Analysis pipelines tailored to the needs of a particular community, hosted through that community’s database, allow researchers to upload, search and visualize private data and public data, select these data and parameterize an association mapping workflow and execute that workflow locally. In order to execute the analysis remotely, data will need to move efficiently from the database to a remote analysis platform.Scientists often want to discover all that they can about a particular entity , but the data are distributed across multiple resources, many of which may be unfamiliar. Each data element on its own is not large, but the total space to be searched is. A hypothetical workflow is as follows: a researcher who works on one species comes to a participating database with a sequence of interest, wanting to find out what biological functions their sequence might be involved in. The researcher identifies homologous sequences in the new database by running BLAST. The database converts the BLAST results to an exchangeable token and queries other databases for information about orthologs. The product of these requests could be as simple as a gene name/symbol and a URL to point the user to the data display at the external database, or could also include provenance and database information for attribution, sequence, publications and many other types of information. For data discovery to work, databases with relevant data and compatible APIs must be discoverable and well documented, and a method should be in place to track usage across different services.There are several mechanisms for outreach to researchers. The most common form of outreach is meeting and conference attendance. With a large number of researchers at meeting and conferences GGB databases can use these opportunities for workshops, presentations or a database booth. GGB database brochures can be handed out during the meeting and conferences. However, there are a number of researchers that are unable to attend meeting and conferences so it is important that GGB database also use other forms of outreach. These include newsletters, mailing lists, blog posts and social media to inform researchers about new tools or data, webinars, workshops and videos.

These forms of outreach can be used together to reach a broader audience. Using social media during conferences and meetings with the appropriate hashtag can send information about new tools and data to researchers who cannot attend the conference. A prime example of this is the Plant and Animal Genome Conference, which has a strong social media presence.Many online resources and databases do not mention the people on their teams and only provide an anonymous contact form.Being anonymous creates a barrier to communication, and if contact/feedback forms don’t generate a response, there is no further recourse for the researcher to get help. Providing individual staff contact information and even photographs makes it easier for researchers to target questions to the appropriate person. Photos can enable researchers to find curators at meetings, and in general encourage communication by putting, literally, a human face on the GGB resources. Building in dedicated time at workshops for a ‘meet the team’ event, well advertized in advance to the research community, is also recommended to increase engagement opportunities.Overcoming the challenge of reliable data submission will require communication among representatives from the appropriate journals, GGB databases and funding agencies to establish guidelines and an easy-to-submit and police system for researchers and the journals/funding agencies and databases. This would likely be best initiated through an inter-agency sponsored workshop, followed up by regular meetings and assessment of effectiveness. Such a workshop could also develop ways to ensure journal publishers and editors are aware of all relevant GGB databases so they can direct authors of each accepted paper to the proper repository, nomenclature clearing house etc.

Providing access to centralized cyber infrastructure where databases, journals and funding agencies could sign off on successful data submission for projects would help make this process easier for all parties and ensure accountability.The GGB databases that currently comprise the AgBioData Consortium were created to serve the needs of researchers for access to curated and integrated data and analysis/visualization tools to aid scientific discovery, translation and application. The funding for these databases, however, is limited and not stable. Maintaining these resources in the longer term so that invaluable data are kept up-to-date and do not get lost is a major issue facing almost all AgBioData databases, their researcher communities and funding agencies.AgBioData databases are supported through a variety of sources. Generally these fall into one of four categories: primarily supported through line-item government funding, such as the USDA-ARS databases MaizeGDB, SoyBase, GrainGenes, Legume Information System and GRIN; primarily supported through competitive federal grants, such as TreeGenes, Hardwood Genomics, Gramene, Planteome, Solanaceae Genomics Network and Araport; supported through a combination of competitive federal grants, commissions and industry, such as the Genome Database for Rosaceae, AgBase, PeanutBase, AnimalQTLdb and CottonGen; and supported primarily through a user subscription model, such as TAIR. With long-term government funding, the USDA-ARS databases enjoy the most stable financial support of the AgBioData databases. They typically represent high-value commodity crops serving a large research and industry community. While the level of support provided by USDAARS generally allows for continuation of base activities and curation, it typically does not provide resources for technical innovation or more resource-efficient systems to be implemented. For these, funding through competitive grants is increasingly necessary,nft system as in the case of the NSF funded Legume Federation award. At the other extreme lies TAIR, which after a phased withdrawal of support by NSF, successfully implemented a subscription-type funding model under a not-for-profit organizational structure.

As the model plant for functional genomics, TAIR also has a large user community making this funding option more feasible to implement than for the databases represented in categories 2 and 3. Many of the AgBioData databases have reported willingness of the scientific stakeholders to budget some funds in their grants to support data deposit and access to their community databases, similar in how they budget for peer reviewed, open access publications costs. Unfortunately, most of the databases do not have organizational structures or processes that would allow them to accept these funds.How can studies of agricultural systems and the ways that people interact with foods they produce, eat, and discard lead us to new understandings about social relations in the past? How do labor roles, gender relations, and status-based inequalities relate to these types of interactions? This dissertation addresses these themes through the lens of food ways in the prehispanic Moche Valley of north coastal Peru. The Peruvian north coast witnessed a profound series of social and political changes during a time period that archaeologists refer to as the Early Intermediate Period, or EIP , with far-flung consequences for members of various social standing, from rural households to political centers. The EIP was marked by an increase in political complexity, with clear shifts in settlement and site reorganization accompanied by an increase in social stratification . These cultural and political changes occurred in a vertically compressed environment that also witnessed periodic El Niño events, which had significant and varied impacts on people’s subsistence practices. Indeed, substantial changes in elevation over the relatively short distance from the coast to the highlands, in the Moche and neighboring river valleys, create different micro-environments within close proximity to one another. Fertile interande an valleys have constituted a prime interaction zone between people of the highlands and the densely populated Peruvian coast, a contact dynamic that initiated in prehistory and continues today.The beginning of the EIP, which includes the Salinar and Gallinazo phases, witnessed the abandonment of earlier ceremonial centers; population increases and expansion of irrigation systems; political fragmentation and the appearance of formal fortifications and settlements in defensive locations; and cooperation and conflict between coastal and highland groups and among polities of various coastal valleys . Between approximately 300 and 800 A.D., the iconic Moche culture flourished on the Peruvian north coast.

The large adobe pyramid complex of the Huacas de Moche was constructed, accompanied by the emergence of a new regional political economy in which Moche rulers exercised significant economic, military, and ideological power over the population of the Moche and adjacent valleys. How did these periods of profound social change affect the prehispanic residents of the Moche Valley in terms of gender relations, status, and the organization of labor in ancient rural households? Foodways data provide a critical lens for examining these issues. Foodways represent a fundamental axis along which identity is constructed and maintained, and are increasingly recognized as having played a prominent role in the emergence of social hierarchies and the negotiation of status and power . In this dissertation, I incorporate archaeobotanical, environmental, and ethnohistorical evidence to address changes in food production, processing, and consumption during the EIP, a period that included the consolidation of the Southern Moche polity, one of the largest and most complex pre-Columbian political systems in the New World. Conducted inconjunction with MOCHE, Inc., a 501c3 nonprofit dedicated to protecting archaeological sites through community heritage empowerment, this project involved a large-scale comparative analysis of paleoethnobotanical data sampled from five EIP habitation sites that span the period of political transformation and state formation in the Moche Valley. The data presented in this dissertation derive from three major projects conducted in the Moche Valley in collaboration between North American and Peruvian archaeologists since 2000: the Moche Origins Project , directed by Brian Billman and Jesus Briceño Rosario ; el Proyecto de Evaluación Arqueológico con Excavaciones en las Lomas de Huanchaco , directed by Gabriel Prieto and Victor Campaña ; and the Galindo Archaeological Project , directed by Gregory Lockard and Francisco Luis Valle . I employ diachronic and spatial analyses of archaeobotanical data from 225 soil samples recovered from five domestic habitation sites excavated within the contexts of these projects to address key issues that have largely remained untested with direct subsistence data. Through these analyses, I trace changes in food production and wild plant food collection during the EIP, considering issues of agricultural intensification and the resulting impacts on labor relations, gender roles, and social inequality for the pre-Columbian inhabitants of rural households in the Moche Valley. The question of scale looms large in this dissertation. The Moche civilization of northern Peru is one of the best-known and most intensely studied archaeological cultures of the ancient New World. The ancient Moche have captured the imagination of scholars and the public alike, characterized by a series of elaborately decorated temple complexes, wealthy elite burials, and exquisite ceramics found over ten river valleys on the desert coast.

