Socio-economics of wheat production in Kailali and Sunsari districts of Nepal

Abstract

For socio-economic assessment on wheat production, research was conducted from March to June, 2019 in two major wheat growing districts of Nepal, Kailai and sunsari. The primary information was collected by face to face interview using the pre-tested semi-structured interview schedule, two Key Informant Surveys were also done.In addition, the secondary information were collected from the review of related literatures. The survey areas were selected by consultating with Agriculture Knowledge Centre and agricultural officials of the local government; sample were selected by using simple random sampling. All total, 194 samples were selected for this study; the outliers and incomplete responses were omitted. The descriptive statistics revealed that Nepal 297 (66.16 %) has the highest area coverage in Sunsari while Gautam (36.50%) has the highest coverage in Kailali. Multiple regression model revealed that wheat cultivated area (p= 0.000), adoption of NARC released varieties (p= 0.000), gender of the household head (p= 0.017), age of the household head (p= 0.040), membership of organization (p= 0.094) and number of family members between age group 15 to 59 years (p= 0.085) have significant effect on wheat production. Furthermore, the unpaired t-test showed that the mean productivity of wheat in Kailali (2.99 Mt./ha) is significantly higher than that of Sunsari (2.81t./ha) at 5% level of significance. To increase the wheat productivity, the concerned government agricultural institutions should: assure access to NARC released improved varieties, make policy to consolidate the fragmented land, encourage the economically active population and the household heads towards wheat production by providing the efficient technical and financial support.

Rice production in Chitwan district of Nepal: An analysis from economic and environmental perspectives

“…Factors affecting the rice yield Findings of this study regarding positive effect of age of the household head on rice production is similar with the findings of Subedi et al (2020); with the increase in age, the farming experience increases, which might contribute to higher yield through better use of input resources and technology. Also, the study revealed that the farm households having their major occupation agriculture have higher yield as compared to their counterparts.…”

“…The rice productivity (yield) was used as dependent variable whereas different socio-economic and demographic characteristics of the respondents were used as explanatory variables. Multiple regression models have been used in several studies to assess the factors affecting the crop yield (Adhikari et al, 2018;Subedi et al, 2020;Bhattarai et al, 2020). The multiple regression model specified in this study is, Y (rice yield) = f (age of the household head, gender of the household head, primary occupation of the household head, number of family members involved in agriculture, livestock standard unit, membership of any organization, subsidy from the government in inputs, area of rice cultivated land) Also, LnY = α0 + βiXi + ei Where; LnY = Rice yield (in natural log form) α0 = Constant βi = Coefficient Xi = Explanatory variables ei = Error term…”

Economics of production and marketing of wheat in Rupandehi district of Nepal

“…Nepal Agricultural Research Council has been recommended more than 40 improved varieties for different ecological regions of Nepal of which 17 for hill and 26 for terai region (Timsina et al, 2018). In terai region, more than 60% of wheat is produced among three regions of Nepal ( Subedi et al, 2020).…”