Refine your search
Collections
Co-Authors
Journals
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
Harish, B. S.
- Biochemical Changes during Plantlet Regeneration in Two Accessions of Mucuna pruriens
Abstract Views :211 |
PDF Views:115
Authors
Affiliations
1 Department of Biochemistry, College of Horticulture, University of Horticultural Sciences, Bagalkot – 587102, IN
2 Department of Studies in Biotechnology, Sahyadri Science College, Shivamogga – 577 102, Karnataka, IN
3 Department of Biochemistry, Davangere University (Kuvempu University P.G Center), Shivagangothri, Davangere - 577 002, Karnataka, IN
4 Department of Chemistry, Jawaharlal Nehru National College of Engineering, Shivamogga – 577201, Karnataka, IN
5 Department of Medicinal and Aromatic plants, College of Horticulture Sciences, University of Horticulture Sciences, Bagalkot – 587102, Karnataka, IN
1 Department of Biochemistry, College of Horticulture, University of Horticultural Sciences, Bagalkot – 587102, IN
2 Department of Studies in Biotechnology, Sahyadri Science College, Shivamogga – 577 102, Karnataka, IN
3 Department of Biochemistry, Davangere University (Kuvempu University P.G Center), Shivagangothri, Davangere - 577 002, Karnataka, IN
4 Department of Chemistry, Jawaharlal Nehru National College of Engineering, Shivamogga – 577201, Karnataka, IN
5 Department of Medicinal and Aromatic plants, College of Horticulture Sciences, University of Horticulture Sciences, Bagalkot – 587102, Karnataka, IN
Source
Journal of Horticultural Sciences, Vol 10, No 1 (2015), Pagination: 1-7Abstract
The genus Mucuna is an important medicinal herb and is extensively used in traditional Indian systems of medicine for various ailments. In vitro culture technique provides an alternative to plant propagation and germplasm conservation. Our aim was to study the biochemical changes occurring during regeneration of shoots (plantlets) from explants of two accessions of Mucuna pruriens, by monitoring the efficiency of nitrogen utilization and changes in levels of some hydrolytic enzymes. A rapid micropropagation system was developed using Murashige and Skoog's (MS) medium supplemented with BAP and IAA combined. In both the accessions, 3.0mg l-1 6-BAP, in combination with 0.2mg l-1 IAA, induced shoot buds and shoot elongation; however for multiple-shoot induction, a slightly higher concentration of cytokinin, i.e., 3.5mg l-1 6-BAP, in combination with 0.2mg l-1 IAA, was required. Results of the present study confirm an active growth of explants revealed by nitrate assimilation enzymes and hydrolytic enzymes. It is concluded that medium composition, growth regulator combination and culture incubation conditions are all vital in both the accessions of Mucuna pruriens for induction of in vitro plant regeneration.Keywords
Mucuna, in vitro, Biochemical Changes, Regeneration, Enzymes.References
- Altaf Ahmad and Abdin, M.Z. 1999. NADH: nitrate reductase and NAD(P)H: nitrate reductase activities in mustard seedlings. Pl. Sci., 143:1-8
- Angosto, T., Gonzalez, F. and Matilla, A. 1988. Partial purification and some biochemical properties of acid phsophatase in germinating chick pea (Cicer arietinum L.) seeds. Physiol. Pl., 74:715-719
- Bradley, D., Kjellborn, P. and Lamb, C. 1992. Elicitor- and wound-induced oxidative cross-linking of a prolinerich plant cell wall protein: a novel, rapid defense response. Cell., 70:21-30
- Brown, D.C.W. and Thorpe, T.A. 1980. Adenosine phosphate and nicotinamide adenine dinucleotide pool sizes during shoot initiation in tobacco callus. Pl. Physiol., 65:587-590
- Campbell, W.H. and Smarrelli, Jr. J. 1978. Purification and kinetics of higher plant nitrate reductase. Pl. Physiol., 61:611-616
- Christopher, T., Prolaram, B. and Subhash, K. 1991. Differential in vitro morphogenetic response in hypocotyl segments of Capsicum annuum. Indian J. Expt’l. Biol., 29:68-69
- Kavi Kishor, P.B. and Mehta, A.R. 1988. Changes in some enzyme activities during growth and organogenesis in dark-grown tobacco callus cultures. Pl. Cell Physiol., 29:255-259
- Kumar, V. 1998. Biochemical and in vitro plantlet regeneration studies in fig (Ficus carica L. cv. Gular). M. Phil. dissertation submitted to Sri Krishnadevaraya University, Anantapur, Andhra Pradesh, India
- Lagrimini, L.M., Gingas, V., Finger, F., Rothstein, S. and Liu, T-T.Y. 1997a. Characterization of antisense transformed plants deficient in the tobacco anionic peroxidase. Pl. Physiol., 114:1187-1196
- Lagrimini, L.M., Joly, R.J., Dunlap, J.R., and Liu, T-T.Y. 1997b. The consequence of peroxidase overexpression in transgenic plants on ischolar_main growth and development. Pl. Mol. Biol., 33:887-895
- Lam, H.M., Coshigano, K., Oliveira, I., Melo-Oliveira, R. and Coruzzi, G. 1996. The molecular genetics of nitrogen assimilation into amino acids in higher plants. Pl. Mol. Biol., 47:569-593
- Lochab, S., Pathak, R.R. and Raghuram, N. 2007. Molecular approaches for enhancement of nitrogen use efficiency in plants. In: Agricultural Nitrogen use & its Environmental Implications (Eds. Abrol, Y.P., Raghuram, N. and Sachdev, M.S.). IK International, Delhi, India, pp. 327-350
- Lorenza M. Bellani, Massimo Guarnieri and Anna Scialabba. 2002. Differences in the activity and distribution of peroxidases from three different portions of germinating Brassica oleracea seeds. Physiol. Pl., 114:102-108
- Malik, C.P. and Kumari, U. 1977. Histochemical studies on the localization of metabolic reserves and enzymes during the initiation and formation of adventitious ischolar_mains inImpatiens balsamina L. New Bot., 4:113-115
