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Technology Forecasting for Envisioning Bt Technology Scenario in Indian Agriculture

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Title Technology Forecasting for Envisioning Bt Technology Scenario in Indian Agriculture
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Creator Mrinmoy Ray
Ramasubramanian V.
K. N. Singh
Santosha Rathod
Ravindra Singh Shekhawat
 
Subject Scientometrics
Grey model
Cross impact analysis (CIA) technique
Activity Index (AI)
Genetic Algorithm (GA)
TOPSIS
MICMAC
CIAT
 
Description Not Available
For scoping the future prospects of Bacillus thuringiensis (Bt) technology in Indian agricultural scenario, case studies of three quantitative/quasi-quantitative techniques of Technology Forecasting tools viz., activity index (AI)-based scientometric analysis, Grey modeling and cross impact analysis (CIA) techniques have been done. Under AI-based scientometric analysis, information relating to abstract, keywords, authors, affiliation, etc., relevant to research publication on applications of Bt technology in India vis-à-vis three other competing country regions—China, USA cum Canada and European countries were collected from ScienceDirect database for the period 1997–2017. AI has been constructed for seven domains viz. Bt Cotton, Bt Maize, Bt Mustard, Bt Brinjal, Bt Soybean, Bt Sunflower, Bt Rice, and ‘Bt related but not crop specific’ under these four regions considered. From the values of AI, it has been found that India’s research effort is higher only in Bt Cotton and Bt Mustard than the other regions considered. Secondly, for Grey modeling, its conventional version as well as Grey model improved by Genetic Algorithm (GA) were fitted using yearly Bt cotton yield of India (2002–2003 to 2016–2017) obtained from Cotton Advisory Board of India. Only the first 11 years were utilized for model fitting and the rest were utilized for validation purposes. The results revealed that Grey model improved by GA performed better. Lastly, for employing CIA technique to study the direct as well as indirect cross impacts of Bt technology, 14 factors were considered. Three types of CIA techniques viz., Direct Classification, Cross-Impact Matrix Multiplication Applied to Classification, and CIA with Time Consideration have been attempted. The ranking of the factors obtained by three methods was combined using Technique for Order Preference by Similarity to an Ideal Solution approach. The analysis suggested that factors viz., Government policy, Bt seed sector, and technological interventions came out to be mainly responsible for future prospects of Bt technology in India.
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Date 2022-02-21T09:25:29Z
2022-02-21T09:25:29Z
2022-02-15
 
Type Article
 
Identifier Ray, M., Ramasubramanian, V., Singh, K.N. et al. Technology Forecasting for Envisioning Bt Technology Scenario in Indian Agriculture. Agric Res (2022). https://doi.org/10.1007/s40003-022-00612-z
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http://krishi.icar.gov.in/jspui/handle/123456789/69930
 
Language English
 
Relation Not Available;
 
Publisher NAAS