Effects of Morning and Afternoon Shade in Combination with Traffic Stress on Seashore Paspalum

Turfgrasses are often exposed to different shade environments in conjunction with traffic stresses (wear and/or compaction) in athletic fields within stadiums. The objective of this study was to assess the effects of morning shade (AMS) and afternoon shade (PMS) alone and in combination with wear and wear plus soil compaction on `Sea Isle 1 seashore paspalum (Paspalum vaginatum Swartz). The study was conducted using two consecutive field trials under sports field conditions from 9 July to 10 Sept. 2001 at the Univ. of Georgia Experiment Station at Griffin. “T” shaped structures constructed of plywood on the sports field were used to provide §90% morning and afternoon shade, respectively, and were in place for 1 year prior to data accumulation. A wear device and a studded roller device simulated turfgrass wear (WD) and wear plus soil compaction (WSC), respectively, to the shaded plots. Only minor differences in turf color, density, or canopy spectral reflectance were found between AMS and PMS under no-traffic treatments in both trials. Grasses under WD generally recovered faster than those exposed to WSC across all light levels, including full sunlight (FL), AMS, and PMS. AMS combined with WD treatment had an average 9% higher rating of color, 11% higher density, and 28% less tissue injury than that of PMS with WD at 7 days after traffic treatment (DAT). Compared to PMS with WSC treatment at 7 DAT, AMS with WSC had 12% higher rating of color, 9% higher density, and 4% less tissue injury. AMS with WD treatment exhibited 11% higher normalized difference vegetation index (NDVI), 4% higher canopy water band index (CWBI), and 13% lower stress index than that of PMS with WD at 7 DAT. AMS with WSC, relative to PMS with WSC, demonstrated 8% higher NDVI, 3% higher CWBI, and 8% lower stress index at 7 DAT. Re sults indicated that AMS (i.e., afternoon sunlight) had less detrimental influences than PMS (i.e., morning sunlight) on turfgrass performance after it was subjected to wear stress or wear plus soil compaction.

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Practical Applications of a Multisensor UAV Platform Based on Multispectral, Thermal and RGB High Resolution Images in Precision Viticulture

Agriculture ◽

10.3390/agriculture8070116 ◽

2018 ◽

Vol 8 (7) ◽

pp. 116 ◽

Cited By ~ 30

Author(s):

Alessandro Matese ◽

Salvatore Di Gennaro

Keyword(s):

Water Stress ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Stress Index ◽

Crop Water Stress Index ◽

Practical Applications ◽

Water Stress Index ◽

Sensing Applications ◽

Wide Range ◽

Precision Viticulture

High spatial ground resolution and highly flexible and timely control due to reduced planning time are the strengths of unmanned aerial vehicle (UAV) platforms for remote sensing applications. These characteristics make them ideal especially in the medium–small agricultural systems typical of many Italian viticulture areas of excellence. UAV can be equipped with a wide range of sensors useful for several applications. Numerous assessments have been made using several imaging sensors with different flight times. This paper describes the implementation of a multisensor UAV system capable of flying with three sensors simultaneously to perform different monitoring options. The intra-vineyard variability was assessed in terms of characterization of the state of vines vigor using a multispectral camera, leaf temperature with a thermal camera and an innovative approach of missing plants analysis with a high spatial resolution RGB camera. The normalized difference vegetation index (NDVI) values detected in different vigor blocks were compared with shoot weights, obtaining a good regression (R2 = 0.69). The crop water stress index (CWSI) map, produced after canopy pure pixel filtering, highlighted the homogeneous water stress areas. The performance index developed from RGB images shows that the method identified 80% of total missing plants. The applicability of a UAV platform to use RGB, multispectral and thermal sensors was tested for specific purposes in precision viticulture and was demonstrated to be a valuable tool for fast multipurpose monitoring in a vineyard.