- Miller, W.B. and Ranwala, A.P. 1994. Characterization and localization of three soluble forms of invertase from Lilium longiflorum flower buds. Physiol. Pl., 92:247 -253
- Murashige, T. and Skoog, F. 1962. A revised medium for rapid growth and bioassays with tobacco tissue cultures. Physiol. Pl., 15:473-497
- Naidu, K.R. and Kavi Kishor, P.B. 1995. Activities of hydrolytic enzymes in callus cultures of tobacco during organogenesis. J. Biosci., 20:629-636
- Naik, M.S., Abrol, Y.P., Nair, T.V.R., and Ramaras, C.S. 1982. Nitrate assimilation – its regulation and relationship to reduced nitrogen in higher plants. Phytochem., 21:495-504
- Narender Singh, Kuldeep Yadav, Suman Kumari, and Renu. 2011. Metabolic changes during differentiation in callus cultures of Stevia rebaudiana (Bertoni). J. Phytol., 3:63-67
- Crawford, N.M. 1995. Nitrate: Nutrient and signal for plant growth. Pl. Cell, 7:859-868
- Oskar J. Sanchez, Alberto Pan, Gregorio Nicolas and Emilia Labrador. 1989. Relation of cell wall peroxidase activity with growth in epicotyls of Cicer arietinum. Physiol. Pl., 75:275-279
- Philippe Lenee and Yves Chupeau. 1989. Development of nitrogen assimilating enzymes during growth of cells derived from protoplasts of sunflower and tobacco. Pl. Sci., 59:109-117
- Riley, P.A. 1997. Melanin. Int’l. J. Biochem. Cell Biol., 29:1235-1239
- Sadasivam, S. and Manickam, A. 2008. Biochemical Methods. New Age International (P) Limited Publishers, New Delhi, India, pp. 137-139
- Singh, S.R., Singh, R. and Dhawan, A.K. 2009. Biochemical changes related to shoot differentiation in callus cultures of Tylophora indica Wight and Arn. J. Indian Bot. Soc., 88:49-53
- Srivastava, H.S. 1980. Regulation of nitrate reductase activity in higher plants. Phytochem., 19:725-733
- Sujatha, M., Sivaraj, N. and Satya Prasad, M. 2000. Biochemical and histological changes during in vitro organogenesis in Jatropha integerrima. Biologia Plant., 40:167-171
- Suzuki, A., Audet, C. and Oaks, A. 1987. Influence of light on the ferredoxin-dependent glutamate synthase in maize leaves. Pl. Physiol., 95:384-389
- Yolanda Cuadrado, Hilario Guerra, Ana Belen Martin, Piedad Gallego, Oscar Hita, Ana Dorado and Nieves Villalobos. 2001. Differences in invertase activity in embryogenic and non-embryogenic calli from Medicago arborea. Pl. Cell Tiss. Org. Cult., 67: 145-151
- Effect of Growth Regulation through Spacing and Pruning on Yield and Quality of Tomato Hybrids (Lychopersicon esculentum Mill.) Grown under Control Conditions
Abstract Views :183 |
PDF Views:2
Authors
Affiliations
1 College of Horticulture, Bagalkot (Karnataka), IN
1 College of Horticulture, Bagalkot (Karnataka), IN
Source
The Asian Journal of Horticulture, Vol 12, No 1 (2017), Pagination: 28-34Abstract
An experiment was conducted at Indian Institute of Horticultural Sciences, Bangalore to study the effect of growth regulation through spacing and pruning on yield and quality of tomato hybrids (Lychopersicon esculentum Mill.) grown under control conditions. The results of present investigation revealed that tomato variety Sun 7611 (V2) recorded the higher (7.42, 7.90, 4.63 and 1.85) number of flowers per cluster at all the stages of crop growth and differed significantly from Arka Abhijith (V1). Where in pruning methods single stem (P1) gave higher (6.74 and 7.09) number of flowers per cluster at 30 and 60 days after transplanting, which were significantly different from P2 (double stem). Tomato grown on single-stem resulted in higher individual fruit weight (77.04 g) than double stemmed plants. Maximum yield of 2.23 kg/plant and 129.4 tonnes per hectare was recorded in plants having two stemmed plant, and the yield of 1.96 kg per plant and 114.38 tons per hectare was obtained from single-stemmed plants. Plants wider spacing gave the highest fruit weight (79.15 g) followed by medium spacing plants (73.92 g) and the least was recorded in closely spacing plants (69.07 g). Fruit yield per plant was significantly reduced under closer plant spacing (1.8 kg) and increased as spacing were increased.Keywords
Growth Regulation, Spacing, Pruning, Quality, Tomato Hybrids.References
- Anonymous (1999). Savernate phase-II Progress Report for Period 1-1-99 to 30-9-99.
- Hiscox, J.D. and Israelam (1979). Method for the extraction of chlorophyll from leaf tissue without maceration., J. Bot., 57: 1332-1334.
- Lim, E.S. and Chen, S.T. (1988). Hydroponic production studies on low land tomato in Malaysia. The effect of pruning system and CHPA application on yield. Proc. of the intenl. Symp. on integrated management practices, AVRDC. Taiwan, pp: 358-364.
- Mangal, J.L. and Kasim, A.M. (1987). Response of tomato varieties to pruning and plant spacing under plastic house. Haryana. J. Hort. Sci., 16(3-4): 248-252.
- Rajewar, S.R. and Patil, V.K. (1979). Flowering and fruiting of some important varieties of tomato as affected by spacing, staking and pruning. Indian J. Agric. Sci., 49(5): 358-360.
- Rasmussen, K. (1986). Varietal trials with green house cucumbers. Gartner Tidenole., 102(38): 1268-1271.
- Takahashi, H. and Sasaki, S. (1981). Studies with lateral tomato shoots. I experiments using semi-forcing conditions. Bull. Akita Prefectual College Agric., 7: 45-49.
- Takahashi, H. and Sasaki, S. (1983). Studies on the lateral shoot utilization of tomatoes. II influence of planting density and fruit thinning on fruit enlargement and yield in semi-forced cultivation. Bull. Akita Prefectural College Agric., 9: 35-41.
