A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Balasubramanian, C.
- Laboratory Evaluation of 7 Isolates of Fungi against Army Worm, Spodoptera litura (Fabricius) (Lepidoptera: Noctuidae) and Castor Hairy Caterpillar, Euproctis fraterna (Moore) (Lepidoptera: Lymantridae)
Authors
1 Department of Zoology, Thiagarajar College, Madurai 09, IN
Source
Journal of Biological Control, Vol 25, No 4 (2011), Pagination: 342-345Abstract
In this report, the insecticidal activity of Metarhizium anisopliae isolated from different geographical regions of Tamil Nadu was evaluated against Spodoptera litura (Fabricius) (Lepidoptera: Noctuidae) and Euproctis fraterna (Moore) (Lepidoptera: Lymantridae) under laboratory conditions. Among the tested isolates, Ma2 isolate at 108 spore/mL was found more effective against S. litura and E. fraterna than Ma1 than and Ma3 isolates.Keywords
Bioassay, LC50, LC90, Lepidoptera, Entomopathogenic Fungi.References
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- Efficacy of Local Isolates of Beauveria bassiana against Spodoptera litura (F.) (Lepidoptera: Noctuidae)
Authors
1 Department of Zoology, Thiagarajar College, Madurai 625 009, Tamil Nadu, IN
Source
Journal of Biological Control, Vol 25, No 1 (2011), Pagination: 22–25Abstract
Isolates of the entomopathogenic mitosporic ascomycete, Beauveria bassiana were evaluated against Spodoptera litura using leaf spray method. Mortality of 66.67, 73.33 and 80.0% with respect to the isolates Bb02, Bb09 and Bb10, respectively, was obtained four days after treatment. LC50 of the isolates was 2.1×106, 3.6×107 and 1.2×107 conidia ml-1 for Bb02, Bb09 and Bb10, respectively. The LT50 value for Bb02 and Bb09 was 4.8 days, whereas it was 4.0 days for Bb10 @108 spore mL-1. The germination percentage was 79.83, 88.33 and 95.53% for Bb02, Bb09 and Bb10, respectively Bb10 isolate was the most virulent with potential for the management of S. litura.Keywords
Beauveria bassiana, Spodoptera litura, Germination, LC50, LT50, Bioassay.References
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- Life Table of the Mexican Beetle, Zygogramma bicolorata Pallister on Parthenium and Sunflower
Authors
1 Project Directorate of Biological Control, P. B. No. 2491, H. A. Farm Post, Bellary Road, Hebbal, Bangalore 560 024, Karnataka, IN
Source
Journal of Biological Control, Vol 12, No 2 (1998), Pagination: 101-106Abstract
Life-table of the Mexican beetle, Zygogramma bicolorata Pallister feeding on parthenium leaves, parthenium leaves smeared with sunflower extract, sunflower leaves and sunflower leaves smeared with parthenium leaf extract have been constructed. The longevity and intrinsic rate of natural increase (rm) varied with extract treated and their respective hosts. The intrinsic rate of natural increase did not change considerably when fed on parthenium leaves and parthenium leaves smeared with sunflower extract (rm=0.44). The beetles fed on sunflower leaves (rm=0.37) and sunflower leaves smeared with parthenium extract (rm=0.35) were also not very different. Shorter generation time was obtained when fed with parthenium and parthenium leaves smeared with sunflower extract.Keywords
Intrinsic Rate of Natural Increase, Life Table, Parthenium hysterophorus, Sunflower, Zygogramma bicolorata.- Food Consumption and Utilization by the Mexican Beetle, Zygogramlna bicolorata Pallister (Coleoptera:Chrysomelidae) on Parthenium hysterophorus Linnaeus
Authors
1 Project Directorate of Biological Control P. B. 2491, H. A. Farm Post, Bellary Road, Hebbal, Bangalore 560 024, Karnataka, IN
Source
Journal of Biological Control, Vol 12, No 1 (1998), Pagination: 19-23Abstract
Quantitative food utilization indices were measured in different larval instars and physiological ages of adult Zygogramma bicolorata Pallister. Among the larval and adult stages of the beetle, third instar larvae and egg laying females ingested maximum food. Various growth parameters like relative consumption rate (RCR), relative growth rate (RGR) and approximate digestibility (AD) were relatively higher in the first, third and fourth instar and egg laying females. Efficiency of conversion of ingested food (ECI) and efficiency of conversion of digested food (ECD) were maximum in first, third and fourth instar larvae and decreasing trend was observed in second instar larvae. During preoviposition stage adult, these parameters increased tremendously in contrast to senescent stage.Keywords
Food Utilization, Mexican Beetle, Parthenium hysterophorus, Zygogramma bicolorata.- Tumor Diagnosis in MRI Brain Image using ACM Segmentation and ANN-LM Classification Techniques
Authors
1 Department of Computer Science and Engineering, Annamalai University, Chidambaram - 608002, Tamil Nadu, IN
2 Department of Computer Science and Engineering, P. S. R. Rengasamy College of Engineering for Women, Sivakasi - 626140, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 1 (2016), Pagination:Abstract
Background: Magnetic Resonance Images (MRI) is an important medical diagnosis tool for the detection of tumours in brain as it provides the detailed information associated to the anatomical structures of the brain. MRI images help the radiologist to find the presence of abnormal cell growths or tumours. MRI image analysis plays a vital role in diagnosis of brain tumours in the earlier stages and treatment of diseases. Methods: Therefore, this paper introduces an efficient MRI brain image analysis method, where, the MRI brain images are classified into normal, non cancerous (benign) brain tumour and cancerous (malignant) brain tumour. This proposed method follows four steps, 1. Pre-processing, 2. Segmentation, 3. Textural and shape feature extraction and 4. Classification. In this proposed MRI image analysis using the region based Active Contour Method (ACM) used for segmentation and Artificial Neural Network (ANN) based Levenberg-Marquardt (LM) algorithm used for classification process, which used to efficiently classify the MRI image as normal and Tumourous. Findings: The results revealed that the proposed MRI brain image tumour diagnosis process is accurate, fast and robust. The classifier based MRI brain image processing approach produced the best MRI brain image classification with use of feature extraction and segmentation results, in terms of accuracy. Best overall classification accuracy results were obtained using the given DioCom Images; The performance results proven that there is not sufficient result given to the classification process when it perform separately. With the use of ACM segmentation and feature extraction approaches, the proposed LM classification approach provides better classification accuracy than the existing approach. Application: The proposed MRI image based brain tumour analysis would efficiently deal with segmentation and classification process for brain tumour analysis with use of feature extraction methods, so this method can yield the better result of brain tumour diagnosis in advance where this method using in medical fields.
Keywords
Active Contour Method (ACM), Artificial Neural Network (ANN) based Levenberg-Marquardt (LM) Algorithm, Magnetic Resonance Images (MRI)- Image Restoration: Design of Non-Linear Filter (LR)
Authors
1 Department of Computer Science and Engineering, P.S.R. Rengasamy College of Engineering for Women, IN
2 Department of Computer Science and Engineering, P.S.R. Engineering College, IN