show the highest cash surplus per cow. The farms with the highest fiber digestibility on their silage (57.74% of neutral detergent fiber) had the lowest cash surplus per cow. They fed the lowest amount of corn silage and were the heaviest feeders of alfalfa silage. The producers with the highest cash surplus have the opportunity to progress if forage quality was improved and the lowest cash surplus herds have the opportunity to improve if they can adjust forage inventory and utilize alternative cropping strategies.
To identify opportunities to manage fiber digestibility and starch intake, the case study approach was pursued. The Penn State Extension dairy team has worked with 143 dairy operations consistently in the past five years to develop cash flow plans, monitor income over feed costs and cost of production. From this group, 50 farms were selected to test corn silage quality, fecal starch and milk urea nitrogen and evaluate its impact on farm profitability.
Forty-four farms completed their actual cash flow plan for 2013 and sampled their corn silage in the fall of 2013 and spring of 2014. Producers responded to questions related to corn hybrids planted and feeding management practices including silage analysis, fecal starch, and milk urea nitrogen monitoring. Additional farms were added for 2014-2015. The total number of farms completing the project was fifty-six. Farms utilized between 1 to 13 different corn hybrids and the process for selection ranged from the cheapest seed to crop yields. Quality parameters such as neutral detergent fiber and starch digestibility did not routinely factor into the decision process.
Operator survey showed that forty percent (n=184) of 2013 respondents implemented one or more management changes after creating a cash flow plan to help manage their business. Fifty-eight percent changed their cropping strategy and 23% of producers received lender approval for a loan.
Ninety-eight percent of 2013 participants (n=184) reported increased understanding of the cost to raise their own feeds. As a result:
- 58% changed their cropping strategy to reflect discussion with their educators
- 23% of 2013 producers received lender approval for a loan
In the first year of the project for the data collection relevant to the econTool and the envTool.
Best management practices related to feeding were evaluated. Corn silage quality, fecal starch and milk urea nitrogen were sampled to collect preliminary data on how forage quality and feed management impact the farm’s economics and potential nutrient excretion. A cash flow plan using both projected and actual numbers were collected for 2013, 2014 and 2015 (actuals will be collected in February 2016).
Forty-four farms in Pennsylvania were sampled twice between the fall of 2013 and the spring of 2014 for corn silage analyses, fecal starch and milk urea nitrogen. Using actual income and expense data, feed and crop costs ranged from an average of $10.04/cwt for farms with a breakeven milk price under $16.00/cwt to $11.44/cwt for farms averaging over $22.00/cwt breakeven milk price. Overall, farms with a lower breakeven milk price (≤$16.00/cwt) averaged $4.46/cwt cash surplus over the higher breakeven farms (≥$22.00/cwt). Farms that regularly monitor corn silage dry matters to drive ration formulation also saw benefits in higher test day milk production and lower breakeven milk price. The 29% of farms (n=38) that reported using batch weights and ration analysis to monitor dry matter intake (DMI) had a breakeven milk price of $19.87/cwt versus $21.25/cwt for the 18% that did not monitor DMI at all.
An unexpected result showed up in the corn silage analysis. Researchers from the University of Wisconsin have reported increases in starch digestibility over time. Evaluating our data we saw this approximately 1/3 of the time with the other third showing no change and the other third actually decreasing. In the first year of sampling fiber digestibility was measured only in the spring and we wanted to examine if changes were occurring fall to spring. Since milk urea nitrogen is a measure of how well the cows are utilizing nitrogen it was important to repeat the sampling again to evaluate a potential correlations with forage quality. A cropping management checklist was developed to capture more detail on how crops were management including the hybrids used, inoculants, measuring dry matter and particle size prior to ensiling.
During year 2 producers attended a cash flow workshop to review their projected versus actual numbers. Results will be presented in February and April 2016. The econTool was developed and is available at http://extension.psu.edu/animals/dairy/business-management/mobile-apps/farm-margin-tool-app This tool is being presented to consultants to use with their clientele.
During both years, in addition to sampling corn silage, milk was tested for milk urea nitrogen (MUN) and manure for fecal starch. This was a means to capture in black and white how the herds were performing based on forage quality and the formulated rations. The ideal standard for MUN is 8 to 12 mg/dl and fecal starch less than 3 percent on a dry matter basis. Samples were taken at the same time as the corn silage in the fall and spring of both years (2014/2015). The average across all herds for MUN was 11.7 mg/dl and fecal starch 3.4 percent on a dry matter basis. There were a few outliers but the herds as a whole were consistent in their results from year to year. This illustrated the rations being fed were on target for protein and carbohydrate nutrition and the production responses were a true reflection of management practices.
Farms incorporating best feeding and cropping management practices showed a 5.8 pound milk increase versus their counterparts. Over the two-year period milk urea nitrogen and fecal starch levels consistently fell within recommended parameters and there was no association to forage quality or feeding management practices. Average changes in seven-hour starch digestibility fall to spring tended to increase for farms that had the same corn hybrid and same structure during the seasonal sampling period (M=6.5 SD=5.01), which is expected and illustrated in controlled research studies. However, this trend was not observed for farms that had either hybrid blends or that changed hybrid and or structure during the sampling period (M=1.8 SD=4.85). They had more varied changes in starch digestibility and were different than the same farms F(1,50) = 7.135, p=0.01.
