J. K. Kruse, N. E. Christians and M. H. Chaplin
Turfgrass managers must continually monitor their fertilization and irrigation programs to ensure optimal appearance while minimizing losses to the environment and maximizing profit. Characterizing the spatial variability of nutrient and moisture status across a golf course or large sports facility requires careful observation and collection of many soil and tissue samples. Optical remote sensing techniques have been shown to be valuable tools in quickly and reliably identifying stressed plants through the use of various vegetative indices derived from reflectance data collected from the crop canopy. Extensive research has been conducted investigating vegetative indices as they relate to the nutritional and moisture status of various agricultural crops with intriguing results. Handheld remote sensing systems are already being used in evaluating the chlorophyll content of turfgrass stands, which in turn is related to the quality of the turfgrass being grown. The use of remotely sensed data may prove to be a valuable tool in the modification of traditional irrigation and fertility programs to reduce inputs and improve environmental quality. The potential exists for the use of an optical remote sensing system to provide maps indicating the moisture and nutritional status of large turfgrass areas, thus enabling the use of site-specific management techniques which will reduce the application of fertilizers and irrigation.
The objectives of this research are to: 1) Evaluate various indices reported in the literature as tools for identifying moisture and nutrient stressed turf, 2) Develop new indices to be used in detection of moisture and nutrient deficiencies, and 3) Determine differences in spectral response of Creeping Bentgrass, Kentucky Bluegrass, and Perennial Ryegrass.
This interim report will focus on some of the studies conducted to date involving remote sensing of turfgrass nitrogen and potassium status. The nitrogen and potassium studies were organized in a randomized complete block design with four replications each. Each replication in the nitrogen study consisted of three treatments: 0.0, 0.5 and 1.0 lbs N/1000ft2/30d applied as urea with all plots receiving 0.1 lbs P/1000ft2/30d and 0.5 lbs K/1000ft2/30d applied as phosphoric acid and potassium chloride respectively. Each replication in the potassium study consisted of three treatments: 0.0, 0.5 and 1.0 K/1000ft2/30d applied as potassium chloride with each plot receiving 0.1 lbs P/1000ft2/30d applied as phosphoric acid and 1.0 lbs N/1000ft2/30d applied as urea. Treatments were split into two applications once every two weeks, and applied in solution using a CO2 backpack sprayer calibrated to apply 3.0 gallons of water/1000ft2. Irrigation was applied immediately following treatments to reduce the risk of fertilizer burn. The study area consisted of 'Penncross' creeping bentgrass (Agrostis palustris Huds.) established on a USGA sand-based green.
Evaluation of turf quality was made twice a month, coinciding with the collection of remotely sensed data. Quality was ranked on a scale of 9 to 1; with 9=best, 5=lowest acceptable and 1=worst. Optical remote sensing data was collected twice monthly using an OceanOptics SD1000 spectrometer mounted on a self contained cart equipped with a hood to block out ambient sunlight and halogen bulbs to provide a consistent source of illumination on the turf. This system was designed to eliminate the problems typically associated with differences due to shade, which is a common occurrence on many turfgrass areas. The spectrometer was calibrated to measure reflectance from 350-1150 nm with a resolution 1.0 nm. The following growth and stress indices were also evaluated:
Tissue was harvested once monthly following collection of remotely sensed optical data and analyzed for plant nutrient content using standard Total Kejhdahl Nitrogen and Inductively Coupled Argon Plasma Spectroscopy plant analysis procedures.
Nitrogen Content vs. Reflectance
The growth and stress indices were correlated with turf quality, percent nitrogen in the tissue, and chlorophyll content to determine if there was any relationship between them. There was a strong correlation between percent nitrogen in the tissue and the Normalized Difference Vegetation Index (NDVI), SR1 and SR3 indices (r = 0.76, -0.68 and -0.79 respectively). The other indices investigated did not correlate well with percent nitrogen, though SR5, SR6 and SR7 correlated with chlorophyll content in the tissue (r = 0.67, -0.75 and -0.74 respectively). NDVI and SR3 also showed a strong correlation with quality (r = 0.80 and -0.83 respectively) (Table 1).
Table 1. Correlation coefficients for reflectance vs. quality, percent nitrogen and chlorophyll content for the nitrogen study.
| Wavelength† | Quality | Chlorophyll Content | Percent Nitrogen |
|---|---|---|---|
| NDVI | 0.80 | -0.10 | 0.76 |
| SR1 | -0.58 | -0.40 | -0.68 |
| SR2 | 0.16 | -0.55 | 0.03 |
| SR3 | -0.83 | 0.22 | -0.79 |
| SR4 | -0.57 | -0.07 | -0.60 |
| SR5 | -0.36 | 0.67 | -0.24 |
| SR6 | -0.12 | -0.75 | -0.40 |
| SR7 | -0.04 | -0.74 | -0.36 |
† Percentage of reflectance at selected wavelength ratios.
Potassium Content vs. Reflectance
There was little correlation between potassium content of the tissue and the growth and stress indices investigated in this study (Table 2). However, SR1, SR2, SR5, SR6 and SR7 showed high correlation with chlorophyll content of the tissue (r = -0.61, -0.78, 0.74, -0.78 and -0.79 respectively) (Table 2).
Table 2. Correlation coefficients for reflectance vs. quality, percent potassium and chlorophyll content for the potassium study.
| Wavelength† | Quality | Chlorophyll Content | Percent Potassium |
|---|---|---|---|
| NDVI | 0.18 | 0.20 | 0.17 |
| SR1 | -0.20 | -0.61 | -0.28 |
| SR2 | 0.26 | -0.78 | -0.03 |
| SR3 | -0.37 | -0.54 | -0.34 |
| SR4 | -0.11 | -0.32 | -0.14 |
| SR5 | -0.17 | 0.74 | -0.12 |
| SR6 | -0.23 | -0.28 | -0.02 |
| SR7 | -0.31 | -0.79 | -0.01 |
† Percentage of reflectance at selected wavelength ratios.
Discussion
Spectral data appears to be able to discriminate between plots of various qualities when the visual symptoms are obvious, such as those resulting from various nitrogen treatments. It was not surprising to find little correlation between quality and the various indices due to the visual similarities between all the potassium treatments. Several indices showed a correlation with chlorophyll content in both studies, which may prove to be valuable in accessing overall turf quality due to the fact that increasing concentrations of chlorophyll result in a greener turfgrass, which is often associated with higher quality. The strong correlations between the reflectance ratios and nitrogen content indicate the possibility that this technology might be successfully utilized in managing turfgrass nitrogen programs on a site-specific basis.
In addition to the two studies whose preliminary results are discussed here, several moisture studies have been conducted investigating the use of the remote sensing equipment to evaluate the moisture status of turfgrass plants growing under fairway conditions on a golf course. Work is also being done to evaluate the influence of soil amendments on spring green-up and heat stress on the reflectance qualities of a turfgrass stand.
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ISU Turfgrass:2003 Turfgrass Report | College of Agriculture |
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