scholarly journals Effect of a Biostimulant on Bermudagrass Fall Color Retention and Spring Green-Up

Agronomy ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 608
Author(s):  
Verónica De Luca ◽  
Diego Gómez de Barreda
Keyword(s):  
Amino Acid ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Cynodon Dactylon ◽  
Field Research ◽  
Dry Weight ◽  
Green Color ◽  
Positive Effects ◽  
Color Retention ◽  
Positive Effect

Field research was conducted in 2017–2019 on “Princess 77” bermudagrass (Cynodon dactylon (L.) Pers.) to determine whether an amino acid based biostimulant program applied in the late season (October-November) and early season (March-April) could extend fall color retention (FCR) or hasten the spring green-up (SGU), respectively. Bermudagrass was treated with the biostimulant under five different managements: non-treated; 6 times at 5 L ha−1 weekly; 3 times at 5 L ha−1 in a 14-day interval; 6 times at 10 L ha−1 weekly; and 3 times at 10 L ha−1 in a 14-day interval. Normalized difference vegetation index (NDVI) and visual ratings (turf green color and percentage of green coverage in the subplot) were determined weekly, and turf clipping dry weight for the SGU studies. At the end of the FCR studies (2017 and 2018), there was no effect of the biostimulant; although, some isolated positive effects were detected during the experiment in 2017 on bermudagrass treated weekly at 10 L ha−1 for NDVI. However, there was a slight positive effect on SGU when this physiological process occurred slowly (year 2018) and the biostimulant was applied weekly at 10 L ha−1 (4.4 kg N ha−1), compared to another performed management and warmer years (2017 and 2019).

scholarly journals Correlations Between Hybrid Bermudagrass Morphology and Wear Tolerance

2015 ◽  
Vol 25 (6) ◽  
pp. 725-730 ◽  
Author(s):  
Alexander R. Kowalewski ◽  
Brian M. Schwartz ◽  
Austin L. Grimshaw ◽  
Dana G. Sullivan ◽  
Jason B. Peake
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Cynodon Dactylon ◽  
Morphological Characteristics ◽  
Quantitative Measure ◽  
Leaf Length ◽  
Leaf Width ◽  
Green Color ◽  
Index Ratio ◽  
Wear Tolerance

Hybrid bermudagrasses (Cynodon dactylon × C. transvaalensis) typically have excellent wear tolerance when compared with other turfgrass species. This trait should be evaluated during variety development to reduce the risk of failure when new grasses are planted in areas with traffic stress. The objective of this research was to evaluate the wear tolerance of four hybrid bermudagrasses with differing morphological characteristics. Traffic was applied to the hybrid bermudagrass varieties ‘Tifway’, ‘TifSport’, and ‘TifTuf’, as well as an experimental hybrids (04-76) using a traffic simulator for 6 weeks. Leaf morphology (leaf width, length, and angle) and quantitative measure of density and color [normalized difference vegetation index ratio (NDVI), dark green color index (DGCI), and percent green turf color] were characterized before traffic, and then percent green turf color after 6 weeks of traffic was measured to estimate wear tolerance. ‘TifTuf’ hybrid bermudagrass provided the greatest wear tolerance, as well as the narrowest and shortest leaf lengths, greatest NDVI values and percent green color, and lowest DGCI before traffic. Conversely, 04-76 produced the poorest wear tolerance, as well as the widest and longest leaves, lowest NDVI values and percent green color, and highest DGCI values before traffic. Regression analysis determined that DGCI, leaf length, and leaf width were inversely, or negatively, correlated to wear tolerance, whereas percent green turf color before traffic was directly correlated to wear tolerance. For these hybrids, DGCI had the strongest correlation to increased wear tolerance.

scholarly journals Using remote sensing for identification of late-season grass weed patches in wheat

Weed Science ◽  
2006 ◽  
Vol 54 (02) ◽  
pp. 346-353 ◽  
Author(s):  
Francisca López-Granados ◽  
Montse Jurado-Expósito ◽  
Jose M. Peña-Barragán ◽  
Luis García-Torres
Keyword(s):  
Vegetation Index ◽  
Near Infrared ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Field Research ◽  
Aerial Images ◽  
Wild Oat ◽  
Late Season ◽  
High Resolution Satellite Imagery ◽  
Grass Weed