- Response of Semi-Determinate and Indeterminate Hybrids of Tomato (Lychopersicon esculentum Mill.) to Pruning and Spacing Grown Under Cover
Abstract Views :188 |
PDF Views:0
Authors
Affiliations
1 College of Horticulture, University of Horticultural Sciences, Bagalkot (Karnataka), IN
1 College of Horticulture, University of Horticultural Sciences, Bagalkot (Karnataka), IN
Source
International Journal of Agricultural Sciences, Vol 13, No 2 (2017), Pagination: 254-260Abstract
The undercover tomato trial was conducted at Indian Institute of Horticultural Sciences, Bangalore. This study was conducted to determine the response of semi-determinate and indeterminate hybrids of tomato to pruning and spacing grown under cover. The results indicated that the plant height was the highest in closer spacing at 30 (92.58 cm) 60 (135.98 cm), 90 (185.25 cm) days after planting and at final harvest (221.35 cm), whereas maximum leaf area (4045.92 cm2 and 5705.73 cm2) was observed in V2 at both first and last harvest. Maximum dry matter (35.31 to 38.48%) was observed in leaves followed by flowers and fruits stem and ischolar_main at first harvest. Maximum (45.18 to 50.4%) dry matter was observed in flower and fruits followed by stem, leave and ischolar_main at final harvest. Sun 7611 (V2) recorded the highest biomass accumulation (22.76 g, 77.81 g and 158.37 g) at vegetative phase, first harvest and at final harvest which was significantly different from Arka Abhijith (V1). Fruit set percentage was higher in Arka Abhijith (59.43%) than Sun 7611 (54.57) more number of flowers formed fruits in single stemmed plants (59.24%) compared to double stemmed plants (54.76%). Among spacing treatments per cent fruit set did not differ significantly. Further fruit yield was significantly higher in P2 (2.23 kg) than P1 (1.96 kg). Maximum fruit yield per plant was obtained in S3 (2.44 kg) followed by S2 (2.03 kg) and the least was observed in S1 (1.81 kg) which were significantly different. However, yield per hectare was significantly improved under closer spacing.Keywords
Semi-Determinate, Indeterminate, Pruning, Spacing.References
- Anonymous (1999). Savernate Phase-II Progress report for period 1-1-99 to 30-9-99.
- Bhatt, R.M. and Rao, N.K.S. (1988).Carbon assimilation and dry matter partitioning in tomato (Lycopersicon esculentum mill) cultivars. Veg. Sci., 15(1):21-30.
- Georgiova, M.K. (1971). The effect of cultural methods on the growth and yield of medium early crops of some tomato cultivars. Rastoniev’dstro., 21: 35-54.
- Mangal, J.L. and Kasim, A.M. (1987). Response of tomato varieties to pruning and plant spacing under plastic house. Haryana. J. Hort. Sci., 16(3-4): 248-252.
- Rajewar, S.R. and Patil, V.K. (1979). Flowering and fruiting of some important varieties of tomato as affected by spacing, staking and pruning. Indian J. Agric. Sci., 49(5) : 358-360.
- Rajewar, S. R., Patil, V. K. and Santakke, M. D. (1981).Growth parameters of some important varieties of tomato (Lycopersicon esculentum Mill) as influenced by spacing, pruning and staking. Andhra Agric. J., 28(12) : 36-42.
- Takahashi, H. and Sasaki, S. (1981). Studies with lateral tomato shoots. I experiments using semi-forcing conditions. Bull. Akita Prefectual College Agric., 7: 45-49.
- Verma, A. (1999). Vegetable scenario in India. Plant Hort. Tech., 1(3): 51-54.
- Characterization of Scented Geranium Accessions for Odour and Chemical Compositions in Southern Transitional Zone of Karnataka
Abstract Views :440 |
PDF Views:0
Authors
Affiliations
1 College of Horticulture, Mysore (Karnataka), IN
2 College of Horticulture, Bagalkot (Karnataka), IN
3 University of Horticultural Sciences, Bagalkot, Dyanagiri (Karnataka), IN
1 College of Horticulture, Mysore (Karnataka), IN
2 College of Horticulture, Bagalkot (Karnataka), IN
3 University of Horticultural Sciences, Bagalkot, Dyanagiri (Karnataka), IN
Source
The Asian Journal of Horticulture, Vol 12, No 2 (2017), Pagination: 234-240Abstract
Scented geranium (Pelargonium spp.: Geraniaceae) is an important, high value aromatic crop of South African origin. Due to high demand and price for the oil, an excellent potential exists for increasing cultivated area in India. An attempt was made to evaluate and characterize the available accessions of scented geranium based on their physico-chemical properties, chemical composition and odour assessment of the oil. There were seven treatments and four replications. All the accessions possessed light yellow coloured oil except PG-10, which possessed light green colour. The oil from PG-10 showed maximum acid value (3.02). The oil from PG-8 recorded the highest ester value (58.737). The oil form KB and CIMAP possessed maximum citronellol and geraniol content while, linalool was found to be maximum in case of PG-11. PG-10 contained maximum isomanthone (8.50%). The oil from PG-1 recorded the highest citronellyl formate content (15.83%). The essential oil was distilled during August from seven accessions upon GC analysis. The concentrations of isomenthone, citronellyl formate and citronellol were maximum in case of PF-10 (7.74, 23.18 and 37.07%, respectively). The major alcohols i.e., citronellol, geraniol, linalool and nerol were maximum in case of the oils of KB, CIMAP, PG-8 and PG-1 during May. Whereas, during August, PG-10 recorded the maximum nerol and cironellol whereas, PG-12 registered the highest concentration of geraniol and linalool. The rosy odour of different accessions is attributed to the presence of higher levels of geraniol, which is evident in the present case with the accession PG-12, during August. Hence, all the accessions differed significantly in all the parameters.Keywords
Geranium, Accessions, Physico-Chemical Properties, Chemical Composition, Odour Assessment.References
- Anonymous (1988). Indian standard specification for the oil of geranium (second revision) Bureau of Indian standards, IS; 587 : 1-4.
- Demarne, F.E. (1989). Genetic improvement of geranium roast (Pelargonium spp.) : Systematical, karyological and biochemical contributions. Ph. D. Thesis, University of Paris.
- Harlalka, R.H. (2000). Problems in distillation of natural essential oils-practices, prospects and trade. EOAI, Bangalore (KARNATAK) INDIA.
- Kaul, P.N., Rao, B.R.R., Bhattacharya, A.K., Singh, C.P. and Singh, K. (1995).Volatile constituent of three cultivars of rose-scented geranium (Pelargonium sp.) as influenced by method of distillation. Pafai J., 17 (4): 21-26.
