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Hossain, M. S.
- Development of Bio-Rational Management Approach against Mango Hopper, Idioscopus nagpurensis (Pruthi) in Bangladesh
Abstract Views :304 |
PDF Views:125
Authors
Affiliations
1 Horticulture Research Centre, Bangladesh Agricultural Research Institute, Gazipur, BD
2 IPM Innovation Lab, Bangladesh Site, Gazipur, Bangladesh, BD
3 Regional Sugarcrops Research Station, BSRI, Gazipur, BD
4 IPM Innovation Lab,Virginia Tech, Blacksburg, VA 24961, US
1 Horticulture Research Centre, Bangladesh Agricultural Research Institute, Gazipur, BD
2 IPM Innovation Lab, Bangladesh Site, Gazipur, Bangladesh, BD
3 Regional Sugarcrops Research Station, BSRI, Gazipur, BD
4 IPM Innovation Lab,Virginia Tech, Blacksburg, VA 24961, US
Source
Journal of Biological Control, Vol 33, No 2 (2019), Pagination: 127-131Abstract
A field experiment was conducted during the 2016-17 mango cropping season in farmers’ fields of Gazipur, Rajshahi and Chapainawabgonj districts of Bangladesh to find an effective bio-rational management option for controlling the mango hopper, Idioscopus nagpurensis (Pruthi) (Hemiptera: Cicadellidae). Randomized Complete Block Design was used incorporating 8 treatments with 3 replications. The treatments were pruning of overcrowded and overlapping branches, spraying of azadirachtin, Beauveria bassiana (Lycomax, Russel IPM), imidacloprid insecticide, installation of yellow sticky grey and blue sticky trap and untreated control. Lowest leafhopper population was recorded in B. bassiana (3.0 hoppers/sweep/tree) followed by imidacloprid (3.7 leafhoppers/sweep/tree) treatments. Highest number of fruit retention was recorded in imidacloprid (40.00 fruits/20 inflorescence/tree) followed B. bassiana (32.67 fruits/20 inflorescence/tree) and azadirachtin (24.00 fruits/20 inflorescence/tree). Imidacloprid treatment offered maximum marginal benefit cost ratio (5.60). Increasing trend of hopper population was recorded in control. Considering health and environment issues, spraying of B. bassiana @ 5.0g/L of water at flower initiation stage, flowering stage and pea stage may be recommended for controlling mango hopper.Keywords
Azadirachtin, Bio-Rational, Beauveria bassiana, Imidacloprid, Mango Hopper.Full Text
References
- Debach P, Rosen D. 1991. Biological Control by Natural Enemies. Cambridge University Press, Cambridge, United Kingdom.
- Hossain AKMA. 1989. Manual on mango cultivation in Bangladesh. FAO/UNDP Publ., 82 pp.
- Irshad M, Gillani WA. 1990. Resistance in Tribolium castaneum against malathion. Pakistan J Zool. 25: 257-262.
- Gomez KA, Gomez AA. 1984. Statistical Procedures for Agricultural Research. 2nd ed. IRRI (International Rice Research Institute) and John Wiley and Sons, New York, USA, 680 pp.
- Karim MA. 1989. Insect pest of mango, pp. 1-25. In: Hossain AKMA. (Ed.). A Field Guide on Insect Pests and Diseases of Mango in Bangladesh and Their Control. FAO/UNDP Publ., 44 pp.
- Pedigo LP. 1999. Entomology and Pest Management. Prentice and Hall Incorporation, London.
- Prabhakara MS, Ghosh SK, Chaudhary M. 2011. Field efficacy of Myco-jaal, an oil based commercial formulation of Beauveria bassiana (Deuteromycotina: Hyphomycetaceae) against mango inflorescence hopper, Idioscopus nitidulus (Walker). Pest Manage Hort Ecosys. 17: 140-143.
- Wen HC, Lee HC. 1978. Bionomics and control of mango brown leafhopper (Idiocerus niveosparsus Leth.). J Agri Res China 27: 47-52.
