scholarly journals Tools for Evaluating Native Grasses as Low Maintenance Turf

2009 ◽  
Vol 19 (3) ◽  
pp. 626-632 ◽  
Author(s):  
Landon D. Bunderson ◽  
Paul G. Johnson ◽  
Kelly L. Kopp ◽  
Adam Van Dyke

Visual ratings are the standard for evaluating turfgrass quality. However, to provide more objective evaluations and to address statistical concerns, other methods have been developed to measure turfgrass quality, including digital image analysis and measurements of chlorophyll content. These have been largely applied to traditionally used turfgrass species, but here we used these methods to evaluate turfgrass quality of nontraditional species and mixtures that are native or adapted to the intermountain west region of North America. Two fertilizer treatments (1.0 or 2.0 lb/1000 ft2 nitrogen) were applied to 21 different species and species mixtures in North Logan, UT. These plots were irrigated to replace 60% of the local evapotranspiration rate and were mowed at 4 inches. Turfgrass quality ratings were most effective in measuring quality among the diverse species used in this study. Because of the wider variation in acceptable visual characteristics and lower quality expectations for low-maintenance native turf, the objective evaluation methods proved less useful. Generally, chlorophyll meter data, digital image analysis of cover, and digital image analysis of color data were not well correlated with human visual quality ratings in this study. Measurements were well correlated in some species, but not in others. These methods can supplement, but cannot replace, human visual turfgrass quality ratings for comparison of dissimilar grasses.

2014 ◽  
Vol 106 (5) ◽  
pp. 1787-1794 ◽  
Author(s):  
Bernd Leinauer ◽  
Dawn M. VanLeeuwen ◽  
Matteo Serena ◽  
Marco Schiavon ◽  
Elena Sevostianova

2021 ◽  
Vol 11 (18) ◽  
pp. 8744
Author(s):  
Yanan Xu ◽  
Keling Tu ◽  
Ying Cheng ◽  
Haonan Hou ◽  
Hailu Cao ◽  
...  

Chlorophyll fluorescence (CF) has been applied to measure the chlorophyll content of seeds, in order to determine seed maturity, but the high price of equipment limits its wider application. Astragalus seeds were used to explore the applicability of digital image analysis technology to the prediction of seed chlorophyll content and to supply a low cost and alternative method. Our research comprised scanning and extracting the characteristic features of Astragalus seeds, determining the chlorophyll content, and establishing a predictive model of chlorophyll content in Astragalus seeds based on characteristic features. The results showed that the R2 of the MLR prediction model established with multiple features was ≥0.947, and the R2 of the MLP model was ≥0.943. By sorting of two single features, the R and G values, the R2 reached 0.969 and 0.965, respectively. A germination result showed that the lower the chlorophyll content, the higher the quality of the seeds. Therefore, we draw a conclusion that digital image analysis technology can be used to predict effectively the chlorophyll content of Astragalus seeds, and provide a reference for the selection of mature and viable Astragalus seeds.


2008 ◽  
Vol 16 (2) ◽  
pp. 185-190 ◽  
Author(s):  
Ivar Skaland ◽  
Irene Øvestad ◽  
Emiel A. M. Janssen ◽  
Jan Klos ◽  
Kjell H. Kjellevold ◽  
...  

2000 ◽  
Vol 10 (2) ◽  
pp. 7-9
Author(s):  
Yaser Natour ◽  
Christine Sapienza ◽  
Mark Schmalz ◽  
Savita Collins

2019 ◽  
Vol 8 (3) ◽  
pp. 11 ◽  
Author(s):  
Gustav Stålhammar ◽  
Thonnie Rose O. See ◽  
Stephen Phillips ◽  
Stefan Seregard ◽  
Hans E. Grossniklaus

2008 ◽  
Vol 14 (2) ◽  
pp. 192-200 ◽  
Author(s):  
Hiromasa Tanaka ◽  
Gojiro Nakagami ◽  
Hiromi Sanada ◽  
Yunita Sari ◽  
Hiroshi Kobayashi ◽  
...  

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