- Kaul, P.N. and Rao, B.R.R. (1999). Quality variation in the essential oils of young and old leaves of three varieties if rose-scented geranium (Pelargonium spp.) PAFAI J., 1 (1) : 35-37.
- Kumar, A., Sharma, A. and Virmani, O.P. (1985). Cultivation and utilization of rose geranium : A review. Curr. Res. Med. & Aromatic Plants, 7 (3) : 137-147.
- Ranade, G.S. (1998).Chemistry of geranium oil. Indian Perfum., 32 (1) : 61-68.
- RAO, B.R.R. (2000). Rose-second geranium (Pelargonium spp.) : indian and international perspective. J. Medicinal & Aromatic Plant Sci., 22 : 302-312.
- Sastry, K.P., Kumar, S., Mehta, V.K., Radhakrishnan, K. and Saleem, S.M. (2000). Cultivation of geranium in the hilly regions of Tamil Nadu. Centennial Conference on Spices and Aromatic Plants Held at Calicut.
- Singh, K., Rao, B.R.R., Kothari, S.K., Singh, C.P., Kaul, P.N. and Kumar, S. (2000). Cultivation of aromatics crops in South India: Problems and prospects. J. Medicinal & Aromatic Plant Sci., 22 : 218-230.
- Sundararaj, N., Nagaraju, S., Venkataramu, M.N. and Jaganath, M.K. (1972). Design and analysis of field experiments, Universtiy of Agricultural Sciences, Bangalure (KARNATAKA) INDIA.
- Evaluation of Scented Geranium Accessions for Morphological and Yield Attributes in Southern Indian Conditions
Abstract Views :238 |
PDF Views:0
Authors
Affiliations
1 College of Horticulture, Mysore (Karnataka), IN
2 College of Horticulture, University of Horticultural Sciences, Bagalkot (Karnataka), IN
3 Indian Institute of Horticultural Research, Bengaluru (Karnataka), IN
1 College of Horticulture, Mysore (Karnataka), IN
2 College of Horticulture, University of Horticultural Sciences, Bagalkot (Karnataka), IN
3 Indian Institute of Horticultural Research, Bengaluru (Karnataka), IN
Source
International Journal of Agricultural Sciences, Vol 14, No 1 (2018), Pagination: 65-69Abstract
Scented geranium (Pelargonium spp.:Geraniaceae) is an important, high value aromatic crop of South African origin. The oil of geranium is obtained by steam distillation of tender plant parts. More than 120 constituents are identified in the oil. Due to high demand and price for the oil, an excellent potential exists for increasing cultivated area in India. An attempt was made to evaluate and characterize the available accessions of scented geranium based on their morphology and yield attributes. There were seven treatments and four replications. PG-12 recorded maximum plant height (53.45 cm), PG-1 recorded maximum plant spread (6706.43 cm2), PG-12 registered maximum number of leaves (469.20), PG-11 recorded the highest (12.35 mm) stem diameter. Flowering was observed in the accessions PG-1, PG-8, PG-10, KB and CIMAP though the extent varied widely. KB recorded the maximum herb yield per plant, per plot and per hectare (0.69 kg, 13.90 kg and 19.30 t, respectively). PG-8 registered the maximum oil content (0.437%), KB recorded the maximum essential oil (2.07 ml, 41.43 ml and 57.53 1, respectively) per plant, per plot and per hectare oil yield. So, KB and PG-8 were found best among all for their essential oil yield and quality.Keywords
Geranium, Accessions, Evaluation.References
- Bhaskar S. (1995). Growth, herbage and oil yield of patchouli (Pogosrtemon patchouli) as influenced by cultivars and nitrogen fertilization. Indian Perfum., 39 (1) : 35-38.
- Bhaskar, S., Vasanthakumar, T. and Srivastava, H.C. (1998). Growth and yield of scented geranium (Pelargonium graveolens) genotypes in relation to nitrogen fertilization. J. Medicinal & Aromatic Plant Sci., 20 : 731-734.
- Kaul, P.N. and Rao, B.R.R. (1999). Quality variation in the essential oils of young and old leaves of three varieties if rose-scented geranium (Pelargonium spp.) PAFAI J., 1 (1) : 35-37.
- Mani, A.K. and Sampah, V. (1981). Seasonal influence on the oil content and quality in geranium. Indian Perfum., 25 (3 & 4) : 41-43.
- Naragund, V.R. and Divakar, N.G. (1983).Varietal evaluation in scented geranium (Pelargonium graveolens). Indian Perfum., 27 (1) : 19-21.
- Pareek, S.K. and Maheshwari, M.L. (1990). Selection of Palmarosa oil grass germplasm for higher yield and quality. Indian Perfum., 34 (1) : 5-13.
- Patra, N.K., Khanuja, S.P.S., Shasaby, A.K., Singh, H.P., Singh, VR., Tanveer, H., Kalra, A., Singh, H.B., Mengi, N., Tyagi, N.K., Naqui, A.A. and Kumar, S. (2000).Genetic improvement of cultivated species of Cymbopogon and Mentha for yield, quality and adaption. J. Medicinal & Aromatic Plant Sci., 22 (1B) : 263-277.
- Ram, M., Gupta, M.M., Naqui, A.A. and Kumar, S. (1995). Commercially viable annual crop of geranium in northern Indian plains. Curr. Res. Medicinal & Aromatic Plants, 17 : 17-20.
- Rao, B.R.R. (2000). Rose-second geranium (Pelargonium spp.) : Indian and International perspective. J. Medicinal & Aromatic Plant Sci., 22 : 302-312.
- Sastry, K.P., Kumar, S., Mehta, V.K., Radhakrishnan, K. and Saleem, S.M. (2000). Cultivation of geranium in the hilly regions of Tamil Nadu. Centennial Conference on Spices and Aromatic Plants Held at Calicut.
- Singh, K., Rao, B.R.R., Kothari, S.K., Singh, C.P., Kaul, P.N. and Kumar, S. (2000). Cultivation of aromatics crops in South India: Problems and prospects. J. Medicinal and Aromatic Plant Sci., 22 : 218-230.
- Sundararaj, N., Nagaraju, S., Venkataramu, M.N. and Jaganath, M.K. (1972). Design and analysis of field experiments, University of Agricultural Sciences, Bangalore (KARNATAKA) INDIA.