In the field study mentioned above, Kumar and Kumar found that understory light transmittance for mixed coconut+multipurpose tree stand ranged between 6 and 75% of that in the open, depending on the time of the day, tree species involved and planting geometry.According to Thomas et al.,4x8ft rolling benches only around25% of the land is properly utilized, when monocropping is practiced in coconut gardens.Furthermore, the grower receives little or no returns from the palms throughout their immature stage, which can last up to 10 years, while the intercrops provide some returns.As a result, mixed species agroforestry systems aimed at increasing spatial and/or temporal complementarities in resource utilization, as well as providing additional returns, have become a unique feature of the coconut-growing regions in the tropics.What explains the functioning of such sophisticated agroecological models is perhaps the “Niche-complementarity hypothesis”.It implies that a bigger suite of species occupying a site may lead to better resource partitioning and utilization making the system more productive than systems involving fewer number of species.Consistent with this, Liyanage and Dassanayake reported increased nut yields when pasture species , black pepper and coffee were inter cropped with coconut.Such beneficial effects of inter cropping have been attributed to improved nutrition of the palm through complementary resource sharing, better retention of soil moisture, reduced weed competition and improved soil quality.

Competition for site resources between coconuts and the associated plants, however, could be a potential problem.Such interactions may be either above ground or below ground.Section 5.1.4 describes the below ground interactions.Furthermore, the nature of inter specific interactions will vary depending on the stage of coconut stand development.A synthesis of the published reports, nevertheless, indicates that growing trees in the inter spaces does not have a strong adverse impact on the yield of coconut palms, except in situations where such trees impede light availability of the palms.Species mixtures generally ensure spatial complementarity in resource use as the components occupy different niches, although the tree-crop interactions may change with time and planting geometry.Although coconut-based polycultural systems are ubiquitous, below ground interactions of woody perennials in such mixed-species systems are rarely studied due to methodological challenges.Furthermore, results from the available studies are also not consistent, implying that the interactions may be either complementary or competitive.Nelliat et al.reported horizontal and vertical stratification of coarse roots in “adequately and separately fertilized multi-storied combination of coconut, cacao and pineapple”.Conversely, Pandey et al.found that the coconut root systems were at close proximity to the intercrops in well fertilized polycultural systems involving three 20-year-old tree species,implying competitive nutrient withdrawal by the coconut palms.Using the 32P soil injection technique, Kumar et al.and Gowda and Kumar investigated root competition in the coconut + dicot MPT agroforestry system.According to Kumar et al., 32P uptake by coconut palm in a species mixture was higher than that of a sole coconut stand, owing to increased subsoil root activity in the former, implying that the coconut root system may grow deeper in mixed-species systems compared to sole coconut systems.Gowda and Kumarexamined root interactions between coconut and dicot trees along a soil fertility gradient.

Notwithstanding major differences in the nutrient status along the gradient as well as dicot tree root characters, uptake of 32P by the coconut palms was not substantially different, signifying non-competitiveness of the associated dicot tree components for P.Nevertheless, the interplanted dicot trees captured significant quantities of the radio-label supplied to the coconut palm, implying a “scavenging effect” by these trees that, in turn, minimizes the potential for lower leaching of nutrient elements.Coconut-based farming systems often involve mixtures of trees that occupy different soil strata and this may entail a certain degree of spatial complementarity in resource use.Occurrence of two or more woody species in mixtures also favors diminished lateral spread and/or facilitates deeper root penetration of the components.In the coconut+dicot tree system investigated by Gowda and Kumar mentioned above, the interplanted dicot trees absorbed considerable quantities of the radio-label applied to the palm, which declined log-linearly with distance from the palms, signifying a substantial potential for “capturing” the lower leaching nutrients, at proximal distances.Proximity of the associated tree component, therefore, is a strong determinant of such plastic responses in tree root distribution.Gowda and Kumar also reported that some dicot species in the coconut+dicot tree mixture developed deeper root systems , while others produced increasingly spreading root systems , denoting that root architecture of mixed tree plantations is species dependent.Thus, there is a need for proper selection of the component crops and their manipulation to optimize productivity in coconut ecosystems.An array of ecosystem services such as provisioning, regulating, supporting, and cultural services are provided by the coconut based multi-strata, multi-species ecosystems.This includes crop species yielding food, fiber, fuel, fodder, timber, medicine, and other basic necessities , besides cash returns.The diverse range of crops integrated into CBFS producing fruits, nuts, drinks , edible oils and cakes, fiber, foliage, timber, bio-fuels, vegetables, spices, and medicinal plants justifies the sobriquet “coconut-based food forests”.The coconut palm also yields organic coconut water, virgin coconut oil, functional foods and health drinks like neera , coconut sugar, cosmeceuticals, oleochemicals, and bio-lubricants and is a popular ingredient in the cuisines of many countries in South and Southeast Asia.Furthermore, the coconut palm produces edible copra for the extraction of coconut oil, as well as desiccated coconut powder, fermented sap, and sap jaggery, among other culinary items.

Also available in both domestic and international markets are a variety of value-added products from coconut oil such as soap, body oil and perfumed hair oil, and kernel-based products such as coconut chips, coconut cream, coconut milk powder, white soft coconut cheese, coconut yoghurt and so on.Tender coconut water is a healthier alternative to many carbonated beverages due to its nutritious properties.Apart from being an important dietary component, the coconut palm and the associated species yield diverse range of aesthetic and artisanal products.Coconut wood is an excellent structural material that is used in the construction of buildings, furniture, flooring, and paneling, and the fabrication of high-end products like handcrafted, biodegradable,flood and drain table and sustainable coconut bowls, as well as for the making of charcoal, chemicals, pulp, and paper.In experimental studies, the mechanical properties of coconut wood compared quite well with those of other structural timbers such as teak , wild jack and the like.Coconut wood thus supplements the supply of raw materials for the wood industry and provides low-cost and durable construction materials.Because of its availability and renewability, coconut’s sustainability can add value to this construction material and thus help to conserve the remaining natural forests, by offsetting the pressure on them.Additionally, CBFS provides byproducts such as coconut shells and fibre, which are presumably underutilized but constitute vital raw materials for cottage enterprises.Coconut shell is a useful bio-fuel as well, despite its relevance as an alternative fuel in homes and small businesses.In addition to offering an alternative and better source of fuel than fuel wood and other traditional fuels, using coconut shell as a fuel reduces CO2 emissions and sanitizes the environment of the harmful hard shell.The husk usually forms 35–45% of the weight of the whole nut when ripe.About 30% of the husk is fibre and 70% is coir dust.The industry uses just about 35% of the total husk available, while there is scope for economically utilizing at least 50% of the husk produced.Coir fiber and coir pith are two important products made from coconut husk.The fibers are used for spinning into yarn for manufacturing mats and mattings, ropes, twines, etc.Pith, which is usually mixed with short fifibers and contains mainly lignin, cellulose, and hemicellulose, is used as a manure and has a variety of industrial applications too.Agrobiodiversity being the critical feature of NbS, CBFS offers innumerable opportunities for integrating diverse forms of crops in the same land management system.

Such systems have provided sustenance, nourishment and livelihood security to large segments of Kerala’s rural and peri-urban populations for millennia, as in other parts of South and Southeast Asia.As described in Table 2 and Section 5, many functional groups of plants, such as food crops , permanent plantation crops, medicinal plants, multipurpose trees, and others, are associated with CBFS, implying their potential to conserve biodiversity in managed ecosystems.Such integrated farming systems generally outperform mono specific production systems in all major aspects of multifunctional agriculture, including food security, environmental functions, economic functions, and social functions.The coconut palm is also very resilient as it can withstand natural calamities like typhoons and flooding.In general, woody perennial-based mixed-species land use systems have the potential to address natural calamities such as droughts, floods, and high temperatures as a consequence of climate change.Improvements in soil organic matter status and water holding capacity, and the resultant yield gains, are also integral features of the coconut-based ecosystems.Osei-Bonsu et al.observed higher soil moisture retention in cacao + coconut mixture in Ghana compared to cacao + Gliricidia sepium system.From Sri Lanka, Arachchi and Liyanage also reported improved soil organic matter status, bulk density, aeration, and water content in the soil profiles of acacia and gliricidia interplanted plots compared to that of sole coconut and Calliandra calothyrsus and L.leucocephala intercropped plots.Although global warming and the consequential faster soil organic matter turnover may exacerbate the deterioration of nutrient-poor tropical soils, such obstacles are less likely in coconut-based multi-strata production systems than in mono specific stands, emphasizing the CBFS’s sustainability.Another major characteristic of CBFS is enhanced carbon capture and storage in soil-crop systems, which has the potential to minimize CO2 emissions.This includes carbon sequestration in soil and biomass , as well as the substitution of fossil fuels with bio-diesel made from biomass or coconut oil.However, only few studies have characterized the carbon sequestration potential of coconut-based ecosystems.The available reports suggest that tree plantations signify remarkable carbon pools as trees hold much more carbon per unit land area than other categories of vegetation, and CBFS has huge potential as a carbon sink.Consistent with this, Navarro et al.reported that coconut plantations exhibit high productivity typical of the tropical humid evergreen forest ecosystems.Ranasinghe and Thimothias estimated that the ecosystem carbon stock of CBFS in Sri Lanka ranged from 32 to 72 Mg C ha–1, while the net carbon balance ranged from 0.4 to 1.9 Mg C ha–1 month–1 under various growth conditions.Carbon storage by coconut palms in mixed stands is clearly greater than that of sole stands, especially when the species-mix involves trees.For instance, in a system involving different inter cropped fruit trees such as guava , litchi , sapota and custard apple grown in association with coconut, Manna et al. reported higher soil carbon sequestration for mixed-species systems than sole coconut.Nutrient management of CBFS is yet another important determinant of soil carbon sequestration, and improved nutrient management may augment the carbon sequestration potential.

