Determinants of Drought Tolerant Rice Variety Adoption: Evidence from Rural farm Household in Northern Part of Bangladesh

Razia Sultana, Md. Habibur Rahman, Mohammad Rashidul Haque, Md. Mohsin Ali Sarkar, Syful Islam

Abstract

The drought-tolerant rice variety Binadhan-19 study was conducted in five districts: Mymensingh, Ranpur, Pabna, Rajshahi and Chapainwabganj of Bangladesh. A total of 200 farmers were randomly selected (40 from each location) to collect the data with a pre-designed questionnaire. Tabular, descriptive statistics and Probit model were used to fulfil objectives. The estimated log-likelihood value of gender, farm size, yield, agricultural extension services have a statistically and significant positive effect on the adoption of the variety. The household characteristic related variables such as age, experience, annual income, human labour, duration of the variety have no statistically significant effect on the adoption of the variety. Marginal coefficients indicate that if male farmers increased by 100%, the probability of adopting the Binadhan-19 variety would increase at 38 times more likely to adopt the variety. If the farm size of Binadhan-19 increased by 100%, the probability of adopting the variety would be increased by 0.07%. A farmer who has access to agricultural extension service is about 39 times more likely to adopt the variety. Again, if the yield increased by 100%, adopting the varieties would increase by 0.08%. The marginal coefficients of locations and soil fertility are negatively significant, indicating that if these two variables increased by 100%, the probability of adopting the varieties would decrease by 0.06% and 30%, respectively.



Keywords


Drought tolerant; Rice; Adoption; Probit model; determinants; Binadhan-19; Bangladesh

Full Text:

PDF


References


Abdoulaye, T., Abass, A., Maziya-Dixon, B., Tarawali, G., Okechukwu, R., Rusike, J., … Ayedun, B. (2014). Awareness and adoption of improved cassava varieties and processing technologies in Nigeria. Journal of Development and Agricultural Economics, 6(2), 67–75. doi: 10.5897/jdae2013.006

Adesina, A. A., Baidu-Forson, J. (1995). Farmers' Perceptions and Adoption of New Agricultural Technology: Evidence from Analysis in Burkina Faso and Guinea, West Africa. Journal of Agricultural Economics, 13(1), 1–9.

Adnan, S. (1993). Living without floods: lessons from the Drought of 1992. Dhaka: Research and Advisory Services.

Adofu, I., Shaibu, S., & Yakubu, S. (2013). The economic impact of improved agricultural technology on cassava productivity in Kogi State of Nigeria. International Journal of Food and Agricultural Economics, 1(1), 63–74.

Afolami, C. A., Obayelu, A. E., & Vaughan, I. I. (2015). Welfare impact of adoption of improved cassava varieties by rural households in South Western Nigeria. Agricultural and Food Economics, 3(1). doi: 10.1186/s40100-015-0037-2

Amao, J., & Awoyemi, T. (2008). Adoption of Improved Cassava Varieties and Its Welfare Effect on Producing Households in Osogbo ADP Zone of Osun State. Gene Conserve, 7(29), 1–11. Retrieved from https://www.cabdirect.org/cabdirect/abstract/20093032490

Asante, B. O., Villano, R. A., Battese, G. E. (2014). The effect of the adoption of yam minisett technology on the technical efficiency of yam farmers in the forest-savanna transition zone of Ghana. African Journal of Agricultural and Resource Economics, 9(2), 75–90.

Asfaw, S. (2010). Estimating Welfare Effect of Modern Agricultural Technologies: A Micro- Perspective from Tanzania and Ethiopia. Retrieved from https://www.semanticscholar.org/paper/Estimating-Welfare-Effect-of-Modern-Agricultural-A-Asfaw/0c8fb82303b049ff29a2312c019505e249391c24

Asfaw, S., Kassie, M., Simtowe, F., & Lipper, L. (2012). Poverty Reduction Effects of Agricultural Technology Adoption: A Micro-evidence from Rural Tanzania. Journal of Development Studies, 48(9), 1288–1305. doi: 10.1080/00220388.2012.671475

Awotide, B. A., Diagne, A., Omonona, B. T. (2012). Impact of Improved Agricultural Technology Adoption on Sustainable Rice Productivity and Rural Farmers’ Welfare in Nigeria: A Local Average Treatment Effect (LATE) Technique. Retrieved from https://aec.afdb.org/sites/default/files/2019/12/04/impact_of_improved_agricultural_technology_adoption_on_sustainable_rice_productivity_and_rural_farmers_welfare_in_nigeria_a_local_average_treatment_effect_late_technique_02.pdf

