Spectral Remote Sensing of the Responses of Soybean Plants to Environmental Stresses

Two hуperspectral remote sensing techniques, spectral reflectance and chlorophyll fluorescence, were used for the identification of biotic stress (sharka disease) in plum trees at an early stage without visible symptoms on the leaves. The research was focused on cultivars that are widely spread in Bulgaria: 'Angelina', 'Black Diamond' and 'Mirabelle'. Hyperspectral reflectance and fluorescence data were collected by means of a portable multichannel fibre-optics spectrometer in the visible and near infrared spectral ranges (400-1000 nm). Statistical and deterministic analyses were applied for assessing the significance of the differences between the spectral data of healthy (control) and infected plum leaves. Comparative analyses were performed with complementary serological test DAS-ELISA, broadly implemented in plant virology. The strong relationship that was found between the results from the two remote sensing techniques and serological analysis indicates the applicability of hyperspectral reflectance and fluorescence techniques for conducting health condition assessments of vegetation easily and without damage before the appearance of visible symptoms.Ke y wor d s: chlorophyll fluorescence, DAS-ELISA, hуperspectral remote sensing, leaf reflectance, sharka

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Quantifying the Nitrogen and Water Stress of Maize Using Spectral Vegetation indices

Ramachandiran¹,

Pazhanivelan²,

Amanullah³

et al. 2016

IJBSM

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Numerous spectral vegetation indices have been developed to characterize vegetation canopies. These indices will easily predict or quantify the plant stress at earlier with help of remote sensing techniques. Field experiments were conducted at the Tamil Nadu Agricultural University, Coimbatore, Tamilnadu, India during rabi 2013 with maize crop. To ensure the stressed environment, the crop was subjected to two irrigation levels (CPE: 0.80, 0.50) and five staggered nitrogen levels (0, 50, 75, 100 and 125% of RDN. The experiment was laid out in FRBD with three replication. Measured spectral reflectance curve of maize exhibited a broad low intensity peak centered in the green region at 550 nm and a sharp rise starting at about 685 nm to a plateau in the vicinity of 762 nm under unstressed environment created with irrigation at 0.80 IW/CPE ratio and fertilizer application at 100% RDN. Significant differences in reflectance were established for nitrogen and water stress at green and NIR region. The spectral indices viz., NDVI, GNDVI, RVI, LCI, IR-RED and SR recorded higher value on unstressed maize crop and plants under stress caused reduction in value of these indices at 60 and 90 DAS. All the spectral vegetation indices correlated positively with LAI and SPAD values with a correlation coefficient above 0.80 at both stages. These results highly support the ability of spectral vegetation indices to quantify the combined effect of nitrogen and water stress on maize too earlier through remote sensing.

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Spectral Remote Sensing of the Responses of Soybean Plants to Environmental Stresses

Cited by 3 publications

References 135 publications

Review – Plant nutritional status analysis employing the visible and near-infrared spectroscopy spectral sensor

Review – Plant nutritional status analysis employing the visible and near-infrared spectroscopy spectral sensor

Application of remote sensing techniques for the identification of biotic stress in plum trees caused by the Plum pox virus

Quantifying the Nitrogen and Water Stress of Maize Using Spectral Vegetation indices

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