Table 2 shows an overview of the most important points from the interviews, divided over the different respondent groups.To begin with, the responses from farmer respondents show that there are many opportunities linked to the usage of AI and smart farming technologies in agriculture.Most importantly, according to them, new smart farming technologies have the potential of increasing their profitability, either by contributing to higher revenues or freeing time spent on some tedious tasks.On the other hand, the large initial costs to set up the technologies are identified as a barrier.However, if economical means allow for investing in such solutions, farmers believe that the investments will pay off in terms of profitability and competitiveness.Other factors that act as demands for smart farming technologies are their potential to be more sustainable and that they make farming more fun.Further barriers according to farmers are the complex solutions and lack of interoperability, as well as the poor prerequisites and opportunities of continuous education regarding technology in agriculture.Also, the fickle market makes smart farming risky to invest in for farmers.From a commercial enterprise point of view, there are many opportunities connected to smart farming, but also some critical barriers to overcome.The respondents of this group see potential in increased cooperation between companies as well as with farmers, business cases in providing Software as a Service and additionally to streamline logistics connected to agriculture.Nevertheless, data sharing and cybersecurity are seen as large hurdles to the use of these technologies.Respondents from research institutes also express a positive view on accelerated use of AI in agriculture.They believe such a development would result in more data collected by the farmers, which would decrease the time researchers themselves spend on gathering data.This would, according to the researcher respondents, lead to a faster and better research on agriculture.However, data sharing hinders, once again, the scientific development since high-paced research is hard to conduct without proper access to data from different sources.An additional identified barrier for smart farming is the mistrust from farmers that the scientifically developed solutions mirror a real agricultural demand and are not just developed for the sake of technology.

Finally, the respondents from governmental agencies claim that there is a great interest and demand for propagating smart farming technologies for national competitiveness as well as other economic reasons.Still, they are not sure how to position themselves in this transition, which slows down the process of digitizing the agricultural sector.This respondent group also views cybersecurity and data sharing as critical barriers to overcome.This paper provides a review of the main opportunities and hurdles for applying AI to agricultural businesses.By conducting a structured literature review and an interview study with 21 respondents from various parts of the agricultural industry, data has been gathered to get a holistic view on the use of smart technology in agriculture.The scope of the thesis is deliberately wide, focusing on three agricultural sectors: arable farming, milk production and beef production.Furthermore, the respondents are categorized by their role in the sector, ranging from governmental authorities, commercial enterprises, researchers as well as farmers.This broad view allows to acquire knowledge that ranges over several production sectors, as well as over several kinds of organizations with different views on the agricultural sector.Driving the farmers towards smart farming technologies are the needs for increased profitability, reduced workload and often a genuine curiosity for new technology.Surprisingly, all these aspects are not completely captured in the literature review.For example, there are studies about the impact smart farming can have on the relation between humans and animals on a farm, but they did not show in the literature review search.On the contrary, some expected drives for smart farming were not expressed by the respondents, such as the advantageous impact that smart farming can have on the environment through less nutrient loss.Instead, profitability stands out as the most influential factor which makes a clear business case an essential requirement connected to the propagation of smart farming technologies.

Since more and more agricultural products become available in the form of SaaS, allowing for sharing and renting equipment, the business case is changing for both farmers and machine producers, opening new possibilities.Nevertheless, for smart farming to really transform the agricultural sector, governmental agencies and commercial enterprises might need to take a more active role in the transition.Such aspirations are especially important to ensure that the governmental and societal demand for reduced emissions and increased sustainability is met in the technological shift.For the transformation to be successful, it is essential that the structures, allowing farmers to apply the smart farming technologies, are modern.One key requirement is that farmers have continuous and easy ways to acquire up-to-date knowledge of how to apply smart farming.Therefore, there is a need to ensure technical, agricultural education which is easily accessible through for example flexible, on-demand courses.Additionally, the smart farming techniques need to be modifiable to match the varying transparency and adaptability demands that different farmers have.Regarding how implementation and propagation of AI in agriculture might be hindered, this study identifies some factors that act as barriers.The most prominent one is how data is managed, which can be further specified to data sharing and ownership as well as cybersecurity.This is a complex question that as of now does not have a clear solution, neither technically nor legally.Here lays an important role for research institutes as well as authorities.However, there is a consensus among respondents that to transition the agricultural sector into a more data-driven and digital environment, the technical infrastructure must be secure.The solution must be able to guarantee that sensitive data is not available for intruders while at the same time guaranteeing access for the intended users.Furthermore, for the end users to be able to benefit from the digitalizing transition of the sector, the data models require a high degree of flexibility.This stems from the wide variety of machinery at farms as well as the varying level of technological interest and knowledge among the farmers.Moreover, an important aspect that slows down the process of implementing smart farming technologies and AI in agriculture is the economical dimension expressed by the respondents.

A large part of this are of course the high investment costs, but other economic aspects also play a part in this barrier.For example, the fickle market demands, the general low profitability in agriculture as well as the trend towards consolidation of farms all contribute to making investments full of risk.Other identified barriers that hinder the spread of AI in agriculture are some social factors, for example the concerns about technological over-dependency and insufficient end user trust towards technology.The lacking trust seems to stem from over-selling from developers of technology as well as a gap between the technology that is developed and the real market demands.As for the technical solutions that could potentially solve the demand for AI and smart farming technologies, there are many possible ways.In this study, findings show that a lot of the data and sensors types already exist.The problem that remains to be solved is to connect the input data to the output data by developing the datasets, and thereby closing the data cycle.Today, the dairy sector generally holds a closed and elaborate data cycle whereas generally the meat and arable sector have less developed data gathering and therefore less precise decision support tools.This is highlighted in both the interviews and the literature review, as high-resolution data allows for more precise and detailed decision support.Although, after a thorough process of data gathering from input to output, one can build models and evaluate which one of them performs best with some specified evaluating metrics.Additionally, a general problem and difficulty in building machine learning models is that models tend to take too many variables at the same time.The results show the importance of ‘starting small’ when building the models, i.e.using few input variables to begin with and then tune the model adding only one more variable at a time.It is also found that all possible use cases and technical solutions demand a high precision for classification model output as well as low prediction errors for regression models.Decision support in agriculture manages and affects core parts of the agricultural business, and therefore it is important that estimations and predictions are accurate.Interestingly, respondents from the arable sector express that they, as of now,hydroponic equipment accept higher levels of total error in the model.However, for future purposes and solutions with increased complexity, the total error must decrease which is likely to affect the bias- variance trade-off.A requirement for achieving precise supervised machine learning models, adapted to the local farm, will be easy pre-processing of the data.Thus, the data labeling process must either be simplified by developers or offered to the farmers as a service by consultants.

Technologically, the agricultural sector has developed for decades, but the shift towards smart farming techniques and data-driven agriculture might be one of the greatest transitions.Applied AI in agriculture has the potential to optimize and streamline agricultural activities in all sectors in agriculture.By data-driven decision support, and even tasks performed completely automatically, farmers hope to improve their output both in terms of quantity and quality, mitigate carbon emissions, decrease work time, and increase profits.For commercial enterprises and governmental agencies, the transition allows for updated supply chains and planning models, improving the agricultural industry on a macro-level.Still, several challenges remain unsolved, jeopardizing the speed of the transition.Here, there are important tasks for companies, authorities and research institutes.Nevertheless, with such strong incentives, the long-term trend towards increased usage of AI in agriculture is clear.The question is no longer if smart farming will continue to develop, but how the hurdles will be resolved, and which stakeholders will benefit from its radical transformative effects.Growing urban populations and the reduction of arable land, increase the need for productive, efficient, and environmentally friendly ways of agricultural production.For more than three decades, agriculture changed towards an increasing degree of automation.Today numerous digital solutions already exist to support farmers’ everyday lives.Examples can be found within the monitoring of crops and soils as well as for data analysis and storage including decision support.Most solutions today need a connection to farm external cloud systems where data and information are being received from and transferred to.Farmers are motivated to actively use this information technology to benefit from increases in farm input efficiencies, from decreases in negative environmental impacts as well as from automated operation documentation.However, farmers in Europe are diverse in their farm produces and many digital solutions only cover partly the activities within farms.This leads to the problem that farmers experience the lack of interoperability of different digital products.

