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Pratheepa, M.
- Seasonal Population Fluctuations of Cotton Bollworm, Helicoverpa armigera (Hubner) in Relation to Biotic and Abiotic Environmental Factors at Raichur, Karnataka, India
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Authors
Affiliations
1 National Bureau of Agriculturally Important Insects, Post Bag No. 2491, H. A. Farm Post, Hebbal, Bellary Road, Bangalore 560024, Karnataka, IN
2 Shrimathi Indira Gandhi College, Tiruchirappalli 620002, Tamil Nadu, IN
3 Department of M.C.A., Shrimathi Indira Gandhi College, Tiruchirappalli 620002, Tamil Nadu, IN
4 Indian Institute of Horticultural Research, Hessaraghatta Lake Post, Bangalore 560089, Karnataka, IN
5 Department of Entomology, Agricultural Research Station, Raichur 584101, Karnataka, IN
1 National Bureau of Agriculturally Important Insects, Post Bag No. 2491, H. A. Farm Post, Hebbal, Bellary Road, Bangalore 560024, Karnataka, IN
2 Shrimathi Indira Gandhi College, Tiruchirappalli 620002, Tamil Nadu, IN
3 Department of M.C.A., Shrimathi Indira Gandhi College, Tiruchirappalli 620002, Tamil Nadu, IN
4 Indian Institute of Horticultural Research, Hessaraghatta Lake Post, Bangalore 560089, Karnataka, IN
5 Department of Entomology, Agricultural Research Station, Raichur 584101, Karnataka, IN
Source
Journal of Biological Control, Vol 24, No 1 (2010), Pagination: 47-50Abstract
An attempt was made to study the effect of abiotic and naturally occurring biotic factors on Helicoverpa armigera (Hubner) (Lepidoptera: Noctuidae) with cotton as a model crop system. The results revealed that Chrysoperla sp. (carnea-group) (r = 0.344) was positively correlated with pest incidence and the weather parameters like maximum temperature (r = -0.309) and rainfall (r = -0.288) were negatively correlated with pest incidence. It was observed that post-monsoon season was most favourable for pest occurrence and it was more when the crop was in flowering and boll formation stage. Spiders and Chrysoperla sp. (carnea-group) were positively correlated with pest incidence during winter.Keywords
Helicoverpa armigera, Cotton, Season, Spiders, Chrysopids.Full Text
- Decision Tree Induction Model for the Population Dynamics of Mirid Bug, Creontiodes biseratense (Distant) (Hemiptera: Miridae) and Its Natural Enemies
Abstract Views :258 |
PDF Views:123
Authors
Affiliations
1 Department of M.C.A., Shrimathi Indira Gandhi College, Trichirappalli 620 002, Tamil Nadu, IN
2 Bharathidasan University, Trichirappalli 620 024, Tamil Nadu, IN
3 Department of Entomology, University of Agricultural Sciences, Raichur 584 102, IN
1 Department of M.C.A., Shrimathi Indira Gandhi College, Trichirappalli 620 002, Tamil Nadu, IN
2 Bharathidasan University, Trichirappalli 620 024, Tamil Nadu, IN
3 Department of Entomology, University of Agricultural Sciences, Raichur 584 102, IN
Source
Journal of Biological Control, Vol 27, No 2 (2013), Pagination: 88-94Abstract
The mirid bug, Creontiodes biseratense (Distant) (Hemiptera: Miridae) is as a serious pest of cotton crop. Forecasting model by linking the pest incidence with season, crop phenology, biotic and abiotic factors enable to understand the dynamics of pest occurrence likely to occur. A data mining technique decision tree induction model is proposed for forecasting the pest incidence and study the population dynamics of mirid bug, C. biseratense in relation to its natural enemies viz., spider Lycosa sp. and coccinellid Cheilomenes sexmaculata Fabricius and abiotic factors. The results of the decision tree agreed well with statistical analysis.Keywords
Creontiodes biseratense, Cotton, Spiders, Coccinellids, Decision Tree, Information Theory, Abiotic.Full Text
References
- Anonymous, 2008a. Project coordinator’s report (2007– 08). All India co-ordinated cotton improvement project, pp. 4.
