Agricultural Research Management Information System

Home
Research Summary
Search
About Us
- ARMIS
- Brochure
Contact Us
Report
User Request
Data Input
Help
- Operation Manual
  - PDF
  - Video
- Program Area & Commodity
We have reached 37600 number of research entries at this moment.

- Logout

Research Detail

Home
Research
Detail

Farmer’s Challenges in Adopting Artificial Insemination of Cattle in Bangladesh

Aditi Mazumder
Kharamatty, Sandhyakutir, Kishoreganj-2300

Md. Jiaul Hoque
Department of Agriculture Extension Education, Bangladesh Agricultural University, Mymensingh-2200

Ashis Kumar Kundu
Department of Livestock Services, Farmgate, Dhaka

Sadia Afrin
Department of Livestock Services, Farmgate, Dhaka

Abstract/ Executive Summary:

Cattle are one of the indices of civilization, sources of wealth, health and prosperity for the nation. Cattle provide us food, cash as well as mechanical power. The production of cattle is low due to their poor genetic makeup, indigenous and large incidence of diseases. Artificial Insemination (AI) is the first generation reproductive biotechnology that has made a profound contribution to the genetic improvement as well as recognized breeding tool of the cattle. But the farmers in Bangladesh are yet to adopt it perfectly. For these, the principle objective of the study was to determine the extent of problems faced by the farmers in adopting AI of cattle. Problem confrontation was measured based on 18 different aspects of AI using four point scale where 3 indicates high problem, 2 medium, 1 low and 0 no problem at all. The study was conducted in Kishoreganj Sadar Upazila under Kishoreganj district. Data were collected from randomly selected 100 farmers out of 340 farmers using an interview schedule. The majority of the farmers (58%) had medium problems while 39% had high and only 3% had low problems in adopting artificial insemination. Among the problems, inseminator problem and heat stage were considered the most critical problems in the survey area.

Keywords: Artificial Insemination, Biotechnology, Cattle

Location: Gangail and KotSholakia villages of Kishoreganj Sadar Upazila under Kishoreganj district.

Start Date:

End Date:

Program Area: Animal Health and Management

Commodity: Cattle

Objectives:

To investigate the extent of problems faced by the farmers in adopting Artificial Insemination (AI) of cattle.

Methodology:

Study area, sampling design and research instrument The study was conducted in Gangail and KotSholakia villages of Kishoreganj Sadar Upazila under Kishoreganj district. The area was selected because a lot of farmers in the area adopt government and non-government Artificial Insemination (AI) for their cattle. In artificial insemination performance, 2010, Kishoreganj Upazila Livestock Hospital ranked the first position among livestock hospital in Bangladesh (DLS, 2010). In total there were 340 farmer families in Gangail and KotSholakia which were considered as population of the study. Thirty percent of the population (total 100 farmers) was randomly selected by using a Table of Random Numbers as a sample of the study and a sample frame was prepared alphabetically before taking the samples. A structured interview schedule was prepared to keep the objectives of the research. To prepare the interview schedule and secure in-depth information, focus group discussion (FGD) was also conducted. Various socio-economic characteristics of the farmers like age, level of education, household size, Farm size, Farming Experience, Training experience, Extension media contact, Social mobility, Cattle strength, Knowledge on Adopting AI for Cattle, Annual family income from crop farming and others, Income from livestock and poultry were considered as the independent variables of the study. The dependent variable was problem confrontation of the farmers in adopting AI for cattle. Problems were measured by using the interview schedule. The farmers were asked to give their opinion on 6 selected aspects of problems including 18 questions which were identified through FGD with the farmers during pre-testing of the questionnaire. To determine the problems faced by the farmers, they were asked to give their opinions against a four-point scale such as ‘high’, ‘medium’, ‘low’ and ‘not at all’. The total score of the faced problem by a respondent could be ranged from 0-54, when ‘0’ indicates no problem and ‘54’ indicate high problems. To ascertain the extent of the seriousness of problems, total score for each of the problems was computed. Problems were then ranked according to the total score. Total score = (high responses x their weightage) + (medium responses x their weightage) + (low responses x their weightage) Data collection, processing and analysis Data were collected by face-to-face interview method with respondents. At the end of data collection, the collected data were coded, compiled, tabulated and analyzed. The local units were converted into standard units. The qualitative data were transferred into quantitative data by appropriate scoring technique. The responses of the respondents that were recorded in the interview schedule were transferred into a master sheet for entering the data into the computer.

Source of Information: Research Article | No. 02, 2020 | Country: Bangladesh| pp. 10-17 | Open Access

Article Link (Online Journal): DOI:https://doi.org/10.18801/jflvs.010120.02

Funding Source:

Budget:

Total Budget (Tk.) :

Achievement/Findings:

Based on the findings ‘inseminator’ ranked first, ‘heat stage’ ranked second, ‘implementation’ ranked third and ‘provision of AI service’ ranked fourth among the six aspects of problem. So, it may be concluded that problems under these four aspects stand as the root problems in the adoption of artificial insemination by the farmers. The findings of the study revealed that the majority of the respondents faced their problems with inseminator facilities. It may be recommended that the Department of Livestock Services and other organizations should take necessary steps such as recruitment of an adequate number of inseminator, arrangement of training of AI workers to develop their skills.

Knowledge Management: Journal