One version of a universal definition for sustainable agriculture is “an agriculture that can evolve indefinitely toward greater human utility, greater efficiency of resource use, and a balance with the environment that is favorable both to humans and to most other species.” The FAO of the United Nations states that “sustainable agriculture should involve the successful management of resources for agriculture to satisfy changing human needs while maintaining or enhancing the quality of the environment and conserving natural resources.” Clearly,rolling bench in envisioning a sustainable agriculture it makes all of the difference whether the goal is to sustain the current world economic order, an individual nation’s agricultural economy, a middle-class American’s life, a farm family’s right to retain owner- ship of their land and other means of production, or an Ethiopian woman’s life. Unless we clearly specify who or what we want to sustain, sustainability advocates risk prescribing future visions that do not consider social inequities and therefore reproduce domination based on class, gender, and race. But how do workers, women, and people of color fit into dominant sustainable agriculture visions?Dominant sustainability discourses generally do not analyze the different interests and classes that participate in the food and agriculture system. An example can be found in the first challenge set forth in the Asilomar Declaration for Sustainable Agriculture*, which is to “promote and sustain healthy rural communities.” Justification for the promotion of rural communities is: “Healthy rural communities are attractive and equitable for farmers, farm workers, and their families. The continuation of traditional values and farming wisdom depends on a stable, multi-generational population.” Thus, although the Asilomar Declaration recognizes corporate land ownership as problematic, it does not address the different interests of farmers and farm workers in general.

It recognizes no inherent problem with an economy based upon land owners who hire landless laborers, and advocates maintaining the existing structure of land tenure. This statement also implies that current rural values, which include the patriarchal family and Christian religious beliefs, are ideals we should advocate and preserve. Similar perspectives are reflected by the National Research Council and the U.S. federal sustainable agriculture research program, Sustainable Agriculture Research and Education . For example, where the National Research Council discusses labor on alternative farms, labor is viewed only as a cost of production. There is no discussion of who the workers are, their working conditions, or their wages. In the same vein, SARE addresses socioeconomic issues primarily in terms of the economic viability of farms, and largely avoids discussion of antagonisms between corporate agriculture, family farms, and farm labor. Those focused on food safety, however, show greater interest in the welfare of the farm worker when they point out that pesticide use in agriculture poses a greater risk to field workers than it does to consumers. Still, where food issues are discussed in the context of sustainability, they usually focus on safety and pay little attention to accessibility. Yet Bill Liebhardt, director of the University of California’s Sustainable Agriculture Research and Education Program, points out that we must “. . . eliminate the very idea of hunger in a state where agriculture is still the largest industry.”This is true in the larger scope as well: worldwide at least 500 million people do not have regular access to sufficient food.Kate Clancy, a professor long active in sustainable agriculture, asks, “Is agriculture sustainable if it doesn’t encompass issues of social justice like hunger?” Yet visions that include factors central to workers and the poor, such as who should have a right to eat or access to land, are not presented in dominant sustainability discourse.

In most cases, traditional gender roles are assumed in discussions of sustainable agriculture, whether women are included or simply overlooked. Populist visions of sustainable agriculture see the family farm as the ideal organizational structure for sustainable agriculture, but generally do not discuss gender roles within the farm family. An exception is Berry, who explicitly discusses differences between men and women on farms and suggests that both women and men suffer when nurturing is the sole purview of women.However, he advocates a return to traditional values associated with the home without questioning the patriarchal privilege that underlies many of these values. The fact that family farms are based on patriarchal relations is not regarded as a problem by the sustain- able agriculture movement, yet on the majority of family farms men control land, capital, and women’s labor.While farm women are resisting their roles as “farm wives” and insisting on wider decision-making roles and access to land, in most sustainability discourse, women’s demands for change have not been incorporated. Often farmers continue to be referred to using masculine pronouns, which fails to acknowledge women’s roles in agricultural production, except as they support the male farmer. In the food safety movement women are often targeted specifically for the part they can play in developing this aspect of agricultural sustainability. In this way traditional gender roles are not questioned, since women are appealed to in their capacity as food purchasers and child care providers and men are excluded. In general, dominant visions for agricultural sustainability do not correct the problem of gender inequities.To some extent, this results from the absence of people of color from decision- making positions in Western agriculture. People of color have been integral to the functioning of American agriculture, but in subordinate roles. African- Americans, Hispanics, and Asian-Americans have historically and currently provide much of the labor in U.S. agriculture, but are much less likely than European-Americans to be farm owners. Even in California,roll bench an extremely ethnically diverse state, only 9.2 percent of farm operators are ethnic minorities; this proportion is inverted among farm workers, 75 percent of whom are ethnic minorities.Farm workers have received few of the benefits of profitable and abundant agriculture; compared to farm owners, they have much lower incomes, live under worse conditions, have less control over the production process, are more often exposed to pesticides, and have higher incidences of health problems related to pesticide use.

It is significant that the impetus for low-input agriculture was generated in part by the level of public distress about farmers losing their land during the 1980s, when the crisis affected mostly European- American farmers and affluent customers. In contrast, little concern has been raised in sustainability discourse about the nearly complete separation of African-American farmers from their land. In 1920 one in seven U.S. farms was black-operated, but in this century the number of farms owned by blacks has declined 94 percent.In addition, the call for a return to traditional rural values fails to challenge racist attitudes historically prevalent in much of the rural U.S. The dominant vision of sustainability in the U.S. does not address racial inequalities prevalent in agriculture.Strategies suggested for achieving sustainability are, of course, intimately linked with the problems perceived, causes attributed, and visions projected. For the Committee for Sustainable Agriculture, sustainable agriculture can be achieved “ . . . through dissemination of information about farming, food processing and marketing techniques that conserve and replenish soil resources, and decrease the use of toxic and synthetic chemicals. By working toward these ecologically benign technologies [sustainability will result].” This statement describes the major strategies employed in the effort toward sustainable agriculture – providing more information to farmers and consumers through better communication, gathering more knowledge about agroecological processes, and developing better technology. Less often, but occasionally mentioned are establishing policy reforms to increase pesticide regulations or limit corporate farming, developing bio-regional communities to localize food production and consumption, and reinvigorating traditional values. While some of these we consider antithetical to sustainability or unrealistic , others are no doubt essential components in the move to sustainable agriculture. We argue not with their inclusion in a package of strategies for sustainability, but with the emphasis placed upon them to the exclusion of other strategies. For example, a primary emphasis has been placed on developing profitable alternative production techniques and systems through science. This is seen both in Western agriculture and in development programs for impoverished countries. Historically in the U.S., agricultural science has been called upon to resolve major socioeconomic and ecological crises in agriculture, such as with the scientifically based land- grant colleges, the Cooperative Extension Service and the Soil Conservation Service. In these instances, science has sanctioned the highly capitalized, chemical-intensive agricultural system in the U.S. and is being uncritically called upon to sanction low-input systems as well.

It is clear, however, that neither science nor new technologies can by themselves solve larger food and agriculture problems, as witnessed by the problems associated with the scientifically based Green Revolution. In addition to the universal sustainability issue of how agricultural products are produced, one scientist proposes that we also address the questions of what and for whom agricultural products are produced.Yet dominant sustainability discourses tend to rely on technology as the solution – that if the right technologies were developed, sustainability would result. For example, the Asilomar Declaration for Sustainable Agriculture states that, “Given scientifically validated techniques, farmers will adopt sustain- able agriculture practices.” In this perspective, an agricultural production system that is both profitable and environmentally sound will be achieved as less environmentally damaging technologies are developed and substituted for existing chemical technologies. This does not examine the overarching structural forces that have contributed to the adoption of re- source-intensive farming practices. Technologies and social relations are inseparably linked, both in terms of their inspiration and their consequences. In agricultural research universities we do not have the Baconian model of the atomistic scientist pursuing “pure knowledge.” Instead, research is often driven by economics and politics; entrepreneurs demand marketable technologies and these are in turn produced. The development of chemical vs. cultural pest management techniques, for example, is not accidental. If agricultural requirements can be responded to profitably, they will be.But maximizing profits depends upon repeated sales of inputs, not products that can be reproduced by the farmers or are self-reproducing under proper environmental conditions.In our view, this vision’s perspective is too partial and fragmented. If we do not go farther in challenging the structures and assumptions that have led to sustainability problems, we place ourselves at the risk of reproducing these problems and generating only very marginal improvements. Achieving a truly sustainable food and agricultural system requires a broader vision and new strategies for both analysis and implementation. Developing this system will require concentrated thinking, innovative actions, and a deep commitment on the part of many people. As a start, we suggest several ways in which we can begin down the path toward a sustainable agricultural system.

