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Jothi, G.
- Peroxidase and Chitinase Activities in Brinjal Inoculated with Meloidogyne incognita (Kofoid & White) Chitwood and Endomycorrhiza
Abstract Views :203 |
PDF Views:115
Authors
Affiliations
1 Department of Nematology, Tamil Nadu Agricultural University, Coimbatore 641 003, Tamil Nadu, IN
1 Department of Nematology, Tamil Nadu Agricultural University, Coimbatore 641 003, Tamil Nadu, IN
Source
Journal of Biological Control, Vol 16, No 2 (2002), Pagination: 161-164Abstract
Studies were conducted to observe the development of peroxidase and chitinase activity in brinjal cv.Co-2 inoculated with Vesicular arbuscular mycorryzae (VAM) and the ischolar_main knot nematode, Meloidogyne incognita. Peroxidase activity was increased and a decrease in chitinase activity was observed which is a defense mechanism of the host lo invading pathogen.Keywords
Chitinase, Meloidogyne incognita, Peroxidase, VAM.Full Text
- Management of Root - Knot Nematode in Brinjal by using VAM and Crop Rotation with Green Gram and Pearl Millet
Abstract Views :217 |
PDF Views:122
Authors
Affiliations
1 Department of Nematology Tamil Nadu Agricultural University Coimbatore 641 003, Tamil Nadu, IN
1 Department of Nematology Tamil Nadu Agricultural University Coimbatore 641 003, Tamil Nadu, IN
Source
Journal of Biological Control, Vol 15, No 1 (2001), Pagination: 77-80Abstract
Effects of vesicular arbuscular mycorrhizal fungi and crop rotation with pearl millet and green gram were investigated in microplots for the management of ischolar_main - knot nematode. VAM fungi increased the yield and stimulated the growth of brinjal. The nematode population was decreased from 143 nematodes /200ml soil to 105 nematodes/200ml soil after the rotation with green gram and pearl millet.Keywords
Brinjal Crop Rotation, Green Gram,G. mosseae, Meloidogyne incognita, Pearl Millet.Full Text
- A Comparison of Missing Data Handling Techniques
Abstract Views :284 |
PDF Views:1
Authors
Affiliations
1 Department of Information Technology, Sona College of Technology, IN
2 Department of Computer Applications, Sona College of Arts and Science, IN
1 Department of Information Technology, Sona College of Technology, IN
2 Department of Computer Applications, Sona College of Arts and Science, IN
Source
ICTACT Journal on Soft Computing, Vol 11, No 4 (2021), Pagination: 2433-2437Abstract
Missing data is a regular concern on data that professionals have to deal with. Efficient analysis techniques have to be followed to find interesting patterns. In this study, we are comparing 16 different imputation methods namely Linear, Index, Values, Nearest, Zero, slinear, Quadratic, Cubic, Barycentric, Krogh, Polynomial, Spline, Piecewise Polynomial, From derivatives, Pchip and Akima. These techniques are performed on real time UCI dataset and are under Missing Completely at a Random (MCAR) assumption, our result suggests the nearest, zero, quadratic and polynomial imputation methods which provides above 96% of accuracy when compared to the other techniques.Keywords
Missing Data, Imputation Methods, Missing Completely at Random.
References
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