- Performance of Different Coriander Genotypes for their Growth and Seed Yield Characters Under Northern Transitional Condition of Karnataka
Abstract Views :171 |
PDF Views:0
Authors
Affiliations
1 College of Horticulture, Bagalkot (Karnataka), IN
2 University of Horticulture Science, Bagalkot (Karnataka, IN
3 College of Horticulture, Mysuru (Karnataka), IN
1 College of Horticulture, Bagalkot (Karnataka), IN
2 University of Horticulture Science, Bagalkot (Karnataka, IN
3 College of Horticulture, Mysuru (Karnataka), IN
Source
International Journal of Agricultural Sciences, Vol 14, No 2 (2018), Pagination: 423-430Abstract
Coriander (Coriandrum sativum L.) is an aromatic spice crop belonging to the family Apiaceae. One of the main reasons for low yield in coriander is due to non availability of region specific genotypes. There are no systematic studies on the performance of different genotypes of coriander for different agro climatic condition. Considering the importance of the crop, the present investigation was taken upto evaluate different coriander genotypes to find out the high yielding genotype and suitable varieties for transitional region of Karnataka. The experiment was conducted at HREC, Devihosur compressing of 21 genotypes with three replications and RCBD design was followed. The varieties exhibited significant differences for all the characters including seed yield in the experiment. DCC-68 recorded the highest seed yield per plant (5.93 g), per plot (290.73 g) and per hectare (15.82 q) and the lowest yield was recorded in DCC-72 (9.60 q).Keywords
Growth, Seed Yield, Genotypes, Coriander.References
- Agrawal, S., Sharma, R.K. and Bhatt, B.N. (1990). Quality evaluation in coriander.Indian Cocoa, Arecanut Spices J., 13(4): 137-137.
- Banafar, R.S. and Nair, P.R. (1992). Varietal performance of fenugreek under Jabalpur condition. Indian Cocoa, Arecanut & Spices J., 16(1): 19-20.
- Farooqi, A.A., Sreeramu, B.S. and Srinivasappa, K.N. (2005). Cultivation of Spice Crops. Universities Press (India) Private Limited, Hyderabad.
- Giridhar, K. and Sarada, C. (2005). Identification of coriander (Coriandrum sativum L.) genotypes for vertisols of Andhra Pradesh. Nat. Symp. Cur. Trends in Onion, Garlic, Chillies and Seed Spices-Production, Marketing and Utilization, SYMSAC-II, NRCOG, Rajgurunagar, pp. 92.
- Hariprasadrao, N. and Srinivasrao, G. (2001). Studies on the performance of exotic and indigenous coriander (Coriandrum sativum L.) genotypes for greens. Andhra Agric. J., 48(3-4): 324-326.
- Moniruzzaman, M., Rahman, M.M., Hossain, M.M., Sirajul, K.A.J.M. and. Khaliq, Q.A. (2013). Evaluation of coriander (Coriandrum sativum L.) genotypes for seed yield and yield contributing characters.Bangladesh. J. Agril. Res.,38(2): 189-202.
- Prabhu, T. and Balakrishnamoorthy, G. (2006). Evaluation of coriander (Coriandrum sativum L.) accessions under irrigated conditions for growth, yield and quality. Proc. Nat. Sem. Emerging Trends in Production, Quality, Processing and Export of Spice, 28-29 March, Coimbatore, p. 13.
- Panse, V.G. and Sukhatme, P.V. (1957). Statistical methods for agriculture workers. Indian Council of Agric. Res. Pub., New Delhi, pp. 152-174.
- Rajagopalan, A., Azhakiyamanavalan, R.S. and Abdul-Khader, M.D. (1996). Evaluation of coriander cultivars for yield. Indian Cocoa, Arecanut & Spices J., 20(1): 13-14.
- Raje, R.S., Singhania, D.L. and Singh, D. (2003). Evaluation of early generation progenies (F2) of fenugreek (Trigonella foenum- graecum L.) crosses for seed yield and yield related characters. J. Spices Aromatic Crops, 12(2): 127-134.
- Sarada, C., Giridhar, K. and Hariprasada, R.N. (2005). Studies on genetic variability, heritability and genetic advance in fenugreek. J. Spices Aromatic Crops., 17(2) : 163-166.
- Saxena, R.P., Pandey, V.P., Datta, J. and Gupta, R.K. (2005). Performance of coriander entries at Kumarganj, Faizabad. Nat. Symp. Cur. Trends in Onion,Garlic, Chillies and Seed Spices-Production, Marketing and Utilization,SYMSAC-II, 25-27 November, NRCOG, Rajgurunagar, pp. 55-56.
- Seemanthini, R., Arumugam, R., Ahmabshah, H. and Muthuswami, S. (1982). CO-2 coriander- a superior dual purpose coriander.South Indian Hort.,30: 240-241.
- Selvarajan, M., Chezhiyan, N., Muthulakshmi, P. and Ramar, A. (2002). Evaluation of coriander genotypes for growth and yield. South Indian Hort., 50(4-6): 458-462.
- Singh, U.B. and Jain, M.K. (1970). Studies on yield and quality variation in coriander. Indian J. Agron., 15: 223-226.
- Shridhar (1989). Studies on variability in coriander (Coriandrum sativum L.) and response of leaf type to nutrition. M.Sc. (Ag.) Thesis, University of Agricultural Sciences, Dharwad (Karnataka) India.
- Shridhar, Sulikeri, G.S. and Hulamani, N.C. (1990). Performance of coriander (Coriandrum sativumL.) genotypes. Karnataka J. Agric Sci., 3(3-4): 213-217.
- Subramanian, S., Rajeswari, E. and Chezhiyan, N. (2005). Screening of coriander genotypes for yield, quality and powdery mildew. South Indian Hort.,53(1-6):168-171.
- Tiwari, R.S. and Agarwal, A. (2004). Production technology of Spices.International Book Distributing Co., India, pp. 254-270.
- Velayudham, A. (2004). Evaluation and effects of organics with bio-inoculants in coriander var. Co 3. M.Sc. (Hort.) Thesis, University of Agricultural Sciences, Dharwad (Karnataka) India.
- Velayudham, A., Hanamashetti, S.I., Madalageri, M.B. and Wali, M.C. (2006). Evaluation of coriander genotypes during 2003-04 Kharif and Rabi seasons. Proc. Nat. Sem. Emerging Trends in Production, Quality, Processing and Export of Spice, 28-29 March, Coimbatore, p. 11.