Banglapedia (2021. June 18). Drought in Bangladesh. Retrieved from https://en.banglapedia.org/index.php/Drought#:~:text=Drought%20mostly%20affects%20Bangladesh%20in,monsoon%20and%20post%2Dmonsoon%20periods.&text=The%20percentage%20of%20drought%20affected,of%20the%20monsoon%20crops%20only

Basak, J. K. (2010). Climate Change Impacts on Rice Production in Bangladesh: Results from a Model. Retrieved from https://www.researchgate.net/publication/346260955_Climate_Change_and_Crop_Production_in_Bangladesh_Insights_from_the_Impacts_of_Climate_and_Groundwater_Variability_on_Rice_Production

Campbell, B. M., Thornton, P., Zougmoré, R., van Asten, P., & Lipper, L. (2014). Sustainable intensification: What is its role in climate smart agriculture? Current Opinion in Environmental Sustainability, 8, 39–43. doi: 10.1016/j.cosust.2014.07.002

Daromola, B. (2005). Government policies and competitiveness of Nigerian Rice Economy. Retrieved from https://www.cabdirect.org/cabdirect/abstract/20113224337

Dontsop-Nguezet, P. M., Manyong, V., Abdoulaye, T., Arega, A., Amato, M. S., Ainembabazi, J. H., .... & Okafor, C. (2016). Non-farm activities and adoption of improved cassava and beans varieties in South-Kivu, DR Congo. Tropicultura, 34(3), 262–275.

Dontsop-Nguezet, P., Diagne, A., Okoruwa, Y. O., & Ojehomon, V. (2011). Impact of Improved Rice Technology (NERICA varieties) on Income and Poverty among Rice Farming Households in Nigeria: A Local Average Treatment Effect (LATE) Approach. Quarterly Journal of International Agriculture, 50(3), 267–291.

Habiba, U., Shaw, R., & Takeuchi, Y. (2011). Chapter 2 Socioeconomic Impact of Droughts in Bangladesh. Community, Environment and Disaster Risk Management, 25–48. doi: 10.1108/s2040-7262(2011)0000008008

Hewitt, K. (1997). Regions at Risk: A Geographical Introduction to Disasters. London: Routledge.

Hossain, M. (1990). Natural Calamities, Instability in Production and Food Policy in Bangladesh. The Bangladesh Development Studies, 18(4), 33–54.

Hossain, M., Bose, M. L., & Mustafi, B. A. A. (2006). Adoption and productivity impact of modern rice varieties in Bangladesh. The Developing Economies, 44(2), 149–166. doi: 10.1111/j.1746-1049.2006.00011.x

Houssou, N., Chapoto, A. (2015). Adoption of Farm Mechanisation, Cropland Expansion, and Intensification in Ghana. Retrieved from https://ideas.repec.org/p/ags/iaae15/211744.html

Huang, W., Zeng, D., & Zhou, S. (2015). Welfare impacts of modern peanut varieties in China. Quarterly Journal of International Agriculture, 54(3), 221–238. Retrieved from https://www.researchgate.net/publication/286865509_Welfare_impacts_of_modern_peanut_varieties_in_China

IPCC. (1997). The regional impacts of climate change: an assessment of vulnerability. Retrieved from https://www.ipcc.ch/report/the-regional-impacts-of-climate-change-an-assessment-of-vulnerability/

IPCC. (2010). World climate report-global drought pattern. Retrieved from www.worldclimaterepor.com/indexphp/2010/02/24/update-on-global-drought-pattern-sipcc-take-note

Jaleel, C. A., Manivannan, P., Wahid, A., Farooq, M., Somasundaram, H., Panneerselvam, R. (2009). Drought stress in plants: a review on morphological characteristics and pigments composition. International Journal of Agricultural Biology, 11, 100–105

Kaliba, A. R. M., Verkuijl, H., & Mwangi, W. (2000). Factors Affecting Adoption of Improved Maize Seeds and Use of Inorganic Fertilizer for Maize Production in the Intermediate and Lowland Zones of Tanzania. Journal of Agricultural and Applied Economics, 32(1), 35–47. doi: 10.1017/s1074070800027802

Khonje, M., Manda, J., Alene, A. D., & Kassie, M. (2015). Analysis of Adoption and Impacts of Improved Maize Varieties in Eastern Zambia. World Development, 66, 695–706. doi: 10.1016/j.worlddev.2014.09.008

Kijima, Y., Otsuka, K., & Sserunkuuma, D. (2008). Assessing the impact of NERICA on income and poverty in central and western Uganda. Agricultural Economics, 38(3), 327–337. doi: 10.1111/j.1574-0862.2008.00303.x

Mottaleb, K. A., Gumma, M. K., Mishra, A. K., & Mohanty, S. (2015). Quantifying production losses due to drought and submergence of rainfed rice at the household level using remotely sensed MODIS data. Agricultural Systems, 137, 227–235. doi: 10.1016/j.agsy.2014.08.014

Nandal, D. S., Rai, K. N. (1986). Impact of Farm Mechanisation on Farm Productivity in Haryana. N. d.: n. d.