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Correlation Analysis Procedures for Canopy Spectral Reflectance Data of Seashore Paspalum under Traffic Stress

Journal of the American Society for Horticultural Science ◽

10.21273/jashs.128.3.0343 ◽

2003 ◽

Vol 128 (3) ◽

pp. 343-348 ◽

Cited By ~ 15

Author(s):

Yiwei Jiang ◽

Robert N. Carrow ◽

Ronny R. Duncan

Keyword(s):

Spectral Reflectance ◽

Soil Compaction ◽

Canopy Temperature ◽

Quality Analysis ◽

Stress Index ◽

Canopy Reflectance ◽

Seashore Paspalum ◽

First Derivative ◽

Turf Quality ◽

Optimum Position

Traffic stresses often cause a decline in turfgrass quality. Analysis of spectral reflectance is valuable for assessing turfgrass canopy status. The objectives of this study were to determine correlations of narrow band canopy reflectance and selected reflectance indices with canopy temperature and turf quality for seashore paspalum exposed to wear and wear plus soil compaction traffic stresses, and to evaluate the effects of the first derivative of reflectance and degree of data smoothing (spectral manipulations) on such correlations. `Sea Isle 1' seashore paspalum (Paspalum vaginatum Swartz) was established on a simulated sports field during 1999 and used for this study. Compared to original reflectance, the first derivative of reflectance increased the correlation coefficient (r) of certain wavelengths with canopy temperature and turf quality under both traffic stresses. Among 217 wavelengths tested between 400 and 1100 nm, the peak correlations of the first derivative of reflectance occurred at 661 nm and 664 nm for both canopy temperature and turf quality under wear stress, respectively, while the highest correlations were found at 667 nm and 820 to 869 nm for both variables under wear plus soil compaction. Collectively, the first derivative of reflectance at 667 nm was the optimum position to determine correlation with canopy temperature (r > 0.62) and turf quality (r < -0.72) under both traffic stresses. All correlations were not sensitive to degrees of smoothing of reflectance from 400 to 1100 nm. A ratio of R936/R661 (IR/R, Infrared/red) and R693/759 (stress index) had the strongest correlations with canopy temperature for wear (r = -0.63) and wear plus soil compaction (r = 0.66), respectively; and a ratio of R693/R759 had the strongest correlation with turf quality for both wear (r = -0.89) and wear plus soil compaction (r = -0.82). The results suggested that the first derivative of reflectance could be used to estimate any single wavelength simultaneously correlated with multiple turf canopy variables such as turf quality and canopy temperature, and that the stress index (R693/R759) was also a good indicator of canopy stress status.

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Assessing Hemlock Decline Using Visible and Near-Infrared Spectroscopy: Indices Comparison and Algorithm Development

Applied Spectroscopy ◽

10.1366/0003702054280595 ◽

2005 ◽

Vol 59 (6) ◽

pp. 836-843 ◽

Cited By ~ 24

Author(s):

Jennifer Pontius ◽

Richard Hallett ◽

Mary Martin

Keyword(s):

Linear Regression ◽

Vegetation Index ◽

Near Infrared ◽

Normalized Difference Vegetation Index ◽

Accuracy Assessment ◽

Stress Index ◽

Regression Equations ◽

Near Infrared Reflectance ◽

Full Spectrum ◽

Hemlock Decline

Near-infrared reflectance spectroscopy was evaluated for its effectiveness at predicting pre-visual decline in eastern hemlock trees. An ASD FieldSpec Pro FR field spectroradiometer measuring 2100 contiguous 1-nm-wide channels from 350 nm to 2500 nm was used to collect spectra from fresh hemlock foliage. Full spectrum partial least squares (PLS) regression equations and reduced stepwise linear regression equations were compared. The best decline predictive model was a 6-term linear regression equation ( R2 = 0.71, RMSE = 0.591) based on: Carter Miller Stress Index (R694/R760), Derivative Chlorophyll Index (FD705/FD723), Normalized Difference Vegetation Index ((R800 – R680)/(R800 + R680)), R950, R1922, and FD1388. Accuracy assessment showed that this equation predicted an 11-class decline rating with a 1-class tolerance accuracy of 96% and differentiated healthy trees from those in very early decline with 72% accuracy. These results indicate that narrow-band sensors could be developed to detect very early stages of hemlock decline, before visual symptoms are apparent. This capability would enable land managers to identify early hemlock woolly adelgid infestations and monitor forest health over large areas of the landscape.

