Innovative tools for the agricultural information system: a conceptual framework

The global food price crises of 2007–2008 and 2010–2011 drew attention to the need for addressing the underlying determinants of malnutrition in low- and middle-income countries (LMICs; Brinkman, de Pee, Sanogo, Subran, & Bloem, 2010; Webb, 2010). Specifically, as the primary source of food and income in LMICs, agriculture received renewed focus. Making agriculture work for nutrition—nutrition-sensitive agriculture—has climbed the international development agenda (Ruel, Alderman, & Maternal and Child Nutrition Study Group, 2013). More recently, given the sharp increase in diet-related chronic diseases underpinned by overweight and obesity in LMICs and the threats of climate change to diets, attention has expanded to leverage food systems to optimize nutrition, health and environmental outcomes (Johnston, Fanzo, & Cogill, 2014). Donors, researchers and implementers mobilized research agendas to invest in understanding how to strengthen agriculture and food systems to realize nutrition outcomes sustainably. Development of conceptual frameworks to aid the investigation of agriculture-food system and nutrition linkages, highlighting multiple direct and indirect complex pathways (Global Panel, 2015; Hawkes, Turner, & Waage, 2012; Johnston et al., 2014; Kadiyala, Harris, Headey, Yosef, & Gillespie, 2014; Lock et al., 2010; Masters et al., 2018). Empirical examination of the linkages between agriculture-food systems and nutrition and the key pathways mediating or modifying these relationships and systematic reviews (Arimond & Ruel, 2004; Girard, Self, McAuliffe, & Olude, 2012; Ruel, Quisumbing, & Balagamwala, 2018). Experimental studies and novel methodological approaches, with improved rigour in testing conventional (e.g., homestead food production) and novel intervention models (e.g., market-based interventions for nutrition; use of participatory videos). These efforts led to widespread recognition of inadequate tools, methods and metrics to study the direct, indirect and dynamic relationships between in agriculture-food systems and nutrition outcomes. There have been several calls to accelerate the development of innovative tools, methods and metrics to underpin the development of a robust scientific evidence base needed to guide policy investments in agriculture-food systems for improved nutrition and health. In response to this demand, several projects and programmes were launched specifically to develop new research methods, including the DFID-funded Innovative Metrics and Methods for Agriculture and Nutrition Actions (IMMANA) programme (Innovative Methods and Metrics for Agriculture and Nutrition Actions [IMMANA], 2018). Research undertaken under IMMANA and others (CGIAR, 2018; Global Dietary Database [GDD], 2014; International Dietary Data Expansion Project [INDDEX], 2018; Sustainable and Healthy Food Systems [SHEFs], 2018) have built on existing theoretical underpinnings and have helped to refine hypothesized pathways, illuminating additional aspects and dynamics between agriculture or food systems and nutrition outcomes, such as food environments, environmental factors and food safety. The Food and Agriculture Organization (FAO) of the United Nations (UN) adopted the High-Level Panel of Experts (HPLE) definition of a food system: "all the elements (environment, people, inputs, processes, infrastructures, institutions, etc.) and activities that relate to the production, processing, distribution, preparation and consumption of food, and the output of these activities, including socio-economic and environmental outcomes" (HLPE, 2017). Agriculture and health are part of the broader milieu of a food system. As such, there has been a proliferation of innovations in programme design and implementation, as well as in metrics and methods and their application. While the body of evidence on effectiveness of food systems to improve nutrition has been recently summarized (Ruel et al., 2018), the portfolio of new methods and metrics has not. It is now necessary to take stock of these developments and plan for the future to support the production of effective and relevant research. Recognition of the multiple pathways through which nutrition impact is achieved brought about new conceptual frameworks, and along with them, new thinking in how to measure the complexity and dynamism within these systems. The innovations that emerged range from new technology to new indices to the application of methods from other fields. New metrics and methods have been developed throughout the pathways (household production, decision-making, income, etc.) linking agriculture and nutrition. In a standard effectiveness map, the row headings are interventions, and the column headings outcomes. In this map, those thematic pathways or domains will be considered the "interventions" through which nutrition is improved. We consider our "outcome" to be tools, metrics or methodological innovations, which are the columns of this map. Some innovations have been widely adopted across settings, and others are still in development. Therefore, each example innovation will be mapped using the studies that pertain to the innovation. Innovations have taken place at every level of measurement (individual, household, national, etc.) and correspond to certain cross-cutting themes. These additional aspects will be coded internally on the map. As an example of technology application at an individual and household level, researchers have utilized accelerometers to measure calorie expenditure in new ways to address intra-household food allocation and gender roles (Zanello, Srinivasan, & Nkegbe, 2017). At a community level, researchers have employed wearable cameras and GIS technology to map changing food environments in urban areas (Schrempft, van Jaarsveld, & Fisher, 2017). A methodological innovation at a sub-national level has been to use Bayesian theory and decision-analysis for making policy that affects nutrition (Yet et al., 2016). More thorough data collection and new indices to capture prices of nutritious foods in markets at the regional level have led to better estimates of cost of nutritious diets in Ghana (Masters et al., 2018). New innovation in this field also includes tools to conceptualize and operationalize food systems, including how