Negatu, W. (1999). The impact of perception and other factors on the adoption of agricultural technology in the Moret and Jiru Woreda (district) of Ethiopia. Agricultural Economics, 21(2), 205–216. doi: 10.1016/s0169-5150(99)00020-1

Nata, J. T., Mjelde, J. W., & Boadu, F. O. (2014). Household adoption of soil-improving practices and food insecurity in Ghana. Agriculture & Food Security, 3(1). doi: 10.1186/2048-7010-3-17

Obasi, G. (1994). WMO's role in the international decade for natural disaster reduction. Bulletin of the American Meteorological Society, 75(9), 1655–1661.

Ogada, M. J., Mwabu, G., & Muchai, D. (2014). Farm technology adoption in Kenya: a simultaneous estimation of inorganic fertilizer and improved maize variety adoption decisions. Agricultural and Food Economics, 2(1). doi: 10.1186/s40100-014-0012-3

Ouma, J., Murithi, F., Mwangi, W., Verkuijl, H., Gethi, M., De Groote, H. (2002). Adoption of Maize Seed and Fertilizer Technologies in Embu District, Kenya. Retrieved from https://repository.cimmyt.org/bitstream/handle/10883/904/447957.pdf?sequence=1&isAllowed=y

Rahman, A. T. M. S., Kamruzzaman, M., Jahan, C. S., Mazumder, Q. H., & Hossain, A. (2016). Evaluation of spatio-temporal dynamics of water table in NW Bangladesh: an integrated approach of GIS and Statistics. Sustainable Water Resources Management, 2(3), 297–312. doi: 10.1007/s40899-016-0057-4

Selvaraju, R., Subbiah, A. R., Baas, S., & Juergens, I. (2006). Livelihood adaptation to climate variability and change in drought-prone areas of Bangladesh. Retrieved from https://www.fao.org/3/a0820e/a0820e.pdf

Shafie, H., Rashid, A., Halder, S. (2009). Endowed wisdom Knowledge of nature and copingwith disasters in Bangladesh. Retrieved from https://www.researchgate.net/publication/328969034_2009_ENDOWED_WISDOM_Knowledge_of_Nature_and_Coping_with_Disasters_in_Bangladesh

Shakya, P. B., & Flinn, J. C. (1985). Adoption of modern varieties and fertilizer use on rice in the Eastern Tarai of Nepal. Journal of Agricultural Economics, 36(3), 409–419. doi: 10.1111/j.1477-9552.1985.tb00188.x

Sheffield, J., Andreadis, K. M., Wood, E. F., & Lettenmaier, D. P. (2009). Global and Continental Drought in the Second Half of the Twentieth Century: Severity–Area–Duration Analysis and Temporal Variability of Large-Scale Events. Journal of Climate, 22(8), 1962–1981. doi: 10.1175/2008jcli2722.1

Sodjinou, E., Glin, L. C., Nicolay, G., Tovignan, S., & Hinvi, J. (2015). Socioeconomic determinants of organic cotton adoption in Benin, West Africa. Agricultural and Food Economics, 3(1). doi: 10.1186/s40100-015-0030-9

Swaminathan, M. S. (1998). Issues and Challenges in Sustainable Increased Rice Production and the Role of Rice in Human Nutrition in the World. International Rice Comission, 98(4-2), 23.

Wilhite, D. A. (2000). Drought: A Global Assessment. London: Routledge.

Wilhite, D. A., & Glantz, M. H. (1985). Understanding: the Drought Phenomenon: The Role of Definitions. Water International, 10(3), 111–120. doi: 10.1080/02508068508686328

Yorobe, J. M., Ali, J., Pede, V. O., Rejesus, R. M., Velarde, O. P., & Wang, H. (2016). Yield and income effects of rice varieties with tolerance of multiple abiotic stresses: the case of green super rice (GSR) and flooding in the Philippines. Agricultural Economics, 47(3), 261–271. doi: 10.1111/agec.12227


Article Metrics

Metrics Loading ...

Metrics powered by PLOS ALM

Refbacks

  • There are currently no refbacks.




Copyright (c) 2021 Razia Sultana, Md. Habibur Rahman, Mohammad Rashidul Haque, Md. Mohsin Ali Sarkar, Syful Islam

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