District representation in meghalaya map (Source http://meghalaya.gov.in/megportal/map).

District representation in meghalaya map (Source http://meghalaya.gov.in/megportal/map).

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Pakistan is ranked 8th in wheat production and the current study is regarding extension workers' competencies about Model Farm Services Centers (MFSCs) in wheat production in changing climate by highlighting the constraints of farming communities. The government of Khyber Pakhtunkhwa established 24 Model Farm Services Centers (MFSCs) during 2005 fo...

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... Moreover, farmers' satisfaction with the services received increases the likelihood of achieving agricultural development outcomes (Ragasa and Mazunda 2018). However, the effectiveness of extension systems in achieving a sustainable development agenda depends upon the quality of the provided services (Kassem et al. 2021), but also on farmers' participation in the planning, provision as well as evaluation of these services (Joshi and Narayan 2019). Services relevance is largely dependent on their ability to meet farmers' needs (Come, Neto, and Cavane 2021). ...
... Services quality attributes include among others adequacy, relevance, availability, timeliness, affordability, equity and fairness, relation or partnerships, accessibility, diversity, and follow-up (Birner et al. 2009;Buadi, Anaman, and Kwarteng 2013;Nederlof et al. 2011;Sylla et al. 2019;Wongtschowski et al. 2016); providers' accountability and sincerity (Awatade, Ghosh, and Singandhupe 2019); the cost of services (Yifei 2017); or particularly ease of understanding, accuracy, and overall usefulness for information services (Debnath, Saravanan, and Datta 2016). Furthermore, perceived benefits (Elias et al. 2016;Joshi and Narayan 2019;Lotfy and Nahed 2016), such as services' ability to yield outcomes in terms of agricultural productivity, food security (Ragasa and Mazunda 2018), income, employment, innovations, and value chain strengthening (Birner et al. 2009) among others determine the extent to which farmers are satisfied with them. Therefore, we measure farmers' satisfaction with services through two lenses: perceived quality and outcomes ( Figure 1). ...
... Inclusion and feedback were positively correlated to satisfaction with advice and training, and advice and credit, respectively. This suggests that increased farmers' participation in the design, implementation, and monitoring of the interventions aiming at supporting them is likely to improve the overall quality of these interventions and their outcomes (Joshi and Narayan 2019). Education enhances farmers awareness of alternatives and the rewards expected from the implemented activities (Elias et al. 2016). ...
... Over the past ten years, several studies have been undertaken regarding farmers' satisfaction with the public agriculture extension services (Ganpat et al., 2014;Elias et al., 2015;Kassem et al., 2021) and their effectiveness (Debnath et al., 2016;Resnick, 2018;Joshi & Narayan, 2019). Findings of these studies indicated mixed results. ...
... The respondent farmers were asked to indicate their agreement or disagreement on a five-point scale; strongly agree (5), agree (4), moderately agree (3), neutral (2) and disagree (1) for each statement. Likert type scales have been used to assess farmer's satisfaction of extension services by several studies (Joshi & Narayan, 2019, Elias et al., 2015, Ganpat et al., 2014. The respondent farmers were also asked to indicate their satisfaction to the overall process of agricultural service provisions initiated by local level governments. ...
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The objectives of the study were to assess the farmer's satisfaction with agricultural services and the local government's performance in delivery of agricultural services under the new federal system of Nepal. The responses of 300 farming households covering three local levels (100 farming households from each municipality) were collected during 2019 and 2020 to analyse responses. Based on the information obtained, a relative importance index (RII) was developed by using 16 parameters that were considered as performance variables in a Likert-type scale. Results showed that about one tenth of the respondents were highly satisfied; about two fifth were satisfied, and nearly half of the respondents were moderately satisfied with the agricultural services at local level. The RII analysis revealed that local governments are effective in providing agricultural services that are relevant to the farmers resulting in increased access to services along with implementation of agricultural related activities. Other positive changes include the timeliness of service delivery by the local level governments, which have also become more accountable in terms of service delivery. On the other hand, the respondents have felt lower levels of agreement related to the capacity of the local staff, the institutional mechanisms, and participatory planning and financial resource allocation for agricultural services. Thus, from a policy perspective, the findings suggest there is a strong need for strengthening local staff capacities, the formulation of appropriate policies, and the establishment of institutional mechanisms to ensure farmer's participation at the local level planning process, and the prioritization of resource allocation to the agriculture sector to achieve improved agricultural service delivery and greater farmer satisfaction.
