Use of Irrigation on Pasture-Based Dairies to Determine Forage and Irrigation Type Efficiencies

View the project final report

• 2016 annual report

Commodities

• Agronomic: grass (misc. perennial), medics/alfalfa
• Animals: bovine
• Animal Products: dairy

Practices

• Animal Production: grazing management
• Crop Production: irrigation
• Education and Training: demonstration, extension, farmer to farmer, on-farm/ranch research

Pasture based dairying in Missouri represents over 40% of the total dairy cows in the state and continues to expand. Most operations are low-input type systems which means the goal is to provide the highest percentage of dry matter pasture intake in a cow’s diet as possible for as many days as possible. This could mean as much as 85-100% of the diet is pasture for short windows of time. Ideally in a grazing system, growth rates, or the amount of dry matter pasture grown per day per hectare across the farm would be fairly consistent throughout the grazing season. However in a continental climate such as Missouri this is not reasonable or expected. Growth rates can range from zero to over 100 kg per hectare per day. Typically operations need 35-45 kilograms of pasture growth per hectare per day on average across the farm. This results in periods of deficits and surplus throughout the season.  Deficits usually occur during periods of heat stress and reduced rainfall during the summer.  Producers initially began evaluating and implementing irrigation more as an insurance policy during these severe periods rather than as a tool to grow more forage.  However, interest grew in how much forage could be grown during inclement weather and the cost to produce it. Optimizing and timely utilization of forages in grazing systems are critical for cash flow, profit and sustainability.  Irrigation is a novel approach to maintaining forage growth in Missouri however we had little data or experience to draw on to make informed decisions. 

Producers requested more information on irrigation efficiency and cost effectiveness of their systems across several forage species.  It was determined the university would measure weekly forage mass of several paddocks on each farm. Each paddock would have a portion that would be irrigated and an area non-irrigated to try and reduce management and any soil type differences. Paddock typically were 2 to 4 hectares in size. Two to three times during the growing season, calibration measurements and clippings occurred to determine forage dry matter prediction equations. Producers provided weather data as well as irrigation and grazing dates. Data was compiled and analyzed via ANOVA evaluating specific points of the growth phase from grazing event to next grazing event.  

There appeared to be a trend of additional forage grown for all species (Alfalfa; P=0.24, Perennial Ryegrass; P=0.11; Tall Fescue; P=0.29).  Crabgrass was not included as the producer did not need additional forage growth and did not irrigate. Irrigation for alfalfa was sporadic due to the system type and labor required.  The irrigated grasses had similar annual increase in dry matter yields per grazing event (Perennial Ryegrass; 125 kilograms per hectare; Tall Fescue; 134 kilograms per hectare) while alfalfa (86 kilograms per hectare) was slightly less possibly due to a deeper root system and more sporadic irrigation events. 

Costs for additional dry matter forage for alfalfa, perennial ryegrass and tall fescue were $0.20, $0.43 and $0.30 per additional kilogram grown above the non-irrigated forage.

Discussion groups on various farms were given updates as they study progressed. Unfortunately for the study but fortunate for the producers, both years had adequate rainfall so a true value of irrigation’s potential for forage growth was not tested. A positive was a trend was noted for all forage species however it may not be cost effective. Prime alfalfa hay could possibly cost $0.26 per kilogram of dry matter delivered. The producer would have to make a decision, if the costs presented here are true every year, if the investment, labor and other costs are cost-effective for their system.

Producers learned the cost of yield with sporadic irrigation practices. If the investment is made, the main costs after will be labor and certainly power (electricity, propane, natural gas) to run the systems. In a year with adequate rainfall, these costs may outweigh the cost of prime alfalfa. The main learning point was the following of evapotranspiration rate for the week. This allows the producer to know how much water needs to be applied each week to keep soil water holding capacities from being depleted resulting in reduced forage growth.

For these two years of irrigation observation, irrigation's costs would be similar to the cost of purchasing prime alfalfa. The decision the producer makes is if the total investment for irrigation outweighs the total cost of purchased alfalfa year after year. These producers we believe would say yes, not only as an insurance policy as stated before but also for fringe benefits of forage re-establishment but also possible cow cooling during heat stress. 

Objective 1: provide information for producers to develop a pasture system that enhances their lifestyle while securing long-term sustainability

• Eight discussion group/pasture walks were held over the grazing season in 2016 and 2017. Facebook group page was formed in early 2016. Information regarding pasture management as well as preliminary information from the irrigation study were shared with producers by the PI of the study as well as host producers. Information was shared through these avenues and a summary of the data will be provided at the end. Producers have already requested if the trial can continue further past year two in order to gather more information under different weather situations.

Objective 2: Determine cost-effectiveness of various irrigation systems across different forage systems

• Data on power usage and cost, time, capital expenditure was collected and compiled in report.

Objective 3: Determine water use efficiency between irrigation species and forage species

• This is ongoing. Raw forage data will be analyzed and confirmed via the forage neural network system and correlated to total water (rainfall and irrigation) as well as just rainfall to determine forage species efficiency. Additional data is needed to address this modeling as none of the forage species were stressed significantly.

Objective 4: Develop webpage for farmers to plug and play various scenarios to determine combinations best for their systems

• Data from this project is updating this model to allow producers to make informed decisions regarding irrigation usage as well as forage or irrigation type. Discussions have already been had with university economists to assist in the development and updating of this tool.