- Basak J, Krishnapuram R. 2005. Interpretable hierarchical clustering by constructing an un-supervised decision tree. IEEE Trans Knowl Data Engg 17 (1): 121–132.
- Ghavami S. 2008. The potential of predatory spiders as biological control agents of cotton pests in Tehran Provinces of Iran. Asian J Expl Sci. 22 (3): 303–306.
- Han J, Kamber M. 2001. Classification and prediction. pp. 285–375. In Data Mining Concepts and Techniques, 2nd ed. Jim Gray, Indian Reprint. Elsevier. Morgan Kaufmann.
- Khan M, Quade A, Murray D. 2007. Damage assessment and action threshold for mirids, Creontiades spp. In Bollgard II cotton in Australia. Second International Lygus Symposium Asilomar. J Insect Sci. 8: 49, p. 27.
- Patil BV, Bheemanna M, Patil SB, Udikery SS, Hosmani A. 2006. Record of mirid bug, Creontiades biseratense (Distant) on cotton from Karnataka, India. Insect Env. 11:176–177.
- Ravi PR, Patil BV. 2008. Biology of mirid bug, Creontiades biseratense (Distant) (Hemiptera: Miridae) on Bt cotton. Karnataka J Agric Sci. 21(2): 234–236.
- Sreedevi K, Verghese A. 2007. Ecology of aphidophagous predators in pomegranate ecosystem in India. Communication Agrl Appl Biol Sci. 72(3): 509–516.
- Surulivelu T, Dhara Jothi B. 2007. Mirid bug, Creontiodes biseratense (Distant) damage on cotton in Coimbatore. http://www.cicr.gov.in
- Trivedi TP, Yadav CP, Vishwadhar, Srivastava CP, Dhandapani, Das DK, Singh, J. 2005. Monitoring and forecasting of Heliothis / Helicoverpa population, pp. 119-140 In: Sharma HC (Ed.) Heliothis / Helicoverpa Management – Emerging trends and strategies for future research. Oxford & IBH Publishing Co. Pvt. Ltd., New Delhi.
- Udikeri SS, Patil SB, Shaila HM, Guruprasad GS, Patil SS, Kranthi KR, Khadi BM. 2009. Mirid menace – a potential emerging sucking pest problem in cotton. http://www.icas.org.
- Venkateshalu V, Kalmath B, Swamy L, Sushila N, Mallapur CP, Reddy N. 2010. Performance of different Bt cotton hybrids against mirid bug, Creontiades biseratense (Distant) (Miridae: Hemiptera). Kar J Agric Sci. 23(1):109–110.
- Venugopal Rao N. 1995. Bioecology and management of Helicoverpa armigera in the cotton ecosystem of Andhra Pradesh, Hyderabad, India. Andhra Pradesh Agricultural University. Ph.D Thesis.
- Zhao H, Ram S. 2004. Constrained cascade generalization of decision trees, IEEE Trans Knowl Data Engg 16 (6): 727–739.
- Neural-Network Classifier for the Prediction of Occurrence of Helicoverpa armigera (Hiibner) and its Natural Enemies
Abstract Views :218 |
PDF Views:123
Authors
Affiliations
1 Dept. of Computer Science, Shrimathi Indira Gandhi College, Tiruchirappalli 620 002, Tamil Nadu., IN
2 Bharathidasan University, Tiruchirappalli 620 024, Tamil Nadu., IN
3 Department of Entomology, University of Agricultural Science, Raichur 584 102, Karnataka, IN
4 Indian Institute of Horticultural Research, Hessaraghatta Lake Post, Bangalore 560 089, Karnataka, IN
1 Dept. of Computer Science, Shrimathi Indira Gandhi College, Tiruchirappalli 620 002, Tamil Nadu., IN
2 Bharathidasan University, Tiruchirappalli 620 024, Tamil Nadu., IN
3 Department of Entomology, University of Agricultural Science, Raichur 584 102, Karnataka, IN
4 Indian Institute of Horticultural Research, Hessaraghatta Lake Post, Bangalore 560 089, Karnataka, IN
Source
Journal of Biological Control, Vol 25, No 2 (2011), Pagination: 134-142Abstract
The cotton bollworm, Helicoverpa armigera (Hiibner) is an important pest in India damaging cotton crop and resulting in economic loss. Accurate and timely prediction of the pest, considering biotic and abiotic factors is essential to reduce the crop loss. In this paper, we present a neural-network classifier for predicting the pest incidence on cotton by considering the season, crop phenology, biotic factors (spiders and Chrysoperla zastrowi sillemi) and abiotic factors such as maximum temperature, minimum temperature, rainfall and relative humidity. Single layer perceptron neural-network with back-propagation algorithm was utilized for the design of the presented intelligent system. Decision tree is presented from the proposed trained neural-network. The results showed that the supervised neural network system could classify or predict the pest incidence as either 'high' or 'low' based upon economic threshold level with high degree of accuracy. Extracting rules from the decision tree helps the user to understand the role of biotic and abiotic factors on H. armigera incidence.Keywords
