Analysis of Socio-economic Factors and Profitability of Hybrid Maize Production in Eastern Terai of Nepal

Adhikari, Surya Prasad; Shrestha, Keshav Prasad; Shrestha, Surendra Lal

doi:10.9734/sajsse/2018/v2i326570

Cited by 4 publications

(7 citation statements)

References 6 publications

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“…However, the farm size was negatively signed and not statistically significant. The result was found different to a study in Eastern Terai of Nepal where the farm size was positive but not significant (Adhikari et al, 2018). The coefficient of education of household head was positive and statistically significant at 5% level.…”

Section: Identification Of Socioeconomic Factors Influencing Both Hybcontrasting

confidence: 99%

“…This indicates that for each year increase in the level of education, the production of maize increased significantly. Education enhances the ability of decision makers by enabling the farmers to think critically and use information sources efficiently (Adhikari et al, 2018). Similarly, a study in Tanzania found that education level had statistically impact on maize yield (Justin, 2015).…”

Section: Identification Of Socioeconomic Factors Influencing Both Hybmentioning

confidence: 98%

“…Socioeconomic characteristics of farmers are important factors influencing maize production. The most important variables included in this category are age, education, household size, farm size, membership, training and extension contact (Adhikari et al, 2018). Likewise, age of household head, ethnicity, credit accessibility, cooperative involvement, extension visit, training, formal sector seed availability were found important factors for the adoption of modern variety of maize (Upadhyay et al, 2018).…”

Section: Introductionmentioning

confidence: 98%

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Socio-economic analysis of open pollinated improved and hybrid maize production in Sindhupalchok district of Nepal

Tiwari

Chandan

Thapa

et al. 2021

J. Agric. Nat. Res.

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The study was conducted from April to June, 2020 for comparative analysis of socioeconomic factors and profitability between Open Pollinated Improved (OPI) varieties and Hybrid varieties on maize production in Sindhupalchok district of Nepal. A structured questionnaire was administered to 80 randomly selected households i.e. 48 HHs cultivated OPI and 32 HHs cultivated hybrid maize varieties. Descriptive statistics, unpaired t-test, multiple linear regressions and indexing were used for data analysis using statistical tools- SPSS version 25 and MS-Excel. Linear regression model revealed that area under maize (5% level), education (5% level), age of household head (1% level), training (1% level), access to credit (5% level) and choice of seed (1 % level) significantly influenced maize production. In addition, unpaired t-test revealed that the productivity of hybrid maize varieties was significantly higher (1% level) than OPI varieties. Fall Armyworm infestation was found to more severe in OPI varieties (5% level) than hybrid. Furthermore, B: C ratio of hybrid varieties (1.59) indicated hybrid maize to be more profitable than OPI (1% level). However, the total cost of cultivation along with the cost of seed per hectare of OPI was found to be lower than hybrid varieties (1% level) thereby significantly increasing the area under maize production for OPI varieties (1% level). Indexing identified- lack of availability of quality seeds and fertilizers (I= 0.78) as the major problem associated with maize production. Ensuring access to quality seeds and fertilizer at subsidy, mechanization and efficient extension services focused on development of affordable hybrid maize varieties or high yielding OPI and its adoption among the farmers in order to increase maize productivity is recommended.

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Section: Identification Of Socioeconomic Factors Influencing Both Hybcontrasting

confidence: 99%

Section: Identification Of Socioeconomic Factors Influencing Both Hybmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 98%

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Socio-economic analysis of open pollinated improved and hybrid maize production in Sindhupalchok district of Nepal

Tiwari

Chandan

Thapa

et al. 2021

J. Agric. Nat. Res.

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“…To estimate the socioeconomic factors influencing the lentil production, multiple regression model was used. Adhikari et al (2018) have used the multiple regression model to estimate the factors determining hybrid maize production. Multiple linear regression analysis is an extension of simple linear regression analysis, used to assess the association between two or more independent variables and a single continuous dependent variable.…”

Section: Multiple Regression Modelmentioning

confidence: 99%

Economics of Lentil Production under Relay and Conventional Tillage Practice

et al. 2022

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The study was intended to find out the most profitable method between the relay and tillage growing method of lentil production. For primary data collection, a simple random sampling method was followed. Household survey was conducted in two districts Bardiya and Kailali in 2021 AD. A total of 107 lentil farmers (43 farmers following relay and 64 farmers following tillage practices) were randomly selected from two pockets area (relay and tillage method adopters) of each district. Benefit-Cost (BC) ratio analysis was done to find out the most profitable method of lentil cultivation. Multiple regression model was applied to estimate the factors determining the lentil production. The average BC ratio is 2.18 which indicates that lentil cultivation is profitable with average productivity of 0.64 mt/ha. The total cost incurred per ha in relay and tillage method was NRs. 24345 and NRs. 33549 respectively. Similarly, gross income from relay and tillage method was found NRs. 56160 and NRs 69870, per ha respectively. In between the two popular methods (relay and tillage) of lentil cultivation, the BC ratio was found 2.31 in the relay method compared to 2.08 in the tillage method. Among the several socio-economic independent variables used in the model, the age of the household head and fertilizer application significantly influenced the lentil production. However, lentil production is negatively affected by the practice of intermixed cropping. Hence the result indicates that relay cropping with mono-cropping and appropriate management of fertilizer could play a crucial role to boost the profitability of lentil farming

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“…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…”

Section: Assessment Of the Factors Affecting The Rice Productionmentioning

confidence: 99%

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

Sapkota

Subedi

Tripathi

et al. 2021

J. Agric. Nat. Res.

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Rice (Oryza sativa L.) is the major staple food in the Nepalese context. Chitwan district of Nepal was purposively selected to analyze the rice production from the socio-economic and environmental perspective. A total of 100 rice growing farmers, 50 organic and 50 inorganic were selected as the sample for the purpose of the study using the simple random method of sampling. Primary data were collected through a pre-tested semi-structure interview schedule and key informant interviews; secondary data were collected reviewing related publications. Descriptive statistics, multiple regression and chi-square test were used for data analysis. The multiple regression revealed that the four explanatory variables included in the model: age of the household head, primary occupation of the household head, number of family members involved in agriculture and subsidy in inputs for rice farming were found to have positive and statistically significant effect on rice yield (P<0.01). Moreover, chi-square test revealed that the farming practices that contributes to climate change mitigation such as: minimum tillage practice (P<0.05), crop diversification (P<0.01), green manuring (P<0.01), agro forestry practice (P<0.05), incorporating crop residues (P<0.1), weed management practice (P<0.01) and pest management practice (P<0.01)were found to be well adopted by the organic rice farmers, in contrast, the farming practices of inorganic rice farmers were statistically and significantly different in this respect. Government should make such policy that could grave the attention of the Nepalese people towards organic agriculture; moreover, encouraging them to make it their primary occupation.

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Analysis of Socio-economic Factors and Profitability of Hybrid Maize Production in Eastern Terai of Nepal

Cited by 4 publications

References 6 publications

Socio-economic analysis of open pollinated improved and hybrid maize production in Sindhupalchok district of Nepal

Socio-economic analysis of open pollinated improved and hybrid maize production in Sindhupalchok district of Nepal

Economics of Lentil Production under Relay and Conventional Tillage Practice

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

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