- Venkatareddy, P., Sriramarao, T., Narasimharao, S.B.S. and Narisireddy, A. (1986). Genetic variability in coriander. Indian, Arecanut & Spices J.,10(3):90-92.
- Yadav, R.K. (1999). Variability in a collection of coriander (Coriandrun sativumL.) germplasm. J. Spices & Arom. Crops, 8(1): 99.
- Conservation of Medicinal Plants Bio-Diversity:Need, Ways and Initiatives
Abstract Views :159 |
PDF Views:0
Authors
Affiliations
1 Department of Medicinal sand Aromatic Crops, College of Horticulture (UHS), Mysuru (Karnataka), IN
2 Department of Medicinal and Aromatic Crops, College of Horticulutre, University of Horticulture Science, Bagalkot (Karnataka), IN
3 College of Horticulture (UHS), Bengaluru (Karnataka), IN
1 Department of Medicinal sand Aromatic Crops, College of Horticulture (UHS), Mysuru (Karnataka), IN
2 Department of Medicinal and Aromatic Crops, College of Horticulutre, University of Horticulture Science, Bagalkot (Karnataka), IN
3 College of Horticulture (UHS), Bengaluru (Karnataka), IN
Source
International Journal of Agricultural Sciences, Vol 14, No 2 (2018), Pagination: 442-447Abstract
The paper discusses about bio-diversity of medicinal plants, the need to conserve, and ways to conserve including the latest tools and approaches besides conventional ones. A special emphasis has been given in listing the species which needs immediate conservation measures especially in the state of Karnataka. Loss of medicinal plants bio-diversity and its impact has also been highlighted. The efforts and initiatives of the University of Horticultural Sciences, Bagalkot, Karnataka in the direction of medicinal plants bio-diversity conservation is elaborated in detail. The approaches and strategies both research and developmental by keeping the future needs of medicinal plants bio-diversity conservation in mind have been discussed.Keywords
Conservation, Bio-Diversity, Initiatives, Medicinal Plants.References
- Denham, A. (1999). Ex situ conservation: Cultivation of woodland medicinal plants. In: Traffic Europe (Ed.): Medicinal plant trade in Europe. Proceedings of the first symposium on the conservation of medicinal plants in trade in Europe, 22.23.6.1998, Kew - pp. 195, TRAFFIC Europe, s.loc.
- Envis news letter of FRLHT,Volume 2, Issue 1,2,3 &4 June 09 - March 2010
- Farnsworth, N.R. and Soejarto, D.D. (1991). “Global Importance of Medicinal Plants” in: Akerele, O., V. Heywood & H. Synge (eds.), Conservation of Medicinal Plants, Cambridge University Press, Cambridge, UK.
- Marshall, N.T. (1998). Searching for a cure. Conservation of medicinal wildlife resources in east and southern Africa. VI+112 pp., xiv, TRAFFIC International, Cambridge (Species in Danger).
- Parrotta, John A. (2002). “Conservation and Sustainable Use of Medicinal Plant Resources - An International Perspective”, World Ayurveda Congress: November 2002.
- Schippmann, U. (1999). Summarizing remarks and conclusions. In: Traffic Europe (Ed.): Medicinal plant trade in Europe. Proceedings of the first symposium on the conservation of medicinal plants in trade in Europe, 22-23.6.1998, Kew - pp.173178, TRAFFIC Europe, s.loc.
- http://en.wikipedia.org/wiki/Svalbard_Global_Seed_Vault
- http://www.redlist.org/
- Interpretation of ECG using Modified Intuitionistic Fuzzy C-Means Clustering for Arrhythmia Data
Abstract Views :202 |
PDF Views:1
Authors
C. K. Roopa
1,
B. S. Harish
2
Affiliations
1 Department of Computer Science, JSS Technical Institution Campus, Mysuru, IN
2 Department of Information Science and Engineering, Sri Jayachamarajendra College of Engineering, IN
1 Department of Computer Science, JSS Technical Institution Campus, Mysuru, IN
2 Department of Information Science and Engineering, Sri Jayachamarajendra College of Engineering, IN
Source
ICTACT Journal on Soft Computing, Vol 9, No 1 (2018), Pagination: 1788-1793Abstract
An electrocardiogram (ECG) is defined as a measure of variation in the electrical activity of the heart and is broadly used in detection and classification of heart-related diseases. The abnormalities present in the heart can be easily analyzed through the variation in electrical signal captured from the heart through impulse waveforms which are generated by certain specialized cardiac tissues. Different authors have developed various clustering models and classification techniques for detecting heart-related diseases. However there still exists a limitation in terms of accuracy. In this article, we proposed a new modified unsupervised clustering algorithm for effective detection of heart diseases. To select the best discriminate feature for effective learning, this article make use of feature selection methods such as principal component analysis, linear discriminative analysis, and regularized locality preserving indexing. The reduced features set are clustered using modified intuitionistic Fuzzy C-means clustering (mifcm) method. The experiment results proved that the proposed method effectively identifies the discriminative features. Further the obtained accuracy is also better when compared to other existing method.Keywords
Electrocardiogram, Heart Diseases, Feature Selection, Intuitionistic Fuzzy C-Means.References
- C. Kulikowski et al., “Medical Imaging Informatics and Medical Informatics: Opportunities and Constraints”, Methods of Information in Medicine, Vol. 41, No. 2, pp. 183-189, 2002.
- J. Wiemer et al., “Informatics United”, Methods of Information in Medicine, Vol. 42, No. 2, pp. 126-133, 2003.
- U.R. Acharya et al., “Automated Detection of Arrhythmias using Different Intervals of Tachycardia ECG Segments with Convolutional Neural Network”, Information Sciences, Vol. 405, pp. 81-90, 2017.
- S.U. Kumar and H.H. Inbarani, “Neighborhood Rough Set based ECG Signal Classification for Diagnosis of Cardiac Diseases”, Soft Computing, Vol. 21, No. 16, pp. 4721-4733, 2017.
- B. Boashash, “Time-Frequency Signal Analysis and Processing: A Comprehensive Reference”, Academic Press, 2015.