Field research was conducted to determine the potential of hyperspectral and multispectral imagery for late-season discrimination and mapping of grass weed infestations in wheat. Differences in reflectance between weed-free wheat and wild oat, canarygrass, and ryegrass were statistically significant in most 25-nm-wide wavebands in the 400- and 900-nm spectrum, mainly due to their differential maturation. Visible (blue, B; green, G; red, R) and near infrared (NIR) wavebands and five vegetation indices: Normalized Difference Vegetation Index (NDVI), Ratio Vegetation Index (RVI), R/B, NIR-R and (R − G)/(R + G), showed potential for discriminating grass weeds and wheat. The efficiency of these wavebands and indices were studied by using color and color-infrared aerial images taken over three naturally infested fields. In StaCruz, areas infested with wild oat and canarygrass patches were discriminated using the indices R, NIR, and NDVI with overall accuracies (OA) of 0.85 to 0.90. In Florida–West, areas infested with wild oat, canarygrass, and ryegrass were discriminated with OA from 0.85 to 0.89. In Florida–East, for the discrimination of the areas infested with wild oat patches, visible wavebands and several vegetation indices provided OA of 0.87 to 0.96. Estimated grass weed area ranged from 56 to 71%, 43 to 47%, and 69 to 80% of the field in the three locations, respectively, with per-class accuracies from 0.87 to 0.94. NDVI was the most efficient vegetation index, with a highly accurate performance in all locations. Our results suggest that mapping grass weed patches in wheat is feasible with high-resolution satellite imagery or aerial photography acquired 2 to 3 wk before crop senescence.

scholarly journals Yield, Quality and Physiological Traits of Red Beet Under Different Magnesium Nutrition and Light Intensity Levels

Agronomy ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. 379
Author(s):  
Sara D’Egidio ◽  
Angelica Galieni ◽  
Fabio Stagnari ◽  
Giancarlo Pagnani ◽  
Michele Pisante
Keyword(s):  
Light Intensity ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Dry Weight ◽  
Total Phenolic ◽  
Storage Roots ◽  
Light Reduction ◽  
Red Beet ◽  
Application Rates ◽  
And Storage

The effects of light intensity and Magnesium (Mg) supply on quality traits, yield and macronutrient assimilation of red beet plants were studied in two greenhouse experiments (in 2017 and 2018). According to a split-plot design, we compared two photosynthetically active radiation (PAR) levels (100% PAR, Full Light, FL and 50% PAR, Light Reduction, LR) as the main factor and three Mg application rates (0, 30, and 60 kg Mg ha−1: MG_0, MG_30 and MG_60, respectively) as the secondary factor. Yield and dry matter accumulations were principally affected by Mg. In both growing seasons, storage root dry weight (DW) increased about 5-fold in MG_60 with respect to MG_0; the highest leaves DW was achieved with the “LR × MG_60” treatment. Nitrogen and Mg contents in leaves and storage roots increased as Mg availability increased; also, the highest chlorophyll content was obtained combining LR and a high Mg rate. Moreover, the reflectance-derivative Normalized Difference Vegetation Index (NDVI670) and Chlorophyll Index (CI) allowed for discriminating the Mg sub-optimal supply in red beet plants. Sucrose was found to be the most abundant sugar in both the leaves and storage organs and was affected by Mg supply. Total phenolic content and betalains in storage roots at harvest were affected by both PAR and Mg application rates. Our results highlight the potential of Mg nutrition in ensuring good yield and quality of red beet crops.

scholarly journals Consequences of climate-induced vegetation changes exceed those of human disturbance for wild impala in the Serengeti ecosystem

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
L Hunninck ◽  
R May ◽  
C R Jackson ◽  
R Palme ◽  
E Røskaft ◽  
...  
Keyword(s):  
Human Disturbance ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Management Strategies ◽  
Forage Quality ◽  
Serengeti Ecosystem ◽  
Human Land Use ◽  
Faecal Samples ◽  
Dry Seasons ◽  
Positive Effect

Abstract In East Africa, climate change is predicted to reduce vegetation quality, and pervasive human disturbance has already resulted in significant declines in biodiversity. We studied the combined effects of reduced forage quality and human disturbance on faecal glucocorticoid metabolite (FGM) concentrations. We predicted that decreasing nutritional quality and increasing human disturbance would have an additive positive effect on FGM levels in wild impala (Aepyceros melampus). Employing a space-for-time approach, we used normalized difference vegetation index (NDVI) as a measure of forage quality, combined with spatially explicit proxies of human disturbance across areas of different protection management strategies in the Serengeti ecosystem. We collected 639 faecal samples, spread over 4 years, including both wet and dry seasons. Impala FGM levels increased significantly with declining NDVI and, to a lesser extent, with increasing proxies for human disturbance. However, we found no interaction between the two, such that impala had elevated FGM levels with low NDVI and low FGM levels with high NDVI regardless of human disturbance levels. This implies that impala will have high FGM levels if forage quality is poor, even with significant protection and reduced human disturbance. Understanding how animals respond to and cope with changes in forage quality and human land use across different protected areas is important for conservationists and managers to better protect species at risk and predict population viability.

