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Indira V.,Sri Parasakthi College for Women | Dhasarthan P.,Prathyusha Institute of Technology and Management
International Journal of Pharma and Bio Sciences | Year: 2011

Modern intensive agriculture practices resulted in environmental pollution, degradation in soil health, agrochemical residues in soil and economic residues of the crop. This necessitated the need for an alternative production system which would be environmentally safe, ecologically sound and economically viable. Performance of biopesticide reduces the use of fertilizers, enhances better growth and creates a suitable environment for raising crops. As far as the growth of yield parameters were concerned, highest seedling growth was observed in panchakavya treated seedling of Bhendi. The number of flowers, number of fruits, fruit length and number of seeds were measured in the control and various organic manure treated plants at various stages of plant development. Soil nutrients of NPK level were rich in control than biopesticide treated soil samples. NPK level was found high when exposed to biopesticide in the following order panchakavya, A. amara, Albiizzia amura: pongamia treated soils respectively compared to control and other treatments. Thus the investigations suggest that the panchakavya has beneficial effect on growth, yield and nutrient content of Bhendi.

The aim of this work was to study the physico-chemical properties of leaf litter wastes. A study was conducted to evaluate the efficiency of an exotic earthworm species Eudrilus eugeniae and an indigenous earthworm species Lampito tnauritii were used for the decomposition of different types of leaf litter wastes into valuable vermicompost. Physico Chemical features of agro wastes before and after composting was analyzed, which increased after vermicomposting. Copyright © EM International.

Manimekalai V.,Sri Parasakthi College for Women | Ravichandran P.,Manonmaniam Sundaranar University
International Journal of Botany | Year: 2012

Cyperus pangorei is a sedge extensively and exclusively used in silk mat weaving. It is a plant that grows along river banks and canals in rice fields and is considered as a weed, expect for its use in silk mat weaving. The objective of the present study was to analyze the chemical composition and wax micro morphology on the culms (stems) of Cyperus pangorei to decipher its role in silky texture of the mats and to know the abundance of waxes that may find use in commercial applications. Scanning Electron Microscopic (SEM) and GC-MS studies revealed several new chemical entities and their accumulation as cuticular wax layers. The analysis of components and morphological features of epicuticular waxes have provided information on four different classes of waxes and one very long chain wax ester-nona-hexacontanoic acid ester (C 69). The epicuticular waxes determined in this sedge also form first of its kind in Cyperaceae. The wax morphologies observed over the culm do not vary among the different culm regions. Wax morphologies such as thick amorphous film, fissured layers, thick crusts, platelets with orthorhombic symmetry and granules were observed. © 2012 Asian Network for Scientific Information.

Thiyagarajan S.,P.A. College | Gnanadurai D.,P.A. College | Malathi S.,Sri Parasakthi College for Women
International Journal of Applied Engineering Research | Year: 2014

Hyper Spectral Images (HSIs) exhibit significant spectral correlation, whose exploitation is crucial for compression. In this paper, a new lossless compression algorithm is proposed for HSIs, which is based on the Modified Ant Colony Optimization (MACO) algorithm and RADON transformation technique. Initially, the given HSI image is preprocessed by using a median filtering technique. After that, the single band image is selected from the original HSI and the color features of that band is extracted by using the HSV model. Then, the MACO algorithm is applied to select the band index based on the fitness value. Subsequently, the single band image is clustered into 6 segments by using the multi-thresholding technique. Furthermore, the RADON transformation and zig-zag encoding techniques are employed to compress the HSI band. Finally, the original band image is reconstructed by performing the zig-zag decoding and inverse RADON transformation techniques. The performance of the proposed system is evaluated in terms of Compression Ratio (CR), Mean Squared Error (MSE) and Peak Signal-to- Noise Ratio (PSNR). The proposed methodology is also compared with the existing methods such as, 3D-SPIHT, JPEG 2000 and 3D-SPECK. From this analysis, it is observed that the proposed method performs well and provides the best results, when compared with the other techniques. © Research India Publications.

Thiyagarajan S.,P.A. College | Dhavamani G.,P.A. College | Malathi S.,Sri Parasakthi College for Women
Current Medical Imaging Reviews | Year: 2016

Background: The Hyper Spectral Image (HSI) compression is a challenging and demanding task in many remote sensing applications, because it has the large hyperspectral data. Optical remote sensing is much increased due to newly imported sensor technologies and advancements. Lossy HSI compression is an essential part for long-terms spectral storage data. In this paper, we provide a new lossy HSI compression algorithm with the help of Residual Dependent Arithmetic Coder (RDAC). Methods: The main intention of this work is to reduce the complexity while compressing the large volume of data by compressing the spectral bands. Here, the Gray Level Co-occurrence Matrix (GLCM) technique is employed to extract the texture features of the given HSI band image. Then, the k-means clustering algorithm is employed to select the reference band in each cluster based on the cluster prominence value. Moreover, the RDAC is used to compress the reference band and the residual band information of each cluster. Finally, the HSI is decompressed with the help of compressed HSI band images. Results: In experiments, the performance of the proposed method is analyzed and evaluated in terms of Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR) and Compression Ratio (CR). Moreover, it is compared with some of the existing HSI compression techniques such as, Set Partitioning in Hierarchical Trees (SPIHT), Joint Photographic Expert Group (JPEG), Set Partitioning Embedded bloCK (3D-SPECK), Inverse Wavelet Transform (IWT) and Reverse Karhunen-Loeve Transform (RKLT). Conclusion: This paper proposes a new RDAC technique for lossy HSI compression. For this purpose, different image processing techniques are used. In this analysis, it is proved that the proposed HSI compression technique provides the best results, when compared to the other techniques. © 2016 Bentham Science Publishers.

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