For fertilizers, farmers with a higher education level, a longer distance to their land plots, dutch buckets more motorcycles appear to use more fertilizers, while those with a higher dependency ratio and larger farmland tend to use less fertilizers.The variable of asset poor shows an insignificant effect on input use.To acquire the farming efficiency, we estimate the translog true random-effects stochastic production frontier function with Mundlak’s adjustments.Table 4 stacks the brief results of the estimation.Most of the mean variables of CRE show a statistical significance implying the presence of time-invariant unobservable characteristic effects.Only five variables of inputs show a significant effect.This indicates the less intensive level of rice production in Thailand, compared with some competing countries such as Vietnam.The results also indicate that fertilizer is the most important input.Fig.2 shows the distribution of predicted farming efficiency scores.The mean score was 0.64 in 2013 and 0.70 in 2017, the vast majority of the households have a farming efficiency score higher than 0.50, and less than 3% of the households have an efficiency score higher than 0.90.The mean efficiency score of our estimation is slightly higher than the score of rice farmers in Thailand, lower than Vietnam and of 0.85 from Huy and Nguyen, and higher than the scores of rice farmers in Cambodia  and in Bangladesh.In our result, the mean score of shock households appears to be lower than that of households in the non-shock group in 2013 and 2017.Table 5 presents the effects of farmers’ risk attitudes and shocks on technical efficiency in rice production and shows that farmers’ willingness to take risks has a positive and significant effect on farming efficiency.This finding further suggests that higher risk-averse farmers are applying more fertilizers and pesticides, and this inefficient use of inputs causes farming inefficiency in their production.In addition, the result from IV fixed-effects estimations by groups of farmers’ risk attitudes shows that households belonging to the risk-averse group appear to have lower farming efficiency.This confirms that more risk-averse farmers are inefficiently using chemical inputs, and this improper application leads to lower farming efficiency.Our findings support the conclusion that rural households’ behavior under risk might explain low agricultural productivity and vicious cycles of poverty in developing countries because these inputs account for a high proportion of production costs.

We run additional estimations with lagged values of attitudes as robustness checks.The results remain consistent.Unsurprisingly, weather shocks significantly and negatively affect rice technical efficiency, while pests and diseases show an insignificant influence in all IV fixed-effects estimations.Regarding the weather shocks, the result is related to the findings of Mishra et al.and Mishra et al.that weather shocks are a major reason affecting agricultural inefficiency in Cambodia and Bangladesh, respectively.This emphasizes the impacts of weather shocks on agricultural production in developing countries and urges governments to support rural households to cope with weather shocks, especially in the context of climate change that causes more frequent extreme weather events.The extensive and improper use of chemical inputs in agriculture has triggered various non-point source pollution and accelerated carbon emissions.This has been deteriorating the ecological environment and endangering public physical and mental health.Abundant use of inorganic fertilizers during farming is linked with the accumulation of contaminants in agricultural soils, including arsenic, cadmium, fluorine, lead, and mercury.Pesticides, fungicides and weedicides are frequently found in the stream water in agricultural areas.These chemicals are also detected in the air of residential environments.Agrochemicals were traced even in human blood and adipose tissue.Various short-term or long-term health casualties are associated with agrochemicals, including dizziness, nausea, diarrhoea, skin, eye irritation, cancer, endocrine disruption, birth defects,etc..Inorganic inputs reduction and replacement with organic inputs with soil protection measures, crop rotation, intercropping, and waste resource utilization are the effective ways to solve the problem.However, farmers use these agrochemicals primarily due to economic benefits.The application of fertilizers and crop protection chemicals has been instrumental in increasing agricultural production, while pesticides, fungicides, and weedicides also reduce the cost of production from diseases, insect pests, and weeds.Organic agriculture practice involving the application of a set of cultural, biological, and mechanical practices is the best alternative that supports the cycling of on-farm resources, promotes ecological balance, and conserves biodiversity.Maintaining or enhancing soil and water quality; conserving wetlands, woodlands, and wildlife with avoiding the use of synthetic fertilizers, sewage sludge, irradiation, and genetic engineering are included in these practices.

Due to the lower cropping intensity under organic farming and the poor socioeconomic status of the farmers, the use of organic inputs is still very negligible in Bangladesh.Approximately only 0.1 % of the country’s total cultivable agricultural land is under organic agriculture.This has left an enormous vacuity to promote the use of organic inputs in agriculture.In addition to cereal and other cash crops, the use of organic inputs must be promoted in various fruit farming.Watermelon is one of the important fruits cultivated in Bangladesh besides mango, jackfruit, papaya, banana, etc.In 2020, around 12,251 ha of land was devoted to watermelon farming, where 254814 MT production was obtained.Because of high profitability and environmental suitability, it is grown extensively in the southern districts of Bangladesh.However, watermelon farmers extensively use different agrochemicals, i.e., fertilizers, pesticides, fungicides, weedicides and even some growth promoters.Since watermelon is a very demanded fruit in Bangladesh, assessing the farmers’ agrochemicals use is necessary.Besides, they are reluctant to use organic inputs for expected lower profit.Their willingness to adopt organic inputs need to be evaluated for ensuring sustainable agriculture in Bangladesh.Rabbany et al.conducted research on the cost of production analysis of watermelon.Yusuf et al.also reported profitability and adoption of watermelon technologies by farmers.Ibrahim et al.explored technical efficiency and its determinants in watermelon production.However, very little is known about agrochemicals usage by watermelon farmers.On the other hand, various studies were conducted on the use of organic inputs in various crops farming.Tur-Cardona et al.explored the acceptance of bio-based fertilizers in European countries.Salam et al.evaluated the impact of organic fertilizer on the yield and efficiency of rice.Rana et al.examined the organic vegetable cultivation attitude of the farmers.Again, very limited information was found that assessed the watermelon farmers’ willingness to adopt organic inputs.Hence, the present study was conducted to contribute to the literature by evaluating the watermelon farmers’ agrochemicals usage and assessing their willingness to adopt organic inputs.The objectives of the study are twofold.First, it assessed the agrochemical usage by the watermelon farmers.Second, it evaluated the farmers’ willingness to adopt organic inputs.The structure of this paper is as follows.The next section provides information on data and methods used to achieve the objectives.Section three presents the results and discusses the obtained findings.The last section provides conclusions with possible recommendations based on the findings.

Farmers in this study use various agrochemicals in the form of fertilizers, pesticides, fungicides, weedicides, growth promoters, etc.Fig.2 illustrates the farmers’ extent of using chemical fertilizers in watermelon farming.Maintaining soil fertility and soil nutrients is crucial for sustainable plant growth,grow bucket and it is usually done through applying fertilizers.Farmers in this study mainly used Urea, TSP, MoP, DAP, Gypsum, Boron, and Zinc fertilizers for watermelon.Urea provides necessary nitrogen to plants that help vegetative growth and aids the photosynthesis process.In watermelon farming, the farmers use four split applications of Urea during tillage, ten days before planting, 10-15 days after planting, and during and at the time of first flowering.Results revealed that about 72.5 % of farmers applied Urea above recommended dose while only about 5 % followed recommended dose.Similarly, most of the farmers used the above recommended doses of TSP.TSP is a popular source of phosphorus, and it helps with the growth and the development of the root system.Two doses of TSP are applied in watermelon farming, i.e., during tillage and ten days before planting.Urea and TSP are two of the three most used fertilizers by the farmers in Bangladesh.This could happen due to the negative effect of notable price reduction of fertilizers by following a universal subsidy policy in the country over the decade.Islam and Hossain also reported farmers tendency to overuse these fertilizers.MoP provides potassium to the plants, assisting the growth of strong stems and helping build the plants’ disease resistance.In the case of MoP, watermelon farmers apply it in four splits with Urea.It was found that most of the farmers were below recommended doses of MoP, while 38.3 % used above recommended doses.On the other hand, Diammonium Phosphate usage was under dose for most of them , while 35.8 % used its overdose.DAP is highly soluble and provides temporary alkalization of pH of the soil solution around the fertilizer granule, which aids better phosphorus uptake.Although about 31.7 % of them applied the recommended doses of Gypsum, the majority were overdosing.Contrarily, more than half of them did not apply Boron and Zinc, while most of the farmers using them were following the recommended dose.Farmers apply plant protection chemicals, i.e., pesticides, fungicides, weedicides, etc.in order to prevent diseases, infestation, and weeds in expectation of increased production.The usage extent of these chemicals by watermelon farmers in this study is elicited in Fig.3.It was observed that most of them used overdoses of pesticide following 35.8 % using below recommended dose.In the case of fungicide, about 70.8 % of farmers applied above recommended doses.Although most farmers did not use weedicide as they manage weed manually, about 12.5 and 23.3 % applied recommended and below recommended doses, respectively.Besides, farmers used growth promoters for sweeter and bigger-sized fruits.It was found that the majority had been using it in overdoses.Overall, farmers are overusing chemical inputs, which can be devastating for the public health, environment and especially their own health.Farmers in Bangladesh usually seek advice on pesticide use from dealers or retailers in their local market, who mostly have superficial knowledge on different inputs because of easier accessibility.Another plausible reason could be the increase in the availability of several brands of chemical inputs in the market, which was also reported in the study by Rahman.The easily availed different chemical inputs at local markets with misleading advertising might confuse the farmers who are mostly illiterate.The factors influencing the adoption of agrochemicals by the watermelon farmers were identified using a Tobit regression model.The results indicate that the education of the farmers exerted a significant and positive influence over the adoption of agrochemicals.It implies that farmers who are more educated use the chemicals better than their counterparts.Farmers with higher years of schooling have better access to information and analytical capabilities, enabling them to use the chemicals more sensibly.The finding confirms the results of Yigezu et al.and Prodhan and Khan.Farming experiences of the watermelon farmers influenced their use of chemicals significantly and positively.Experienced farmers tend to have better knowledge about the crops’ required doses that prevent the overdoseof chemicals.The same echoes were found in the studies of Nnadi and Akwiwu and Rahman and Haque.However, farm size held by the farmers illustrates a significant but negative effect on their use of agrochemicals indicating that small farms used these chemicals better than large ones.