- Development of Biorational Management for Tomato Leaf Miner, Tuta absoluta
Abstract Views :296 |
PDF Views:137
Authors
Affiliations
1 Horticulture Research Center, Bangaladesh Agrcultural Research Insititute (BARI), Gazipur, BD
2 Breeder Seed Production Station, BARI, Debigonj, Panchagarh, BD
3 Regional Sugar Crops Research Station, Gazipur, BD
4 IPM Innovation Lab, Bangladesh site, Gazipur, BD
5 IPM Innovation Lab, Virginia Tech, 526 Prices Fork Road, Blacksburg, VA 24061, US
1 Horticulture Research Center, Bangaladesh Agrcultural Research Insititute (BARI), Gazipur, BD
2 Breeder Seed Production Station, BARI, Debigonj, Panchagarh, BD
3 Regional Sugar Crops Research Station, Gazipur, BD
4 IPM Innovation Lab, Bangladesh site, Gazipur, BD
5 IPM Innovation Lab, Virginia Tech, 526 Prices Fork Road, Blacksburg, VA 24061, US
Source
Journal of Biological Control, Vol 33, No 2 (2019), Pagination: 132-136Abstract
The experiment was carried out in farmers’ fields of Chaklarhat, Tunirhat, Panchagarh and Research Field of Horticulture Research Center, Bari, Gazipur from October 2017 to June 2018 to findan effective and suitable management approach against tomato leaf miner, Tuta absoluta. There was a total of ten treatments, viz., Treatment 1 = Application of Metarrhizium anisolpiae (Lycomax, Russel IPM) biopesticide in soil @ 5g/L of water, Treatment 2 = Foliar spray of azadirachtin (Bio-Neem plus 1EC @ 1ml/L of water), Treatment 3 = Foliar spray of Bacillus thuringiensis (Biocure) @ 2g/L of water, Treatment 4 = Mass trapping through installation of delta sex pheromone trap, Treatment 5 = Spraying of spinosad (Tracer 45WSC) @ 0.5ml/L of water, Treatment 6 = Spraying with chlorantraniprole (Coragen 20SC) @ 0.5ml/L of water, Treatment 7 = Hand picking and destruction of infested leaf and fruit, Treatment 8 = Foliar spray of B. thuringiensis (Biocure) @ 2g/L of water + mass trapping through installation of delta sex pheromone trap + application of M. anisolpiae biopesticide in soil @ 5g/L of water, Treatment 9 = Foliar spray of azadirachtin (Bio-Neem plus 1EC @ 1ml/L of water) + mass trapping through installation of delta sex pheromone trap + Application of M. anisopliae (Lycomax, Russel IPM) biopesticide in soil @ 5g/L of water and Treatment 10 = untreated control were evaluated against T. absoluta following RCB design with three replications. Results revealed that foliar spray of azadirachtin (Bio- Neem plus 1EC @ 1ml/L of water) + mass trapping through installation of delta sex pheromone trap + application of M. anisopliae (Lycomax, Russel IPM) biopesticide in soil @ 5g/L of water performed best in reducing T. absoluta infestation, increase of marketable yield and highest marginal benefit cost ratio.Keywords
Biopesticides, Management, Neem, Pheromone Traps, Tuta absoluta.Full Text
References
- Desneux N, Luna MG, Guillemaudand T, Urbeneja A. 2011. The invasive South American tomato pinworm, Tuta absoluta, continues to spread in Afro-Eurasia and beyond: The new threat to tomato world production. J Pest Sci. 84: 403–408. https://doi.org/10.1007/s10340-011-0398-6
- Hossain MS, Mian MY, Muniappan R. 2016. First Record of Tuta absoluta (Lepidoptera: Gelechiidae) from Bangladesh. J Agri Urban Ent. 32: 101-105. https://doi.org/10.3954/1523-5475-32.1.101
- Sridhar V, Chakravarthy AK, Asokan R., Vinesh LS, Rebijith KB, Vennila S. 2014. New record of the invasive south American tomato leaf miner, Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae) in India. Pest Manag Hort Ecosyst. 20: 148–154.
- Urbaneja A, Desneux N, Gabarra R, Arnó J, Gonzalez-Cabrera J, Mafra-Neto A, Stoltman L, Pinto ADS, Parra JRP. 2013. Biology, ecology and management of the South American tomato pinworm, Tuta absoluta, pp. 98–125. In: Pena J (Ed.). Potential invasive pests of agricultural crops. CAB International, Oxfordshire, UK, 464 pp.
- Venkatramanan S, Marathe A, Eubank S, Marathe M, Adiga A. 2017. Hybrid models for ecological and anthropogenic drivers of pest invasion: Case study of Tuta absoluta in Nepal. In: Proceedings of International Conference on Biodiversity, climate change assessment and impacts on Livelihood, 10-12 January 2017, Kathmandu, Nepal.
- Face Detection for Behaviour Analysis using Deep Learning
Abstract Views :156 |
PDF Views:1
Authors
Affiliations
1 Electronics & Telecommunication Engineering Department, Northeastern University, Boston, US
1 Electronics & Telecommunication Engineering Department, Northeastern University, Boston, US
Source
Digital Signal Processing, Vol 12, No 7-9 (2020), Pagination:Abstract
The smart classroom of the future we envision will greatly enhance the learning experience and achieve seamless communication between students and teachers through real-time detection and machine intelligence. Additionally, facial recognition can capture student emotions such as happiness, sadness, neutrality, anger, nausea, surprise, and more. From this sentiment we analyze it and in the analysis derive the final overall student behavior of a particular speech. So, you can also get results in the form of teacher feedback and student feedback from student behavior. The three main parts of the student attendance system are then described in detail using two deep learning facial recognition algorithms. Behavioral analysis model based on facial recognition neural network or Haar classifier. iii) Automatic teacher feedback based on student behavior analysis.