Back-Propagation Algorithm, Biotic And Abiotic Factors, Helicoverpa armigera, Knowledge Extraction, Neuralnetwork Classifier, Pest Prediction.Full Text
- Incidence of Aggressive Territoriality between Two Ant Species: Camponotus compressus Fab. and Oecophylla smaragdina Fab. (Hymenoptera:Formicidae)
Abstract Views :196 |
PDF Views:84
Authors
Affiliations
1 Department of Zoology, Bangalore University, Bengaluru 560 056, IN
2 National Bureau of Agricultural Insect Resources, Bengaluru 560 024, IN
3 G.P.S. Institute of Agriculture Management, #1 Tech Industrial Complex, Peenya Industrial Estate, Peenya 1st Stage, Bengaluru 560 058, IN
1 Department of Zoology, Bangalore University, Bengaluru 560 056, IN
2 National Bureau of Agricultural Insect Resources, Bengaluru 560 024, IN
3 G.P.S. Institute of Agriculture Management, #1 Tech Industrial Complex, Peenya Industrial Estate, Peenya 1st Stage, Bengaluru 560 058, IN
Source
Current Science, Vol 111, No 12 (2016), Pagination: 2044-2046Abstract
Interspecific rivalry among higher animals is not uncommon. However, it is less noticed among invertebrates, which function at micro ecological levels. One such incident was encountered by the authors in an old, neglected mango orchard on the outskirts of Bengaluru, India, between two species of ants, Camponotus compressus Fabricius and Oecophylla smaragdina Fabricius. While these two spatially co-existed and foraged in the orchard, rivalry was found on three trees which harboured arboreal O. smaragdina nests, where C. compressus (a ground nester) also began nesting at the base of the tree.
Foragers of O. smaragdina while descending the tree trunks found C. compressus at the base of the tree an intrusion (or vice versa?) and interspecific rivalry ensued for nearly seven weeks leading to mortality in both species. Overall, O. smaragdina suffered six times more loss in terms of number and biomass, but prevailed over C. compressus. The latter was forced to abandon nesting. It is important to record such interspecific processes, in insects at a micro ecological level.
Keywords
Aggressive Territoriality, Ants, Interspecific Rivalry, Micro Ecological Levels.Full Text
- Optimized Binning Technique in Decision Tree Model for Predicting The Helicoverpa armigera (Hubner) Incidence on Cotton
Abstract Views :245 |
PDF Views:114
Authors
Affiliations
1 ICAR-National Bureau of Agricultural Insect Resources, Bengaluru – 560024, Karnataka, IN
2 Department of Computer Science, Jain University, Bengaluru – 560011, Karnataka, IN
3 University of Agricultural Sciences, Agricultural Research Station, Raichur - 584102, Karnataka, IN
1 ICAR-National Bureau of Agricultural Insect Resources, Bengaluru – 560024, Karnataka, IN
2 Department of Computer Science, Jain University, Bengaluru – 560011, Karnataka, IN
3 University of Agricultural Sciences, Agricultural Research Station, Raichur - 584102, Karnataka, IN
Source
Journal of Biological Control, Vol 32, No 1 (2018), Pagination: 31-36Abstract
The data mining technique decision tree induction model is a popular method used for prediction and classification problems. The most suitable model in pest forewarning systems is decision tree analysis since pest surveillance data contains biotic, abiotic and environmental variables and IF-THEN rules can be easily framed. The abiotic factors like maximum and minimum temperature, rainfall, relative humidity, etc. are continuous numerical data and are important in climate-change studies. The decision tree model is implemented after pre-processing the data which are suitable for analysis. Data discretization is a pre-processing technique which is used to transform the continuous numerical data into categorical data resulting in interval as nominal values. The most commonly used binning methods are equal-width partitioning and equal-depth partitioning. The total number of bins created for the variable is important because either large number of bins or small number of bins affects the accuracy in results of IF-THEN rules. Hence, optimized binning technique based on Mean Integrated Squared Error (MISE) method is proposed for forming accurate IF-THEN rules in predicting the pest Helicoverpa armigera incidence on cotton crop based on decision tree analysis.Keywords
Bin Optimization, Decision Tree, Discretization, Helicoverpa armigera, If-Then Rules, Pest Prediction.Full Text
References
- Dhaliwal GS, Arora R. 1996. Integrated pest management: Achievements and Challenges, pp. 308–355. In: Dhaliwal GS, Arora R. (Eds). Principles of Insect Pest Management, NATIC, India.