During the program years of 2013/2014 and 2014/2015, 1,576 producers and consultants attended workshops where the results of this project were presented. The farms that dropped out of the project the first year sold their operation. Sharing results from the first year, ten farms were eager to participate in the second year of the project for a total of 58 farms. In addition, consultants saw the value of tying together cropping, feeding and financial management and scheduled workshops for their producers to determine their breakeven cost of production and then have discussions on their cropping and feeding management practices. Over the same time period 695 producers and consultants got involved with first time cash flow plan analyses either through a workshop setting or by a presentation of basic dairy farm management.
Cash flow workshops and individual meetings were held with all producers the first year. The results from their cash flow plans as well as the sampling results were presented. Fourteen farms were added to the project the second year for a total of 60 farms. However, due to some farms going out of business or incomplete financial information was not forth coming, the project ended with 48 farms with complete financial and sample results.
Producers from the 2013/2014 time period were contacted to document what they had used from this project. Ninety-eight percent of 2013 participants reported increased understanding of the cost to raise their own feeds, 23% received lender approval for a loan, and 58% changed their cropping strategy to reflect discussion with their extension specialist. Producers from the 2014/2015 time period will be contacted in spring 2016 after their actual 2015 financial numbers are collected and analyzed.
In addition to face to face interactions with producers and consultants, several articles were written about the results from this project as they surfaced. Dairy $ense is a monthly web based article written about dairy herd management. Articles from December 2014 and April, June, and September 2015 referred to results from this project. Articles can be found at http://extension.psu.edu/animals/dairy/business-management/financial-tools/dairy-sense
Additional Project Outcomes
Impacts of Results/Outcomes
Dairy producers in the project were asked management questions related to ensiling and feeding. In 2013/2014 and 2014/2015, 44 and 46 producers responded respectively. Seventy-five to eighty-five percent of the producers said they fill their structures within 3 days of harvesting corn silage. A similar percentage indicated they monitor dry matter at ensiling. In 2014, sixty percent said they were checking particle size at ensiling and in 2015 eighty-five percent responded positively to this management practice. The project brought on ten additional farms and it is possible the new farms were responding favorably to that question. A much lower number, thirty percent, were ensiling at the proper dry matter for the particular structure. This low percentage could be related to weather conditions, labor or other factors that made this management practice challenging. Figure 4 shows the annual average milk production using the dairy herd improvement association (DHIA) data based on how producers responded to monitoring particle size pre-ensiling. The herds monitoring particle size showed significantly higher milk production compared to the herds not monitoring particle size.
Producers survey on their feeding management practices also showed substantial though variable use of practices. With the same number of producers responding, thirty percent stated they did not monitor dry matter intake. The Extension dairy team wanted to know how the seventy percent were determining intake. Between fifty to fifty-five percent use batch weights with the dry matter percent from the formulated ration. Only fifteen to eighteen percent use batch weights and the actual dry matter percent from the total mixed ration. Knowing the variability of forage dry matter, the formulated ration dry matters provide little more than an educated approximation to create feeding plans.
The project also evaluated how frequently dry matter was being monitored on high moisture ingredients. Thirty to thirty-five percent of producers monitor dry matter daily/weekly with a slightly higher number (forty percent) doing it monthly or as samples are submitted for analyses. Figure 5 illustrates the difference in annual average milk production comparing producers who test monthly/as submitted versus daily/weekly. There was a significant difference in milk production when dry matter is tested more frequently. These two practices are likely an indicator of good overall management that is contributing to higher animal performance.
Another area the team investigated was the amount of corn silage dry matter fed and if there were any commonalities related to the feed ingredients being used to compliment those diets. There was an equal distribution between farms that fed greater than or less than 19 pounds of corn silage dry matter. Herds feeding high corn silage diets tended to feed high levels of small grain silage, dry corn grain and liquid sugar. The low corn silage herds fed higher levels of alfalfa or grass forage and high moisture corn grain.
Best management practices were evaluated for both feeding and cropping practices (Figures 4 and 5). The herds checking particle size of their forages prior to ensiling showed a significantly higher milk production, which was reflected in both years. Similar results showed for feeding management where dry matters were daily/weekly versus monthly/as needed. This reflects more on the farms being good managers and paying attention to details versus the management practice per se. Once the 2015 actual financial data is completed an analysis will be conducted to examine if the farms with the improved production based on management practices also show the best breakeven cost of production.
