Application of UAV Remote Sensing in Monitoring Banana Fusarium Wilt

Fusarium wilt poses a current threat to worldwide banana plantation areas. To treat the Fusarium wilt disease and adjust banana planting methods accordingly, it is important to introduce timely monitoring processes. In this chapter, the multispectral images acquired by unmanned aerial vehicle (UAV) was used to establish a method to identify which banana regions were infected or uninfected with Fusarium wilt disease. The vegetation indices (VIs), including the normalised difference vegetation index (NDVI), normalised difference red edge index (NDRE), structural independent pigment index (SIPI), red-edge structural independent pigment index (SIPIRE), green chlorophyll index (CIgreen), red-edge chlorophyll index (CIRE), anthocyanin reflectance index (ARI), and carotenoid index (CARI), were selected for deciding the biophysical and biochemical characteristics of the banana plants. The relationships between the VIs and those plants infected or uninfected with Fusarium wilt were assessed using the binary logistic regression method. The results suggest that UAV-based multispectral imagery with a red-edge band is effective to identify banana Fusarium wilt disease, and that the CIRE had the best performance.

ASSESSMENT AND DIAGNOSTIC INDICATORS OF ORGANIC MATTER QUALITATIVE COMPOSITION OF YAROSLAVL VOLGA REGION POST-AGROGENIC SOILS AGAINST THE BACKGROUND OF MODERN CLIMATE CHANGES

The purpose of this work was to characterize the postagrogenic transformation of soil organic matter (SOM). For decision of this purpose the results of chemodestructive fractionation (CDF), the content of chlorophylls a and b , pheophetins and carotenoids, and Margalef's pigment index (PI) were used newly. Subjects of inquiry-humus horizons of soils of arable lands and fallow areas of Poshekhonsky district of the Yaroslavl region of the Russian Federation-were stitch together into two groups with differ in the type of land use. In one of them, the soils remained arable for 30-40 years (arable-arable group), in the other - the soils of arable land for the same time period were transferred to the fallow (arable-fallow group). It was found that increasing the soil water content of fallow plots compared to arable soils can lead: to improved livelihoods of the soil algocenoses (the value of PI Margalef decreased) to increase the carbon content of organic compounds, to increase the number legkomyslenno fraction in the organic component of soil, increased hydrolytic processes that reduce the content of carotenoids and chlorins (in particular, pheophytinand chlorophylls a and b) in SOM composition. Thus, results of CDF and content of chlorophylls a and b , pheophetins and carotenoids can be used to assess the postagrogenic transformation of SOM, and Margalef's PI-to characterize soil algocenosis.

DETECTION OF BACTERIAL WILT DISEASE (<i>PSEUDOMONAS SOLANCEARUM</i>) IN BRINJAL USING HYPERSPECTRAL REMOTE SENSING

<p><strong>Abstract.</strong> Bacterial wilt disease (pathogen: <i>Pseudomonas solancearum</i>) is a major problem affecting brinjal crop. Infected leaves show yellowing, loss in turgidity, drying and ultimately the entire plant collapses. The study aims to examine the potential of hyperspectral remote sensing for detection of biotic stress caused due to bacterial wilt disease and identify best spectral band widths and hyperspectral indices indicative of disease infestation. This study was conducted in a farmer’s plot at Alampur in Baruipur block, South 24 Pargana district, West Bengal. Canopy spectra (using ASD Fieldspec 2 Spectroradiometer), chlorophyll content (by Chlorophyll meter) and Leaf Area Index (LAI) (by plant canopy imager) were collected. The healthy plants had green and fully turgid leaves whereas diseased plants had lower chlorophyll content and LAI. The reduction in chlorophyll content lowered reflectance in green region and internal leaf damage in near-infrared region. A correlation analysis was carried out between reflectance at specific bandwidths and hyperspectral indices with chlorophyll content and LAI of healthy and stressed plants. Bandwidths of 528&amp;ndash;531&amp;thinsp;nm, 550&amp;ndash;570&amp;thinsp;nm, 710&amp;ndash;760&amp;thinsp;nm, and single bands such as 800&amp;thinsp;nm and 920&amp;thinsp;nm and indices viz. Greenness index, Modified Chlorophyll Absorption in Reflectance Index (MCARI), Transformed Chlorophyll Absorption in Reflectance Index (TCARI), Triangular Vegetation Index (TVI), Simple Ratio Pigment Index (SRPI), Photochemical Reflectance Index (PRI 2), Lichtenthaler Indices (LIC1, LIC2), Structure Intensive Pigment Index (SIPI) etc. were found to have strong positive correlation (R²&amp;thinsp;&amp;gt;&amp;thinsp;0.9) with plant parameters. These specific bandwidths and indices can be helpful in biophysical parameter estimation and early detection of crop stress, crop growth and disease monitoring.</p>