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USE OF GREENDRONE UAS SYSTEM FOR MAIZE CROP MONITORING

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-2-w6-263-2017 ◽

2017 ◽

Vol XLII-2/W6 ◽

pp. 263-268 ◽

Cited By ~ 2

Author(s):

A. K. Nasir ◽

M. Tharani

Keyword(s):

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Low Cost ◽

Research Work ◽

Aerial Images ◽

Stress Index ◽

Maize Crop ◽

Crop Monitoring ◽

Water Stress Index ◽

Long Endurance

This research work presents the use of a low-cost Unmanned Aerial System (UAS) – GreenDrone for the monitoring of Maize crop. GreenDrone consist of a long endurance fixed wing air-frame equipped with a modified Canon camera for the calculation of Normalized Difference Vegetation Index (NDVI) and FLIR thermal camera for Water Stress Index (WSI) calculations. Several flights were conducted over the study site in order to acquire data during different phases of the crop growth. By the calculation of NDVI and NGB images we were able to identify areas with potential low yield, spatial variability in the plant counts, and irregularities in nitrogen application and water application related issues. Furthermore, some parameters which are important for the acquisition of good aerial images in order to create quality Orthomosaic image are also discussed.

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Seasonal dynamics of lingonberry and blueberry spectra

Silva Fennica ◽

10.14214/sf.10150 ◽

2019 ◽

Vol 53 (2) ◽

Author(s):

Petri Forsström ◽

Jouni Peltoniemi ◽

Miina Rautiainen

Keyword(s):

Vegetation Index ◽

Near Infrared ◽

Normalized Difference Vegetation Index ◽

Reference Data ◽

Leaf Growth ◽

Vegetation Indices ◽

Growing Season ◽

Moisture Stress ◽

Stress Index ◽

Infrared Spectral

Accurate mapping of the spatial distribution of understory species from spectral images requires ground reference data which represent the prevailing phenological stage at the time of image acquisition. We measured the spectral bidirectional reflectance factors (BRFs, 350â2500 nm) at varying view angles for lingonberry ( L.) and blueberry ( L.) throughout the growing season of 2017 using Finnish Geospatial Research Instituteâs FIGIFIGO field goniometer. Additionally, we measured spectra of leaves and berries of both species, and flowers of lingonberry. Both lingonberry and blueberry showed seasonality in visible and near-infrared spectral regions which was linked to occurrences of leaf growth, flowering, berrying, and leaf senescence. The seasonality of spectra differed between species due to different phenologies (evergreen vs. deciduous). Vegetation indices, normalized difference vegetation index (NDVI), moisture stress index (MSI), plant senescence reflectance index (PSRI), and red-edge inflection point (REIP2), showed characteristic seasonal trends. NDVI and PSRI were sensitive to the presence of flowers and berries of lingonberry, while with blueberry the effects were less evident. Off-nadir observations supported differentiating the dwarf shrub species from each other but showed little improvement for detection of flowers and berries. Lingonberry and blueberry can be identified by their spectral signatures if ground reference data are available over the entire growing season. The spectral data measured in this study are reposited in the publicly open SPECCHIO Spectral Information System.Vaccinium vitis-idaeaVaccinium myrtillus

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Salinity Tolerance and Recovery Attributes of Warm-season Turfgrass Cultivars

HortScience ◽

10.21273/hortsci13963-19 ◽

2019 ◽

Vol 54 (9) ◽

pp. 1625-1631 ◽

Cited By ~ 1

Author(s):

Manuel Chavarria ◽

Benjamin Wherley ◽

James Thomas ◽

Ambika Chandra ◽

Paul Raymer

Keyword(s):

Salinity Stress ◽

Salinity Tolerance ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Recovery Period ◽

Warm Season ◽

Shoot Biomass ◽

Seashore Paspalum ◽

Turf Quality ◽

Elevated Salinity

As population growth places greater pressures on potable water supplies, nonpotable recycled irrigation water is becoming widely used on turfgrass areas including golf courses, sports fields, parks, and lawns. Nonpotable recycled waters often have elevated salinity levels, and therefore turfgrasses must, increasingly, have good salinity tolerance to persist in these environments. This greenhouse study evaluated 10 commonly used cultivars representing warm-season turfgrass species of bermudagrass (Cynodon spp.), zoysiagrass (Zoysia spp.), st. augustinegrass [Stenotaphrum secundatum (Walt.) Kuntze], and seashore paspalum (Paspalum vaginatum Swartz) for their comparative salinity tolerance at electrical conductivity (EC) levels of 2.5 (control), 15, 30, and 45 dS·m–1. Salinity treatments were imposed on the grasses for 10 weeks via subirrigation, followed by a 4-week freshwater recovery period. Attributes, including turf quality, the normalized difference vegetation index (NDVI), canopy firing, and shoot biomass reductions were evaluated before and after salinity stress, as well as after the 4-week freshwater recovery period. Results showed considerable differences in salinity tolerance among the cultivars and species used, with the greatest tolerance to elevated salinity noted within seashore paspalum cultivars and Celebration® bermudagrass. In comparison with growth in 2.5-dS·m–1 control conditions, increased shoot growth and turf quality were noted for many bermudagrass and seashore paspalum cultivars at 15 dS·m–1. However, st. augustinegrass and some zoysiagrass cultivars responded to elevated salinity with decreased growth and turf quality. No cultivars that had been exposed to 30- or 45-dS·m–1 salinity recovered to acceptable levels, although bermudagrass and seashore paspalum recovered to acceptable levels after exposure to 15-dS·m–1 salinity. More severe salinity stress was noted during year 2, which coincided with greater greenhouse temperatures relative to year 1.