to frame and measure cost-effectiveness of complex interventions, which have a range of outcomes (Masters et al., 2018). In this EGM, the columns will be types of innovation or novel application. The aim of the gap map is to articulate and summarize the innovation in tools, metrics and methods that have been created and applied to understand food systems and agriculture-nutrition linkages in the last ten years. We have chosen the ten-year period based on the focus on and funding for agriculture-nutrition linkages that emerged following the global food price crisis in 2007–2008, as well as wanting to focus on new innovations, which, by definition, would no longer be novel if developed more than a decade ago. We also aim to highlight gaps and opportunities for future development. Although the intervention-outcome framework is most common for maps on effectiveness studies, this framework will be organized differently. We will take an approach that considers tools, metrics and methods (types of innovation/application in the columns) for agriculture-food systems-nutrition research (thematic domain in the rows). The map will be organized around a combination of conceptual frameworks that include the definition of food systems offered by the HPLE report on nutrition (HLPE, 2017), predefined pathways to improved nutrition (Global Panel, 2015; Hawkes et al., 2012; Herforth, Nicolò, Veillerette, & Dufour, 2016; Kadiyala et al., 2014), as well as additional themes that have been identified as more research is being undertaken on this topic (Grace et al., 2018; Masters, 2016; SHEFs, 2018) (Appendix APPENDIX A). These conceptual frameworks (illustrated in Appendix A) overlap a great deal. For instance, each highlights the role of on-farm production as a means for direct consumption as well as a potential income source, both which influence food availability and diet quality, and thus contribute to nutrition outcomes. Frameworks 1 (Kadiyala et al., 2014), 2 (Hawkes et al., 2012) and 3 (Herforth et al., 2016) are very similar—in fact the most substantive difference is the visual organization of components. These frameworks include aspects of women's time, income and employment. The same three highlight interacting aspects of care, education or knowledge, as well as overall health as drivers of nutrition outcomes. Each framework also has differences, both in how it is visualized and the content. Each represents "indirect" determinants of nutrition outcomes, such as the role of climate, the environment, policy, governance and culture, inequity, and so forth, but some are shown as an outside layer of influence, whereas some of these are considered within the central framework. For instance, Framework 4 shows the interactions between environment or sustainability aspects and food production, highlighting that human health should always be balanced against planetary health, since they are symbiotic in the long run (Tuomisto et al., 2017). Several highlight important domains that are not equally represented on the other. Frameworks 5 (Masters, 2016) and 6 (Global Panel, 2015) propose the most current thinking about markets and the economic role of nutrition. These support the idea that production will lead to consumption only where, when and for whom markets are missing. The Global Panel Metrics and Methods Framework (Framework 6) puts the food environment as the central milieu into which other dynamics feed, and diet diversity, adequacy and safety as general by-products of that food environment. In contrast, Framework 2 (Hawkes et al., 2012) specifically articulates the subsequent layers of the food environment that progressively lead to nutritional status. We will use all frameworks generally to ensure that the EGM is comprehensive and that the domains within conceptual pathways in agriculture to nutrition literature are represented and categorized logically, while maintaining iterative methods of refining the domains based on search results. Governments, non-government donors, implementing agencies and academia have all made significant investments, both intellectually and financially, in improving agriculture or food systems for nutrition outcomes. This investment has gone beyond scholarship and documentation and taken the form of application and innovation of tools, metrics and methods at every level. Stakeholders have called for a synthesis project on this topic in order to visualize the current portfolio of these developments, strategically plan the next wave of investment and shape the next generation of agriculture-nutrition research. There are no current gap maps on the topic of metrics and methods on the topic of agriculture and food systems for nutrition (or to improve nutrition outcomes). Some mapping exercises have been undertaken on pathways between agriculture and nutrition, namely the 2012 LCIRAH "Current and planned research on agriculture for improved nutrition: a mapping and a gap analysis", which led the way to the IMMANA programme (IMMANA, 2018). The FAO Compendium of nutrition-sensitive indicators also summarizes the most well-established indicators on the subject (Herforth et al., 2016), but does not fully capture innovative tools and methodologies, as well as metrics that are in development currently. Furthermore, to our knowledge, none of these synthesis projects have been systematic or published as a formal EGM, and overall there have been no EGM of tools, metrics, or methodologies; rather most existing gap maps focus on effectiveness studies. The main objective of this EGM is to guide funders and researchers in the most promising areas of innovation within the study of food systems or agriculture to nutrition pathways, and demonstrate their phase of development and other thematic trends. We also will be able to demonstrate where there are gaps in existing innovative tools, metrics and methods that correspond to key domains identified in these conceptual frameworks. Empty cells in the map will indicate where no new methods, metrics or tools either exist or have been developed in the last decade within those domains. Furthermore, we intend that this EGM will then be used to shape future investments in this field, both by pursuing opportunities to take the most promising developments to the next level, and focusing attention on where there are gaps in available tools, metrics