Spectral reflectance pattern in soybean for assessing yellow mosaic disease

Gazala, I. F. Saad; Sahoo, Rabi Narayan; Pandey, Rakesh; Mandal, Bikash; Gupta, Vinod Kumar; Singh, Rajendra; Sinha, Parimal

doi:10.1007/s13337-013-0161-0

Cited by 63 publications

(21 citation statements)

References 37 publications

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“…Diseased plants usually exhibit discrete lesions on leaves, corresponding to necrotic or chlorotic regions, with greater reflectance values in the visible range [ 16 ]. A sharp transition from low to high reflectance usually occurs in the wavelengths between the visible and the NIR regions (around 700 nm), and this transition usually shifts to shorter wavelengths in diseased crops [ 17 ]. The first derivative reflectance allows to easily compute the wavelength were this transition occurs.…”

Section: Introductionmentioning

confidence: 99%

Leaf and canopy reflectance spectrometry applied to the estimation of angular leaf spot disease severity of common bean crops

et al. 2018

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This study is aimed at (i) estimating the angular leaf spot (ALS) disease severity in common beans crops in Brazil, caused by the fungus Pseudocercospora griseola, employing leaf and canopy spectral reflectance data, (ii) evaluating the informative spectral regions in the detection, and (iii) comparing the estimation accuracy when the reflectance or the first derivative reflectance (FDR) is employed. Three data sets of useful spectral reflectance measurements in the 440 to 850 nm range were employed; measurements were taken over the leaves and canopy of bean crops with different levels of disease. A system based in Principal Component Analysis (PCA) and Artificial Neural Networks (ANN) was developed to estimate the disease severity from leaf and canopy hyperspectral reflectance spectra. Levels of disease to be taken as true reference were determined from the proportion of the total leaf surface covered by necrotic lesions on RGB images. When estimating ALS disease severity in bean crops by using hyperspectral reflectance spectrometry, this study suggests that (i) successful estimations with coefficients of determination up to 0.87 can be achieved if the spectra is acquired by the spectroradiometer in contact with the leaves, (ii) unsuccessful estimations are obtained when the spectra are acquired by the spectroradiometer from one or more meters above the crop, (iii) the red to near-infrared spectral region (630–850 nm) offers the same precision in the estimation as the blue to near-infrared spectral region (440–850), and (iv) neither significant improvements nor significant detriments are achieved when the input data to the estimation processing system are the FDR spectra, instead of the reflectance spectra.

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Section: Introductionmentioning

confidence: 99%

Leaf and canopy reflectance spectrometry applied to the estimation of angular leaf spot disease severity of common bean crops

et al. 2018

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“…Spectral reflectance (650-900 nm) was measured for all treatments on various days. The leaves with nitrogen deficiency show yellow and pale appearance [32][33][34][35]. Fig.…”

Section: Resultsmentioning

confidence: 99%

Estimating Plant Macronutrients Using VNIR Spectroradiometry

Mani¹,

Shanmugam²

2019

Pol. J. Environ. Stud.

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Leaf nutrient levels are traditionally quantified by laboratory chemical analysis, which is time consuming and requires huge investment. The objective of this research is to estimate the nutrient content of groundnut leaves using an assembled visible near-infrared spectroradiometer (650-900 nm). This method is faster and requires less time and investment compared to conventional chemical analysis. Different fertilizer was applied for different conditions along with one control of groundnut plants. The nutrient deficiency in the groundnut plants was created artificially. The leaf samples were collected in the growth of different days. The samples were analyzed for major nutrient concentrations, which are acquired by field conditions. This research provides the guidelines on the nutrient estimation of the groundnut leaves. The peak reflectance esteem was seen in the infrared range (650-900 nm) and the reflectance value was observed for nitrogen (716 nm), phosphorus (737 nm), and potassium (720 nm). This study may provide guidelines for estimating macronutrients and yield estimation of groundnut plants.

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“…Alteration due to virus infection in leguminous fruits received very little attention. 1,6 Therefore, it was planned to study the effect of CABMV infection on the chemical composition of the cowpea cv. Pusa Dofasali fruits Two lots of 120 cowpea cv.…”

Section: Resultsmentioning

confidence: 99%

Study on Effect of Cabmv Infection on the Changes in Chemical Composition of Cowpea Cv. Pusa Dofasali

YADAV¹,

KUMAR²

2019

Int J Life Sci Pharm Res

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The total nitrogen protein, nitrate nitrogen, nitrite nitrogen, and total free amino acids are higher in CABMV infected cowpea cv. Pusa Dofasali plant parts i.e. leaves, stems and roots than their healthy counterparts. However, the ammoniacal nitrogen was lower in infected plant parts than the healthy ones. The maximum amounts of total nitrogen, protein and total free amino acids was recorded in diseased leaves, nitrate nitrogen, and nitrite nitrogen in diseased roots and ammoniacal nitrogen in healthy leaves. The minimum amounts of total nitrogen, protein, nitrate nitrogen, nitrite nitrogen, ammoniacal nitrogen, and total free amino acids were present in the stem. Generally, nitrogenous fractions showed an increase up to 80 th day of inoculation and afterwards, their concentration decreased. The concentration of total nitrogen, protein, nitrate nitrogen, nitrite nitrogen and total free amino acids was higher in diseased seed but ammoniacal nitrogen was higher in healthy seeds than diseased ones. An increased concentration of nitrogenous fraction in the virus infected plant parts of cowpea was observed. Unless previously fixed nitrogen was effectively used (or) transported elsewhere, the presence of excess nitrogenous compounds could alter the C/N ratio, which might inhibit the normal rate of nitrogen fixation. Virus infection usually brings about drastic changes in many physiological processes such changes were mainly studied with the vegetative parts of the host. Alteration due to virus infection in leguminous fruits received very little attention. Therefore, it was planned to study the effect of CABMV infection on the chemical composition of the cowpea cv. Pusa Dofasali fruits.

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Spectral reflectance pattern in soybean for assessing yellow mosaic disease

Cited by 63 publications

References 37 publications

Leaf and canopy reflectance spectrometry applied to the estimation of angular leaf spot disease severity of common bean crops

Leaf and canopy reflectance spectrometry applied to the estimation of angular leaf spot disease severity of common bean crops

Estimating Plant Macronutrients Using VNIR Spectroradiometry

Study on Effect of Cabmv Infection on the Changes in Chemical Composition of Cowpea Cv. Pusa Dofasali

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