THE POTENTIAL OF MOVING PICTURES DOES PARTICIPATORY VIDEO ENABLE LEARNING FOR LOCAL INNOVATION?

N° ISBN - 978-2-7380-1284-5International audienceLearning is essential for local innovation and enhancing the ability of the rural clients to discover new solutions to prevailing challenges. Equally, the growing complexities of the challenges in the theatre of agriculture and rural development require multi-actor learning process. Participatory communication through face-to-face interaction remains an important approach to support local people's innovation capacity. Is there any mean other than face-to-face interaction that enables learning for innovations? Video has been used for several decades, however, in most cases instrumentally as a mass media for expert information dissemination. In recent years the interest in the alternative use of video, mostly known as participatory video, has grown. This study attempts to understand the potential of participatory video to support learning for local innovation by reviewing available literature about the cases of participatory video in the field of agriculture and natural resource management. A deductive coding approach was employed in order to identify the potentials of participatory video. The documented cases we found in the literature suggest that participatory video has a substantial role for both vertical and horizontal flow of local knowledge and information in a multi-actor setting. It creates a ‘safe space' for communication where different actors are able to articulate their perceptions. What follows, actors get an opportunity for reciprocal learning process. Participatory video facilitates communication for the marginalized segment of developing nations in Asia and Africa to represent their knowledge and skills and to link these to other knowledge bodies such as scientific, formal, managerial and bureaucratic. Participatory video stimulates reflection and experimentation by creating new impetus for learning within and across stakeholder (actor) groups. Nevertheless, potentials of participatory video depend on careful analysis of social competencies of facilitators, institutional ambience and role of intermediaries and facilitating organizations. We also proposed future research angles on these issues

Determinants of Willingness-to-Pay A Premium Price for Integrated Pest Management Produced Fruits and Vegetables in Trinidad

Overuse of pesticide in crop production poses enormous challenges to the health of farm families, consumers, and the environment. Integrated Pest Management (IPM) is an ecosystem approach to crop production that combines different management strategies and practices to grow healthy crops and minimize the use of pesticides. As a result of increasing awareness, education and per capita income, there is an increasing concern for food safety and demand for safe products among consumers of high-income countries. Consequently, this study was conducted among 266 randomly surveyed consumers of an affluent Caribbean country, Trinidad to ascertain the factors influencing consumers Willingness-To-Pay (WTP) a premium price for IPM grown-fruits and vegetables. The consumers responses for the dichotomous question, Would you be Willing to Pay an additional cost of 10% for the IPM produces from the current market prices? were analysed using Binary logit regression model. Results indicated that females ageing over 26 years and having children, those with higher annual income and higher level of education were all most likely to pay a premium to obtain IPM grown fruits and vegetables. Willingness-to-purchase IPM produce was found to increase with income, education and age. The findings of this study are promising to those developing marketing strategies, besides enabling the producers to understand that producing fruits and vegetables through IPM would fetch them premium

Higher Order Markov Structure-Based Logistic Model and Likelihood Inference for Ordinal Data

Azzalini (1994) proposed a first order Markov chain for binary data. Azzalini’s model is extended for ordinal data and introduces a second order model. Further, the test statistics are developed and the power of the test is determined. An application using real data is also presented

Zero Truncated Bivariate Poisson Model: Marginal-Conditional Modeling Approach with an Application to Traffic Accident Data

Abstract A new covariate dependent zero-truncated bivariate Poisson model is proposed in this paper employing generalized linear model. A marginal-conditional approach is used to show the bivariate model. The proposed model with estimation procedure and tests for goodness-of-fit and under (or over) dispersion are shown and applied to road safety data. Two correlated outcome variables considered in this study are number of cars involved in an accident and number of casualties for given number of cars

Impact of farmers’ climate risk perception and socio-economic attributes on their choice of ICT-based agricultural information services: empirical evidence from Pakistan

In Pakistan, research on information and communication technologies-based agricultural information services (ICTbAIS) have gained significant attention owing to the overwhelming population of smallholder farmers (whose information needs are unable to be met by the conventional extension services) and the increasing incidence of climatic risk. This study is, therefore, conducted in the Punjab province of Pakistan (mixed cropping region) to explore farmers’ use of ICTbAIS and understand the relationship between farmers’ socio-economic attributes, risk perception, and choices of ICTbAIS. A sample of 480 farmers was drawn using a multistage sampling approach, and farmers were interviewed face-to-face. To analyze the dataset, a multivariate Probit (MVP) model was employed. The results show that Television (TV) and mobile-based advisory and mobile-based consultations appeared to be the most used ICTbAIS, followed by radio and internet-based advisory. The estimates of the MVP model showed that farmers’ age, education, farmland, tenancy status, off-farm income, and climate risk perception are significant determinants of their choices of ICTbAIS. Based on our results, we suggest policymakers and extension agencies to improve the content of ICTbAIS and make efforts for the awareness and training of farmers regarding the use of contemporary ICTs

Rice farmers’ perceptions about temperature and rainfall variations, respective adaptation measures, and determinants: implications for sustainable farming systems

In Pakistan, climate change is adversely affecting agricultural production and undermining the food security and subsistence of millions of farm households. Farmers’ understanding of climate change and their adaptation strategies can serve as a useful step to help minimize climate risks. This study explores farmers’ perception of and adaptation strategies to climate change and their determinants in the rice-growing zone of Punjab province, as this region of the country is highly vulnerable to climate change impacts. The multistage stratified-random sampling method was used to select 480 farmers from the four rice districts of the region, and data were collected using a structured questionnaire. Logistic regression and contingency tables are used to analyze the determinants of farmers’ adopted strategies and adaptation extent (number of adopted strategies). Results show that farmers perceived significant changes in the climate, including the rise in average summer and winter temperatures and the decline in overall precipitation. The study further found that farmers’ adopted adaptation strategies include supplementary irrigation, adjustments in rice cultivation dates, crop diversification, use of climate-smart varieties, better fertilizer management, and farm resizing. Logit model showed that farmers’ age, primary occupation, income, landholding, access to irrigation, credit, climate information, and farm advisory appeared to be the significant determinants of their adaptation decision. The adaptation extent strongly correlates with farmers’ education and access to climate information and credit services. Based on these findings, this study suggests the relevant institutions improve farmers’ access to irrigation water, credit, farm advisory, and climate information to improve their adaptation extent and hence resilience of the rice-farming system

A generalized right truncated bivariate Poisson regression model with applications to health data.