and methods. A secondary objective of this EGM is to identify trends in investigation and application that would be suitable for further synthesis. All previous EGMs published to date have been compilations of effectiveness studies, therefore this EGM will be novel in many aspects. We are not aware of any protocols or published EGMs on which to model this project. There are several synthesis reports on this topic (Hawkes et al., 2012; Herforth et al., 2016), but as mentioned previously, none of them are current, systematic or are formal EGMs. We will use published, well-established conceptual frameworks to define thematic domains of agriculture-to-nutrition in order to categorize the identified tools, metrics and methods. Therefore, our "intervention" will be each broad domain on the food systems or agriculture to nutrition pathway. The columns of our map, (outcome in effectiveness maps) will be each item of innovation (tool, metric or method) that has been developed or applied to capture or measure these domains. Limit the search to work published after 2008. Identify completely new tools, metrics or methods that were introduced after 2008 with no previous iterations. Identify tools, metrics or methods that existed prior to 2008 but have been significantly revised or modified since. As a "significant" change or modification is difficult to determine, we will rely on the group or authors' own assertions and explanations, and make an expert judgement as a group when unclear. Identify new, novel or innovative applications of existing tools and methods. This will mostly entail applying these cross-disciplinarily. This will be the most difficult aspect of "newness" to define, and we therefore will also rely on the authors' description and justification, and secondarily make a collective expert decision. Because some of the tools, metrics and methods are in their infancy, while others are globally adopted and have become standard practice, we will code each study based on the current (e.g. in 2019) stage of development of the innovation. We will further code and categorize innovations by several thematic filters (e.g., gender, equity, economics, technology, private-sector engagement, conflict or political fragility), geographical application, and level of measurement. The "intervention" (rows), will be defined using agriculture-to-nutrition conceptual frameworks mentioned previously, divided into "domains" of influence on agriculture and food systems or nutrition, such as household or on-farm production, food policy and governance, or food environments and markets. The columns, or categories of innovations/applications, will be grouped by different classifications of tools (technology application and instruments to capture data on a range of agriculture-nutrition topics), metrics (new indices and measures to quantify agriculture-nutrition linkages) and methods (research design and analytical approaches applied to agriculture and nutrition research). We will code each study related to an item and group the items iteratively once all items have been mapped. We have chosen to do this since some well-adopted innovations will have many papers that use the tool, metric or method, while others will have only a few, and some will apply the tool, metric or method in different ways. Users will be able to see each individual item as well as grouping by tool, metric or method. Traditional EGMs include a quality assessment of each item, such as a risk of bias rating, which are not designed to evaluate tools, methods or metrics. In place of a quality assessment, this EGM will summarize the stage of development or application (explained below). We will add filter codes for certain cross-cutting themes such as gender or private-sector engagement. It will also categorize the measurement level (individual, household, district, national, etc.), and setting or geographical application (Asia, Africa, global, etc.). We also may add other filters as the search progresses. The framework structure is shown in Appendix APPENDIX B. This map will only include tools, metrics and methods that have been applied to agriculture-nutrition pathways in any country at any level: individual, household, community or district, sub-national, national and global. The problem we are considering is any domain that exists on the conceptual pathway between agriculture and/or food systems and nutrition outcomes. These domains have been grouped (through using frameworks and extensive rounds of expert consultation) by broad themes around food production, food safety, value-chains, markets and food environments, food policy and governance, environment and climate, among others. We have organized the domains around broad themes in order to group items with minimal double- or triple-coding, but we do envision that some items will appear in more than one domain. Whenever possible we will select a "primary" domain and use the filters and codes to indicate other aspects of the tools that are cross-cutting, such as gender, technology or economics. The first column lists 12 broad domains, and the second column are examples of what types of work would fit in to these domains. All included tools, metrics or methods must explicitly relate to either agriculture/food systems, or to nutrition. Any tools, metrics and methods that are not related to either agriculture/food systems or nutrition will be excluded. Most of the domains could be measured at various levels (individual, national, global, etc.). We will not differentiate in the domains, but rather in the internal coding of each tool, metric or method innovation. As the initial results are identified, we may refine these domains and add sub-domains using an iterative methodology. Specifically, we propose the following overarching categories based on the conceptual frameworks discussed previously (Table 1). The domains of food safety, food environments and economic evaluations each have systematic reviews on methods and metrics. We will include the items that are included in those reviews and also use these items to test the framework. The primary "outcome", of the gap map (i.e., the columns in the map) is the innovative item (tool, metric or method) created and applied to studying and describing the broad agriculture to nutrition pathways. We will define "tool" as is a vehicle or an