Farms incorporating best feeding and cropping management practices showed a 5.8 pound milk increase versus their counterparts. Over the two year period milk urea nitrogen and fecal starch levels consistently fell within recommended parameters and there was no association to forage quality or feeding management practices. Average changes in seven-hour starch digestibility fall to spring tended to increase for farms that had the same corn hybrid and same structure during the seasonal sampling period (M=6.5 SD=5.01), which is expected and illustrated in controlled research studies. However, this trend was not observed for farms that had either hybrid blends or that changed hybrid and or structure during the sampling period (M=1.8 SD=4.85). They had more varied changes in starch digestibility and were different than the same farms F(1,50) = 7.135, p=0.01.
The second year of sample collection yielded similar results from the previous year on corn silage quality, especially as it relates to starch digestibility. The crop checklist yielded interesting results. Of the 56 farms sampled, approximately 13 farms had one hybrid, 26 farms had two to three hybrids, with the remaining 17 farms with greater than 3 hybrids. Over 50% of the farms were using a silage hybrid with the rest using dual purpose, leafy and brown mid-rib. Thirty four farms used one type of hybrid (i.e. silage hybrid only), however the rest of the herds used more than two types. This additional information helped to explain what was being observed related to starch digestibility in the corn silages, Figure 3.
The herds feeding the same hybrid out of the same structure fall to spring observed the expected response in starch digestibility. On average the starch digestibility increased 6.7%, which is what would be expected over several months of ensiling. The herds that had blended hybrids in the same structure fall to spring observed very little change in starch digestibility. The herds with the most variability were the ones feeding a blended hybrid in different structures fall to spring. Fiber digestibility varied in the herds segregated the same way as starch digestibility. Because of these unexpected results it was unrealistic to develop an envTool to examine nitrogen, phosphorus and emissions when there was this unexpected variability in corn silage quality and how it impacts nutrient usage by the cow.
To assess the ability for milk urea nitrogen (MUN) and fecal starch analysis as metrics that might indicate managment opportunities to enhance starch utilization, for both 2014 and 2015, MUN and fecal starch was monitored on the 56 cooperating farms. Results indicated there was little change seen from fall to spring sampling, and most samples were within the recommended ranges for each variable. However, monitoring indicated opportunity for improvement on many farms.
A second case study focused on changes in starch digestibility in corn silage from fall to spring and saught to determine how this impacted feed management. Change in 7-hr percent starch digestibility was tracked from fall 2014 to spring 2015. During the first year of sampling, changes in starch digestibility were expected to increase as has been found in controlled research studies. Our study found such increases only in a third of the farms, while one-third saw little to no change, and the other third saw decreases. For the subsequent sampling period, greater detail in hybrids and structures were captured for sampling period. Initial analyses indicate that farms that had the same hybrid (single) and same structure fall to spring experienced the expected increase in starch digestibility(M=6.5 SD=5.01). Farms that had blended (more than 1 hybrid) samples with same structure had less increase and some had decreases (M=0.2 SD=4.80). Finally, farms that changed hybrid and/or structure had a more varied response to change in starch digestibility (M=2.4 SD=4.80). Farms in the SAME category (M=6.5 SD=5.01) had higher changes in starch digestibility when compared to farms in either of the other categories (BLEND, CHANGE) combined (M=1.8 SD=4.85), F(1,50) = 7.135, p=0.01. Potential contributions from hybrid selection, harvest management and time from ensilement are still under investigation.
The 2014 actual costs and 2015 cash flow plan break-evens have been summarized for all participants for the past two years. The fifty-six project participants’ minimum, average, and maximum break-evens for 2013 & 2014 actuals and 2014 & 2015 cash flow plan break-evens were analyzed nonparametrically. Fifty-one farms had both actual and plan break-evens in 2014. Forty-five farms had higher actual break-even than planned, while six farms had lower actual break-evens than planned. The average difference was a $3.01 higher actual break-even than was planned. Due to high milk prices in 2014, many operations took the opportunity to invest in capital improvements of the operation. The 2015 actual break-evens will be calculated in February 2016.
Evidence of adoption comes from participation in cash flow monitoring and in feed management practices considered in the case study of starch digestibility and starch uptake. Results showed widespread interest in these approaches, however knowledge of effective use of multiple structures, management of sileage composition, and hybrid selection appeared to be a limiting factor.
Areas needing additional study
Our research showed that monitoring only milk income or feed costs per cow or per cwt does not provide insight on making informed decisions. Wolf (2010) showed that income over feed cost (IOFC) could be used to monitor profit by including gross milk income and feed cost. Using IOFC accounts for the volatility in milk and feed markets, giving the producer a better metric for evaluating profit margin. Income over feed cost is the measure of what remains of the milk income after subtracting the feed cost of the lactating cows on a per-cow-per-day basis or on a per hundredweight basis. Income over feed cost can be used to evaluate nutrition and pasture management as well. Using the Penn State IOFC tool (Ishler et al., 2013), the amount spent on purchased feeds or the cost of home-raised feeds can be evaluated against the current milk production. Further, we showed that focus on more specific indicators such as fiber digestibility and starch digestibility add important information relevant for feed management. As these results are based on small sample, further study is needed to explore intra-year variation of these indicators, variation across farm characteristics, and other dairy production practices.