- George HJ, Ron K, Karl P. 1994. Irrelevant features and the subset selection problem. In: William W Cohen and Haym Hirsh (Eds.) Machine Learning: Proceedings of the Eleventh International Conference. 121-129, Morgan Kaufmann Publishers, San Francisco, CA.
- Gupta GK. 2006. Classification. In: Introduction to Data Mining with Case Studies, Prentice-Hall of India, 106– 136. https://doi.org/10.1016/B978-044451636-7/50013-9
- Leonardo T, Miriam EP. 2002. The distribution and movement of cotton bollworm, Helicoverpa armigera Hübner (Lepidoptera: Noctuidae) larvae on cotton. Philippine J Sci, 131: 91–98.
- Pratheepa M, Meena K, Subramaniam KR, Venugopalan R, Bheemanna H. 2011. A decision tree analysis for predicting the occurrence of the pest, Helicoverpa armigera and its natural enemies on cotton based on economic threshold level. Curr Sci. 100(2): 238–246.
- Shimazaki H, Shinomoto S. 2007. A method of selecting the binsize of a Time Histogram. Neural Comput.19(6): 1503–1527.
- SPSS V 17.0. 2008. Statistical Package for Social Sciences. SPSS Inc. Illinois, Chicago,USA.
- Sotiris K, Dimitris K. 2006. Discretization techniques: A recent survey. GESTS International Trans Comput. Sci Engineering. 32(1): 47–58.
- Zhao H, Ram S. 2004. Constrained cascade generalization of decision trees. IEEE Trans Knowledge Data Engineering. 16(6): 727–739. Available from: https://dl.acm.org/citation.cfm?id=1437601 https://doi.org/10.1109/TKDE.2004.3
- A Bayesian Classification Approach for Predicting Gesonia gemma Swinhoe Population on Soybean Crop in Relation to Abiotic Factors Based on Economic Threshold Level
Abstract Views :256 |
PDF Views:126
Authors
Affiliations
1 Division of Genomic Resources, ICAR-National Bureau of Agricultural Insect Resources, Bengaluru – 560024, Karnataka, IN
1 Division of Genomic Resources, ICAR-National Bureau of Agricultural Insect Resources, Bengaluru – 560024, Karnataka, IN
Source
Journal of Biological Control, Vol 32, No 1 (2018), Pagination: 68-73Abstract
Predicting of insect pest population with accuracy and speed when given large data set will make a major contribution to the success of integrated pest management. Naïve Bayesian classification has been proposed for predicting the insect pest Gesonia gemma Swinhoe on soybean crop. The Naïve Bayesian classifier works based on Bayes’ theorem and can predict class probabilities that a given tuple from the dataset belongs to a particular class. The dataset includes abiotic factors as features along with the class feature (pest incidence) are separated as training data and testing data, then the model was built on the training set by finding the probability for each of its features in relation with the class feature. The Naïve Bayesian classification from the trained model, best fits the testing data with 90% accuracy, thus the proposed approach can be very useful in predicting the pest G. gemma on soybean crop.Keywords
Abiotic, Bayesian Classification, Gesonia gemma, Naïve Population Dynamics, Soybean.Full Text
References
- Agarwal DK, Billore SD, Sharma AN, Dupare BU, Srivastava SK. 2013. Soybean: Introduction, improvement, and utilization in india-problems and prospects. Agric Res. 2(4): 293–300. https://doi.org/10.1007/s40003-0130088-0
- Antony JC, Pratheepa M. 2017. Study of population dynamics of soybean semi-looper Gesonia gemma Swinhoe by using rule induction model in Maharashtra, India. Legume Res. 40(2): 369–373.
