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Goswami, J.
- Efficacy of Metarhizium Anisopliae, Beauveria Bassiana and Neem Oil against Tomato Fruit Borer, Helicoverpa Armigera under Field Condition
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Authors
Affiliations
1 Krishi Vigyan Kendra (A.A.U.), Kaliapani Changmaigaon (Assam), IN
2 Krishi Vigyan Kendra (A.A.U.), Kajalgaon, Chirang (Assam), IN
3 Directorate of Extension Education, Assam Agricultural University, Jorhat (Assam), IN
1 Krishi Vigyan Kendra (A.A.U.), Kaliapani Changmaigaon (Assam), IN
2 Krishi Vigyan Kendra (A.A.U.), Kajalgaon, Chirang (Assam), IN
3 Directorate of Extension Education, Assam Agricultural University, Jorhat (Assam), IN
Source
Asian Journal of Bio Science, Vol 9, No 2 (2014), Pagination: 151-155Abstract
A field study was conducted at farmers field of Jorhat, Assam during 2010-11 to evaluate the efficacy of three commercial biopesticides, two based on insect pathogenic fungi viz., Beauveria bassiana and Metarhizium anisopliae and one botanical-Neem oil in comparison with chemical-cypermethrin against the tomato fruit borer (Helicoverpa armigera). The study revealed the reduction in fruit damage was upto 92.20 per cent in cypermethrin treated plot followed by 91.12 per cent, 88.74 per cent and 87.01 per cent in the plots treated with Neem oil, B. Bassiana and M. Anisopliae, respectively due to H. armigera larvae over control. The study showed that neem oil was nearly as effective as cypermethrin in reducing fruit damage leading to increased yield. The highest increase in yield over control was noticed in cypermethrin treated plots (62.85%) followed by neem oil treated plots (41.83%). The entomopathogenic fungi- Beauveria bassiana and Metarhizium anisopliae could be effectively used as pest management option in production of organic tomato to reduce the pest population below economic threshold level and increased yield.Keywords
Metarhizium anisopliae, Beauveria bassiana, Neem Oil, Helicoverpa armigeraReferences
- Basedow, Th., Ossiewatsch, H.R., Bernal, Vega, J.A., Kollman, S., Elshafie, H.A.F. and Nicol, C.M.Y. (2002). Control of aphids and whiteflies (Homoptera, Aphididae and Aleyrodidae) with different neem preparations in laboratory, greenhouse and field: effects and limitations. J. Plant Dis. & Protec., 109 (6) : 612-623.
- Deshpande, M., Venkatesh, K., Rodrigues, V. and Hasan, G. (2000). The inositol 1,4,5-trisphosphate receptor is required for maintenance of olfactory adaptation in Drosophila antennae, J. Neurobiol., 43(3) : 282-288.
- Dhandapani, N., Umeshchandra, S.R. and Murugan, M. (2003). Biointensive pest management (BIPM) in major vegetable crops: an Inadian perspective. Food Agric. Environ., 1 (2) : 333-339.
- El-Shafie, H.A.F. (2001). The use of neem products for sustainable management of homopterous key pests on potato and eggplant in Sudan. Ph.D. Thesis, Institute of Phytopathology and Applied Zoology Experimental station Justus Liebig University of Giessen, Germany.
- Elshafie, H.A.F. and Basedow, Th. (2003). The efficacy of different neem preparations for the control of insects damaging potatoes and eggplants in the Sudan. Crop Protec., 22 (8): 1015-1021.
- Elshafie, H.A.F. and Abdelraheem, B.A., (2012). Field evaluation of three biopesticides for integrated management of major pests of tomato, Solanum lycopersicum L. in Sudan. Agric. Bio. J. N. Am., 3 (9) : 340-344.
- Faria, M.R. and de Wraight, M.P. (2007). Mycoinsecticides and mycoacaricides: a comprehensive list with worldwide coverage and international classification of formulation types. Biological Control, 43 (3) : 237-256.
- Kumari, Beena, Madan, V.K., Kumar, R. and Kathpal, T.S. (2002). Monitoring of seasonal vegetables for pesticide residues. Environ. Monit. Assess., 74 (3) : 263-270.
- Lowery, D.T., Isman, M.B. and Brad, N.L. (1993). Laboratory and field evaluation of neem for the control of aphids (Homoptera: Aphididae). J. Econom. Entomol., 86 (3) : 864-870.
- Mochiah, M.B., Banful, B., Fening, K.N., Amoabeng, B.W., Offei Bonsu, K., Ekyem, S., Braimah, H. and Owusu-Akyaw, M. (2011). Botanicals for the management of insect pests in organic vegetable production. J. Entomol. & Nematol., 3 (6) : 85-97.
- Mudathir, M. and Basedow, T. (2003). Field experiments on the effects of neem products on pests and yield of okra Abelmoschus esculentus, Tomato, Lycopersicon esculentum and onion, Allium cepa in Sudan. Mitt. Deut. Ges. Allg. Angew. Entomol., 14 (1-6) : 407-410.
- Nguyen, T.H. Nguyen, Borgemeister, C., Poehling, H.M. and Zimmermann, G. (2007). Laboratory investigations on the potential of entomopathogenic fungi for biocontrol of Helicoverpa armigera (Lepidoptera: Noctuidae) larvae and pupae. Biocon. Sci. Tech., 17(8) : 853-864.
- Naher, P., Yadav, P., Kulye, M., Hadapad, A., Hussani, M., Tour, U., Keller, S., Chandler, A.G., Thomas, B. and Deshpande, M.V. (2004). Evaluation of indigenous fungal isolates, Metarhizium anisopliae M34412, Beauveria bassiana B3301 and Nomuraearileyi N812 for the control of Helicoverpa armigera (Hubner) in pigeonpea field. J. Biol. Control, 18 (1) : 1-8.
- Neupane, F. P. and Sah., L.N. (1988). Efficacy of some insecticides against the chickpea pod borer, Heliothis armigera Hubner. J. Inst. Agric. Anim. Sci., 9 : 103-105.
- Nagaraju, N., Venkatesh, H.M., Warburton, H., Muniyappa, V., Chancellor, T.C.B. and Colvin, J. (2002). Farmers’ perceptions and practices for managing tomato leaf curl virus disease in southern India. Internat. J. Pest Mgmt., 48 (4) : 333-338.