The most studied taxa belonged to the hymenoptera , either as natural enemies , pollinators or pests.Furthermore, many arthropod taxa were studied in intercropping systems,ebb flow trays stressing the key part of landscape heterogeneity in smallholder farming.Only 4.9% of all articles assessed the management of both pollinators and natural enemies and/or pests.Except for integrated pest management , options that represented combined forms of different arthropod management were rarely evaluated in the same study.Regarding management practices, farmers’ strategies to improve an ES or counter an EDS mostly concerned chemical, organic and cultural practices for pest and habitat management.Most of them were related to pest control and implied pesticide applications.Nevertheless, several management strategies sought to improve environmental quality of agroecosystems.Arthropod management included traditional practices mostly by habitat management.Other common strategies were related to storage facilities and pest control.Overall, 40.2% of articles addressed farmers’ perceptions, actions and/or knowledge related to arthropods in SHF.Research covering farmers’ knowledge or perceptions was mainly carried on cultural services , especially for pollinator-related services.In contrast, farmers’ knowledge or perception was not prevalent in common agricultural services like pollination or pest-related functions.Very few studies addressed farmers’ point of view on processes related to soil and to species as bioindicators.Overall, farmers’ opinion and knowledge was poorly considered as 73.8% of all articles had a participation index scoring 0 or 1.In particular, farmers were poorly involved in the identification or survey processes: 78.2% of the 1264 taxa registered in the 122 articles were studied without local stakeholders.Farmers’ involvement was mainly passive through surveys or on-field sampling, and mostly aimed at collecting agronomic data, without consideration of their viewpoint in research questions or methods definitions.

Furthermore, 17.2% of articles did not report any or not explicitly mention farmer’s involvement within the research process.In this review, we evaluated current literature on arthropod-related services and disservices in smallholder systems.Despite an increasing number of studies focusing on insect-related services in the last decades , we found that only 9.0% of the arthropod literature concerned agricultural systems.Even more challenging, only 0.34% of the search outputs referred to SHF, albeit 84% of the world’s farms are small-holding, operating on about 12% of the world’s land.These results are in line with recent findings pointing that agricultural ES research is strongly biased towards large scale intensive farming landscapes and temperate biomes in HICs.This review is subject to limitations inherent to the chosen scope and focus on recent literature.In addition, it is likely that some SHF studies from L&MIC may not be published in indexed peer-reviewed journals but rather in technical reports or local academic canals, keeping several potentially relevant documents out of our scope.Similarly, despite a multilingual search, we might have omitted several references, particularly from the Asian continent, which is a limitation commonly reported in the literature.Most studied functions concerned pest, which reflects the longstanding negative view of arthropod roles in agroecosystems.In most cases, arthropods were studied only as pests or pest antagonists with no consideration of other ecological roles they could play.However, as smallholders’ actions may be driven mainly by EDS reduction , the negative impacts of these actions on ES supply should also be taken into account.

A few studies assessed floral visitors as potential enhancers of yield but almost none considered both pest control strategies and the maintenance of beneficial insects.Moving in that direction, Integrated Pest Management strategies could be adjusted for pollinator protection practices along with other beneficial arthropods for the agroecosystem.This relatively new paradigm of integrated pest and pollinator management merges both the welfare of all pollinators into the crop pest protection programs and benefits of alternative pollinators into crop production.IPPM can fit smallholder farming sustainable objectives as it intends to minimize trade-offs between ES and EDS, and to maximize co-benefits and synergies from insect management.However, any application of these principles calls for extensive transdisciplinary research among scientists, farmers and stakeholders in order to develop collectively onfield trials and monitoring instruments, but also to co-design decision support tools and evaluation of IPPM adoption.In the reviewed literature, arthropods were mainly studied separately along the food production process.However, agricultural ES and EDS require a wider consideration of the different crop stages, including management of harvested products as well as crop and non-crop habitats.This is especially important for ES and EDS related to arthropods whose life cycles often encompass both cultivated and natural habitats.The lack of a landscape level consideration may hamper farmers’ actions and proper management strategies.Indeed, the majority of reviewed papers presented pest management through chemical pesticide applications in the different crop system components while more sustainable management of traditional SHF requires a multidimensional view of the system.

Farmers aware of the role of the entomofauna at the landscape level could lower pesticide use, even if their awareness is oriented towards phenomena they observe in their fields or storages.Indeed, various articles raised the importance of increasing the entomological literacy of farmers, for example through training programs on pollinators , to achieve sustainable management actions in SHF.Arthropods also support social practices and cultural values by enabling the identification and analysis of changes in intergenerational transmission of knowledge.We found few studies focusing on how farmers’ knowledge is linked to arthropod-related ES.A similar trend was documented by Rawluk & Saunders who pointed at the scarcity of documentation of farmers’ knowledge on beneficial insects’ biology or ecology in agroecosystems.Farmer’s knowledge or perception mainly concerned pest-related functions because of the strong interdependence of smallholder farming on pest threats and risks.This makes control techniques essential to increase productivity while dealing with harsh environmental conditions.The few articles directly engaging emic local knowledge systems on arthropod-related ES dealt primarily with bees’ handling.These practices cover a broad range of cultural, medicinal or educational services that contribute to empowering bio-cultural diversity and endogenous development.These relationships would be worth studying further and together with other services or disservices to assess potential trade offs and synergies in the agricultural system.The objectives of most articles were either to identify and/or study the biology/ecology of arthropod species providing specific ES.However,4×8 flood tray several articles reported farmers being unable to recognize or identify arthropods and/ or their functions correctly , leading to inappropriate arthropod management.Furthermore, local beliefs in spontaneous generation can substitute concepts of insect reproduction and metamorphosis cycles.

These statements illustrate the mismatch between scientific and local knowledge that can be detrimental to cope with agronomic problems.Most farmers have a remarkable experiential knowledge of several elements in their agricultural landscapes resulting from long-term human-agrobiodiversity interactions.However, certain aspects might be difficult or impossible to observe such as the morphological differences between immature stages of two different pest species or the predatory behavior of small parasitic wasps of crop herbivores.This may affect farmers’ understanding of pest damage and bio-control.For example, farmers can easily observe that insect pests may be preyed upon by vertebrates but not by other insects or microorganisms.Likewise, farmers might over-react to certain pests that cause sub-economic damages or may perceive non-pest species as threatening.Misidentification remains the main issue reported in the literature, either for species names or for their ecological functions.On the other hand, even professional entomologists may have a limited knowledge on the taxonomy and ecology of many arthropods living in tropical SHS.It is therefore mandatory to reinforce transdisciplinary research by fostering the complementarity between local and scientific knowledge for arthropod management in SHF.The recognition of local classifications could be an opportunity to build synergies between knowledge systems and generate a common vision of arthropod communities.In the reviewed literature, scientists made the vast majority of taxonomic identifications, asking farmers subsequently to recognize them and then evaluate/validate their knowledge.Very few studies proceeded to recognize local categories and how arthropods were locally classified or named.This perspective widens the gaps between scientific and farmer knowledge, potentially affecting the effective implementation of more sustainable agriculture practices.Among the great diversity of insect species, farmers may name a set of organisms by a single term, even when they are not related species.Ethnoentomological studies have shown that a lack of name designation does not always reflect a missing category, as when a combination of words or concepts encompasses adjacent categories.Folk entomological classifications include cultural, social and ecological dimensions to differentiate life-forms based on morphologic, biological, behavior, utilitarian and psycho-emotional criteria.Thus, involving folk and farmers’ knowledge systems that differ from the taxonomic systems may allow broadening the scope of research in the direction of knowledge co-construction through.This may be achieved through the development of collective referential categories between scientific and folk knowledge systems or through a monitoring of knowledge changes.Including emic knowledge and intrinsic value of entomofauna in SHF may also help to better understand their socio-ecological roles in the agroecosystem, as proposed for pollinators and natural enemies.

