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ARS Home » Pacific West Area » Maricopa, Arizona » U.S. Arid Land Agricultural Research Center » Water Management and Conservation Research » Research » Publications at this Location » Publication #404859
Research Project: Increasing the Utility of Turf in Urban Environments of the Southwest U.S.

Location: Water Management and Conservation Research

Title: Spectral reflectance estimated genetic variation in hybrid turf bermudagrass

Author
item Serba, Desalegn
item WU, YANQI - Oklahoma State University
item Hejl, Reagan
item Williams, Clinton
item BRONSON, KEVIN - Texas A&M University

Submitted to: Grass Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/2/2023
Publication Date: 11/20/2023
Citation: Serba, D.D., Wu, Y., Hejl, R.W., Williams, C.F., Bronson, K. 2023. Spectral reflectance estimated genetic variation in hybrid turf bermudagrass. Grass Research. 3. Article 22. https://doi.org/10.48130/GR-2023-0022.
DOI: https://doi.org/10.48130/GR-2023-0022

Interpretive Summary: For assessing the biophysical properties of turfgrass, high throughput phenotyping (HTP), utilizing both remote and proximal sensing technologies, has become essential. We assessed turf bermudagrass hybrids in the greenhouse using the RapidScan CS-45 active crop canopy sensor, which detects canopy reflectance at wavelengths of 670 nm, 730 nm, and 780 nm. We calculated four spectral vegetation indices estimating canopy photosynthetic area and two indices for chlorophyll content from the reflectance data. The results indicated that the hybrids are genetically variable in spectral vegetation indices estimating photosynthetic area and chlorophyll content. Using a multi-trait genotype-ideotype distance index (MGIDI) as a selection differential, ten superior genotypes were identified. The spectral vegetation indices were crucial for the quick establishment of turfgrass in the field and mild-winter color retention.

Technical Abstract: High throughput phenotyping (HTP) utilizing both remote and proximal sensing technologies has emerged as a vital tool for evaluating the biophysical characteristics of turfgrass. This study was conducted to assess the genetic diversity of hybrid turf bermudagrass using spectral reflectance indices and use of HTP for germplasm enhancement. A total of 50 accessions of the hybrid bermudagrass (Cynodon dactylon × C. transvaalensis) were grown in the greenhouse in three replications. The spectral data were gathered using a height independent active crop canopy sensor, 'RapidScan CS-45', which measures canopy reflectance at the wavelengths of 670 nm, 730 nm, and 780 nm. The reflectance data were used to derive three indices related to canopy photosynthetic area and other three related to chlorophyll content. All vegetation indices showed significant genotype-to-genotype variation. Ten superior genotypes were identified using the multi-trait genotype-ideotype distance index (MGIDI) as a selection differential. On 48 of the genotypes that were established in the field in two replications, establishment rate and winter color data were also gathered. The results of a linear regression analysis demonstrated the importance of spectral vegetation indices (SVI) for the turfgrass quick establishment (percentage area coverage) and winter color retention. This study brings attention to the potential use of the proximal sensing in turfgrass germplasm enhancement for establishment speed, aesthetic value, and mild-winter color retention.