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volume 46 issue 4 (december 2012) : 389 - 392

FACTORS INFLUENCING THE ADOPTION OF NEW FEEDING TECHNOLOGY BY THE FARMER INTEREST GROUPS (FIGs) OF VELLORE DISTRICT IN TAMIL NADU

B
B. Rajesh Kumar
D
D. Baskaran
A
A. Serma Saravana Pandian
1Madras Veterinary College, Tamil Nadu Veterinary and Animal Sciences University, Vepery, Chennai-600 007, India

  • Submitted|

  • First Online |

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Cite article:- Kumar Rajesh B., Baskaran D., Pandian Saravana Serma A. (2025). FACTORS INFLUENCING THE ADOPTION OF NEW FEEDING TECHNOLOGY BY THE FARMER INTEREST GROUPS (FIGs) OF VELLORE DISTRICT IN TAMIL NADU. Indian Journal of Animal Research. 46(4): 389 - 392. doi: .

ABSTRACT

The factors influencing the new feeding technology ie., Dairy Cattle feed computation for Farmer Interest Groups (FIGs) in Vellore District of Tamil Nadu was analysed. The study was conducted among the 150 adopters and 102 non adopters of Farmer Interest Groups belonging to 12 villages from each of the 12 blocks of Vellore district. Binary logistic regression analysis was fitted to study the factors, which influenced the adoption of new low cost cattle feed computation technology. The factors influencing adoption rate of the new feeding technology were total dairy income, animal holding and net returns per litre of milk. On the other hand the variables such as age, education, family size, experience in dairy farming and net agricultural income had no significant effect towards the adoption rate. Further, the logit model had correctly predicted the adopters and non adopters by 97 per cent.

REFERENCES

  1. Krober, T.F., Steingass H., Funk R. and Drochner W., (1999). Effects of reduced crude protein supply on dry matter intake digestibility, excretion and performance of dairy cows in a lactation period. Zuechtungs Kunde, 71: 182–195.
  2. Kim, S., (2005). The effect of socioeconomic factors on the adoption of best management practices in beef cattle production. J. Soil and Water Conservation, 60(3): 111.
  3. Niels, M.N., Kristensen T., and Hansen H., (2003). The effect of low protein supplementation to dairy cow grazing clover grass during half of the day. Livest. Prod.Sci., 81: 293 – 306.
  4. Orskov, E.r., (1998). The feeding of ruminant (principles and practice). 2nd Edn., Chalcombe Publication, U.K.
  5. Panda, D.K. (2009). Participation in the Group Based Microfinance and its Impact on Rural Households: Quasi experimental Evidence from an Indian State. Global J. Finance and Management, 1 (2): 171 – 183.
  6. Woolridge, J.M. (2002). Econometric Analysis for Cross-section and Panel Data. Cambridge, Mass.: The MIT Press.
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Indian Journal of Animal Research
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    volume 46 issue 4 (december 2012) : 389 - 392

    FACTORS INFLUENCING THE ADOPTION OF NEW FEEDING TECHNOLOGY BY THE FARMER INTEREST GROUPS (FIGs) OF VELLORE DISTRICT IN TAMIL NADU

    B
    B. Rajesh Kumar
    D
    D. Baskaran
    A
    A. Serma Saravana Pandian
    1Madras Veterinary College, Tamil Nadu Veterinary and Animal Sciences University, Vepery, Chennai-600 007, India

    • Submitted|

    • First Online |

    • doi

    Cite article:- Kumar Rajesh B., Baskaran D., Pandian Saravana Serma A. (2025). FACTORS INFLUENCING THE ADOPTION OF NEW FEEDING TECHNOLOGY BY THE FARMER INTEREST GROUPS (FIGs) OF VELLORE DISTRICT IN TAMIL NADU. Indian Journal of Animal Research. 46(4): 389 - 392. doi: .

    ABSTRACT

    The factors influencing the new feeding technology ie., Dairy Cattle feed computation for Farmer Interest Groups (FIGs) in Vellore District of Tamil Nadu was analysed. The study was conducted among the 150 adopters and 102 non adopters of Farmer Interest Groups belonging to 12 villages from each of the 12 blocks of Vellore district. Binary logistic regression analysis was fitted to study the factors, which influenced the adoption of new low cost cattle feed computation technology. The factors influencing adoption rate of the new feeding technology were total dairy income, animal holding and net returns per litre of milk. On the other hand the variables such as age, education, family size, experience in dairy farming and net agricultural income had no significant effect towards the adoption rate. Further, the logit model had correctly predicted the adopters and non adopters by 97 per cent.

    REFERENCES

    1. Krober, T.F., Steingass H., Funk R. and Drochner W., (1999). Effects of reduced crude protein supply on dry matter intake digestibility, excretion and performance of dairy cows in a lactation period. Zuechtungs Kunde, 71: 182–195.
    2. Kim, S., (2005). The effect of socioeconomic factors on the adoption of best management practices in beef cattle production. J. Soil and Water Conservation, 60(3): 111.
    3. Niels, M.N., Kristensen T., and Hansen H., (2003). The effect of low protein supplementation to dairy cow grazing clover grass during half of the day. Livest. Prod.Sci., 81: 293 – 306.
    4. Orskov, E.r., (1998). The feeding of ruminant (principles and practice). 2nd Edn., Chalcombe Publication, U.K.
    5. Panda, D.K. (2009). Participation in the Group Based Microfinance and its Impact on Rural Households: Quasi experimental Evidence from an Indian State. Global J. Finance and Management, 1 (2): 171 – 183.
    6. Woolridge, J.M. (2002). Econometric Analysis for Cross-section and Panel Data. Cambridge, Mass.: The MIT Press.
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