While several authors recognized the importance of including farmers in agroecosystem ES and EDS studies, our review shows that questions related to local knowledge remained of limited interest for researchers.Poor participation of farmers and local people is a persistent problem in agricultural ES research and may have long-term implications to link different types of experience around a common problem.Applying transdisciplinary research concepts and methods may address this issue by favoring the initial co-design and co-creation of collaboration frameworks and research questions, the bidirectional information fluxes between scientists and farmers and the building of a solution-oriented knowledge.In our review, only three studies out of 122 actively engaged farmers.These works documented the successful application of participatory approaches.For example by improving pest control networks Landis et al. report on capacity building on IPM practices for wheat, providing a common learning process for farmers, crop advisors, and students.Also Smith et al. proposed a coordinated pollinator management plan integrating both local and scientific knowledge while Christmann et al. investigated human values regarding friendly actions for pollinator protection by a participatory approach focusing on farmers decision making.Such initiatives may not only trigger large system change and achieve broader systemic impact on SHF but also catalyze sustainable agriculture transition process as it combines both knowledge and social processes among actors.Coronavirus disease 2019 is a highly contagious infectious disease threating global public health and has declared as a pandemic crisis around the world.The COVID-19 is caused by the most recently discovered coronavirus Severe Acute Respiratory Syndrome Coronavirus 2 which is under the family of Coronaviridae a large family of enveloped, positive-sense RNA viruses that are important pathogens of humans and other mammals.In 2003 and 2012, two deadly human Coronavirus , namely SARS-CoV and MERS-CoV, have emerged respectively.Recently, the SARS-CoV-2 is a third new type of CoV, which is even more pathogenic, is straightening across the world in an unparalleled manner.In Bangladesh, the first-ever confirmed case was reported on March 8, 2020.In these contrast, several strategies have been executing to control the COVID-19, some of them concerning to the social distancing, hand washing, lockdown measures and etc..To combat against the COVID-19, it is essential to boost up the body immunity and animal originated protein and fiber enriched foods play a crucial role for this perseverance.In Bangladesh, about 37% of all animal protein meat consumption comes from poultry.Particularly, about 65–70 thousand commercial poultry farms are currently operating all over the country.Moreover, poultry rearing by women is common practice in almost all families in villages and plays a crucial role in self-employed and livelihood advancement of the poor women.

Agro-experts receive a system generated automated email for each query or complaint assigned to them or when status of a query or complaint is changed. Agro-experts can also visualize their performance based on the number of queries or complaints they resolved.Agriculture in developing countries contributes a big portion to national GDP, but there is a lack of effective support for farmers to adopt suitable agricultural practices through technology advancements. Farmers usually require timely advice and suggestions on crop patterns, diseases and prevention actions to tackle emerging situations. However, the development of a reliable, scalable, real time responsive system that is available 24/7 and fulfills the information requirements and support of farmers is still an open issue, especially in large agricultural countries like Egypt. The agri-culture sector’s data can be historical as well as processes related. Processing and analysing these massive amounts of data is challenging and involves a number of critical decisions such as selection of data storage depending on the nature and modalities of data involved. The large amounts of data being collected in the agriculture sector is expected to have an impact not only on smart farming but will also improve the decision-making capabilities of the farmers and government. The future of agriculture undoubtedly seems to lie in embarking on big data technologies and smart farming. Moreover, integration of concepts like Data Force Analytics and by providing a series of training to the system users, the whole process can be speed up overtime.

Consequently, farmers will be able to directly interact with such systems for their queries without interacting with human resources. To make a progress towards few of these challenges, the architecture of AgroSupportAnalytics has been developed. This has enabled building a support system that facilitates the provision of timely advice and relevant predictions to farmers. This, operational currently, will ensure a reduction and mitigation of significant negative effects of many serious challenges and threats facing the farming community and hence the agriculture sector in Egypt. The support provided will be more consistent, timely, reliable, and at easy reach, not only for ‘research centres’ but also for the ’agricultural associations,’ with minimal training and resources needed. The developed architecture of Agro Support Analytics has been designed on the basis of the following non-functional requirements. Scalability ‘ The Agro Support Analytics has several separated components in the architecture that allows easy scalability by upgrading one or more of those individual components. As an example, if the number of farmers/users/clients grows that may require splitting the Web Service by adding new capacity to deal with the client demand which means more Web Servers on the Information and Analysis Services Layer. Resilience and Redundancy ‘ The architecture of Agro Support Analytics is resilient as the critical components can be split in tiers that are clustered and geographically split to ensure failover, hence a more resilient system. Maintenance flexibility – As with the case of scalability, having distinct tiers allows pin pointed maintenance actions that do not produce collateral unwanted effects. This means that maintenance scheduling has fewer dependencies from 3rd party components. Developer Friendly Environment ‘ Having the several coding layers split by distinct tiers allows developers to focus on their individual task without having to share resources or bear in mind collateral potential impacts in each other’s tasks/domains. This is the type of architecture that also empowers frameworks and programming cultures like that of Agile development methodologies.

The prototype system is being operational currently and undergoing a process of outreach campaign to ensure sufficient stakeholder awareness of the services and capabilities it provides. A few snapshots of the Agro Support Analytics system is shown as Fig. 4. A transition stage is expected to follow in the near future whereby both farmers and agricultural experts will be using the system for their usual query-response activities. That is, besides the efficiency and effectiveness in dealing with farmers’ enquiries, the presented system can provide a sustainable and near real-time advice to the large sector of farmers in Egypt, that is besides vitally needed insights and projections of future events, relevant to their decision and action making. Currently, the Agro Support Analytics system doesn’t directly cater for IoT integration and analytics, which can also be an interesting future direction.The increase in population growth is accompanied by an increase in demand for food production. The FAO reported that the world population would be reached 9.73 billion by 2050, and the increase will continue till reach 11.2 billion by 2100 . Many challenges impede agricultural production, which leads to a decrease in crop productivity, such as soil salinity in arid conditions . In addition, the climate also affects the quantity and quality of crops and may lead to an increase in soil sensitivity to desertification . Therefore, the focus on survey land resources to use in agricultural development in arid regions is necessary . In developing world countries, the agricultural sector is one of the most important pillars of national income. Therefore, implementing new technologies to improve the agricultural sector is a significant issue for supporting the national economy in those countries . Agricultural production includes the production of food for humans and livestock, in addition to the raw materials needed for the industrial process. Since the ancient time till now, there are several agricultural development revolutions; the first agricultural revolution was by Egyptian and Greek ancient civilizations that had reflected interesting of the ancient people in the development of agricultural methods, where papyri indicating the develop irrigation systems from more than 6000 BCE.

Egyptians and Greeks developed several agricultural machinery and equipment, for example, tympanum, pumps, Shadouf, and Sakai . The second agricultural revolution was showed during the 17th century that followed the end of feudalism in the continent of Europe. Furthermore, the third agricultural revolution had activated during 1930–1960 of the last century, where an expansion uses of mineral fertilizers to increase agricultural production, as well as increased usage of pesticides parallel with the development of various agricultural machinery . The fourth agricultural revolution occurred during the past two decades, which there was a significant development in information communication technology and AI. These technologies have facilitated controlling the equipment and devices remotely, where robots have been used in agricultural operations such as harvesting and weeding, and also drones have also been used to fertilize crops and monitor crop growth stages. Smart agriculture is a technology that relies on its implementation on the use of AI and IoT in cyber-physical farm management . Smart agriculture addresses many issues related to crop production as it allows monitoring of the changes of climate factors, soil characteristics, soil moisture, etc. The Internet of Things technology is able to link various remote sensors such as robots, ground sensors, and drones, as this technology allows devices to be linked together using the internet to be operated automatically . The main idea of precision agriculture is improving the spatial management practices to increase crop production on the one hand and avoid the misuse of fertilizers and pesticides on the other hand . Numerous research has been conducted on applying ANN models in smart irrigation water management . The estimation of reference evapotranspiration is one of the essential parameters for crop irrigation because it determines irrigation scheduling . The Penman-Monteith model is the most often used for estimating evapotranspiration, although it needs a large amount of data for accurate ET estimates. Because GIS is linked with remote sensing, artificial intelligence, GPS technology, and other technologies,potted blackberry plant it may conserve a significant quantity of water that would otherwise be needed for irrigation. Mohd et al. created SWAMP ; a web-based Geospatial DecisionSupport System ; and a graphical user interface based on widget technology for simple access to different views for the rice IWM Scheme.

The system offers data on irrigation water demand and supply, as well as irrigation efficiency and a water productivity index. One of the most significant aspects of this system is providing real-time information by visualizing the presented results. Climate-Smart Agriculture was created to address three key issues: food security, adaptation, and mitigation . CSA has received much interest, particularly in developing countries, because of its potential to improve food security and farm system resilience while lowering greenhouse gas emissions . This is particularly important in Africa, where economic development is based on agricultural expansion, which is the most susceptible to climate change . Smart Agriculture is an evolution of precision agriculture by innovating smart methods to achieve multifunctional regarding the farm management remotely supported by alternatives appropriate solutions of farm management in real-time. Fig. 1 showed that robots could fulfill essential roles in controlling the agricultural process and anticipate automatic analysis and planning so that the electronic cyber-physical cycle becomes semi-autonomous . European Union , highlighted the technologies importance of high-resolution satellite images, Unmanned Aerial Vehicles , agricultural robots, and sensor nodes to collect data that could be integrated into future strategies of European agriculture smart farming signed in April 2019 by 24 EU countries . Parallel to expanding the various sensing methods for collecting, processing,and analyzing data, the volume of data used in agricultural management has become very big. Thus this leads to a decrease in the ability of the 4G network to connect all components of the smart network in remote locations. Recently, after the operation of the ultra-fast 5G switch, the process of transferring and processing data has become easy . Smart agriculture technology based on the Internet of Things technologies has many advantages related to all agricultural processes and practices in real-time, which include irrigation and plant protection, improving product quality, fertilization process control, and disease prediction, etc.. The advantages of smart agriculture can be summarized as follows: 1) Increasing the amount of real-time data on the crop, 2) Remote monitoring and controlling of farmers, 3) Controlling water and other natural resources, 4) Improving livestock management, 5)Accurate evaluation of soil and crops; 6)Improving agricultural production. This work aims to review published articles on the techniques above with regards to smart farming, in addition, highlight some approaches to smart farming in developing countries.The current work considered a large number of research topics to explore scientific methods relating to smart farming. Consequently, this work covered many aspects regarding the agricultural practices, decision-making, and technologies involved. We have used several sources from various scientific publishers such as Springer, Elsevier, Wiley, MDPI, etc. The sources varied from books, book chapters, conference proceedings, and articles, in addition to research project reports. Thus, this work has relied on 58 published documents, most of which were published during the last three years, and the authors from different countries worldwide. Meanwhile, a particular focus was dedicated to some smart agriculture approaches in the Africa continent. Subsequently, the review highlights the main components of smart farming, such as IoT, the role of internet connection, and smart sensing.