- Orden, M.E.M., Patricio, M.G. and Canoy, V.V. (1994). Extent of pesticide use in vegetable production in Nueva Ecija: Empirical evidence and policy implications. Research and Development Highlights 1994, Central Luzon State University, Republic of the Philippines. pp.196-213.
- Pandey, A.K., Namgyal, D., Mehdi, M., Mir, M.S. and Shikh, B.A. (2006). A case study : Major insect pest associated with different vegetable crops in cold arid region, Ladakh of Jammu and Kashmir. J. Entoml. Res., 30 (2) : 169-174.
- Reddy, S.G.E., Sharma, D. and Kumar, N.K. Krishna (2007). Residues of sweet pepper and tomato grown under greenhouse and open field cultivation. Pest. Res. J., 19 (2) : 239-243.
- Rijal, J.P., GC, Y.D., Thapa, R.B. and Kafle, L.N. (2008). Efficacy ofMetarhizium anisopliae and Beauveria bassiana against Helicoverpa armigera in Chickpea, under Field conditions in Nepal. Formosan Entomol., 28 (4) : 249-258.
- Schmutterer, H. (Ed.) (1995). The neem tree. Source of unique natural products for integrated pest management, medicine, industry and other purposes. Weinheim, New York, Basel, Cambridge, Tokyo (VCH).
- Siddig, S.A. (1987). A proposed management programme including neem treatments for combating potato pests in Sudan, pp. 449-459. In: Natural pesticides from the neem tree (Azadirachta indica A. Juss) and other Tropical Plants. (eds. H. Schmutterer and K.R.S. Ascher), Proceedings of 3rd International Neem Conference, Nairobi, 1986.
- Siddig, S.A. (1991). Evaluation of neem seed and leaf water extracts and powders for the control of insect pests in Sudan. Technical Bulletin 6. Agriculture Research Corporation, Shambat Research Station, 39pp.
- Saxena, R.C. (2011). Neem in pest management. J. Eco-friendly Agric., 6 (2) : 105-116.
- Tefera, Tadele and Pringle, K.L. (2004). Evaluation of Beauveria bassiana and Metarhizium anisopliae for Controlling Chilo partellus (Lepidoptera: Crambidae) in Maize. Biocon. Sci. Tech., 14 (8) : 849-853.
- Walstad, J.D., Anderson, R.F. and Stambaugh, W.J. (1970). Effects of environmental condition of two species of muscardine fungi, Beauveria bassiana (Bals.) Vuill and Metarhizium anisopliae (Metsch.) Sorokin. J. Invertebr. Pathol., 16: 221-226.
- Expansion of Sericulture in India Using Geospatial Tools and Web Technology
Abstract Views :224 |
PDF Views:79
Authors
B. K. Handique
1,
P. T. Das
1,
J. Goswami
1,
C. Goswami
1,
P. S. Singh
1,
C. J. Prabhakar
2,
C. M. Bajpeyi
2,
P. L. N. Raju
1
Affiliations
1 North Eastern Space Applications Centre, Department of Space, Shillong 793 103, IN
2 Central Silk Board, Ministry of Textiles, B.T.M. Layout, Madivala, Bengaluru 560 068, IN
1 North Eastern Space Applications Centre, Department of Space, Shillong 793 103, IN
2 Central Silk Board, Ministry of Textiles, B.T.M. Layout, Madivala, Bengaluru 560 068, IN
Source
Current Science, Vol 111, No 8 (2016), Pagination: 1312-1318Abstract
Potential areas for expansion of sericulture in 108 selected districts covering 24 states in the country were mapped using remote sensing, GIS and GPS tools. Special emphasis was given to northeastern (NE) region, where 41 districts out of a total of 108 districts were selected. Potential area identification for sericulture development was based on land evaluation, water resources and climatic requirements for growing silkworm food plants as well as rearing silkworms. Among NE states, Mizoram has maximum highly suitable area (4.7% of total geographical area) followed by Meghalaya (2.8%), that can be brought under mulberry sericulture. Among non-traditional sericulture states, Himachal Pradesh has the highest suitable area (0.9% highly suitable and 6.2% moderately suitable areas) in the selected districts. Among the five traditional sericulture states, Tamil Nadu has the highest area under highly suitable category, which is about 4% of the total geographical area in the selected districts. To provide information on sericulture and spatial information on potential areas for the selected 108 districts, a geoportal titled 'Sericulture Information Linkages and Knowledge System' (SILKS) was conceptualized and developed using open source GIS, and put in the public domain (http://silks.csb.gov.in). Within three years, the portal could make a significant impact in the country particularly in NE states and a number of sericulture expansion activities have been taken up based on the study.Keywords
Geoportal, Geospatial Tools, Open Source GIS, Sericulture, Web Technology.References
- Rama Rao, N., Protection for Indian Sericulture. Curr. Sci., 1938, 7(6), 263–266.
- Navalgund, R. R., Parihar, J. S., Ajai and Nageswara Rao, P. P., Crop inventory using remotely sensed data. Curr. Sci., 1991, 61(3&4), 162–171.
- Nageswara Rao, P. P., Ranganath, B. K. and Chandrashekhar, M. G., Remote sensing applications in sericulture. Indian Silk, 1991, 30, 7–15.
- CSB, Manual of Satellite Remote Sensing Applications for Sericulture Development, Central Silk Board, Bangalore, 1994.
- Sys, C., Land Evaluation: Part I, II& III. 1985, State University Ghent Publication, Belgium.
- Sys, C., Ranst, V., Debaveye, J. and Beernaert, F., Land evaluation Part III, crop requirements. Agric. Pub. 1993, No. 7, ITC, Ghent.
- NRSC, Manual–National Land Use Land Cover Mapping using Multi-temporal Satellite Data, Land Use Division, National Remote Sensing Agency, Hyderabad, 2006.
- NRSC, Wasteland Atlas of India, National Remote Sensing Agency, Hyderabad, 2011, pp. 4–14.
- FAO, Manual of Sericulture, United Nations, Rome, Italy, 1990.
- Patel, N. R., Mandal, U. K. and Pande, L. M., Agro-ecological zoning system. A remote sensing and GIS perspective. J. Agrometeorol., 2000, 2(1), 1–13.
- Goovaerts, P., Performance comparison of geostatistical algorithms for incorporating elevation into the mapping of precipitation. Geocomputation, 1999, 99, 1–17.
