Spectral reflectance of healthy and diseased watermelon leaves

Blazquez, C. H.; Edwards, G. J.

doi:10.1111/j.1744-7348.1986.tb07646.x

Cited by 55 publications

(12 citation statements)

References 9 publications

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“…Leaf reflectance changes in response to eight stress agents including pathogens have been documented for six vascular plant species (Carter 1993). There have also been reports of field experiments using ground-based radiometers to assess the severity of watermelon disease (Blazquez and Edwards 1986), various leaf and root diseases (Nilsson 1991), anther smut disease in Silene dioica (Nilsson and Carlsson 1994), barley stripe disease (Nilsson and Johnsson 1996) and Rhizoctonia blight in creeping bentgrass (Raikes and Burpee 1998). As the incidence of panicle blast increased at the dough stage, R470/R570 (reflectance at 470 nm divided by reflectance at 570 nm), R520/R675, and R570/R675 decreased significantly (Kobayashi et al 2001).…”

Section: Introductionmentioning

confidence: 98%

Ratio of rice reflectance for estimating leaf blast severity with a multispectral radiometer

Kobayashi

Kanda

Naito

et al. 2003

Journal of General Plant Pathology

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Rice reflectance was measured to determine the spectral regions most sensitive to leaf blast infection with a multispectral radiometer. As disease severity increased, reflectance also increased in the 400-500 nm (blue), 570-700 nm (red), and 900-2000 nm regions but decreased in the 500-570 nm and 700-900 nm regions. The increased reflectance in the blue and red regions may be attributed to decreased chlorophyll and carotenoid contents in response to the blast infection. The maximum and minimum reflectance differences occurred at 680 nm and 760 nm for the nondiseased and diseased rice, respectively. The spectral location of maximum sensitivity was 675 nm regardless of disease severity. Rice reflectance ratios were evaluated as indicators of leaf blast severity. Two ratios, R550/R675 (reflectance at 550 nm divided by reflectance at 675 nm), and R570/R675 quantified the significant disease severity. These wavelengths were selected based on the sensitivity minima and maxima. The ratios of nondiseased rice plants varied depending on growth stage. The variation in ratios must be considered when they are used to estimate leaf blast severity.

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Section: Introductionmentioning

confidence: 98%

Ratio of rice reflectance for estimating leaf blast severity with a multispectral radiometer

Kobayashi

Kanda

Naito

et al. 2003

Journal of General Plant Pathology

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“…Duggar] on cotton. Blazquez and Edwards (1986) found that diseased watermelon (Citrullus vulgaris Schrad.) leaves had lower reflectance values in later stages of disease development as opposed to early stages.…”

Section: Introductionmentioning

confidence: 98%

Evaluating Remote Sensing for Determining and Classifying Soybean Anomalies

Shaw

Kelley

2005

Precision Agric

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Two soybean fields were monitored in 2001 and 2002 to determine the utility of multispectral imagery for locating and classifying crop anomalies. Crop anomalies may be due to planter problems, soil problems, weed infestations and stressed soybean plants. Three image collection dates per location for each year were used in a supervised classification analysis. In 2002, aerial images were evaluated for potential use as a directed scouting tool. Remotely sensed data as a scouting tool detected 50-100% of anomalies detected by ground truthing. The number of anomalies detected by aerial imagery decreased through the growing season, while the number of anomalies found from directed scouting remained relatively constant. Thus, agreement was higher later in the growing season, since remote sensing was detecting more anomalies than the ground truthing efforts did. Excluding bare soil and healthy soybean situations, anomalies due to stress on soybean plants in the form of iron chlorosis and stunted plants yielded highest classification accuracies, ranging from 83% to 90% both years. This is attributed to differences in coloration of soybean plants with iron chlorosis and lack of full canopy coverage of stunted soybean. Herbicide damage due to overlap of spray boom led to classification accuracies from 50% to 67%. The overlap of the spray boom was not widespread in the field; thus, fewer areas of interests could be constructed for testing purposes, which may explain the decrease in classification accuracies.

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“…Multispectral radiometers that are held above the crop canopy are common remote-sensing instruments that have been used to quantify foliar disease intensity and yield losses in a range of pathosystems (7,20,21,33,35,43). These studies have detected significant quantitative relationships between percentage of reflectance measurements and foliar disease intensity.…”

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confidence: 99%

Use of a Multispectral Radiometer for Noninvasive Assessments of Foliar Disease Caused by Ray Blight in Pyrethrum

et al. 2007

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. Use of a multispectral radiometer for noninvasive assessments of foliar disease caused by ray blight in pyrethrum. Plant Dis. 91:1397-1406.Foliar disease due to ray blight (Phoma ligulicola) in pyrethrum was quantified at three locations over 2 years in Tasmania, Australia. To obtain a range of ray blight disease intensities, replicated plots were treated with fungicides that varied in efficacy to control ray blight. Visual disease assessments and measurement of canopy reflectance were made at least once during spring (September through December). Visual assessments involved removal of flowering stems at ground level from which measurements of defoliation severity and the incidence of stems with ray blight were obtained. Reflectance of sunlight from pyrethrum canopies was measured at 485, 560, 660, 830, and 1,650 nm using a handheld multispectral radiometer. Measurements from these wavelengths also were used to calculate all possible reflectance ratios, as well as four vegetative indices. Relationships between wavelength bands, reflectance ratios, vegetative indices, and disease intensity measures were described by linear regression analyses. Several wavelength bands, ratios, and vegetative indices were significantly related in a linear fashion to visual measures of disease intensity. The most consistent relationships, with high R 2 and low coefficients of variation values, varied with crop growth stage over time. The ratio 830/560 was identified as the best predictor of stem height, defoliation severity, and number of flowers produced on each stem in October. However, reflectance within the near-infrared range (830 nm) and the difference vegetative index was superior in November. The use of radiometric assessment of disease was noninvasive and provided savings in disease assessment time, which is critical where visual assessment is difficult and requires destructive sampling, as with pyrethrum.

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Spectral reflectance of healthy and diseased watermelon leaves

Cited by 55 publications

References 9 publications

Ratio of rice reflectance for estimating leaf blast severity with a multispectral radiometer

Ratio of rice reflectance for estimating leaf blast severity with a multispectral radiometer

Evaluating Remote Sensing for Determining and Classifying Soybean Anomalies

Use of a Multispectral Radiometer for Noninvasive Assessments of Foliar Disease Caused by Ray Blight in Pyrethrum

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