aid to collect information and data (e.g., a survey module to collect data required to compute an index or a piece of technology). "Metrics" will be defined as the parameters (measures) or indices used for measurement, comparison or tracking performance (e.g., disability adjusted life years; household dietary diversity score and Women's Empowerment in Agriculture Index [WEAI]). We define "method" as the process and approach involved in a systematic inquiry of relationships between agriculture, nutrition and health and generally refer to study design or application of an analytical method to this topic (e.g., impact evaluations using various types of counterfactuals, pathway analyses, decision analyses). Several types of "innovation" are described above. We will identify each tool metric or method and group them together once identified. Some methods or tools will have slight variation in their application or analysis, but we will group these logically together as an item if the construction of the item is similar. We will include all of the studies on the map. Each item might have multiple innovative components that fit distinctly within the categories of tools, metrics or methods. We propose that these will not be exclusive, rather the appropriate component of a paper or project will be categorized accordingly, and the total number of items summarized separately. In order to determine what is substantial enough for inclusion as a separate item (rather than a much smaller exploratory innovation and we will use the published or study considering only primary and secondary We will group tools, metrics and methods into the following with some examples in the column (Table a tool, metric or method developed or applied definition in or since 2008. In published and/or as well as projects from that tools, metrics and methods in development. In any for the of and/or used to quantify or a potential between agriculture or food systems and nutrition. This will be defined by the tool, metric or method being related to either the broader agriculture field, food systems as defined in the Panel of Experts (HPLE) or the broader nutrition field, since several methods and metrics used to study this are only explicitly to one of the pathway. Nutrition or nutritional on the of the pathway will be including all of malnutrition diet-related chronic of nutrition measurement diets, or diet-related diseases or diet-related will be interventions to improve nutrition and their pathways to the influence of and food on nutrition; governance and policy through which agriculture and nutrition are and between climate, and/or and nutrition at a and so that have been to agriculture, food systems and nutrition pathways, as long as explicitly in to these pathways and the as new, novel or For and and or and metrics or methods not applied to the domains that agriculture, food systems and nutrition, as explicitly defined by the HPLE or the conceptual frameworks included in the metrics or methods developed or applied prior to 2008. with no in studies. the are for production, or they will be the are as a for or models for general (i.e., if the to or they will be excluded. studies not explicitly related to production, or other related themes. the for studies, if the are specifically mentioned in the of agriculture or if studies, they will be the are a model of general or not mentioned in to they will be excluded. nutrition. nutrition. the paper is related to nutrition and nutritional food for diseases (e.g., or as etc.) will all be excluded. The gap map will include primary research of any as certain study may in fact be an innovative method of application to study the agriculture-nutrition will be excluded. Study types that may demonstrate new innovations or novel applications could include a new study standard study using new or innovative tools, metrics or methods, or studies specifically or a new tool, metric or method. These would therefore as a primary study describing how the approach or design is a a or guide for a new or a developed impact or an impact using well-established study but using new tools or metrics. We will use the described to determine what is considered or (Table We will include research in the EGM as long as it within the agriculture/food systems to nutrition framework and the inclusion and could be undertaken as part of a or be Traditional methods such as focus group or individual will have to be innovative or applied in new ways to be considered for this documentation of the food environment through participatory using such as to or a new within a survey are all examples of innovation in methods that will be included in the Any innovation or application of tools, metrics and methods place will be could be from a country or or they could be applied with to LMICs approaches, etc.). We will include studies and identified through expert and We will a comprehensive and project search that includes with search in Appendix APPENDIX with in Appendix APPENDIX We will also search various project and research and key and in the of key both of research and International Research Research for Development FAO IMMANA The impact and since The evaluations Development The of the Nutrition and The of the The of the The The key we will use for tracking et Global Panel Hawkes et Herforth et Kadiyala et and et et Some included studies and reports We will use a method of researchers to search and then on and the first of with a or a decision in the of For the search we will use with by a We do not plan to use any or The in with the IMMANA will and an to the initial and to the inclusion and and further We will then the code the projects and the coding for stage of innovation or application, which will a quality assessment in this of innovation or application in development and or internal and effectiveness and and widespread application Global or geographical application global, etc.) filters will be used to identify cross-cutting which will not have (e.g., cost of dynamics and be about or about gender in and health gender women's (e.g., The filters categories will be applied if the of the item specifically the of the item to that or the research item is to a The same research in of the search and will the coding of these filters and which will have been through with subject and a one but may also be modified once