- Thornthwaite, An approach for a rational classification of climate. Geog. Rev., 1948, 38, 55–94.
- FAO, A framework for land evaluation. Soil Bulletin, Food and Agriculture Organization. United Nations, Rome, Italy, 1976, No. 32.
- Climate Resilient Technological Interventions to Ensure Food Security in Flood Affected Area – An Experience from Nicra Village, Dhubri, Assam
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Authors
Affiliations
1 Krishi Vigyan Kendra (A.A.U.), Dhubri (Assam), IN
2 Directorate of Extension Education, Assam Agricultural University, Jorhat (Assam), IN
1 Krishi Vigyan Kendra (A.A.U.), Dhubri (Assam), IN
2 Directorate of Extension Education, Assam Agricultural University, Jorhat (Assam), IN
Source
International Journal of Plant Protection, Vol 10, No 2 (2017), Pagination: 442-447Abstract
The study was conducted in villages of Dhubri district in Assam under National Innovation on Climate Resilient Agriculture (NICRA) project implemented by Krishi Vigyan Kendra, Dhubri during 2013 to 2015. The villages are situated under Bilasipara sub-division in the district ‘Dhubri’ of Assam, India on 26° 15. 425´ to 26° 16.570´ N latitude and 90° 14.034´ to 90° 18.040´ E longitude at an elevation of 128 ft from mean sea level. Recurrent floods has been the principal constraints in food production in these villages affecting mainly winter (Kharif) rice during the growing season as well as summer rice (Boro and Ahu) at the time of maturity. The prevailing weather patterns of the area were observed to have a strong bearing on the occurrence, intensity and magnitude of floods. About 71 per cent of total rainfall occurs during monsoon period (June to September), the winter being virtually dry leaving little scope for growing any Rabi crop. To ensure rice production to climatic variability leading to flood, site specific climate resilient technologies such as staggered planting rice variety ‘Gitesh’, flood escaping, short duration HYV rice ‘Luit’ for post and pre-flood situation, submergence tolerant rice variety ‘Swarna Sub 1’ and mid duration HYV of rice ‘Joymati’ during preflood situation were tested and demonstrated in the project villages. It was necessary to observe the performance of these varieties to the climatic vulnerability as well as farmer’s acceptability. The average yield of the rice variety ‘Gitesh’ (45 days aged seedlings), ‘Luit’ (post flood situation), ‘Luit’ (pre-flood situation), ‘Swarna Sub 1’ and ‘Jomati’ were found to be 40 to 42, 26.3 to 36, 23.35 to 31.39, 33 to 45 and 42.37 to 50.76 q per hectare, respectively. As a result of the study and demonstration to endure recurrent flood and climatic variability, the newly introduced winter rice varieties, Gitesh has spread over the highest area in the project villages (90.00%) followed by ‘Swarna Sub 1’ (75.00 %) and ‘Luit’ (66.67 %) due to flexibility in seedling age facilitating delayed transplanting, submergence tolerance upto 14 days and allowance for transplanting after recession of flood, respectively.Keywords
Flood, Rice, Climate, Resilient.References
- Kavikumar, K.S. (2010). Climate sensitivity of Indian Agriculture: Role of technological development and information diffusion, In: Lead papers, 2010. National symposium on climate change and rainfed agriculture, February 18 -20, 2010. Indian society of Dry land Agriculture, Central Research Institute for Dry land Agriculture, Hyderabad, India. pp. 192.
- Sarkar, R. K., Panda, D., Reddy, J. N., Patnaik, S. S. C., Mackill, D. J. and Ismail, A.M. (2009). Performance of submergence tolerant rice (Oryza sativa) genotypes carrying the Sub 1 quantitative traits locus under stressed and non-stressed natural field conditions. Indian J. Agric. Sci., 79 (11): 876 – 883.
- Sarma, A. and Saikia, P. (2009). Performance of staggered planting of Sali rice variety Gitesh and Ranjit in farmers field of Golaghat district of Assam. Adv. Pl. Sci., 22 (1) : 77 -78.
- Development of a Muga Disease Early Warning System – A Mobile-Based Service for Seri Farmers
Abstract Views :165 |
PDF Views:68
Authors
J. Goswami
1,
D. K. Gogoi
2,
N. Rasid
1,
B. K. Handique
1,
G. Subrahmanyam
2,
P. P. Bora
2,
R. Das
2,
P. L. N. Raju
1
Affiliations
1 North Eastern Space Applications Centre, Department of Space, Umiam 793 103, IN
2 Central Muga Eri Research and Training Institute, Central Silk Board, Lahdoigarh, Jorhat 785 700, IN
1 North Eastern Space Applications Centre, Department of Space, Umiam 793 103, IN
2 Central Muga Eri Research and Training Institute, Central Silk Board, Lahdoigarh, Jorhat 785 700, IN
Source
Current Science, Vol 121, No 10 (2021), Pagination: 1328-1334Abstract
Flacherie is a major bacterial disease causing >40% loss during Muga summer crops. For finding the ischolar_main causes of the diseases, relationships were established between rearing and production data corresponding to land use/land cover, land surface temperature and meteorological parameters. Adverse affects were found in farms associated with anthropogenic activities, in contrast to forest cover which shows a negative trend. Muga disease early warning system, a mobile-based application and dashboard has been developed to predict rate of flacherie infestation at least 5–10 days in advance, for proper precautionary measures by the farmers to avoid disease outbreak and crop lossKeywords
Crop Loss, Early Warning System, Flacherie Disease, Mobile-Based Service, Muga Silkworm, Remote Sensing. Muga Silkworm.References
- Tikader, A., Vijayan, K. and Saratchandra, B., Muga silkworm, Antheraea assamensis (Lepidoptera: Saturniidae) – an overview of distribution, biology and breeding. Eur. J. Entomol., 2013, 110(2).
- Kumar, R. and Rajkhowa, G., Muga silkworm, Antheraea assamensis (Insecta: Lepidoptera: Saturniidae): rearing and insect. Hartmann and Weipert. Proceedings: Biodiversität und Naturausstattung im Himalaya IV.–Erfurt, Germany, 2012, pp. 187–190.
- FAO, Manuals of Sericulture, Food and Agriculture Organization, Rome, 1976.