scholarly journals Optical Sensing of Turfgrass Chlorophyll Content and Tissue Nitrogen

HortScience ◽  
2004 ◽  
Vol 39 (5) ◽  
pp. 1130-1132 ◽  
Author(s):  
G.E. Bell ◽  
B.M. Howell ◽  
G.V. Johnson ◽  
W.R. Raun ◽  
J.B. Solie ◽  
...  
Keyword(s):  
Chlorophyll Content ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Cynodon Dactylon ◽  
Optical Sensing ◽  
Creeping Bentgrass ◽  
N Fertilization ◽  
Agrostis Palustris ◽  
Small Areas ◽  
N Rates

Differences in soil microenvironment affect the availability of N in small areas of large turfgrass stands. Optical sensing may provide a method for assessing plant N needs among these small areas and could help improve turfgrass uniformity. The purpose of this study was to determine if optical sensing was useful for measuring turfgrass responses stimulated by N fertilization. Areas of `U3' bermudagrass [Cynodon dactylon (L.) Pers.], `Midfield' bermudagrass [C. dactylon (L.) Pers. × C. transvaalensis Burtt-Davy], and `SR1020' creeping bentgrass (Agrostis palustris Huds.) were divided into randomized complete blocks and fertilized with different N rates. A spectrometer was used to measure energy reflected from the turfgrass within the experimental units at 350 to1100 nm wavelengths. This spectral information was used to calculate normalized difference vegetation index (NDVI) and green normalized difference vegetation index (GNDVI). These spectral indices were regressed with tissue N and chlorophyll content determined from turfgrass clippings collected immediately following optical sensing. The coefficients of determination for NDVI and GNDVI regressed with tissue N averaged r2 = 0.76 and r2 = 0.81, respectively. The coefficients of determination for NDVI and GNDVI regressed with chlorophyll averaged r2 = 0.70 and r2 = 0.75, respectively. Optical sensing was equally effective for estimating turfgrass responses to N fertilization as more commonly used evaluations such as shoot growth rate (SGR regressed with tissue N; r2 = 0.81) and visual color evaluation (color regressed with chlorophyll; r2 = 0.64).

scholarly journals Durability and concentration of organic colorant in the visual quality of Discovery TM bermudagrass

2020 ◽  
Vol 26 (4) ◽  
pp. 621-632
Author(s):  
Matheus Vinícios Leal do Nascimento ◽  
Patrick Luan Ferreira dos Santos ◽  
João Victor Costa ◽  
Juliana Trindade Martins ◽  
Roberto Lyra Villas Bôas ◽  
...  
Keyword(s):  
Water Conservation ◽  
Color Index ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Visual Quality ◽  
Operating Costs ◽  
Aesthetic Quality ◽  
Green Color ◽  
Warm Weather

Abstract The painting of sports turfs with colorants is a common practice, with the main objective to maintain grass appearance for maximum aesthetic quality. Colorants are used to provide green color to grasses during periods of stress and dormancy and are considered an alternative for warm weather grasses during the winter months. Recent increases in the use of colorants is due to water conservation efforts as well as lower operating costs compared to winter overseeding. The objective of this study was to evaluate durability and doses of organic colorant in terms of visual quality of DiscoveryTM bermudagrass. The experiment was installed in the field, subdivided into plots of DiscoveryTM bermudagrass treated with lawn-specific commercial, organic colorant as follows 0 ml L-1 (Control); 33 ml L-1; 50 ml L-1; 66.6 ml L-1 (manufacturer’s recommendation); 83 ml L-1; 100 ml L-1. At 10 day intervals the green color index, reflectance, normalized difference vegetation index (NDVI), and digital images were measured and assessed. The results indicate that, given the durability of the product, doses between 66.6 and 83.3 ml L-1 are recommended.

scholarly journals Response of Hybrid Bermudagrass and Manilagrass to Soil Moisture Using Water-table Depth Gradient Tanks