Technical note: Algal Pigment Index 2 in the Atlantic off the southwest Iberian Peninsula: standard and regional algorithms

In this study, Algal Pigment Index 2 (API2) is investigated in Sagres, an area located in the Atlantic off the southwestern Iberian Peninsula. Standard results provided by the MEdium Resolution Image Spectrometer (MERIS) ocean colour sensor were compared with alternative data products, determined through a regional inversion scheme, using both MERIS and in situ remote sensing reflectances (Rrs) as input data. The reference quantity for performance assessment is in situ total chlorophyll a (TChl a) concentration estimated through a phytoplankton absorption coefficient (i.e. equivalent to API2). Additional comparison of data products has also been addressed for TChl a concentration determined by high-performance liquid chromatography. The MERIS matchup analysis revealed a systematic underestimation of TChl a, which was confirmed with an independent comparison of product map analysis. The study demonstrates the importance of regional algorithms for the study area that could complement upcoming standard results of the current Sentinel-3/OLCI space mission.

Technical Note: Algal Pigment Index 2 in the Atlantic off the Southwest Iberian Peninsula: standard and regional algorithms

In this study, Algal Pigment Index 2 (API2) is investigated in Sagres, an area located in the Atlantic off the southwestern Iberian Peninsula. Standard results provided by MEdium Resolution Image Spectrometer (MERIS) ocean color sensor were compared with alternative data products, determined through a regional inversion scheme, using both MERIS and in situ remote sensing reflectances (Rrs) as input data. The reference quantity for performance assessment is in situ total chlorophyll a (TChla) concentration estimated through phytoplankton absorption coefficient (i.e., equivalent to API2). Additional comparison of data products has also been addressed to TChla concentration determined by High Performance Liquid Chromatography. The MERIS matchup analysis revealed a systematic underestimation of TChla, which was confirmed with an independent comparison of product maps analysis. The study demonstrates the importance of regional algorithms for the study area that could complement upcoming standard results of the present Sentinel-3/OLCI space mission.

Assessment of MERIS ocean color data products for European seas

The accuracy of marine data products from the Medium Resolution Imaging Spectrometer (MERIS) operated on board the Envisat platform is investigated with the aid of in situ geographically distributed measurements from different European seas. The assessment focuses on standard products from the 2012 data update commonly identified as 3rd Reprocessing. Results indicate atmospherically corrected data affected by a negative bias of several tens percent at the 413 nm center wavelength, significantly decreasing to a few percent at 560 nm and increasing again at 665 nm. Such an underestimate at the blue center wavelengths leads to an average overestimate of the algal-1 MERIS pigment index largely exceeding 100% for the considered European seas. A comparable overestimate is also observed for the algal-2 pigment index independently determined from top-of-atmosphere radiance through the application of neural networks.

Assessment of MERIS ocean color data products for European seas

The accuracy of marine data products from the Medium Resolution Imaging Spectrometer (MERIS) operated onboard the Envisat platform, is investigated with the aid of in situ geographically distributed measurements from different European seas. The assessment focusses on standard products from the 2012 data update commonly identified as 3rd Reprocessing. Results indicate atmospherically corrected data affected by a negative bias of several tens percent at the 413 nm center-wavelength, significantly decreasing to a few percent at 560 nm and increasing again at 665 nm. Such an underestimate at the blue center-wavelengths leads to an average overestimate of the algal-1 MERIS pigment index largely exceeding 100% for the considered European seas. A comparable overestimate is also observed for the algal-2 pigment index independently determined from top-of-atmosphere radiance through the application of neural networks.