The average hatchability rate was 74%. This hatching rate was relatively similar to earlier report in Benin , dutch buckets but higher than what was observed in Zimbabwe as documented by Zvakare et al. . The average weight of guinea fowl obtained was lower than that obtained by Ogah in Nigeria, but higher than that reported in Ghana . This average weight varies by region. These variations in weight may be due to the environmental conditions which differ from one region to another and which can be favorable or not to the good growth of guinea fowls. In rural areas, a mortality rate of 10% was observed one week after hatching. This mortality rate could be as high as 22% at 3 months of age. To limit these mortalities, farmers used the bark and leaves of certain locally available plants which are macerated and included in the drinking water of guinea fowl. Some of these plants materials employed by farmers during the survey include Azadirachta indica and Khaya senegalensis. Old practices relating to the use of traditional medicine are still relevant because of the low income of farmers and their distance from urban centres. Nevertheless, the use of traditional medication still has its drawback in most cases due to non-precise diagnosis and medication dosage . Therefore, it would be necessary to verify the effectiveness of these ethno-veterinary plants in order to validate for a better recommendation . About the characterization of guinea fowl farming system, the results of the present study made it possible to identify four categories of guinea fowl farmers in Benin which differed based on location, sex, level of education, activity carried out and type of incubation. In Alibori region, where guinea fowl production in general constituted the primary occupation of respondents, followed by crop production, women were moderately involved in guinea fowl rearing. This result is explained by the involvement of more men in large ruminants production, which they believe was more profitable. In this region, the incubation of eggs was almost natural through the involvement of mother hens, ducks and turkeys.

On the other hand, women were fairly involved in guinea fowl farming in the region of Atacora where agriculture was the dominant activity but associated with guinea fowl production. Guinea fowl farming was mainly engaged in by men in Benin unlike the case of Zimbabwe where women were more involved in this sector. Individuals with a high level of education were involved in guinea fowl rearing as a secondary activity. These results suggest that guinea fowl production was mostly done by illiterates, who had more empirical experience in the field as also reported by Kwesisi et al. . In terms of comparison of the four groups of guinea fowl farmers, it can be deduced that cluster 3 showed the best performance. It is made up of mostly young farmers between 25 and 50 years of age with middle experience in guinea fowl breeding. Although most of the respondents in this group are represented in almost all regions, they are best found in the Borgou, Couffo and Mono regions. These guinea fowl farmers mostly adopt a semi-intensive breeding system and use artificial incubation to hatch their eggs better than others clusters. Cluster 4 farmers, who were better represented in Atlantique, Collines and Zou regions, took the second place based on these variables . The farmers in cluster 2 took the third position and those in cluster 1 who were relatively women occupy the last place in this classification. Any capacity building and support program should be aimed at these clusters of farmers in order to get more women involved in guinea fowl farming and ultimately increase the productivity of the species. However, in Botswana, Moreki et al. reported that women were mainly beneficiaries of guinea fowl projects. This situation, although deliberately targeted women, demonstrated that women can also raise guinea fowl. This last cluster had more illiterate farmers than all other groups. This is part of the reason for their poor performance. Nevertheless, this high rate of illiteracy, which is not peculiar to guinea fowl production, is a potential disadvantage for large-scale production of guinea fowl because of its negative influence on the adoption of new technologies .

Land reform programmes are initiatives in which nations attempt to correct inequalities in ownership and access to land, by re-allocating the land from the land-endowed to the landless , 2000; World Bank, 1975. Previous landowners may be compensated for their land, during the implementation of these initiatives. Globally, countries which implemented agrarian reform or land reform have struggled to attain synergy between the social and economic objectives of land reform programmes . In the past two decades, land reform implementation in South Africa experienced such a dilemma ; different sub-programmes were implemented with different objectives and a diversity of outcomes can be observed. In South Africa , the initial programmes were socially oriented, and this resulted in social diversity of new landowners. However, in recent years, the programmes aimed at establishing farmers with good economic performance by giving land mainly to those with financial resources to use it . Not only institutional drivers can be attributed to the existence of land reform farms since the farms also vary for example, in natural capital and physical capital endowments. Variations in institutional drivers, and natural and physical capital endowments of land reform farms are anticipated to influence agricultural land use and the success of policies and interventions implemented for further development of these farms . Farming system research is applied to better understand agricultural land use, its drivers and to design strategies for development . Further, farming system research focuses on decisions regarding production and consumption taken by a farming household . In this study, we consider a farming system to be “a population of individual farm systems that have broadly similar resource bases, enterprise patterns, household livelihoods and for which similar development strategies and interventions would be appropriate”.Identifying farming system types allows a shift from broader generalisation towards targeted, context-based development approaches based on identified challenges and opportunities, which may differ among types .

The types of variables used to explore farming system diversity vary and depend on the purpose of the classification . Farming system typologies are of two kinds: structural which focuses on structural variables and functional which focuses on decisions made by farmers regarding production and consumption . Statistical methods used to explore farming system diversity often include a combination of multivariate analysis with cluster analysis and Bayesian systems . These methods group farms around key characteristics with an aim to increase variation between groups and to decrease it within a group. To our knowledge, no studies have systematically classified farming system types in land reform farms of SA, grow bucket and we envisage that the results will contribute towards sustainable economic use of these farms. The aim of this study is to generate systemic knowledge on farming systems in land reform farms of the Waterberg District in South Africa . Towards this aim, we identified principal variables underlying the diversity in land use, classified farming system types, characterised the identified types, and analysed the drivers of the diversity among types. We conducted the study in the Waterberg District Municipality of the Limpopo Province, South Africa .In each of the surveyed farms, we targeted at least 15% of the ‘active households’ for data collection. A household was considered active when it had ‘at least one household member on a beneficiary list2 of a farm and also at least one household member involved in farm management or land use’. The distance between farms and the nearest urban centres were recorded and were considered proxy for ‘farm location’. Three locations were identified: the urban location at less than 16 km distance, peri-urban location between 16 and 40 km and rural location at above 40 km.

Using semi-structured questionnaires, we interviewed respondents who are either household heads or their representatives. We collected qualitative and quantitative data for the 2013/2014 agricultural year by asking recall data for the 12 months before the date of interview. Data about the agricultural activities being practiced being livestock farming , horticulture farming and crop farming , and combinations of these activities, and the land use associated with each of the agricultural activities, were collected under land use. Data about agricultural commodities produced, quantities produced, quantities sold and produce not for sale were collected under income generation. Data about the use of production factors and associated costs were collected under production costs. In the study area, production inputs were acquired mainly from formal markets, whereas agricultural produce was sold on both formal and informal markets. Remuneration of hired labour was pre-determined4 in this study, as it was governed by the Basic Conditions of Employment Amendment Act, no 20 of 2013 , 2014. This paper adopts the descriptions of formal and informal markets as given by Ferris et al. . Informal markets operate outside of the taxation system, with no prescribed quality standards and volumes of goods, whilst the opposite suffices for formal markets. Examples of informal markets for produce are sales which take place at farm gate, roadside, village and rural gathering, and examples of formal markets on the other hand, comprises retailers, fresh produce markets and livestock auction. For each of the agricultural commodities produced, data about the type of market used to sell the produce was collected under market type for produce. We conducted focus group discussions with representatives of active households to collect data about farm organisational arrangements, farm physical capital endowmentand households’ access to farms’ natural, physical, financial and social capitals. In farms owned by households individually, data about farm physical capital endowment was collected from the respondents. In instances where respondents were unsure, transect walks were taken to verify the existence of listed activities and to assess the extent of agricultural land use. To understand the drivers of farming systems, we cross-examined the findings of this study on farm organisational arrangements, farm physical capital endowment and market types for produce. The knowledge generated from those cross-examinations was used to make deductions about the influence which the aforementioned factors had on the presence and emergence of farming system types. Table 3 provides description of variables used for PCA.