- Madhusudhan, K. N. et al., Impact of varying different abiotic factors on the survivability of tasar silkworm in outdoor rearing fields. J. Entomol. Zool. Stud., 2017, 5(6), 957–963.
- Chakravorty, C., Das, R., Neog, R., Das, K and Sahu, M., A Diagnostic Manual for Diseases and Pests of Muga Silkworms and their Host Plants, Central Muga Eri Research and Training Institute, CSB Publication, 2007, 1st edn.
- Subrahmanyam, G. et al., Isolation and molecular identification of microsporidian pathogen causing nosemosis in Muga silkworm, Antheraea assamensis Helfer (Lepidoptera: Saturniidae). Indian J. Microbiol., 2019, 59(4), 525–529.
- Ueda, S., Kimura, R. and Suzuki, K., Studies on the growth of the silkworm, Bombyx mori L., 4: Mutual relationships between the growth in the fifth instar larvae and the productivity of silk substance. Bull. Sericult. Exp. Station, 1975.
- Benjamin, K. V. and Jolly, M. S., Principles of silkworm rearing.
- In Proceedings of Seminar on Problems and Prospects of Sericulture (ed. Mahalingam, S.), Vellore, 1986, pp. 63–108.
- Sys, C. et al., Land Evaluation. Part I, II & III: Crop Requirements, Agricultural Publications N° 7, GADC, Brussels, Belgium, 1993, p. 191.
- Sys, C., Van Ranst, E., Debaveye, J. and Beenaert, F., Land evaluation part III. Crop Requirements. Agriculture Publication, 1993, vol. 7, p. 166.
- Handique, B. K. et al., Expansion of sericulture in India using geospatial tools and web technology. Curr. Sci., 2016, 111(8), 1312–1318.
- National Remote Sensing Agency, Manual of National Land Use/Land Cover Mapping using Multi-Temporal Satellite Data, Hyderabad, 2006.
- Malik, B., The problem of shifting cultivation in the Garo Hills of North-East India, 1860–1970. Conserv. Soc., 2003, 287–315.
- Willmer, C. W., Stone, G. and Johnston, I., Environmental Physiology of Animals, Blackwell Science, Oxford, UK, 2009, 2dn edn, pp. 175–183.
- Shirota, T., Selection of healthy silkworm strain through high temperature rearing of fifth instar larvae. Rep. Silk Sci. Res. Inst. (Jpn), 1992.
- Tajima, Y. and Ohnuma, A., Preliminary experiments on the breeding procedure for synthesizing a high temperature resistant commercial strain of the silkworm, Bombyx mori. Rep. Silk Sci. Res. Inst. (Jpn), 1995, 1–16.
- Space technology support for development of agriculture in the North Eastern Region of India – scope and challenges
Abstract Views :131 |
PDF Views:72
Authors
B. K. Handique
1,
C. Goswami
1,
P. T. Das
1,
J. Goswami
1,
P. Jena
1,
F. Dutta
1,
D. K. Jha
1,
S. P. Aggarwal
1
Affiliations
1 North Eastern Space Applications Centre, Umiam 793 103, India, IN
1 North Eastern Space Applications Centre, Umiam 793 103, India, IN
Source
Current Science, Vol 123, No 8 (2022), Pagination: 975-986Abstract
The North Eastern Region of India (NER) has tremendous scope for accelerating its growth in agriculture and allied areas through advanced data acquisition, interpretation and dissemination methods with geospatial technology. For several thematic applications, geospatial tools and techniques are being used to provide synoptic, cost-efficient and timely information for effective crop planning and monitoring in the region. A review of space applications in agriculture, horticulture, sericulture, land-use suitability, shifting cultivation, groundwater prospecting, soil resources management, etc. has been made, highlighting the scope and limitation of using these advanced technologies. Satellite remote sensing has several limitations in NER, viz. small and fragmented farmlands, persistent clouds during monsoon, mixed farming, steep hills, etc. Considering these facts, unmanned aerial vehicles (UAVs) are used as an alternative for satellite remote sensing applications in agriculture. The increased availability of very high resolution satellite and UAV data will offer opportunities for innovative solutions to fulfil specific user needs of agriculture and allied sectors in NERReferences
- Roy, A., Dhar, D. S., Tripathi, A. K., Singh, N. U., Kumar, D., Das, S. K. and Debnath, A., Growth performance of agriculture and allied sectors in the North East India. Econ. Affairs, 2014, 59, 783–795.
- Seitinthang, L., Cropping pattern of North East India: an appraisal. Am. Res. Thoughts, 2014, 1, 488–498.
- Dikshit, K. R. and Dikshit, J. K., Agriculture in North-East India: past and present. In North-East India: Land People and Economy, Springer Nature, 2014, pp. 587–637.
- Punitha, P. et al., Shifting cultivation in North East India: social dimension, cross cultural reflection and strategies for improvement. Indian J. Agric. Sci., 2018, 88, 811–819.
- Sahoo, P. M., Rai, A., Singh, R., Handique, B. K. and Rao, C. S., Integrated approach based on remote sensing and GIS for estimation of area under paddy crop in North-Eastern hilly region. J. Indian Soc. Agric. Stat., 2005, 59, 151–160.
- Justice, C. O. et al., An overview of MODIS land data processing and product status. Remote Sensing Environ., 2002, 83, 3–15.
- Navalgund, R., Jayaraman, V. and Roy, P., Remote sensing applications: an overview. Curr. Sci., 2007, 93(12), 1747–1766.
- Navalgund, R., Parihar, J. S., Ajai and Rao, P. P. N., Crop inventory using remotely sensed data. Curr. Sci., 1991, 61(3 and 4), 162–171.
- Dadhwal, V. K., Singh, R. P., Dutta, S. and Parihar, J. S., Remote sensing based crop inventory: a review of Indian experience. Trop. Ecol., 2002, 43, 107–122.
- Heupel, K., Spengler, D. and Itzerott, S., A progressive crop-type classification using multitemporal remote sensing data and phenological information. PFG-J. Photogramm. Remote Sensing Geoinf. Sci., 2018, 86, 53–69.
- Croft, H. and Chen, J. M., Leaf pigment content. In Comprehensive Remote Sensing (ed. Liang, S.), Elsevier, 2018, pp. 117– 142; https://doi.org/10.1016/b978-0-12-409548-9.10547-0.