- Duda RO, Hart PE. 1973. Pattern classification and scene analysis. John Wiley, NY.
- Good IJ. 1965. The estimation of probabilities: An essay on modern Bayesian methods. M.I.T. Press, Cambridge, MA.
- Han J, Kamber M. 2006. Data mining: Concepts and techniques. Morgan Kaufmann, San Francisco, CA.
- Sharma AN. 2011. Insect pests of soybean: Present management strategies and future thrusts. 3rd Congress on Insect Science - Pest Management for Food Security and Environment Health, organized by Indian Society for the Advancement of Insect Science, Ludhiana, India, 18th-20th Apr 2011.
- Southwood TRE. 1977. The relevance of population dynamics theory to pest status. In: Cherret JM and Sagar GR (Eds.) Origins of Pest, Parasite, Disease and Weed Problems. Blackwell Scientific Publications, Oxford, UK.
- Zaidi NA, Cerquides J, Carman MJ, Webb GI. 2013. Alleviating Naïve Bayes attribute independence assumption by attribute weighting. J Mach Learn Res. 14: 1947–1988.
- Yadav SS, Nayak MK, Srivastava AK, Gupta MP, Tomar DS. 2014. Population dynamics of insect defoliator of soybean and correlation with weather parameters. Ann Plant Protect Sci. 22: 208–209.
- Pithy Stems - An Effective and Viable Option to Conserve Sub Social and Solitary Bees and Wasps
Abstract Views :322 |
PDF Views:143
Authors
Affiliations
1 Division of Insect Ecology, ICAR – National Bureau of Agricultural Insect Resources (NBAIR), H.A Farm Post, PB No 2491, Bellary Road, Bangalore – 560024, Karnataka, IN
1 Division of Insect Ecology, ICAR – National Bureau of Agricultural Insect Resources (NBAIR), H.A Farm Post, PB No 2491, Bellary Road, Bangalore – 560024, Karnataka, IN
Source
Journal of Biological Control, Vol 32, No 3 (2018), Pagination: 152-154Abstract
Artificial trap nesting of bees will help in their conservation in situ and utilizing them for enhancing pollination service in cropping systems. The present study was undertaken to study the nesting behavior and rate of acceptance of pithy stems for nesting by the different bee species at ICAR-NBAIR Yelahanka Campus (13.096792N, 77.565976E). Fifteen nests comprising of pithy stems of Caesalpinia pulcherrima each made into three bundles containing five nests each were placed at three places in two sites viz., Site 1 (Pollinator Garden) and Site 2 (Vegetable block). The days taken by the bees to accept the trap nests placed in the pollinator garden and vegetable field were found to be 5.87 and 11.53 days with a percent acceptance of 80 and 66.67 per cent, respectively. The average number of cells built by the bees in the nests obtained from the pollinator garden and vegetable ecosystem were found to be 6.00 and 5.33 respectively. Ceratina binghami, C. hieroglyphica, Megachile lerma and predatory sphecid wasps were found to emerge out from the trap nests. Diversity of the stem nesting bees was found to be higher in the nests placed in the pollinator garden as compared to vegetable block.Keywords
Ceratina binghami, Conservation, Diversity, Evenness, Pithy Stems, Richness.Full Text
References
- Biesmeijer JC, Roberts SPM, Reemer M, Ohlemuller R, Edwards M, Peeters T. 2006. Parallel declines in pollinators and insect-pollinated plants in Britain and the Netherlands. Science 313: 351–354.