With this study, it is aimed to determine how effectively the farmers of 19 Mayıs district of Samsun province use the Agricultural Information System (AIS), their usage habits of internet and social media, the possibilities and the reasons that prevent these opportunities in today's widespread Agricultural Information System. The research is considered important in terms of the formation of an Information Society for the producer and the farmers' ability to use AIS in the digital environment. The primary data obtained from the survey studies conducted with 105 agricultural producers in 38 neighborhoods in 19 Mayıs district of Samsun province constituted the main material of the study. As a result of the studies and analysis, it was determined that 71 of 105 producers surveyed in 19 Mayıs district use AIS, and 34 producers do not.In addition, it was determined that 64 of the participants used the Agricultural Monitoring and Information System, while 41 people did not. It was observed that the participants with a low average according to the survey results in the research area were aware of AIS, but expressed that the internet was confusing in its use, lack of time and trust problems. It is revealed that AIS is a set of methods that will enable not only farmers but also public institutions and private users to access information in the easiest way and that it positively affects the lives of producers. AIS is of great benefit in conveying information to producers, public officials and politicians. From this point of view, the importance of making new regulations and further developing the system in order to use AIS effectively and efficiently is understood once again. These improvements should be made both on the system basis and on the education and internet access of the farmers using the system. For the development of the country, it is very important that our producers are equipped with information and adapt to the digital environment. For this reason, trainings should be given, seminars should be organized and studies should be carried out in order for agricultural producers to gain sufficient skills in the internet and digital environment.