- NASA, Reflected near-infrared waves, National Aeronautics and Space, Administration, 2010; https://science.nasa.gov/ems/08_ nearinfraredwaves (accessed on 10 December 2021).
- DeRiggi, J., Identify healthy vegetation from space. DAI, 2017; https://dai-globaldigital.com/about/
- Richards, J., Remote Sensing Digital Image Analysis, SpringerVerlag, Berlin, Germany, 1999, p. 240.
- Salah, M., A survey of modern classification techniques in remote sensing for improved image classification, J. Geomat., 2017, 11.
- Neetu and Ray, S. S., Exploring machine learning classification algorithms for crop classification using Sentinel 2 data. Int. Arch. Photogram, Remote Sensing Spat. Inf. Sci., 2019, XLII-3/W6, 573– 578; https://doi.org/10.5194/isprs-archives-XLII-3-W6-573-2019
- Singha, M., Dong, J., Zhang, G. and Xiao, X., High resolution paddy rice maps in cloud-prone Bangladesh and Northeast India using Sentinel-1 data. Sci. Data, 2019, 6, 1–10.
- George, A., Crop discrimination and mapping using Sentinel-1 data in North East India. M.Sc. (Remote Sensing and GIS) thesis, Kerala University of Fisheries and Ocean Studies, Panangad, Kerala, 2018.
- Sahoo, P. M., Rai, A., Krishnamoorthy, S., Handique, B. K., Rao, P. P. N., Oza, M. P. and Parihar, J. S., Sampling approach for estimation of crop acreage under cloud cover satellite data in hilly regions. Proc. SPIE, 2006, 64, 1–9.
- Ghazaryan, G., Dubovyk, O., Löw, F., Lavreniuk, M., Kolotii, A., Schellberg, J. and Kussul, N., A rule-based approach for crop identification using multi-temporal and multi-sensor phenological metrics. Eur. J. Remote Sensing, 2018, 51, 511–524.
- Son, N. T., Chen, C. F., Chen, C. R., Duc, H. N. and Chang, L. Y., A phenology-based classification of time-series MODIS data for rice crop monitoring in Mekong Delta, Vietnam. Remote Sensing, 2013, 6, 135–156.
- Turner, M. D. and Congalton, R. G., Classification of multi-temporal SPOT-XS satellite data for mapping rice fields on a West African floodplain. Int. J. Remote Sensing, 1998, 19, 21–41.
- Wang, J., Huang, J., Zhang, K., Ki, X., She, B., Wei, C., Gao, J. and Song, X., Rice fields mapping in fragmented area using multitemporal HJ-1A/B CCD images. Remote Sensing, 2015, 7, 3467– 3488.
- Wang, J. et al., Mapping paddy rice planting area in wheat–rice double-cropped areas through integration of Landsat-8 OLI, MODIS, and PALSAR images. Sci. Rep., 2015, 5, 1–11.
- Singha, M., Wu, B. and Zhang, M., An object-based paddy rice classification using multi-spectral data and crop phenology in Assam, Northeast India. Remote Sensing, 2016, 8, 1–20.
- Ahmed, R. and Sajjad, H., Crop acreage estimation of Boro paddy using remote sensing and GIS techniques: a case from Nagaon district, Assam, India. Adv. Appl. Agric. Sci., 2015, 3, 16–25.
- Rajpoot, S. et al., Jute crop production estimation in major states of India: a comparative study of last 6 years’ FASAL and DES estimates. Int. Arch. Photogramm. Remote Sensing Spat. Inf. Sci., 2019, XLII-3/W6, 129–136.
- Parihar, J. S. and Oza, M. P., FASAL: an integrated approach for crop assessment and production forecasting. In Agriculture and Hydrology Applications of Remote Sensing (eds Kuligowski, R. J. et al.), 2006, pp. 1–13; https://doi.org/10.1117/12.713157.
- Shanmugapriya, P., Rathika, S., Ramesh, T. and Janaki, P., Applications of remote sensing in agriculture – a review. Int. J. Curr. Microbiol. Appl. Sci., 2019, 8, 2270–2283.
- Patel, N. R. and Yadav, K., Monitoring of spatio-temporal pattern of drought stress by use of integrated drought index over Bundelkhand region, India. Nat. Hazard, 2015, 77, 663–677.
- Rao, P. P. N., Shobha, V., Ramesh, K. and Somashekhar, R., Satellite-based assessment of agricultural drought in Karnataka State. J. Indian Soc. Remote Sensing, 2005, 33, 429–434.
- Dadhwal, V. K. and Ray, S. S., Crop assessment using remote sensing – Part II: Crop condition and yield assessment. In Proceedings of the National Seminar on Remote Sensing and Agricultural Statistics: Rationale, Scope and Aims, Ahmedabad, 1998.
- Miedema, P., The effects of low temperature on Zea mays. Adv. Agron., 1982, 2113, 60322–60323.
- Brun, K., Diedrichs, A. L., Chaar, J. E., Dujovne, D., Taffernaberry, C., Mercado, G. and Watteyne, T., A demo of the PEACH IoTbased frost event prediction system for precision agriculture. In 13th Annual IEEE International Conference on Sensing, Communication and Networking (SECON), London, UK, 2016.
- Choudhury, B., Webster, R., Sharma, V., Goswami, J., Meetei, T., Krishnappa, R. and Raju, P. L. N., Frost damage to maize in North East India: assessment and estimated loss of yield by hyperspectral proximal remote sensing. J. Appl. Remote Sensing, 2019, 13, 044527.
- Goswami, J., Sharma, V., Chaudhury, B. U. and Raju, P. L. N., Rapid identification of abiotic stress (frost) in in-filed maize crop using UAV remote sensing. In Proceedings of International Workshop on Earth Observations for Agricultural Monitoring, New Delhi, India, 1978, pp. 467–471; https://doi.org/10.5194/ isprs-archives-XLII-3-W6-467-2019.
- Bhanage, V., Latha, R. and Murthy, B. S., Estimation of water stress over Assam using remote sensing data. In Conference paper, NIRD, Assam, 2018; https://www.researchgate.net/publication/ 322635575
- Banerjee, S. and Pandey, A. C., Crop insurance model to consolidate academia–industry cooperation: a case study over Assam, India. Spat. Inf. Res., 2019, 27, 719–731.
- Sharma, A., Ojha, N., Pozzer, A., Beig, G. and Gunthe, S. S., Revisiting the crop yield loss in India attributable to ozone. Atmos. Environ., 2019, X(1), 100008.