- https://doi.org/10.1126/science.1127863 PMid:16857940
- Bosch J, Maeta Y, Rust R. 2001. A phylogenetic analysis of nesting behavior in the genus Osmia (Hymenoptera: Megachilidae). Ann Entomol Soc Am. 94: 617–627. https://doi.org/10.1603/0013-8746(2001)094[0617:APA ONB]2.0.CO;2
- Buschini MLT. 2005. Species diversity and community structure in trap-nesting bees in Southern Brazil. Apidologie 37: 58–66 https://doi.org/10.1051/apido:2005059
- Cane JH, Griswold T, Parker FD. 2007. Substrates and materials used for nesting by North American Osmia Bees (Hymenoptera: Apiformes: Megachilidae). Ann Entomol Soc Am. 100(3): 350–358. https://doi.org/10.1603/0013-8746(2007)100[350:SAMUFN]2.0 .CO;2
- Gathmann A, Greiler HJ, Tscharntke T. 1994. Trap nesting bees and wasps colonizing set-aside fields: succession and body size, management by cutting and sowing. Oecologia 98: 8–14. https://doi.org/10.1007/ BF00326084 PMid:28312790
- McIntosh M. 1996. Nest-Substrate preferences of the twignesters Ceratina acantha, Ceratina nanula (Apidae) and Pemphredon lethifer (Sphecidae). J Kansas Entomol Soc. 69(4): 216–231.
- Potts SG, Biesmeijer JC, Kremen C, Neumann P, Schweiger O, Kunin WE. 2010. Global pollinator declines: Trends, impacts and drivers. Tree 25: 345–353. https://doi.org/10.1016/j.tree.2010.01.007 PMid:20188434
- Strickler K., Scott VL, Fischer RL. 1996. Comparative nesting ecology of two sympatric leafcutting bees that differ in body size (Hymenoptera: Megachilidae). J Kans Entomol Soc. 69: 26–44.
- Zhang H, John R, Peng Z, Yuan J, Chu C, Du G, Zhou S. 2012. The relationship between species richness and evenness in plant communities along a successional gradient: A study from sub-alpine meadows of the Eastern QinghaiTibetan Plateau, China. PLoS One 7(11): 49024. https://doi.org/10.1371/journal.pone.0049024 PMid:23152845 PMCid:PMC3494667
- Biodiversity of Pollinators in Four Bee-Friendly Plant Species
Abstract Views :248 |
PDF Views:211
Authors
Affiliations
1 ICAR-National Bureau of Agricultural Insect Resources, Post Bag No. 2491, H. A. Farm Post, Hebbal, Bengaluru – 560024, Karnataka, IN
1 ICAR-National Bureau of Agricultural Insect Resources, Post Bag No. 2491, H. A. Farm Post, Hebbal, Bengaluru – 560024, Karnataka, IN
Source
Journal of Biological Control, Vol 33, No 4 (2019), Pagination: 360-364Abstract
Bees are the primary pollinators of many important agricultural crops. Enhancing the suitability of farm landscapes for native pollinators by growing flowering non crop plants is necessary for in-situ conservation of bee pollinators. A study has been conducted to find the role of four different plants, viz., Hamelia patens, Ocimum basilicum, Asystesia sp. and Jacquemontia sp. in the conservation of native bee pollinators. The different species of bees visiting the flowers were Apis cerana, A. florea, Hoplonomia sp., Amegilla zonata, A. confusa and Ceratina hieroglyphica. The diversity indices were higher during morning hours than the afternoon. The number of bees visited per flower, time spent and numbers of flowers visited on Jacquemontia sp. were more compared to other plant species. Biodiversity indices were calculated by using Insect Biodiversity Analysis Portal, which is an online tool to carry out biodiversity analysis and hosted at https://www.nbair.res.in/Biodiversity. The planting of bee-friendly plant species as identified in this study will help support healthy, diverse pollinator and other beneficial insect communities.Keywords
Bee Pollinators, Biodiversity Indices, In-Situ Conservation, Non-Crop Plants.Full Text
References
- Duffy KJ, Johnson SD, Peter CI. 2014. A temporal dimension to the influence of pollen rewards on bee behaviour and fecundity in Aloe tenuior. PLoS ONE 9: e94908. https://doi.org/10.1371/journal.pone.0094908 PMid:24755611 PMCid:PMC 3995886
- Emile May. 2018. Managing land for pollinators and conservation biocontrol. https://www.ecolandscaping.org/01/landscaping-for-wildlife/beneficialspollinators/managing-land-pollinators-conservation-biocontrol/
- Fussell M, Corbet SA. 1992. Flower usage by bumblebees - a basis for forage plant management. J Appl Ecol. 29: 451-465. https://doi.org/10.2307/2404513
- Jones EL, Leather SR. Invertebrates in urban areas: A review. European J Entomol. 109: 463-478.