HortScience ◽  
2021 ◽  
pp. 1-7
Author(s):  
Gerald Henry ◽  
Rebecca Grubbs ◽  
Chase Straw ◽  
Kevin Tucker ◽  
Jared Hoyle
Keyword(s):  
Soil Moisture ◽  
Water Table ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Cynodon Dactylon ◽  
Field Capacity ◽  
Water Table Depth ◽  
Habitat Specialization ◽  
Depth Gradient ◽  
Turfgrass Quality

Previous research involving turfgrass response to soil moisture used methodology that may compromise root morphology or fail to control outside environmental factors. Water-table depth gradient tanks were employed in the greenhouse to identify habitat specialization of hybrid bermudagrass [Cynodon dactylon (L.) Pers. × C. transvaalensis Burtt-Davy] and manilagrass [Zoysia matrella (L.) Merr.] maintained at 2.5 and 5.1 cm. Turfgrass quality (TQ), normalized difference vegetation index (NDVI), canopy temperature (CT), and root biomass (RB) were used as metrics for plants grown in monoculture in sandy clay loam soil. Mowing height did not affect growth of turfgrass species in response to soil moisture. Turfgrass quality, NDVI, and RB were greatest, whereas CT was lowest at wetter levels [27- to 58-cm depth to the water-table (DWT)] of each tank where plants were growing at or above field capacity. However, bermudagrass RB was greatest at 27-cm DWT, whereas manilagrass RB at 27-cm DWT was lower than RB at 42.5- to 73.5-cm DWT in 2013 and lower than all other levels in 2014. Both species responded similarly to droughty levels (120- to 151-cm DWT) of the tanks. Turfgrass quality, NDVI, and RB were lowest, whereas CT was highest at higher droughty levels. Bermudagrass may be more competitive than manilagrass when soil moisture is high whereas both species are less competitive when soil moisture is low.

scholarly journals Evaluating the Salinity Tolerance of Clonal-type Bermudagrass Cultivars and an Experimental Selection

HortScience ◽  
2017 ◽  
Vol 52 (1) ◽  
pp. 185-191 ◽  
Author(s):  
Mingying Xiang ◽  
Justin Q. Moss ◽  
Dennis L. Martin ◽  
Kemin Su ◽  
Bruce L. Dunn ◽  
...  
Keyword(s):  
United States ◽  
Salinity Tolerance ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Perennial Grass ◽  
Warm Season ◽  
Dry Weight ◽  
The United States ◽  
Clonal Type ◽  
Salinity Levels

Bermudagrass (Cynodon sp.) is a highly productive, warm-season, perennial grass that has been grown in the United States for turfgrass, forage, pasture, rangeland, and roadside use. At the same time, many bermudagrass production and reclamation sites across the United States are affected by soil salinity issues. Therefore, identifying bermudagrass with improved salinity tolerance is important for successfully producing bermudagrass and for reclaiming salt-affected sites with saline irrigated water. In this project, the relative salinity tolerance of seven clonal-type bermudagrass was determined, including industry standards and an Oklahoma State University (OSU) experimental line. The experiment was conducted under a controlled environment with six replications of each treatment. Seven bermudagrass entries were exposed to four salinity levels (1.5, 15, 30, and 45 dS·m−1) consecutively via subirrigation systems. The relative salinity tolerance among entries was determined by normalized difference vegetation index (NDVI), digital image analysis (DIA), leaf firing (LF), turf quality (TQ), shoot dry weight (SW), visual rating (VR), and dark green color index (DGCI). Results indicated that there were variable responses to salinity stress among the entries studied. As salinity levels of the irrigation water increased, all evaluation criterion decreased, except LF. All entries had acceptable TQ when exposed to 15 dS·m−1. When exposed to 30 dS·m−1, experimental entry OKC1302 had less LF than all other entries except ‘Tifway’, while ‘Midlawn’ showed more LF than all the entries. Leaf firing ranged from 1.0 to 2.7 at 45 dS·m−1, where ‘Tifway’ outperformed all other entries. At 45 dS·m−1, the live green cover as measured using DIA ranged from 3.07% to 24.72%. The parameters LF, TQ, NDVI, DGCI, SW, and DIA were all highly correlated with one another, indicating their usefulness as relative salinity tolerance measurements.