- Handique, B. K., Goswami, J., Qadir, A., Gupta, C. and Raju, P. L. N., Rapid assessment of boro paddy infestation by brown plant hopper in Morigaon district, Assam, India using unmanned aerial vehicle. Curr. Sci., 2016, 111(10), 1604–1606.
- NITI Aayog, Annual Report 2016–17, National Institute for Transforming India, New Delhi, India, 2018, pp. 27–31.
- Raju, P. L. N., Handique, B. K. and Goswami, C., Remote sensing data for horticulture development in NE. Smart Agripost., 2019, 36–40.
- Das, P. T. and Sudhakar, S., Land suitability analysis for orange and pineapple: a multi criteria decision making approach using geo spatial technology. J. Geogr. Inf. Syst., 2014, 6, 40–44.
- Das, A., Ghosh, P., Choudhury, B., Patel, D., Munda, G., Ngachan, S. and Chowdhury, P., Climate change in North East India: recent facts and events – worry for agricultural management. In Proceedings of the Workshop on Impact of Climate Change on Agriculture, Ahmedabad, India, ISPRS XXXVIII-8/W3, 2009, pp. 32–37.
- Sen, T. K., Pande, L. M., Sehgal, J. L., Maji, A. K. and Chamuah, G. S., Satellite remote sensing in soil resource inventory of Dibrugarh district (part), Assam. J. Indian Soc. Remote Sensing, 1992, 20, 95–104.
- Ahuja, R. L., Manchanda, M. L., Sangwan, B. S., Goyal, P. V. and Agarwal, R. P., Utilization of remotely sensed data for soil resource mapping and its interpretation for land use planning of Bhiwani district, Haryana. J. Indian Soc. Remote Sensing, 1992, 20, 105–120.
- Sehgal, J. L., Sharma, P. K. and Karale, R. L., Soil resource inventory of Punjab using remote sensing technique. J. Indian Soc. Remote Sensing, 1988, 16, 39–47.
- Kudrat, M., Tiwari, A. K., Saha, S. K. and Bhan, S. K., Soil resource mapping using IRS-1A-LISS II digital data – a case study of Kandi area adjacent to Chandigarh, India. Int. J. Remote Sensing, 1992, 13, 3287–3302.
- Sharma, E., Rai, S. C. and Sharma, R., Soil, water and nutrient conservation in mountain farming systems: case-study from the Sikkim Himalaya. J. Environ. Manage., 2001, 61, 123–135.
- Choudhury, B. U. et al., Spatial variability in distribution of organic carbon stocks in the soils of North East India. Curr. Sci., 2013, 104(5), 604–614.
- Abdelrahman, M. A. E., Natarajan, A. and Hegde, R., Assessment of land suitability and capability by integrating remote sensing and GIS for agriculture in Chamarajanagar district, Karnataka, India. Egyp. J. Remote Sensing Space Sci., 2016, 19, 125–141.
- Sys, C., Van Ranst, E. and Debaveye, I. J., Land evaluation. Part I: Principles in land evaluation and crop production calculations. General Administration for Development Cooperation, Brussels, Belgium, 1991.
- Parthasarathy, U., Johny, A. K., Jayarajan, K. and Parthasarathy, V. A., Site suitability of turmeric production in India – a GIS interpretation. Nat. Prod. Rad., 2007, 6, 142–147.
- Moshia, M., Mashatola, M., Shaker, P., Fouché, P. and Boshomane, M., Land suitability assessment and precision farming prospects for irrigated maize–soybean intercropping in Syferkuil experimental farm using geospatial information technology. J. Agric. Soc. Res., 2009, 8, 1–12.
- Jafari, S. and Zaredar, N., Land suitability analysis using multi attribute decision making approach. Int. J. Environ. Sci. Dev., 2010, 1, 441–445.
- Bhaskar, B. P., Baruah, U., Vadivelu, S., Raja, P. and Sarkar, D., Remote sensing and GIS in the management of wetland resources of Majuli Island, Assam, India. Trop. Ecol., 2010, 51, 31–40.
- Lallianthanga, R. K., Sailo, R. L. and Colney, L., Identification of potential wet rice cultivation areas in Mizoram, India: a remote sensing and GIS approach. Int. J. Geol. Earth Environ. Sci., 2013, 3, 49–56.
- Sarmah, K., Deka, C. R. and Konwar, R., Land suitability analysis for identification of summer paddy cultivation sites based on multi criteria evaluation through GIS. Eur. Acad. Res., 2015, 2, 13584– 13606.
- Anilkumar, R., Chutia, D., Goswami, J., Sharma, V. and Raju, P. L. N., Evaluation of the performance of the fused product of Hyperion and RapidEye red edge bands in the context of classification accuracy. J. Geomat., 2018, 12, 35–46.
- Karthik, T., Veeraswami, G. G. and Samal, P. K., Forest recovery following shifting cultivation: an overview of existing research. Trop. Conserv. Sci., 2009, 2, 374–387.
- Coomes, O. T., Grimard, F. and Burt, G. J., Tropical forests and shifting cultivation: secondary forest fallow dynamics among traditional farmers of the Peruvian Amazon. Ecol. Econ., 2000, 32, 109–124.
- Pebam, R., A novel approach to understand the spatial and temporal pattern of shifting cultivation fields using GIS techniques in Longding division of Arunachal Pradesh, India. Int. J. Eng. Res. Appl., 2018, 8, 61–67.
- Kurien, A. J., Lele, S. and Nagendra, H., Farms or forests? Understanding and mapping shifting cultivation using the case study of West Garo hills, India. Land, 2019, 8, 1–26.
- Thong, P., Sahoo, U. K., Pebam, R. and Thangjam, U., Spatial and temporal dynamics of shifting cultivation in Manipur, Northeast India based on time-series satellite data. Remote Sensing Appl. Soc. Environ., 2019, 14, 126–137.
- Pasha, S. V., Behera, M. D., Mahawar, S. K., Barik, S. K. and Joshi, S. R., Assessment of shifting cultivation fallows in Northeastern India using Landsat imageries. Trop. Ecol., 2020, 61, 65–75.
- Das, P., Mudi, S., Behera, M. D., Barik, S. K., Mishra, D. R. and Roy, P. S., Automated mapping for long-term analysis of shifting cultivation in Northeast India. Remote Sensing, 2021, 13, 1066.