- Kremen C, Williams NM, Thorp RW. 2002. Crop pollination from native bees at risk from agricultural intensification. Proc Nat Acad Sci. 99: 16812-16816.https://doi.org/10.1073/pnas.262413599 PMid:12486221 PMCid: PMC139226
- Piedade-Kiill, Lucia H, Neusa Taroda R. 2000. Biologia floral e sistema de reprodução de Jacquemontia multiflora (Choisy) Hallier f. (Convolvulaceae). Rev Bras Fisioter. 23: 37-43. https://doi.org/10.1590/S0100-84042000000100004
- Pywell RF, Meek WR, Hulmes L, Hulmes S, James KL, Nowakowski M, Carvell C. 2011. Management to enhance pollen and nectar resources for bumble bees and butterflies within intensively farmed landscapes. J Insect Conserv. 15: 853-864. https://doi.org/10.1007/s10841-011-9383-x
- Silvia KD, Gimenes M. 2016. The efficiency of bees in pollinating ephemeral flowers of Jacquemontia bracteosa (Convolvulaceae). Iheringia Ser Zool. 106: ISSN 0073-4721, On-line version ISSN 1678-4766. https://doi.org/10.1590/1678-4766e2016025
- Does India Have the Invasive Brown Marmorated Stink Bug, Halyomorpha Halys (Stål)
Abstract Views :297 |
PDF Views:84
Authors
Affiliations
1 ICAR-National Bureau of Agricultural Insect Resources, Hebbal, Bengaluru 560 024, IN
1 ICAR-National Bureau of Agricultural Insect Resources, Hebbal, Bengaluru 560 024, IN
Source
Current Science, Vol 120, No 2 (2021), Pagination: 268-269Abstract
No Abstract.Full Text
References
- Stål, C., Ӧfvers. Kongl. Vetensk.-Akad. Förh., 1855, 12(4), 181–192.
- Cianferoni, F., Graziani, F., Dioli, P. and Ceccolini, F., Biologia, 2018, 73(6), 599–607.
- Fabricius, J. C., Impensis C. G. Proft, Fil. Soc., Hafniae, 1794, 4, 472.
- Fabricius, J. C., Suppl. Proft Storch, Hafniae, 1798, 2, 572.
- Stål, C., Ӧfvers. Kongl. Vetensk.-Akad. Förh., 1868, 24(7), 501–522.
- Vidyasagar, P. S. P. V. and Bhat, K. S., Curr. Sci., 1986, 55(21), 1096–1097.
- Daniel, M., J. Plant. Crops, 2010, 38(1), 78–81.
- Bergroth, E., Ann. Mag. Nat. Hist., 1915, 15(8), 481–493.
- Salini, S. and Viraktamath, C. A., Zootaxa, 2015, 3924(1), 1–76.
- Vétek, G., Papp, V., Haltrich, A. and Rédei, D., Zootaxa, 2014, 3780(1), 194– 200.
- Karun, N. C. and Sridhar, K. R., J. Bio.Con, 2013, 27(2), 139–143.
- Nikam, K. N. and More, S. V., Biolife, 2016, 4(1), 209–212.
- Gupta, R. and Pathania, P. C., Rec. Zool. Surv. India, 2017, 117(4), 356–366.
- Ghauri, M. S. K., Reichenbachia. Staatl. Mus. Tierk. Dres., 1980, 18(21), 129– 146.
- Kment, P. and Březíková, M., Klapalekiana, 2018, 54, 221–232.
- Abbasi, Q. A. and Ahmad, I., Mushi, 1974, 48(7), 71–78.
- Ghauri, M. S. K., J. Nat. Hist., 1978, 12, 163–175.