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Vineyard Variability Analysis through UAV-Based Vigour Maps to Assess Climate Change Impacts

Agronomy ◽

10.3390/agronomy9100581 ◽

2019 ◽

Vol 9 (10) ◽

pp. 581 ◽

Cited By ~ 9

Author(s):

Luís Pádua ◽

Pedro Marques ◽

Telmo Adão ◽

Nathalie Guimarães ◽

António Sousa ◽

...

Keyword(s):

Climate Change ◽

Water Stress ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Crop Yields ◽

Moisture Stress ◽

Temporal Analysis ◽

Stress Index ◽

Crop Water Stress Index ◽

Multi Temporal

Climate change is projected to be a key influence on crop yields across the globe. Regarding viticulture, primary climate vectors with a significant impact include temperature, moisture stress, and radiation. Within this context, it is of foremost importance to monitor soils’ moisture levels, as well as to detect pests, diseases, and possible problems with irrigation equipment. Regular monitoring activities will enable timely measures that may trigger field interventions that are used to preserve grapevines’ phytosanitary state, saving both time and money, while assuring a more sustainable activity. This study employs unmanned aerial vehicles (UAVs) to acquire aerial imagery, using RGB, multispectral and thermal infrared sensors in a vineyard located in the Portuguese Douro wine region. Data acquired enabled the multi-temporal characterization of the vineyard development throughout a season through the computation of the normalized difference vegetation index, crop surface models, and the crop water stress index. Moreover, vigour maps were computed in three classes (high, medium, and low) with different approaches: (1) considering the whole vineyard, including inter-row vegetation and bare soil; (2) considering only automatically detected grapevine vegetation; and (3) also considering grapevine vegetation by only applying a normalization process before creating the vigour maps. Results showed that vigour maps considering only grapevine vegetation provided an accurate representation of the vineyard variability. Furthermore, significant spatial associations can be gathered through (i) a multi-temporal analysis of vigour maps, and (ii) by comparing vigour maps with both height and water stress estimation. This type of analysis can assist, in a significant way, the decision-making processes in viticulture.

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Crop Sensor Based Non-destructive Estimation of Nitrogen Nutritional Status, Yield, and Grain Protein Content in Wheat

Agriculture ◽

10.3390/agriculture10050148 ◽

2020 ◽

Vol 10 (5) ◽

pp. 148 ◽

Cited By ~ 2

Author(s):

Marta Aranguren ◽

Ander Castellón ◽

Ana Aizpurua

Keyword(s):

Protein Content ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Plant Biomass ◽

Nitrogen Nutrition ◽

Stem Elongation ◽

Field Trials ◽

Grain Protein Content ◽

Grain Protein ◽

Single Model

Minimum NNI (Nitrogen Nutrition Index) values have been developed for each key growing stage of wheat (Triticum aestivum) to achieve high grain yields and grain protein content (GPC). However, the determination of NNI is time-consuming. This study aimed to (i) determine if the NNI can be predicted using the proximal sensing tools RapidScan CS-45 (NDVI (Normalized Difference Vegetation Index) and NDRE (Normalized Difference Red Edge)) and Yara N-TesterTM and if a single model for several growing stages could be used to predict the NNI (or if growing stage-specific models would be necessary); (ii) to determine if yield and GPC can be predicted using both tools; and (iii) to determine if the predictions are improved using normalized values rather than absolute values. Field trials were established for three consecutive growing seasons where different N fertilization doses were applied. The tools were applied during stem elongation, leaf-flag emergence, and mid-flowering. In the same stages, the plant biomass was sampled, N was analyzed, and the NNI was calculated. The NDVI was able to estimate the NNI with a single model for all growing stages (R2 = 0.70). RapidScan indexes were able to predict the yield at leaf-flag emergence with normalized values (R2 = 0.70–0.76). The sensors were not able to predict GPC. Data normalization improved the model for yield but not for NNI prediction.