Information about the operations and production capacity of agricultural producers, on the one hand, and knowledge of how to integrate existing databases related to this sector at the micro and macro levels, on the other, can influence agribusiness policy adjustments and the creation of policies that will have the intended effects. Information exchange among government agencies, institutions, farmers, and other agricultural sector participants fosters greater understanding and expedites the settlement of issues impacting agricultural producers themselves. A conceptual framework for the agricultural industry's information system is presented in this article. Through the analysis of farm operations and based on expertise framework, the agricultural sector aims to promote the industry's expansion in a comprehensive and encompassing manner. This indicates that since they are the fundamental building blocks for creating a sizable database in this field, any organisations with information access ought to be included. When information from agricultural holding activities is combined with data from other sources, it gives agricultural producers a strong foundation for decision-making.

This chapter provides an introduction to agricultural and farm management information systems. This chapter provides an overview of the components, subsystems, processes, and operations in agricultural information systems. This chapter also covers the impact of these systems in improving the efficiency, and productivity of farm output. This chapter introduces several technologies related to the use of information systems in agriculture, including agricultural information systems (AIS), farm management information systems (FMIS), e-agriculture, and precision agriculture. This chapter introduces state-of-the-art technologies used in agriculture in the current context apart from providing an introduction to the use and adoption rates of these information systems. This chapter concludes with a brief discussion on the issues facing the adoption and implementation of agricultural information systems and presents some of the key issues that decision makers need to take to improve the acceptance and use of these information systems.

In order to promote the application of the Internet of Things (IoT) technology in the agricultural product circulation system and to improve the agricultural product trading efficiency in China, first, the IoT technology, IoT industrial system, and agricultural information system based on the IoT technology are theoretically expounded; then, with H Company as an example, the intelligent sensor and Radio Frequency Identification (RFID) are taken as the core part of the sensing equipment of the company’s agricultural product circulation information system, the Wi-FiZigBee network is selected as its intelligent sensor network layer, and ZigBee, PAN, LAN, and WAN are used as the technical support of the system to analyze the operation environment of the system. The results show that the operation speed and average signal coverage of the system are higher than those of the agricultural product circulation information system without IoT technology; from 2015 to 2019, the proportion of H Company’s investment in agricultural science and technology in the total investment increases year by year, reaching 90% in 2019, and the proportion of the H Company’s agricultural circulation income in the total income also shows an increasing trend. The agricultural product circulation information system can improve the agricultural product trading efficiency based on the IoT technology.

Information and communication technologies (ICT) in general and information systems in particular help the decision-making process, increase market and price information, impact the effectiveness of using objective resources such as land, workforce, or capital with evident managerial and profitability effects. The use of information systems in agriculture nowadays represents an opportunity as well as a significant development effect in agriculture in our country and for the improvement of quality of life in rural areas. Our country represents one of the countries where the use of ICT has significantly increased in recent years, although the economic infrastructure and level of knowledge mastered by individuals and businesses (especially in agriculture and rural areas), has been inadequate. Despite the extensive information provided through the internet and social media in general, information networks and platforms, communication and interaction for the agricultural economy sector are still at an early stage of development in our country. Based on the level of information systems usage in rural areas and the structural problems that economic stakeholders and entities face in the Albanian terrain, the role of ICT in the economic activity in these areas remains weak and with invisible effects.

