Factors Affecting Farm Mechanization – A Case Study in Assam, India

Barman, Sinki; Deka, Nivedita; Deka, Pallavi

doi:10.9734/ajaees/2019/v32i130146

Cited by 6 publications

(6 citation statements)

References 2 publications

(2 reference statements)

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“…So, achievement of higher education was associated to adoption of farm machineries (Figure 1). The findings of this investigation are in accordance with Barman et al (2019).…”

Section: Education Status Of Respondentssupporting

confidence: 91%

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Status of farm mechanization and its impact on maize production in Jhapa District, Nepal

Kandel

Poudel

Saru

et al. 2021

Arch. Agric. Environ. Sci.

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A survey research was carried out in 2020 in maize zone, Jhapa to identify and analyze the status of farm mechanization and its impact in the maize production. Kankai Municipality and Jhapa Rural municipality were purposively selected for the study as these areas were under the command area of prime minister agriculture modernization project, project implementation unit, maize zone Jhapa. Thereafter, a total of 70 samples were selected using random sampling method. Thirty-three samples were selected from Kankai Municipality and remaining thirty-seven were selected from remaining Jhapa rural municipality. Primary data were collected using semi-structured questionnaire, focal group discussion and key informant interview whereas secondary data were obtained through a review of relevant literature. Both descriptive and analytical statistics were used to analyze the data. It was found that the status of mechanization was still in the initial phase in the study area. Results showed that mechanization was limited to two cultural operations namely tillage and threshing of which only in case of tillage, farm machineries were adopted by more than ninety percent of the respondent farmers while in case of sowing more than ninety percent of respondent didn’t use any modern equipment. Insect and pest in maize field was major problem faced by the farmers. Therefore, productivity of maize in Kankai area was higher as compared to Jhapa area as adoption of mechanization was higher in Kankai area.

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“…So, achievement of higher education was associated to adoption of farm machineries (Figure 1). The findings of this investigation are in accordance with Barman et al (2019).…”

Section: Education Status Of Respondentssupporting

confidence: 91%

“…Mechanization helps in efficient and large scale production leading to commercialization in agriculture sector (Barman et al, 2019). Mechanization can reduce labor cost, work load, time of operation and ultimately helps to increase production and productivity of farm.…”

Section: Original Research Articlementioning

confidence: 99%

Status of farm mechanization and its impact on maize production in Jhapa District, Nepal

Kandel

Poudel

Saru

et al. 2021

Arch. Agric. Environ. Sci.

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“…Farmers' responses of each parameter are codified as scores. Barman et al, (2019) also used Logit Regression analysis to examine the factors affecting farm mechanization [3]. Logit Analysis was with the help of following formula: P = 1/(1+e -AL) Where, P is the probability that famers adoption level AL = x (1) + x (2)*AGE+ x (3)*OCC+ x (4)* EDU+ x (5)*LH+ x (6)*TRN+ x(7)* SO + x (8)*EF+ x (9)* IO + x (9)* ME Where, a) AGE is the age of head of the household (proxy for experience) b) OCC is the Occupation of the farmers, farming: 1 otherwise 0 c) EDU is the maximum education level of head of the household d) LH is the farm size e) TRN is the Training received at KVK f) SO is Scientific orientation YES=1, 0 Otherwise g) EF is the Experience in Farming.…”

Section: Methodsmentioning

confidence: 99%

KMAS as a Tool for Dissemination of Agricultural Technologies in Nagaon District of Assam

Barman¹,

Deka²,

Deka

2021

AJAEES

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Development of Agricultural and allied activities can be achieved through various approaches of Information and communication (ICT) tools. Kisan Mobile Advisory system (KMAS) is one of ICT approaches for dissemination of agricultural technologies to the farming community through SMSs. KVK, Nagaon created a registered farmers group and information related to crop production, insect pest control, dairy and poultry farming, fishery and other marketing related information was sent to users in monthly basis for many years. A sample size of 100 registered farmers were selected for the study in order to examine the impact of KMAS for technology dissemination in Nagaon district. With the help of Pretested scheduled with Simple Random sampling data were collected and analyze in percent analysis. The survey showed that majority of the farmers found agricultural information as increase in knowledge (41.00%), partially applicable (73.00%). The overall impact of the KMAS was low About at 55 percent, medium at 38 per cent and high at 7 per cent. Further they suggested that messages on latest technologies should be served flowed by local language, voice messages.

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“…There are also plenty of studies analyzing the influence of demographic characteristics such as age, gender, and level of education on the adoption of agricultural mechanization [7][8][9][10][11]. Meanwhile, GC et al [7] studied the impact of internet use on agricultural mechanization adoption in Nepal.…”

Section: Introductionmentioning

confidence: 99%

Adoption of Agriculture Mechanization on Paddy Farmers in Indonesia: Demographic Determinants, Internet Access Influence, and The Impact of Adoption on The Yield

Kadir¹,

Prasetyo²

2022

asks

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This study aims to identify the demographic determinants of the agriculture mechanization adoption on paddy farmers in Indonesia and the impact of internet use by farmers on the probability of being adopters. Besides, it also analyses the difference in the average paddy yield cultivated by adopters and non-adopters to determine the adoption impact on agricultural productivity. We found that farmers' level of education and age significantly impacts the probability of being adopters. However, the magnitude of the age impact tends to be diminishing with the increase in age. The probability of being adopters is affected significantly by gender, region, and the farm scale. Male farmers tend to be more likely of being adopters than their female counterparts. Farmers in Java have a slightly higher probability of being adopters than farmers outside Java. Adopting agriculture mechanization also has a positive association with the farm scale, where the larger the farm scale, the more likely the farmers are to be adopters. Our study also found that internet use positively and significantly impacts the farmers' probability of being adopters. Moreover, our study also confirmed a strong indication that the mechanization adoption affects the paddy yield positively indicated by the higher paddy yield average of adopters than non-adopters. Therefore, boosting the adoption of mechanization must be done, for instance, by attracting young people with high education to get involved in agriculture and up-scaling the implementation of tools and agricultural machinery assistance facilitated by the government.

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Factors Affecting Farm Mechanization – A Case Study in Assam, India

Cited by 6 publications

References 2 publications

Status of farm mechanization and its impact on maize production in Jhapa District, Nepal

Status of farm mechanization and its impact on maize production in Jhapa District, Nepal

KMAS as a Tool for Dissemination of Agricultural Technologies in Nagaon District of Assam

Adoption of Agriculture Mechanization on Paddy Farmers in Indonesia: Demographic Determinants, Internet Access Influence, and The Impact of Adoption on The Yield

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