Production Economics and Determinants of Potato Production in Nuwakot, Nepal

Bhatta

2020

J. Agric. Nat. Res.

Self Cite

Production and profit from maize farming can be substantially increased by allocating resources efficiently and adopting improved maize variety. In this context, a study was undertaken to determine the allocative efficiency and factors affecting adoption of improved maize variety in Eastern hills of Nepal. Random sampling was conducted in eastern part of Khotang district namely, Halesi municipality and Diktel Rupakot Majuwagadi municipality during month of March 2019. Pretested semi-structured questionnaire was administered among 80 randomly selected farmers cultivating maize since last two years. Face to face interview was scheduled to obtain data. Cobb Douglas production function was used to determine allocative efficiency; probit regression model was launched to determine factors affecting adoption of improved maize variety. Significant positive relation of cost of seed, planting, and weeding with income has suggested to increase expenditure on certified maize seed over own farm seed, line sowing over broadcasting, and weeding. The model revealed that increasing all the factors of production by 100% would result in increase in income by 71.83%. Furthermore, cultivating improved maize variety is more profitable than own farm seed. Probit regression model showed that, farmers who have received training, who were member of cooperatives and who have received high schooling were more likely to adopt open-pollinated improved maize variety. Unavailability of inputs (seed, fertilizer, and labor), insect pest attack and adverse climatic conditions were major constraint of maize farming. Therefore, it would be better to suggest maize producers to increase expenditure on seed; make maize field weed free and adopt line sowing method. In addition, providing training, increasing access over inputs and encouraging farmers towards cooperatives could be virtuous for sustainable maize production.

Section: Cobb-douglas Production Function Analysissupporting

confidence: 67%

Section: Cobb-douglas Production Functionmentioning

confidence: 99%

Allocative efficiency and adoption of improved maize variety: A case of eastern hills of Nepal

Katel

Bhatta

2020

J. Agric. Nat. Res.

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“…Similar result of under utilization of chemical fertilizer and seed were found by Dhakal et al (2015) and Sapkota et al (2018). Similarly, decreasing cost of human labor and FYM is supported by Dhakal et al (2015) but decreasing cost of FYM is in contrast with the finding of Dahal and Rijal (2019); Ghimire and Dhakal, (2014). Decreasing in cost of animal power is supported by Sapkota et al (2018).…”

Section: Estimation Of Allocative Efficiency Of Maize Farmingsupporting

confidence: 69%

Resource Use Efficiency and Profitability of Maize Farming in Sindhuli, Nepal: Cobb-Douglas Production Function Analysis

Int J Appl Sci Biotechnol

Rijal

2019

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The study was conducted to determine the resource use efficiency, profitability and demography of maize farming in Sindhuli district. This study was conducted in 120 maize producers, 60 from Kamalamai Municipality (KMC) and 60 from Marin rural municipality. Pretested semi-structured questionnaire was administered to randomly selected farmers. Maize producers were interviewed using face to face interview method in the month of October 2018. All the data were entered into SPSS and Microsoft excel and analysis was done by using Microsoft excel and SPSS. Cobb- Douglas production function was used to determine the resource use efficiency of maize production. Benefit cost ratio in the research area is 1.20 which indicates that maize production was profitable and farmers of Sindhuli get additional 20 paisa with investment of one rupee in maize farming. Productivity, cost and income per hectare of maize farming in Sindhuli was 1.98 tons, Rs 42423.3 and Rs 50805 respectively. 10% increase in chemical fertilizer, FYM and seed cost resulted in increase in income by 7.21%, 2.43% and 0.6% respectively. 10% increase in labor and animal power resulted into 0.2% and 0.07% decrease in output. For optimal allocation of resource expenditure on seed and chemical fertilizer were need to be increased by 89.93% each. Labor, animal power and FYM were over utilized resources for maize farming. The sum of coefficients was 0.983 which implied decreasing return to scale, 100% increase in all the factor of production included in the model would result in 98.30% increase in maize production. Int. J. Appl. Sci. Biotechnol. Vol 7(2): 257-263

“…Probit model was used to determine the factors that influence farmers to follow climate change adaptation strategies in Dhading district. Probit model is statistical probability model with two categories in the dependent variable (Liao, 1994) cited by Dahal and Rijal (2019). Probit model is based on the cumulative normal probability distribution.…”

Section: Probit Modelmentioning

confidence: 99%

Perception, Impact And Determinants Of Climate Change Adaptation Among Vegetable Growers Of Dhading District Of Nepal

Shrestha

2020

SAARC J Agric

Climate change is one of the most challenging problems for the agricultural development. The purpose of this study is to analyze perception of climate change, its impacts and determinants among vegetable growers and to identify major adaptation strategies used by them. The study was based on survey of 75 vegetable growers; 34 from Benighat Rorang rural municipality and 41 from Siddhalek rural municipality of Dhading district of Nepal. Data were collected using face to face interview. The study provided empirical evidence of decreased in intensity, duration and frequency of rainfall and increase in annual temperature, drought duration and frost severity. Incidence of disease and pest, decline in soil fertility, scarcity of water and severe frost/hailstones were major problems. The 45.33% vegetable growers were compelled to change planting and 54.67% of them to change harvesting due to climate change effect. The adaptation practices such as mulching (24%), green/plastic house (29.3%), drip irrigation (8%), IPM (12.5%), change in crop variety (31.3%) and cropping pattern were found common practices adopted by farmers. The probability of adapting climate change mitigating factors was 70.26% higher for those who had received training in vegetable cultivation. Use of new climate smart agricultural technologies and providing training about vegetable cultivation were found suitable strategies to mitigate the negative impacts of climate change. SAARC J. Agri., 17(2): 239-251 (2019)