Market information availability is a basic requirement for countries’ economic growth. Market information can be from different sources and need to be addressed to different stakeholders across a different locality. It needed to be made available for public access too. The content will also be updated throughout time. More than 80% of the Ethiopian population life is based on agriculture. The reality is there is no agricultural information system and platform deployed in the country except the (ECX) dashboard, deployed in local markets. Actually, the information infrastructure, such as the Internet, is rarely available. The only way the larger public can get access to the agricultural information is only through call and SMS service. So, in the mobile crowdsourcing system for an agricultural market information system, anyone in the system can access summarized and updated information. The aim of the proposed system is processing and providing aggregated and updated agricultural market price information to stakeholders from crowd data of SMS. The proposed system has five basic components: SMS manager component, information extraction component, data analysis component, crowd management, and request management component. As a means of evaluating the proposed architecture, we have developed a prototype that implements the components of the proposed architecture. It is also tested using sample SMSs. Evaluation result showed that the proposed architecture can provide a mobile-based crowdsourcing system for agro-market information for low-end mobile phone users with price aggregation performance of 80%.

The study investigates how the richness of social media technologies impact on their use for knowledge sharing among the primary knowledge actors in the Agricultural Knowledge and Information Systems. The overall research is based on the amalgamation of the Agricultural Knowledge and Information Systems (AKIS) model, Nonaka’s SECI model, and the media richness theory (MRT). The AKIS model was applied to discover how the use of web 2.0 technologies for knowledge sharing could enhance interactive communication among the primary knowledge actors in Agricultural Knowledge and Information Systems. The SECI model was used to identify the different stages involved in the creation and sharing of knowledge among the knowledge actors and the MRT was also employed to assess how the richness of the web 2.0 technologies could affect the interaction among the knowledge actors through the various SECI processes involved in the knowledge sharing process. The study proposes that there exists a positive correlation between the tacitness of knowledge and the richness of media used for sharing knowledge, which can be used as the basis for selecting the appropriate social media technologies for the different modes of the SECI processes for effective knowledge sharing among knowledge actors.

Various agriculture-based information communication technologies (ICTs) are used throughout the world with various degrees of sophistication. In this paper, we have analysed these ICTs and then suggested a holistic and comprehensive prototypic agricultural ICT model. Until now, agricultural information systems have been implemented using various technologies such as radio, internet radio, internet, wide area networks (WANs) and mobile phones in various developed and developing countries. We have examined examples of such ICTs implemented in developing countries including India, Bangladesh, Sri Lanka, African and Latin American countries. Some developed countries, such as Australia, have nationwide ICTs spanning a spectrum of fields, including agriculture. After examining these ICTs, we have developed an agricultural information system which uses many software and hardware technologies and spans the whole agricultural system, from the scientists and policy-makers to the common farmers and from the national level to the village level. This information system makes use of the latest technologies, including DSS, intelligent systems, data-mining, data warehousing, and high-performance computer (HPC) grids. This paper details seminal research done in the development of an architectural model for implementing a high-end agricultural information system. This architectural model can be used to develop a more detailed framework.

