Socioeconomic impact of improved variety of Chinese potato in Tamil Nadu

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Published

2023-06-28

DOI:

https://doi.org/10.58993/ijh/2023.80.2.8

Keywords:

Plectranthus rotundifolius, Impact assessment, Logistic regression, Technology adoption
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Issue

Vol. 80 No. 2 (2023): Indian Journal of Horticulture

Section

Research Articles

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Copyright (c) 2023 Indian Journal of Horticulture

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This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Authors

  • Prakash Division of Extension and Social Sciences, ICAR-Central Tuber Crops Research Institute, Thiruvananthapuram-695017, Kerala, India.
  • D Jaganathan Division of Extension and Social Sciences, ICAR-Central Tuber Crops Research Institute, Thiruvananthapuram-695017, Kerala, India.
  • Sheela Immanuel Division of Extension and Social Sciences, ICAR-Central Tuber Crops Research Institute, Thiruvananthapuram-695017, Kerala, India.
  • R Muthuraj Division of Crop Production, ICAR-Central Tuber Crops Research Institute, Thiruvananthapuram- 695017, Kerala, India
  • P S Sivakumar Division of Extension and Social Sciences, ICAR-Central Tuber Crops Research Institute, Thiruvananthapuram-695017, Kerala, India.

Abstract

The socioeconomic impact was based on a farm household survey conducted in Tenkasi and Tirunelveli districts of Tamil Nadu among 200 Chinese potato producers during 2021/2022. A logistic regression model was employed to identify factors determining the adoption of ‘SreeDhara’, and the Inverse Probability Weighted Regression Adjustment (IPWRA) method was used to assess the impact of the adoption of ‘SreeDhara’ on yield and income. The cost of cultivation, gross income, and net income for ‘SreeDhara’ adopters were 7, 37, and 87% higher than for non-adopters. Years of schooling, farm income, access to extension services, and block dummies had significant, positive effects on adopting the variety. The IPWRA results indicated yield and income of ‘SreeDhara’ adopters were higher than non-adopters by 23.65 and 24.99 %, respectively. The most significant constraints to adopting Chinese potatoes were lack of awareness about ‘SreeDhara,’ inaccessibility to credit, and the non-availability of crop insurance. Thus, recognizing its higher nutritional value and potential farm income, institutional support in the form of better extension linkages, credit facilities, and crop insurance to Chinese potato growers needs to be strengthened.

How to Cite

Prakash, D Jaganathan, Sheela Immanuel, R Muthuraj, & P S Sivakumar. (2023). Socioeconomic impact of improved variety of Chinese potato in Tamil Nadu. Indian Journal of Horticulture, 80(2), 177–183. https://doi.org/10.58993/ijh/2023.80.2.8

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References

Abdulai, A. and Huffman, W. 2014. The adoption

and impact of soil and water conservation

technology: an endogenous switching regression

application. Land Econ.90: 26–43.

Acheampong, P.P., Addison, M. and Wongnaa,

C.A. 2022. Assessment of impact of adoption of

improved cassava varieties on yields in Ghana:

An endogenous switching approach. Cogent

Econ. Finance.10:1-18.

Asfaw, S., Shiferaw, B., Simtowe, F. and

Lipper, L. 2012. Impact of modern agricultural

technologies on smallholder welfare: Evidence

from Tanzania and Ethiopia. Food Policy.

:283–95.

Evenson, R.E. and Gollin, D. 2003. Crop variety

improvement and its effect on productivity: The

impact of international agricultural research,

CABI Publishing, USA.

Kana, H.A., Aliyu, I.A. and Chammang, H.B.

Review on neglected and under-utilized

root and tuber crops as food security in achieving

the millennium development goals in Nigeria. J.

Agric. Vet. Sci.4:27–33.

Manda, J., Gardebroek, C., Kuntashula, E.

and Alene, A. D. 2018. Impact of improved

maize varieties on food security in Eastern

Zambia: A doubly robust analysis. Rev. Dev.

Econ.22:1709–28.

Mariano, M.J., Villano, R. and Fleming, E. 2012.

Factors influencing farmers’ adoption of modern

rice technologies and good management

practices in the Philippines. Agric. Syst. 110:41–

Nikam, V., Kumar, S. and Kingsly, I.T. 2019.

Impact assessment of mobile app using

economics surplus model. Indian J. Agric.

Sci.89:147-51.

Rahman, S., Norton, G.W. and Rashid, M.H.A.

Economic impacts of integrated pest

management on vegetable production in

Bangladesh. Crop Prot.113:6-14.

Ransom, J.K., Paudyal, K. and Adhikari, K.

Adoption of improved maize varieties in

the Hills of Nepal. Agric. Econ. 29:299-305.

Sharma, P., Dupare, B.U. and Patel, R.M. 2018.

Technology adoption, its impact and determinants:

the case of soybean in Madhya Pradesh, Agric.

Econ. Res. Rev. 31:281-89.

Shiyani, R.L., Joshi, P.K., Asokan, M. and

Bantilan, M.C.S. 2002. Adoption of improved

chickpea varieties: KRIBHCO experience in

Tribal Region of Gujarat, India. Agric. Econ.

:33-39.

Sudha, M., Gajanana, T.M. and Murthy, D.S.

Economic impact of commercial hybrid

seed production in vegetables on farm income,

employment and farm welfare – A case of tomato

and okra in Karnataka. Agric. Econ. Res. Rev.

:251-68.

Sunny, F.A., Huang, Z. and Karimanzira,

T.T.P.2018. Investigating key factors

influencing farming decisions based on soil

testing and fertilizer recommendation facilities

(STFRF)-A case study on rural Bangladesh.

Sustain.10:4331.

Suri, T. 2011. Selection and Comparative

advantage in technology adoption.

Econometrica.79:159–209.

Tambo, J. A. and Mockshell, J. 2018. Differential

impacts of conservation agriculture technology

options on household income in Sub-Saharan

Africa. Ecol. Econ.151:95-105.

Zheng, H. and Ma, W. 2021. Smartphonebased information acquisition and wheat farm

performance: Insights from a Doubly Robust

IPWRA Estimator. Electron. Commer. Res. 1–26.

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