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

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

Summary

Optimizing and timely utilization of forages in grazing systems are critical for cash flow, profit and sustainability. Rainfall in Missouri as well across other areas of the fescue belt can be sporadic and impact forage pasture growth forcing producers to supplement more expensive harvested forages or grains/commodities.  Irrigation is a novel approach to maintaining forage growth in Missouri with little data or experience to draw on to make informed decisions.  Six pasture based dairy farms utilizing one of three types of irrigation (center pivot, spider, pods) and 4 species of forages (perennial ryegrass, tall fescue/clover, alfalfa and crabgrass) The main objective is to provide information for producers to develop a pasture system that enhances their lifestyle while securing long-term sustainability. This entails measuring forage response to irrigation, the type of irrigation, forage species response and the costs associated with irrigation.

Three to six paddocks on each farm were measured weekly beginning mid-May and ending October 30. Farms were measured weekly using sonar sensor technology mounted to an ATV. Records on irrigation dates, water applied, grazing/harvest events and rainfall were provided by the producer. Forage grown was calculated by subtracting the last weekly measured event (post-graze) from the previous week (pre-graze) around a documented grazing event. Measurements for irrigated and non-irrigated areas were only counted if an irrigation event occurred prior to the grazing event. All species were measured however crabgrass was not used in the data as the producer did not use irrigation due to forage growth rates exceeding his forage feed demand. In short, the producer did not need the surplus forage thus the choice to not irrigate. Preliminary data suggests in year one a response for all irrigated species was found but was not as defined as expected (range 18-29% more forage per grazing event). This may be due to natural rainfall exceeding historical rainfall as well as evapotranspiration rates for the month for four of the six months.   Data presented is preliminary and will be filtered via forage neural network at later date.

The project is on track to start year two in early May. Additional paddocks may be added for each farm to give more irrigated/grazing events as well as give more certainty to calculated growth rates.

Objectives/Performance Targets

Thus far, the study has proceeded according to the original plan, with only minor modifications. The original study aims are as follows:

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

• Six discussion group/pasture walks were held over the grazing season in 2016. 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 will continue to be shared through these avenues in year two with a summary of the data 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 is still being collected.

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

• 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.

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

• At the end of year two forage data collection efforts will begin to start 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 of this tool.

Accomplishments/Milestones

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

• Six discussion group/pasture walks were held over the grazing season in 2016. Facebook group page was formed in early 2016. At each discussion group 15-50 producers participated in discussion and received new information regarding the study. In year one it was simply updates on calculated growth rates of various forages as well as amount of water applied.
• Discussion evolved at the discussion groups and on the Facebook group page to following daily ET rates as their usage as a guideline for irrigation application. Further information provided was soil water holding capacity (SWHC) of each of the producer’s farms. A tool is being developed for a weekly monitoring system to allow producers to use ET rate and their SWHC to determine irrigation needs.
• Some producers had made the decision to continuous irrigate with the center pivot system at low levels of water application twice weekly while others attempted to irrigate only in times of need. The producers trying to selectively irrigate have decided to have a more structured schedule based on the forage yield information. Additionally the type of irrigator (spider) and the forage species (alfalfa) limited the times for irrigation to roughly 14 days post grazing to avoid damaging the alfalfa with drag water lines. This again gave reason for the decision for a more structured irrigation schedule.

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

• Data on power usage and cost, time, capital expenditure is still being collected.

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

• 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.

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

• At the end of year two forage data collection efforts will begin to start 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 of this tool.

Impacts and Contributions/Outcomes

The original objectives are being met. Actual forage measurements are being completed weekly. Collection of rainfall data, grazing and irrigation events and actual water applied were at times difficult to obtain due to the busy schedules of the producers. Data collection of these parameters was just recently completed and analysis for correlations will begin soon. Producers were enrolled in CoCoRaHS and approved rainfall gages purchased for each producer to assist collection of this data. Graduate students will meet with producers weekly to collect this data to speed the process of this information being available. Producers are adopting new technology to them (use of SWHC and ET) to make irrigation more efficient and cost effective. At the end of year two data will be compiled and analyzed. If significant results are obtained results will be reported to Journal of Crop Science. These researchers believe this study will continue after year two and wish to thank NC SARE for the contribution and understanding of importance of this trial.

SARE 2016 irrigation

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