Agriculture is the back bone of Ethiopia’s economy. Despite the strength and volume of agriculture related information and training available through Ethiopia’s vast public extension system, ensuring farmers receive up-to-date data and knowledge in a timely, complete and quality manner remains a great challenge. The existing practice for delivering agricultural information through agricultural extension officers, farmer-to-farmer visit and mass Medias couldn’t satisfy the information needs of rural farmers. This is attributed by few numbers of extension officers, budget bottle neck and absence of electricity and network. This paper presents a SMS based agricultural information system (SMSbAIS) aimed to solve such challenges in agricultural sector. The SMSbAIS was developed based on a conceptual framework, developed during the course of this research, is used as a platform where rural farmers and agricultural extension officers can get agricultural knowledge service, request agricultural information and supply any information that demands the intervention of higher agricultural officers. It helps users not only to request for agricultural information; it also used to deliver such information to the hands of users via their mobile phones. The system is developed using Rapid Application Development (RAD) methodology with a series of iterative development and testing is done based on System Usability Scale (SUS) method. Testing and evaluation is targeted the systems usability, accuracy and performance. Therefore, it was found that on the SUS scale that ranges from 0 to 100, the system scored 87.6 with feedback from 20 users. The Query Understanding engine (QUE) accurately translated 90% of all incoming user requests. The mean average response system time is found to be 3.34 s. These results show that problem of lack of appropriate and easily accessible agricultural information can be solved using a system like the one developed in this research based on a framework that seeks solutions to challenges faced in accessing agricultural information in rural community.

In order to study the role of information technology in the promotion of agricultural development and information in today's social and economic development of the most important strategic impact, on the basis of modern management, this paper investigates and studies the existing agricultural machinery management information system through the application of grey theory, information system engineering, information system utility, and other theories. The results show that a new agricultural machinery equipment management information system is developed through PHP and Mysql databases, and the system data is summarized and analyzed to obtain agricultural machinery management information. Through the experiment, the authors found that ordinary users can inquire about agricultural policies and science and technology through the internet and can also inquire about the scientific and technological schemes of various agricultural development processes.

Agriculture and food systems are important determinants of nutrition and consequent public health. However, an understanding of the links among agriculture, food systems, nutrition, public health and the associated policy levers, is relatively under-developed. A framework conceptualizing these key relationships, relevant to a range of country contexts, would help inform policymakers as to how agriculture and food policy could improve nutrition and public health, particularly in low- and middle-income countries (LMIC). The objectives of this paper are: to present a conceptual framework, relevant to a range of country contexts and focused on the policymaker as the user, which depicts the key relationships among agriculture, the food system, nutrition and public health; and to describe how the framework can be used for understanding the impacts of agriculture and food system policies on nutrition outcomes. Existing conceptual frameworks, highlighting the relationships among agriculture, the food system, nutrition and public health (n = 37) were identified, reviewed and categorized, based on the key themes they address. Building on this analysis and synthesis a conceptual framework was developed that assists in identifying associated policy levers and their effects on elements of the framework. The end product is a conceptual framework that presents key domains linking agriculture and food systems to nutritional outcomes and public health. The framework is relevant to a range of contexts, for example low-, middle- and high-income settings; and to policymakers wishing to examine the potential direct and indirect impacts of agriculture and food system policies.

The development of agriculture, and the reform of the rural economy in China in the last decade has brought about great changes, which have raised increased demand for information and highlighted the madequate performance of existing agricultural library and information systems. An effec tive system calls for systematic allocation of information re sources. and efficient information dissemination, which implies sound information policies to ensure cooperation, resource sharing and networking among libraries and information services. A critical overview of China's agricultural library and information systems is given, with particular emphasis on the future importance of networking.

The study investigates how the media richness of web 2.0 technologies impact on their use for knowledge sharing among the primary knowledge actors in the Agricultural Knowledge and Information Systems as evidenced from the Cocoa Industry in Ghana. Three theories- Agricultural Knowledge and Information Systems (AKIS) model, SECI model, and the Media Richness Theory (MRT) were combined to establish that there exists a positive relationship between the tacitness of knowledge and media richness which can be used as the basis for selecting appropriate social media technologies for different types of the SECI processes for effective knowledge sharing

In this paper, after analyzing the importance of constructing agricultural product logistics information system and features of multi-agent, combining agent technology and logistics technology, the agricultural product logistics information system based on multi-agent is studied, and the model of this system is given, and coordination mechanisms between agents are also discussed. Moreover, implementation scheme of the system is introduced. It is intelligent, reconstructed easily and has strong ability to interact, it can provide some basis for developing agricultural product logistics information system further.