- NeSDR, North Eastern Spatial Data Repository, https://www. nesdr.gov.in/ (accessed on 10 September 2021).
- Sharma, R., Xu, J. and Sharma, G., Traditional agroforestry in the Eastern Himalayan Region: land management system supporting ecosystem services. Trop. Ecol., 2007, 48, 1–12.
- Giri, K., Mishra, G., Jayaraj, R. S. C. and Kumar, R., Agrobio-cultural diversity of alder based shifting cultivation practiced by Angami tribe in Khonoma village, Kohima, Nagaland. Curr. Sci., 2018, 115(4), 598–599.
- Rizvi, R. H., Dhyani, S. K., Newaj, R., Karmakar, P. S. and Saxena, A., Mapping agroforestry area in India through remote sensing and preliminary estimates. Indian Farm., 2014, 63, 62–64.
- Press Information Bureau, India will restore 26 million hectares of degraded land by 2030 (press release), Government of India. https://pib.gov.in/Pressreleaseshare.aspx?PRID=1584542 (accessed on 9 September 2019).
- Ramos, N. C., Gastauer, M. and Cordeiro, A. A. C., Environmental filtering of agroforestry systems reduce the risk of biological invasion. Agrofor. Syst., 2015, 89, 279–289.
- Hernandez, R. R. et al., The native shrub, Piliostigma reticulatum, as an ecological ‘resource island’ for mango trees in the Sahel. Agric. Ecosyst. Environ., 2015, 204, 51–61.
- Asbjornsen, H., Hernandez-Santana, V., Liebman, M., Bayala, J., Chen, J., Helmers, M. and Schulte, L., Targeting perennial vegetation in agricultural landscapes for enhancing ecosystem services. Renew. Agric. Food Syst., 2014, 29, 101–125.
- NRCAF, The Vision-2050, National Research Centre for Agroforestry, Ministry of Agriculture and Farmers Welfare, Governmnet of India, New Delhi, India, 2013.
- MEA, Millennium Ecosystem Assessment, Ecosystems and human well-being: biodiversity synthesis. World Resources Institute, Washington, DC, USA, 2005.
- Rizvi, R. H., Newaj, R., Handa, A. K., Sridhar, K. B. and Kumar, A., Agroforestry mapping in India through geospatial technologies: present status and way forward. Technical Bulletin 1/2019, ICARCentral Agroforestry Research Institute, Jhansi, 2019, pp. 1–35.
- Nath, A. J. et al., Agroforestry land suitability analysis in the Eastern Indian Himalayan region. Environ. Challeng., 2021, 100199, 1–22.
- Lakhankar, T., Krakauer, N. and Khanbilvardi, R., Applications of microwave remote sensing of soil moisture for agricultural applications. Int. J. Terraspace Sci. Eng., 2009, 2, 81–91.
- Prakash, A., Thermal remote sensing: concepts, issues and applications. Int. Arch. Photogramm. Remote Sensing, 2000, 33, 239–243.
- Aryalekshmi, B. N., Biradar, R. C. and Ahamed, J. M., Thermal imaging techniques in agricultural applications. Int. J. Innov. Technol. Explor. Eng., 2019, 8, 2162–2168.
- Mahlein, A. K., Oerke, E. C., Steiner, U. and Dehne, H. W., Recent advances in sensing plant diseases for precision crop protection. Eur. J. Plant Pathol., 2012, 133, 197–209.
- Sahoo, R. N., Ray, S. S. and Manjunath, K. R., Hyperspectral remote sensing of agriculture. Curr. Sci., 2015, 108(5), 848–859.
- Goswami, J., Das, R., Sarma, K. K. and Raju, P. L. N.. Red edge position (REP), an indicator for crop stress detection: implication on rice (Oryza sativa L). Int. J. Environ. Climate Change, 2021, 11, 88–96.
- Handique, B. K. et al., Hierarchical classification for assessment of horticultural crops in mixed cropping pattern using UAV-borne multi-spectral sensor. Int. Arch. Photogramm., Remote Sensing Spat. Inf. Sci., 2020, XLIII-B3-2020, 67–74, https://doi.org/10. 5194/isprs-archives-XLIII-B3-2020-67-2020
- Dubovik, O., Schuster, G. L., Xu, F., Hu, Y., Bösch, H., Landgraf, J. and Li, Z., Grand challenges in satellite remote sensing. Front. Remote Sensing, 2021, 2, 1–10; https://doi.org/10.3389/frsen.2021. 619818
- Kim, J., Jeong, U., Ahn, M.-H., Kim, J. H., Park, R. J. and Lee, H., New era of air quality monitoring from space geostationary environment monitoring spectrometer (GEMS). Bull. Am. Meteorol. Soc., 2020, 101, E1–E22; doi:10.1175/BAMS-D-18-0013.
- Gao, F., Masek, J., Schwaller, M. and Hall, F., On the blending of the Landsat and MODIS surface reflectance: predicting daily Landsat surface reflectance. IEEE Trans. Geosci. Remote Sensing, 2006, 44, 2207–2218.
- Pape, A. D. and Franklin, S. E., MODIS-based change detection for Grizzly Bear habitat mapping in Alberta. Photogramm. Eng. Remote Sensing, 2008, 74, 973–985.
- Simpson, J. J. and Stitt, J. R., A procedure for the detection and removal of cloud shadow from AVHRR data over land. IEEE Trans. Geosci. Remote Sensing, 1998, 36, 880–897.
- Liu, C. A., Chen, Z. X., Shao, Y., Chen, J. S., Hasi, T. and Pan, H., Research advances of SAR remote sensing for agriculture applications: a review. J. Integr. Agric., 2019, 18, 506–525.
- Conway, D. and Donnelly, S., Remote sensing, GIS and ground truthing. In Doing Development Research (eds Desai, V. and Potter, R. B.), SAGE Publications Ltd, 2006, pp. 251–261; https:// dx.doi.org/10.4135/9781849208925.
- Raju, P. L. N. et al., Training and capacity building initiatives in space technology applications for North Eastern Region – role of NESAC in expanding the outreach. In Asian Conference on Remote Sensing, New Delhi, 2017.
- Parks, S., The importance of calibrating your remote sensing imagery, 2020; https://www.materials-talks.com/author/susan-parks/ (accessed on 24 January 2021).