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The Salinity Tolerance of Seeded-type Common Bermudagrass Cultivars and Experimental Selections

HortTechnology ◽

10.21273/horttech03975-18 ◽

2018 ◽

Vol 28 (3) ◽

pp. 276-283 ◽

Cited By ~ 2

Author(s):

Mingying Xiang ◽

Justin Q. Moss ◽

Dennis L. Martin ◽

Yanqi Wu

Keyword(s):

Salinity Tolerance ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Cynodon Dactylon ◽

Block Design ◽

Seashore Paspalum ◽

Green Cover ◽

Salinity Levels ◽

The Common ◽

Common Bermudagrass

Turfgrass managers are using reclaimed water as an irrigation resource because of the decreasing availability and increasing cost of fresh water. Much attention, thereby, has been drawn to select salinity-tolerant turfgrass cultivars. An experiment was conducted to evaluate the relative salinity tolerance of 10 common bermudagrasses (Cynodon dactylon) under a controlled environment in a randomized complete block design with six replications. ‘SeaStar’ seashore paspalum (Paspalum vaginatum) was included in this study as a salinity-tolerant standard. All entries were tested under four salinity levels (1.5, 15, 30, and 45 dS·m−1) consecutively using subirrigation systems. The relative salinity tolerance among entries was determined by various parameters, including the normalized difference vegetation index (NDVI), percentage green cover determined by digital image analysis (DIA), leaf firing (LF), turf quality (TQ), shoot vertical growth (VG), and dark green color index (DGCI). Results indicated that salinity tolerance varied among entries. Except LF, all parameters decreased as the salinity levels of the irrigation water increased. ‘Princess 77’ and ‘Yukon’ provided the highest level of performance among the common bermudagrass entries at the 30 dS·m−1 salinity level. At 45 dS·m−1, the percent green cover as measured using DIA varied from 4.97% to 16.11% among common bermudagrasses, where ‘SeaStar’ with a DIA of 22.92% was higher than all the common bermudagrass entries. The parameters LF, TQ, NDVI, DGCI, VG, and DIA were all correlated with one another. Leaf firing had the highest correlation with other parameters, which defined its value as a relative salinity tolerance measurement for common bermudagrass development and selection.

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Transpiration and Normalized Difference Vegetation Index Response of Seashore Paspalum to Soil Drying

HortScience ◽

10.21273/hortsci.44.7.2046 ◽

2009 ◽

Vol 44 (7) ◽

pp. 2046-2048 ◽

Cited By ~ 6

Author(s):

Georgene L. Johnson ◽

Thomas R. Sinclair ◽

Kevin Kenworthy

Keyword(s):

Plant Species ◽

Transpiration Rate ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Leaf Gas Exchange ◽

Organic Soil ◽

Soil Drying ◽

Seashore Paspalum ◽

Consistent Response ◽

Reflectance Measurements

A consistent response has been observed among many plant species in their leaf gas exchange as soils are subjected to a drying cycle; except for one case, these studies have not included turfgrass species. The current study reports the change in transpiration rate of six genotypes of seashore paspalum (Paspalum vaginatum Swartz) during soil drying when grown on either an organic soil or sand. On organic soil, the response was consistent with results with other plant species in that there was no decline in transpiration rate until the fraction of transpirable soil water (FTSW) reached the range of 0.25 to 0.31. The decline in transpiration rate when plants were grown on sand occurred in the FTSW range of 0.10 to 0.17, which was also consistent with reports for other species when grown on sand. The lower FTSW for the decline in transpiration rate on sand appears to be a result of the greater retention of water in fully wetted sand in pot experiments as compared with field conditions. Because the decline in transpiration occurred at a higher FTSW in ‘SeaIsle Supreme’, ‘Aloha’, and ‘SeaIsle 1’ than in ‘SeaIsle 2000’, this is an indication that these genotypes are water-conserving and may be better suited to water-deficit conditions. Quality changes in these grasses were monitored daily during the drying cycle by reflectance measurements of their normalized difference vegetation index (NDVI). No change in NDVI was observed for grasses grown on either soil type until the soil had become very dry and transpiration had decreased to low rates.

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