Cutting Edge: Sod shelf life and irrigation needs assessment

Researchers examined transplant success of bermudagrass and zoysiagrass sod and a needs-based socioeconomic survey of water-saving irrigation programs

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Aerial view of Ghost Creek golf course

Seasonal effects on shelf life and transplant success of bermudagrass and zoysiagrass sod in Oklahoma

Sod is a perishable commodity, and its quality deteriorates quickly after harvesting due to desiccation and heating within the sod stack or roll. The objective of this research was to determine the effects of storage time and harvest season of bermuda­grass (Cynodon dactylon × C. tranvaalensis OKC1131) and zoysiagrass (Zoysia japonica Meyer) sod on post-harvest transplant success. A field study was conducted as a split-split plot design for two seasons (late spring and early summer) at two locations: Turfgrass Research Center, Stillwater, Okla., and Cimarron Valley Research Station, Perkins, Okla. Sod was harvested from Tulsa Grass & Sod Farms and Riverview Sod Ranch and delivered as small rolls on a standard pallet.

The internal temperature within sod rolls and slabs was measured continuously over five storage hours (0, 24, 48, 72 and 96 hours). Best quality sod slabs and rolls were selected for each cultivar on each storage time for transplanting into the field. The moisture content of the sod slabs and rolls and sod handling quality were evaluated at time of planting. Weekly measurements included visual ratings, green coverage using digital image analysis, normalized difference vegetative index and normalized difference red edge using handheld sensors. Additionally, sod root count was measured 30 days after planting. Results indicated that increased storage time had a significant impact on sod handling quality for zoysiagrass as compared to bermudagrass, and green coverage decreased with an increase in storage time for bermudagrass. Project findings provide an understanding of ideal storage time for respective seasons and valuable information to sod growers on how to optimize the storage time and harvesting season to achieve higher transplant success.

— Manveer Singh (manveer.singh@okstate.edu) and Charles Fontanier, Ph.D., Oklahoma State University, Stillwater

Aerial view of Ghost Creek golf course

Needs assessment for remote sensing- and machine learning-guided precision turfgrass irrigation programs: Findings from a socioeconomic survey

New technologies including mobile remote sensing and artificial intelligence-guided precision irrigation management (PIM) programs may offer turfgrass managers additional tools to reduce water use and improve turf quality. However, adoption of these new practices may be limited by factors such as startup costs, perceived importance and the learning curve associated with new technology. This project conducted an industry-wide survey of turfgrass professionals to investigate their current irrigation management strategies and how likely they may be to adopt new PIM technologies.

Survey participants included turfgrass researchers, superintendents, sod farmers and landscape professionals. Survey responses indicated current water use and cost for existing operations, importance ratings of various characteristics associated with PIM and water conservation, and likelihood of adoption based on cost-benefit scenarios. The survey results revealed a keen interest in the turfgrass industry regarding the adoption of PIM technologies. Concerns related to drought and regulatory constraints ranked high as factors driving the need for water conservation. Early detection of biotic and abiotic stress emerged as a primary and practical application for PIM technology. The results from this survey will help to guide research, development, training and education for turfgrass PIM and its associated decision support systems.

— William Errickson (william.errickson@njaes.rutgers.edu) and Bingru Huang, Ph.D., Rutgers University, New Brunswick, N.J.


Darrell J. Pehr (dpehr@gcsaa.org) is GCM’s science editor.