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Rice Ecosystems and Adoption of Modern Rice Varieties in Odisha, East India: Intensity, Determinants and Policy Implications

Author

Listed:
  • Kirtti Ranjan Paltasingh
  • Phanindra Goyari
  • Kiril Tochkov

    (SMVD University, India
    University of Hyderabad, India
    Texas Christian University, USA)

Abstract

Odisha is one of the major rice producing states of the eastern region of India. But, the adoption of modern agricultural technologies like modern varieties (MVs) of paddy is still low and skewed across regions and farmer groups in the state even after five decades of inception of green revolution in India. The state has two distinct ecosystems because out of 6.5 million hectares of gross cropped area of the state, 49% is still rainfed and 51% is irrigated. The patterns of adoption of MVs of rice and constraints in adoption process differ in both ecosystems. On this background, the present paper tries to analyze the intensity of adoption of MVs of rice and its determinants in irrigated and rainfed rice ecosystems of the state. The study is based on the primary data at the household level collected by a multistage purposive sampling method. The sample included 300 farm households from six villages of two districts, i.e., Cuttack and Khordha. These two districts represent the irrigated ecosystem and rainfed ecosystem, respectively. The study found that the total study region shows an increasing trend in the adoption intensity with the rise in the size of operational landholding even though the absolute area for large farmer group is the lowest. This positive association is higher in the irrigated region than in the rainfed ecosystem. There is no huge difference in adoption intensity of MVs across the farmer groups in the irrigated region as compared to their counterparts in the rainfed ecosystem. From the tobit model regression results, the study has found a glaring difference between the specific factors influencing the adoption intensity in both ecosystems. Factors like education, farm size, land position, extension visits, credit accessibility, local market, seed availability, perception about taste of MVs and shorter maturity of MVs were significantly influencing the adoption intensity in irrigated ecosystem. But, in the rainfed ecosystem, variables like non-farm activities, soil quality, land position, seed availability, perception on shorter maturity and higher yield of MVs were the significant determinants of adoption intensity. The pooled sample regression results reveal that the ecosystem dummy variable plays a significant role in the adoption decision. Therefore, the study pitches for the development of irrigation facilities along with rigorous implementation of farmer field school program and strengthening of agricultural extension networks.

Suggested Citation

  • Kirtti Ranjan Paltasingh & Phanindra Goyari & Kiril Tochkov, 2017. "Rice Ecosystems and Adoption of Modern Rice Varieties in Odisha, East India: Intensity, Determinants and Policy Implications," Journal of Developing Areas, Tennessee State University, College of Business, vol. 51(3), pages 197-213, July-Sept.
  • Handle: RePEc:jda:journl:vol.51:year:2017:issue3:pp:197-213
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    Citations

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    Cited by:

    1. Saroj & Kirtti Ranjan Paltasingh, 2024. "What promotes production contract in Indian agriculture? Managing market risk versus profit orientation," Agricultural Economics, International Association of Agricultural Economists, vol. 55(1), pages 140-153, January.
    2. Paltasingh, Kirtti Ranjan & Basantaray, Amit Kumar & Jena, Pabitra Kumar, 2022. "Land tenure security and farm efficiency in Indian agriculture: Revisiting an old debate," Land Use Policy, Elsevier, vol. 114(C).
    3. Paltasingh, Kirtti Ranjan, 2018. "Land tenure security and adoption of modern rice technology in Odisha, Eastern India: Revisiting Besley’s hypothesis," Land Use Policy, Elsevier, vol. 78(C), pages 236-244.

    More about this item

    Keywords

    Odisha; rice ecosystems; modern varieties; adoption; tobit model;
    All these keywords.

    JEL classification:

    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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