PREDICTING FARMERS’ UPTAKE OF NEW LIVELIHOOD TECHNOLOGIES THROUGH ADOPT MODEL
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Date
2020
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Indira Gandhi Krishi Vishwavidyalaya, Raipur
Abstract
The present study entitled “Predicting Farmers’ Uptake of New Livelihood Technologies through ADOPT Model” was carried out in four district namely Balodabazar, Raipur, Dhamtari and Kanker of Chhattisgarh state because FLD (Front Line Demonstration) of particular technology was conducted in these districts. In this present study, kadaknath poultry farming and oyster mushroom production were selected purposively because these were livelihood improvement technologies which have been introduced and sustained by ICAR-NIBSM (National Institute of Biotic Stress Management), Baronda and KVKs of IGKV, Raipur Chhattisgarh. The stakeholders (who were directly involved in FLD) like 8 researchers, 27 progressive farmers, 15 business personnel and 10 self-help group of kadaknath poultry farming.
Similarly, 15 researchers, 20 progressive growers, 15 business personnel and 10 self-help group of oyster mushroom production were selected, inthis way the total 120 stakeholders (60 stakeholders from each technology) were selected for the study.
The ADOPT (Adoption Diffusion Outcome Prediction Tool) was used to evaluate and predict the likely level of adoption in percentage as well as time take to reach that the pick level of adoption in the years. It was found that majority of the stakeholders from both technologies were belongs to young age group (up to 35 years). In case of education level, majority of the stakeholders from both the livelihood technologies had graduation and above level education.
For specific farm experience majority of the stakeholders had experience between 1-3 years (53.33%) and under 6 and above years category (40.00%) for kadaknath poultry farming and oyster mushroom production, respectively. In case of specific business experience, majority of the stakeholders for both technologies had experience between 1-3 years for kadaknath poultry farming (65.00%) and for oyster mushroom production (46.67%).Majority (36.67%)of kadaknath poultry farming stakeholders had 11-20 years farming experience and about half of the stakeholders of oyster mushroom production had farming experience between 1-10 years.
It was found that, in case of kadaknath poultry farming technique, the major farming practices that were did not adopted by farmers were hatching of eggs (69.23%), secondly vaccination and health management (61.54%). In this production technique marketing was one of the major practice and it adopted by majority of farmers (82.69%). In case of oyster mushroom production technique, all growers (100%) agreed with substrate preparation and majority of the growers (82.22%) sterilize their substrate for mushroom production. Three fourth (73.33%) of oyster mushroom growers did not prepared spawn.
The ADOPT model predicted the peak adoption level of kadaknath poultry farming among progressive farmers to be 14 per cent. This means that only 14 per cent of the farmers in our defined population will adopt the kadaknath poultry farming in 17 years. Further in 5 years from the starting of an adoption programme, 3 per cent of the farmers’ population will adopt the kadaknath poultry farming, rising up to 10 per cent over period of 10 years.
On the other hand, the ADOPT model predicted the peak adoption level of oyster mushroom production among progressive growers to be 58 per cent. This means that 58 per cent of the growers in our defined population will adopt the oyster mushroom production in 12 years. Further in 5 years from the start of an adoption programme, 27 per cent of the growers’ population will adopt the oyster mushroom production, rising up to 55 per cent over period of 10 years.
The variables with most influence on predicted peak adoption of kadaknath poultry farming were “profit benefit in the years that the innovation is used”, “environmental costs and benefits” “future profit benefit”, “risk exposure of the innovation”, and “ease and convenience of the innovation”. For time to peak adoption, the most influential variables were “relative existing skills and knowledge”, “innovation complexity”, “ease of trialing”, “relative upfront cost of the innovation” and “short-term constraints”. On the other hand, the variables with most influence on peak adoption of oyster mushroom production were “environmental costs and benefits”, “profit benefit in the years that the innovation is used”, “future benefits in future”, “risk exposure of the innovation”, “ease and convenience of the innovation” and “enterprise scale”. For time to peak adoption, the most influential variables were “relative existing skills and knowledge”, “innovation complexity”, “ease of trialing”, “short-term constraints” and “group involvement”.
Description
PREDICTING FARMERS’ UPTAKE OF NEW LIVELIHOOD TECHNOLOGIES THROUGH ADOPT MODEL