Applications of Topramezone and SpeedZone® for Postemergence Goosegrass (Eleusine indica) Control in Hybrid Bermudagrass

2021 ◽  
pp. 1-21
Author(s):  
Devon E. Carroll ◽  
James T. Brosnan ◽  
Gregory K. Breeden
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Field Research ◽  
Eleusine Indica

ABSTRACT Topramezone and carfentrazone + 2,4-D + mecoprop-p + dicamba (SpeedZone®) are herbicides labeled for postemergence goosegrass (Eleusine indica L. Gaertn.) control in hybrid bermudagrass (C. dactylon x C. transvaalensis Burtt Davy). Field research was conducted in Knoxville, TN during 2019 and 2020 to evaluate goosegrass control and hybrid bermudagrass tolerance to these herbicides applied alone and in mixture. Treatments included topramezone (12.2 g ha-1), SpeedZone® [carfentrazone (33.6 g ha-1) + 2,4-D (1029 g ha-1) + mecoprop-p (322 g ha-1) + dicamba (91 g ha-1)] and SpeedZone® + topramezone at 12.2, 6.1, 3.6, or 2.4 g ha-1. A non-treated control was included for comparison. Hybrid bermudagrass tolerance was assessed on four cultivars (‘Northbridge’, ‘Tifway’, ‘Tahoma 31’, and ‘TifTuf’) via visual ratings of turfgrass injury and assessments of normalized difference vegetation index (NDVI). At the termination of the experiment, SpeedZone® alone and in mixture with topramezone controlled goosegrass ≥ topramezone alone. Mixtures of SpeedZone® + topramezone reduced injury on all cultivars compared to topramezone alone, particularly when mixtures delivered ≤ 6.1 g ha-1 topramezone. Injury subsided on all cultivars by 28 days after treatment regardless of herbicide. Findings suggest that SpeedZone® can be mixed with topramezone at the rates tested herein to minimize hybrid bermudagrass injury from topramezone applications for goosegrass control.

scholarly journals Application of Optical Sensors for Nitrogen Management in Chrysanthemum

HortScience ◽  
2016 ◽  
Vol 51 (7) ◽  
pp. 915-920 ◽  
Author(s):  
Amir Ali Khoddamzadeh ◽  
Bruce L. Dunn
Keyword(s):  
Plant Height ◽  
Optical Sensors ◽  
Crop Production ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Dry Weight ◽  
Fertilizer Treatment ◽  
Shoot Dry Weight ◽  
Fertilizer Rates ◽  
Leaf N

Nitrogen (N) is an important component of proteins and chlorophyll, and has been correlated with optical sensors as a means to determine N status during crop production. In this experiment, chrysanthemum ‘Amico Bronze’ and ‘Jacqueline Yellow’ had initial controlled-release fertilizer rates of 0, 5, 10, 15, or 20 g. Normalized Difference Vegetation Index (NDVI), Soil Plant Analytical Development (SPAD), and atLEAF sensor readings were taken at 10, 17, 24, 31, 38, and 45 days after adding initial fertilizer treatments (DAT). NDVI was correlated with leaf N concentration at all sampling dates except 17 DAT. Values for NDVI increased linearly up to 31 DAT for all treatments then plateaued at 45 DAT. Values for SPAD were only correlated with leaf N at 24 DAT, whereas, NDVI was correlated as early as 10 DAT. The atLEAF sensor was not correlated with leaf N at any sampling date. With weeks combined, correlation analysis showed correlations among leaf N and fertilizer rates, fertilizer rates and SPAD, and SPAD with NDVI and atLEAF. Thirty-one days after initial fertilizer treatment, 10 pots per treatment per cultivar were supplemented as following: 15 g supplemented to the 0 g treatment, 10 g to the 5 g treatment, and 5 g to the 10 g treatment at 31 DAT. With supplemented fertilizer treatments (SFTs), NDVI increased weekly until 45 DAT for ‘Amico Bronze’, while SPAD values did not increase in any treatments. The greatest atLEAF values occurred with 10 (+5) g and 0 (+15) g N in both cultivars. All sensor readings were only taken on leaves without any flowers. The greatest number of flowers, plant height, and shoot dry weight occurred with 10 (+5) g of additional N, but no differences occurred between 5 (+10) g and 0 (+15) g for height and shoot dry weight. No correlations existed between fertilizer rates, SPAD, NDVI, and leaf N for SFT in either cultivar. In summary, results indicated that NDVI values correlated greater (P ≤ 0.05 and P ≤ 0.01) with leaf N than SPAD and atLEAF chlorophyll sensors. Supplemental fertilizer application improved plant quality in terms of number of flowers, plant height, and shoot dry weight for all treatments, indicating that SFT could be used to correct N deficiency during crop production; however, not in combination with nondestructive sensor readings because of inconsistencies in the ability of all three sensors to separate among fertilizer treatments during a short production schedule.

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