... These results, meetings, and demand for service indicators are consistent with farmers' perception of adopting no-till tillage in South Africa [52], satisfaction with extension services in Ethiopia [51], and adaptation to climate change in Ghana [59]. Equally, Joshi and Narayan [73] found that the frequency of extension contact is a significant indicator in the performance measurement of agricultural extension in sustainable livelihoods in India. ...
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Background In this study, we present the current situation and the role of agricultural extension services for farmers and indicates the potential solutions for the optimum effectiveness of these services. Thus, we investigate the vital determinants influencing the farmers’ attitudes toward using agricultural extension services in Ghana and Zambia. Methods In this study, we used a mixed-method research analysis of data from a household survey of 240 farmers and 8 key informant interviews in the Upper West Region of Ghana and the Southern Province of Zambia. Results The significant factors affecting the association of agricultural extension officers with farmers are regular meetings, demand for services and productivity, and the adoption rate of technology. Notably, approaches based on information communication technology indicators include owning cell phones; further, having radio access significantly affects agricultural practices. However, the role of gender, access to credit, and owning a television would influence food safety and nutrition. Conclusions Understanding the critical determinants will provide potential solutions to national agricultural research institutes, private research entities, and policymakers to scale-up the effectiveness of agricultural extension services, particularly in Ghana and Zambia.
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Abstract This paper describes a systematic method that identified constructs and indicators of a measurement model to assess rice farmers' Sustainable Agriculture Potential (SAP). The method used the Rural Livelihood Assessment Framework (RLAF) definition to define SAP's primary constructs. The capital assets defined in RLAF (Human, Social, financial, Physical, and Natural) were then explained using previous Sustainable agriculture (SA) research findings. An initial 130 indicators were framed into five-point Likert scale questions to form a research questionnaire. The questionnaire was initially administered among 64 selected farmers in a dominant rice cultivation region (Mahaweli Block H ) in Sri Lanka. The responses were analyzed using the measurement model analysis technique using the Partial Least Square Structural Equation Modelling (PLS-SEM). Based on this analysis, 87 questions were identified as effective measures of the farmers' SAP. The refined questionnaire was surveyed among 386 rice farmers randomly selected in the same region. The responses were analyzed using the PLS-SEM techniques for each capital asset in the form of measurement models. The analysis proved those 87 questions (indicators) are productive and can explain farmers' SAP compositely. The researcher believes the model will be helpful for future researchers in assessing the strengths of SAP and the nexus between SAP and other variables, such as their ability to adopt more organic-centric farming and resilience to other varying factors impacting their farming. Also, the method used to maximize the variance explained in developing indicators and ruling out the less productive indicators could be insightful for researchers in future studies. Keywords: Capital assets, Formative indicators, PLS-SEM, Rural Livelihood, Sri Lankan rice farmers, Sustainable agriculture
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This paper systematically identifies the constructs and indicators to measure Sri Lankan rice farmers’ Sustainable Agriculture potential (SAP) in the regions of Mahaweli Block H in Anuradhapura district, a dominant rice cultivation district in the country. Insights from Rural Livelihood Assessment Framework helped identify the primary constructs of SAP: The constructs of farmers’ SAP are derived as Human, Social, Financial, Physical, and Natural capitals. The principles of Sustainable Agriculture discussed in modern literature and the various research studies carried out in this domain are insightful to derive an exhaustive list of indicators that might adequately explain the constructs of SAP. The researcher adopted a quantitative descriptive approach, developed a comprehensive set of indicators (130), pre-tested them, and conducted a pilot survey with 64 samples. The measurement model analysis techniques in PLS-SEM helped shorten the Questionnaire with the most productive questions (87). This short-listed Questionnaire was again surveyed in a larger sample space, 386, to attest to their validity further. The study found five constructs and 87 productive questions that can explain farmers’ SAP, and the researcher believes that these compositions of SAP and the indicators will be helpful for future researchers.
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