- J. Kim, H.S. Shin, K. Shin and M. Lee, Robust Algorithm for Arrhythmia Classification in ECG using Extreme Learning Machine, Biomedical Engineering, Vol. 8, No. 1, pp. 1-31, 2009.
- P. Raman and S. Ghosh, “Classification of Heart Diseases based on ECG Analysis using FCM and SVM Methods”, International Journal of Engineering Science, Vol. 67, No. 1, pp. 31-39, 2016.
- P. Radha and B. Srinvasan, “Hybrid Prediction Model for the Risk of Cardiovascular Disease in Type-2 Diabetic Patients”, Expert Systems with Applications, Vol. 2, No. 10, pp. 23-29, 2014.
- C.K. Roopa, B.S. Harish and S.V. Arun Kumar, “A Novel Method of Clustering ECG Arrhythmia using Robust Spatial Kernel Fuzzy C-Means”, Proceedings of 8th International Conference on Advances in Computing and Communications, pp. 221-234, 2018.
- R. Varatharajan, G. Manogaran and M.K. Priyan, “A Big Data Classification Approach using LDA with an Enhanced SVM Method for ECG Signals in Cloud Computing”, Multimedia Tools and Applications, Vol. 77, No. 8, pp. 1-24, 2018.
- A. Dallali, A. Kachouri and M. Samet, “Classification of Cardiac Arrhythmia Using WT, HRV, and Fuzzy C-Means Clustering”, Signal Processing: An International Journal, Vol. 5, No. 3, pp. 101-109, 2011.
- A.N. Benaichouche., H. Oulhadj and P. Siarry, “Improved Spatial Fuzzy C means Clustering for Image Segmentation using PSO Initialization, Mahalanobis Distance and Post-Segmentation Correction”, Digital Signal Processing, Vol. 23, No. 5, pp. 1390-1400, 2013.
- S. Wold, K. Esbensen and P. Geladi, “Principal Component Analysis”, Chemometrics and Intelligent Laboratory Systems, Vol. 2, No. 1-3, pp. 37-52, 1987.
- R.A. Fisher, “The Use of Multiple Measurements in Taxonomic Problems”, Annals of Human Genetics, Vol. 7, pp. 179-188, 1936.
- D. Cai, X. He, W.V. Zhang and J. Han, “Regularized Locality Preserving Indexing Via Spectral Regression”, Proceedings of 6th ACM Conference on Information and Knowledge Management, pp. 741-750, 2007.
- M. Sugeno and T. Terano, “A Model of Learning Based on Fuzzy Information”, Kybernetes, Vol. 6, pp. 157-166, 1977.
- R.R. Yager, “On the Measure of Fuzziness and Negation Part I: Membership in the Unit Interval”, International Journal of General Systems, Vol. 5, No. 2, pp. 221-229, 1979.
- S.V. Arun Kumar and B.S. Harish, “A Modified Intuitionistic Fuzzy Clustering Algorithm for Medical Image Segmentation”, Journal of Intelligent Systems, Vol. 27, No. 4, pp. 593-607, 2017.
- M.S. Catia et al., “Takagi-Sugeno Fuzzy Modeling using Mixed Fuzzy Clustering”, IEEE Transaction of Fuzzy Systems, Vol. 25, No. 6, pp. 1417-1429, 2017.
- Symbolic Representation of Internet Traffic Data using Multiple Kernel Fuzzy C-Means
Abstract Views :750 |
PDF Views:1
Authors
N. Manju
1,
B. S. Harish
2
Affiliations
1 Department of Information Science and Engineering, Sri Jayachamarajendra College of Engineering, IN
2 Department of Information Science and Engineering, JSS Science and Technology University, IN
1 Department of Information Science and Engineering, Sri Jayachamarajendra College of Engineering, IN
2 Department of Information Science and Engineering, JSS Science and Technology University, IN
Source
ICTACT Journal on Soft Computing, Vol 9, No 4 (2019), Pagination: 1951-1955Abstract
Network traffic classification is a core part of the network traffic management. Network management is a critical task since the various new applications are emerging every moment and increase in the number of users of an internet. Due to this problem, there is a need of internet traffic classification for smooth management of an internet by the internet service providers (ISP). Network traffic can be classified based on port, payload and statistical approach. In the proposed work, a novel method to represent internet traffic data based on clustering of feature vector using Multiple Kernel Fuzzy C-Means (MKFCM) is proposed. Further, feature vector of each cluster is used to build an interval valued representation (symbolic) using mean and standard deviation. In addition, this interval valued features are stored in knowledge base as a representative of the cluster. Further, to classify the symbolic interval data, we used symbolic classifier. To validate the effectiveness of the proposed model, experimentation is conducted on standard Cambridge University internet traffic dataset. Further, the proposed symbolic classifier compared with other existing classifiers such as Naïve Bayes, KNN and SVM classifier. The experiment outcome infers that; the proposed symbolic representation classifier performs better than other classifiers.Keywords
Internet Traffic, Representation, Symbolic Feature, Classification.References
- M. Roughan, S. Sen, O. Spatscheck and N. Duffield, “Class-of-Service Mapping for QoS: A Statistical Signature-based Approach to IP Traffic Classification”, Proceedings of 4th ACM Conference on Internet Measurement, pp. 135-148, 2004.
- T. Karagiannis, K. Papagiannaki and M. Faloutsos, “BLINC: Multilevel Traffic Classification in the Dark”, Proceedings of ACM International Conference on Computer Communication Review, pp. 229-240, 2005.
- T.T. Nguyen and G.J. Armitage, “A Survey of Techniques for Internet Traffic Classification using Machine Learning”, IEEE Communications Surveys and Tutorials, Vol. 20, No. 1, pp. 56-76, 2008.
- A. Finamore, M. Mellia, M. Meo and D. Rossi, “Kiss: Stochastic Packet Inspection Classifier for UDP Traffic”, IEEE/ACM Transactions on Networking, Vol. 18, No. 5, pp. 1505-1515, 2010.
- Y. Xiang, W. Zhou and M. Guo, “Flexible Deterministic Packet Marking: An IP Traceback System to Find the Real Source of Attacks”, IEEE Transactions on Parallel and Distributed Systems, Vol. 20, No. 4, pp. 567-580, 2009.