- Gupta, C. et al., Applications of unmanned aerial vehicle (UAV) based remote sensing in North Eastern Region of India. ISG Newsl., 2018, 23 & 24.
- Khanal, S., KC, K., Fulton, J. P., Shearer, S. and Ozkan, E., Remote sensing in agriculture – accomplishments, limitations, and opportunities. Remote Sensing, 2020, 12, 3783–3785.
- Çoban, S. and Oktay, T., Legal and ethical issues of unmanned aerial vehicles. J. Aviat., 2018, 2, 31–35.
- Roseman, C. A. and Argrow, B. M., Weather hazard risk quantification for sUAS safety risk management. J. Atmos. Ocean. Technol., 2020, 37, 1251–1268.
- Singha, M., Dong, J., Zhang, G. and Xiao, X., High resolution paddy rice maps in cloud-prone Bangladesh and Northeast India using Sentinel-1 data. Sci. Data, 2019, 6, 1–10.
- Goswami, J., Sarma, K. K., Handique, B. K., Das, R., Rahman, N. and Raju, P. L. N., Study of cropping system in Morigaon district of Assam using geospatial technique. Int. J. Adv. Remote Sensing GIS Geogr., 2017, 5, 53–59.
- Hiloidhari, M., Das, D. and Baruah, D. C., Bioenergy potential from crop residue biomass in India. Renew. Sustain. Energy Rev., 2014, 32, 504–505.
- Hiloidhari, M. and Baruah, D. C., GIS mapping of rice straw residue for bioenergy purpose in a rural area of Assam, India. Biomass Bioenerg., 2014, 71, 125–133.
- Goswami, J., Chutia, D. and Sudhakar, S., A geospatial approach to climatic zone specific effective horticultural planning in East Khasi Hills district of Meghalaya, India. J. Geogr. Inf. Syst., 2012, 4, 267–272.
- Das, P. T., Handique, B. K. and Raju, P. L. N., Expansion of boro rice in Meghalaya using space technology. Curr. Sci., 2018, 115(10), 1865–1870.
- Negi, A., Adhikari, T., Goswami, C., Handique, B. K. and Raju, P. L. N., Site suitability analysis for turmeric in Jaintia Hills of Meghalaya, India using analytical hierarchical process and weighted overlay analysis: a comparative approach. Curr. Sci., 2020, 118(8), 1246–1254.
- Handique, B. K., Khan, A. Q., Goswami, C., Prashnani, M., Gupta, C. and Raju, P. L. N., Crop discrimination using multispectral sensor onboard unmanned aerial vehicle. Proc. Natl. Acad. Sci., India, Sect. A, 2017, 87, 713–719.
- Lallianthanga, R. K. and Sailo, R. L., Geospatial planning for improved land use system in Saiha District, Mizoram, India. Sci. Vis., 2013, 13, 120–132.
- Lallianthanga, R. K. and Sailo, R. L., A remote sensing & GIS approach for land use planning in Champhai district, Mizoram, India. Int. J. Eng. Sci. Res. Technol., 2013, 2, 3156–3163.
- Lallianthanga, R. K. and Hmingthanpuii, Integrated land use planning of Aizawl district, Mizoram, India using geospatial techniques. Int. J. Adv. Remote Sensing GIS, 2013, 2, 341–350.
- Lallianthanga, R. K., Sailo, R. L., Hmingthanpuii and Lalhmachhuana, H., Land use planning for Lawngtlai district, Mizoram, India: a remote sensing and GIS perspective. Int. J. Curr. Res. Acad. Rev., 2014, 2, 42–53.
- Sarma, P. K., Al, E. H., Baruah, B., Mipun, B. S. and Talukdar, B. K., Assessment of changing trends of shifting cultivation in Garo Hills landscape of Meghalaya – a geospatial approach. Int. Res. J. Environ. Sci., 2015, 4, 1–7.
- Chakraborty, K., Sarma, K. K., Kundu, S. S. and Das, A. K., Shifting cultivation dynamics in Barak basin of North East India – a geospatial approach. Int. J. Adv. Earth Environ. Sci., 2015, 3, 21–29.
- Nongkynrih, J. M., Pohshna, C. and Sarma, K. K., Dynamics of shifting cultivation in relation to slope and elevation in parts. Curr. Sci., 2018, 114(5), 1094–1099.
- Lalbiakmawia, F., Ground water quality mapping of Kolasib district, Mizoram, India using geo-spatial technology. SSRG Int. J. Geoinf. Geol. Sci., 2015, 2, 1–7.
- Lalbiakmawia, F. and Vanthangliana, V., Application of geo-spatial technologies for groundwater quality mapping of Aizawl district, Mizoram, India. Sci. Vis., 2015, 15, 115–123.
- Lalbiakmawia, F. and Kumar, S., Assessment of groundwater conditions in Bilkhawthlir rural development block, Kolasib district, Mizoram, India. Adv. Eng. Res., 2018, 178, 74–86; https://doi.org/10.2991/msc-18.2018.13.
- Maji, A. K., Nayak, D. C., Krishna, N. D. R., Srinivas, C. V., Kamble, K., Reddy, O. G. P. and Velayutham, M., Soil information system of Arunachal Pradesh in a GIS environment for land use planning. JAG, 2001, 3, 69–77.
- Tao, D. L., Singh, N. J. and Goswami, C., Spatial variability of soil organic carbon and available nutrients under different topography and land uses. IJPSS, 2018, 21, 1–16.
- Raj, U., Hebbar, R., Ravishankar, H. M., Jacob, J., Ray, D., Meti, S., Shebin, S. M. and Pradeep, B., Geospatial technology for acreage estimation of natural rubber and identification of potential areas for its cultivation in Tripura, National Remote Sensing Centre, Hyderabad and Rubber Research Institute of India, Kerala, 2012.
- Chakraborty, K., Sudhakar, S., Sarma, K. K., Raju, P. L. N. and Das, A. K., Recognizing the rapid expansion of rubber plantation – a threat to native forest in parts of Northeast India. Curr. Sci., 2018, 114(1), 207–213.
- Kalita, P., Identification of potential sites for mulberry cultivation in West Garo Hills of Meghalaya using geospatial techniques. M.Sc. (Applied Geography and Geoinformatics) thesis, Central University of Karnataka, Kalaburagi, India, 2017.