A generalized right truncated bivariate Poisson regression model is proposed in this paper. Estimation and tests for goodness of fit and over or under dispersion are illustrated for both untruncated and right truncated bivariate Poisson regression models using marginal-conditional approach. Estimation and test procedures are illustrated for bivariate Poisson regression models with applications to Health and Retirement Study data on number of health conditions and the number of health care services utilized. The proposed test statistics are easy to compute and it is evident from the results that the models fit the data very well. A comparison between the right truncated and untruncated bivariate Poisson regression models using the test for nonnested models clearly shows that the truncated model performs significantly better than the untruncated model

Analysis of repeated measures data

This book presents a broad range of statistical techniques to address emerging needs in the field of repeated measures. It also provides a comprehensive overview of extensions of generalized linear models for the bivariate exponential family of distributions, which represent a new development in analysing repeated measures data. The demand for statistical models for correlated outcomes has grown rapidly recently, mainly due to presence of two types of underlying associations: associations between outcomes, and associations between explanatory variables and outcomes. The book systematically addresses key problems arising in the modelling of repeated measures data, bearing in mind those factors that play a major role in estimating the underlying relationships between covariates and outcome variables for correlated outcome data. In addition, it presents new approaches to addressing current challenges in the field of repeated measures and models based on conditional and joint probabilities. Markov models of first and higher orders are used for conditional models in addition to conditional probabilities as a function of covariates. Similarly, joint models are developed using both marginal-conditional probabilities as well as joint probabilities as a function of covariates. In addition to generalized linear models for bivariate outcomes, it highlights extended semi-parametric models for continuous failure time data and their applications in order to include models for a broader range of outcome variables that researchers encounter in various fields. The book further discusses the problem of analysing repeated measures data for failure time in the competing risk framework, which is now taking on an increasingly important role in the field of survival analysis, reliability and actuarial science. Details on how to perform the analyses are included in each chapter and supplemented with newly developed R packages and functions along with SAS codes and macro/IML. It is a valuable resource for researchers, graduate students and other users of statistical techniques for analysing repeated measures data

Exploring the Adoption of Decision-Support Tools in Ontario Rainbow Trout Farming Using SWOT and AHP Analysis

Decision-support tools (DSTs) are gaining traction in various industries, including agriculture, to enhance productivity, optimize resource utilization, and improve overall farm management. In the context of rainbow trout farming, two DSTs, AquaManager, and AquaOp Farm Management System, have emerged as potential tools to address the challenges faced by Ontario-based producers. This study aims to investigate the potential adoption of these two DSTs by employing the Strengths, Weaknesses, Opportunities, and Threats (SWOT) and Analytic Hierarchy Process (AHP) methods. The SWOT analysis will provide a comprehensive overview of the internal and external factors influencing the adoption of AquaManager and AquaOp. This includes strengths such as cost-effectiveness, data integration capabilities, and user-friendly interfaces, as well as weaknesses related to technical complexity, initial investment costs, and reliance on internet connectivity. Opportunities include the increasing demand for sustainable and efficient aquaculture practices, government support for DST adoption, and the potential to improve farm profitability and environmental sustainability. Threats include privacy concerns, compatibility issues with existing farm systems, and the potential for cybersecurity risks. The AHP will be employed to systematically assess the relative importance of the various SWOT factors and evaluate the overall suitability of AquaManager and AquaOp for Ontario rainbow trout farmers. This involves pairwise comparisons of factors based on their impact on the decision-making process, allowing for a clear prioritization of factors and identifying critical success factors for successful DST adoption. The findings of this study will provide valuable insights into the factors influencing the adoption of AquaManager and AquaOp in Ontario rainbow trout farming. This information can be utilized to develop targeted strategies to promote DST adoption, enhance farm performance, and contribute to the sustainability of the Ontario aquaculture industry

Agricultural Extension Agents' Use of Learning-Based Extension Methods in Trinidad and Tobago

Abstract: Agricultural extension agents are highly credited for their roles of providing advice to farmers and supporting their learning and decision-making to improve livelihoods. The use of appropriate methods to promote learning in developing countries, including Trinidad and Tobago, has often been highlighted as a development priority. Nevertheless, agricultural extension agents encounter difficulties in applying new competencies. Understanding and utilising appropriate methods based on farmers’ learning needs is critical. This study sought to investigate extension agents’ use of learning-based extension methods. A survey was conducted with 106 extension agents. Descriptive statistics and logistic regression analysis were used to analyse data. The findings show that male agents prefer Plant Clinics and Farmer Field School learning methods. Social influence and networking among organisations had a significant influence on the use of Discovery Based Learning methods. The positive influence of social pressure motivated the agents. The study recommends supporting facilitative conditions through a coordinated programme and to focus on farmers’ learning as a critical consideration for improving the use and impact of learning-based methods   Keywords: Learning-based methods, agricultural extension, extension agent, Trinidad and Tobag