- Z.M. Fadlullah, T. Taleb, A.V. Vasilakos, M. Guizani and N. Kato, “DTRAB: Combating Against Attacks on Encrypted Protocols through Traffic-Feature Analysis”, IEEE/ACM Transactions on Networking, Vol. 18, No. 4, pp. 1234-1247, 2010.
- R. Buyya, C.S. Yeo, S. Venugopal, J. Broberg and I. Brandic, “Cloud Computing and Emerging IT Platforms: Vision, Hype, and Reality for Delivering Computing as the 5th Utility”, Future Generation Computer Systems, Vol. 25, No. 6, pp. 599-616, 2009.
- M. Armbrust, A. Fox and R. Griffith, “A View of Cloud Computing”, Communications of the ACM, Vol. 53, No. 4, pp. 50-58, 2010.
- H. Dreger, A. Feldmann, M. Mai, V. Paxson and R. Sommer, “Dynamic Application-Layer Protocol Analysis for Network Intrusion Detection”, Proceedings of 15th International USENIX Association Symposium on Security, pp. 257-272, 2006.
- A.W. Moore and K. Papagiannaki, “Toward the Accurate Identification of Network Applications”, Proceedings of International Workshop on Passive and Active Network Measurement, pp. 41-54, 2005.
- S. Sen, O. Spatscheck and D. Wang, “Accurate, Scalable in-Network Identification of P2P Traffic using Application Signatures”, Proceedings of 13th International Conference on World Wide Web, pp. 512-521, 2004.
- R.C. Jaiswal and S.D. Lokhande, “Machine Learning based Internet Traffic Recognition with Statistical Approach”, Proceedings of Annual IEEE International Conference on Networking and Security, pp. 1-6, 2013.
- R.Y. Wang, L.I.U. Zhen and Z. Ling, “Method of Data Cleaning for Network Traffic Classification”, The Journal of China Universities of Posts and Telecommunications, Vol. 21, No. 3, pp. 35-45, 2014.
- L. Zhen and L. Qiong, “A New Feature Selection Method for Internet Traffic Classification using ML”, Physics Procedia, Vol. 33, pp. 1338-1345, 2012.
- M. Sun, J. Chen, Y. Zhang and S. Shi, “A New Method of Feature Selection for Flow Classification”, Physics Procedia, Vol. 24, pp. 1729-1736, 2012.
- H. Zhang, G.Lu, M.T. Qassrawi, Y. Zhang and X. Yu, “Feature Selection for Optimizing Traffic Classification”, Computer Communications, Vol. 35, No. 12, pp. 1457-1471, 2012.
- A. Fahad, Z. Tari, I. Khalil and I. Habib, “Toward an Efficient and Scalable Feature Selection Approach for Internet Traffic Classification”, Computer Networks, Vol. 57, No. 9, pp. 2040-2057, 2013.
- S. Wang and X. Yao, “Multiclass Imbalance Problems: Analysis and Potential Solutions”, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), Vol. 42, No. 4, pp. 1119-1130, 2012.
- L. Peng, Lizhi, B. Yang, Y. Chen and X. Zhou, “An Under-Sampling Imbalanced Learning of Data Gravitation Based Classification”, Proceedings of 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, pp. 1-6, 2016.
- L. Peng, H. Zhang, B. Yang and Y. Chen, “A New Approach for Imbalanced Data Classification based on Data Gravitation”, Information Sciences, Vol. 288, pp. 347-373, 2014.
- L. Peng, H. Zhang, B. Yang and Y. Chen, “Imbalanced Traffic Identification using an Imbalanced Data Gravitation-based Classification Model”, Computer Communications, Vol. 102, pp. 177-189, 2017.
- T.T.T. Nguyen, G. Armitage, P. Branch and S. Zander, “Timely and Continuous Machine-Learning-based Classification for Interactive IP Traffic”, IEEE/ACM Transactions on Networking, Vol. 20, No. 6, pp. 1880-1894, 2012.
- Neeraj Namdev, Shikha Agrawal and Sanjay Silkari, “Recent Advancement in Machine Learning based Internet Traffic Classification”, Procedia Computer Science, Vol. 60, pp. 784-791, 2015.
- Y. Wang, Y. Xiang, J. Zhang, W. Zhou, G. Wei and L.T. Yang, “Internet Traffic Classification using Constrained Clustering”, IEEE Transactions on Parallel and Distributed Systems, Vol. 25, No. 11, pp. 2932-2943, 2014.
- Hardeep Singh, “Performance Analysis of Unsupervised Machine Learning Techniques for Network Traffic Classification”, Proceedings of 5th IEEE International Conference on Advanced Computing and Communication Technologies, pp. 1-6, 2015.
- J. Erman, M. Arlitt and A. Mahanti, “Traffic Classification using Clustering Algorithms”, Proceedings of SIGCOMM workshop on Mining Network Data, pp. 1-5, 2006.
- D.S. Guru, B.S. Harish and S. Manjunath. “Symbolic Representation of Text Documents”, Proceedings of 3rd Annual ACM Bangalore Conference, pp. 1-5, 2010.
- B.S. Harish, B. Prasad and B. Udayasri, “Classification of Text Documents using Adaptive Fuzzy C-Means Clustering”, Proceedings of IEEE International Conference on Recent Advances in Intelligent Informatics, pp. 205-214, 2014.
- K.R. Muller, S. Mika, G. Ratsch, K. Tsuda and B. Scholkopf, “An Introduction to Kernel-Based Learning Algorithms”, IEEE Transactions on Neural Networks, Vol. 12, No. 2, pp. 181-200, 2001.
- Hsin Chien Huang, Yung-Yu Chuang and Chu-Song Chen, “Multiple Kernel Fuzzy Clustering”, IEEE Transactions on Fuzzy Systems, Vol. 20, No. 1, pp. 120-134, 2012.
- D. Cai, X. He, W.V. Zhang and J. Han, “Regularized Locality Preserving Indexing via Spectral Regression”, Proceedings of 16th ACM International Conference on Information and Knowledge Management, pp. 741-750, 2007.
- A. Moore, Z. Denis Zuev and M. Crogan, “Discriminators for Use in Flow-Based Classification”, Technical Report, Department of Computer Science, Queen Mary University of London, pp. 1-19, 2013.
- F. Ertam and A. Engin, “A New Approach for Internet Traffic Classification: GA-WK-ELM”, Measurement, Vol. 95, pp. 135-142, 2017.