horticulture – Page 36 – Nature Ecrogrow

The recruitment of refugees with an agricultural background proved to be almost impossible

Meanwhile, the proposals to consolidate oversight and implement regulations in a clear way will accommodate smaller firms and researchers, who do not have legal staff or experience with handling federal regulations. These stakeholders will face lower financial and time constraints.With a clearer and more streamlined process, the US will see a proliferation of GE crops. Small to mid-sized innovators may find niche markets in editing crops that lag in breeding efficiency. These benefits will be particularly fruitful for specialty crops like grapes, almonds, and pistachios that are ripe for rapid advancements. The US agricultural sector also awaits innovations that will increase adaptation to the worsening threats of climate change such as fire, drought, and flooding. If federal policy keeps up with these advancements by streamlining and demystifying regulations, the United States will benefit from crops that are safer, cheaper, and more resilient.Although Jewish agricultural settlements have had a long history in Latin America, particularly in Argentina and Brazil, those founded as a result of the panic emigration out of Europe on the heels of World War II are unique. Never before in the history of mankind had the leaders of thirty two nations gathered together in one location to collectively discuss the fate of countless Jewish people. Indeed, the 1938 International Conference at Évian-les-Bains in France, would give rise to the idea of having Jewish refugees settle as agricultural pioneers in lands distant from the turmoil that unfolded in Europe. Jewish refugees were given the opportunity to start life anew as agriculturalists, an occupation most unfamiliar to the Jew, who was, in the main, an urbanized professional or skilled craftsman. Torn from the relative comfort of their European homes by hostile Germans,low round pots the refugees attempted to build a new existence under the protection of host countries such as Bolivia and the Dominican Republic.

The success, or failure, of the refugee colonies of Sosúa in the Dominican Republic and Buena Tierra in Bolivia, is still being debated today, more than a half-century after their establishment, and in some ways provides a model for contemporary studies of similar crises that are currently unfolding in Africa and the Middle East. The property at Sosúa amounted to 26, 000 plus acres that had been abandoned by its former owners, the United Fruit Company, or the UFC. During its time in the hands of the international company, the lands were part of a larger banana plantation, and through the dealings of the Dominican dictator Rafael Leonidas Trujillo Molina; the massive property had become part of his vast business empire. It had some basic infrastructure that had been built for the UFC’s operations, which included some outbuildings and “over twenty houses, miles of fencing, some electricity, a few roads, and some running water, including a 50,000 gallon reservoir.”There were the remnants of a pier that the U.F.C. had built to ship the bananas that it had, with moderate success, grown in the shallow soil at Sosúa. The property sported incredible views of the blue Caribbean just beyond a crescent-shaped, pristine white sand beach that stretched for about eight miles along the coast and inland for seven miles framing Sosúa Bay. Its waters, being mostly calm year round, were a most welcome sight and an invitation to take advantage of the diversions that ocean sports offered. One could take a leisurely stroll down one of the paths to the beach, take a pleasant dive or swim, and even fish within Sosúa Bay’s placid waters. Indeed, there would be settlers who disdained farm work and spent the bulk of their time enjoying the warm tropical weather sunbathing at Sosúa beach. Joseph Rosen and others of his team had scoured the island looking for appropriate properties on which to resettle the refugees. Some of the properties that Rosen’s team had surveyed proved to be less than desirable; however, the Sosúa tract held some promise.

It had some cultivable land that the UFC had previously utilized as a banana plantation, and some very basic infrastructure. The American analysts, under Rosen’s direction “explored lands, half of which Trujillo owned, that Dominican officials offered for settlement [that was] suitable for settlement of more than 28,000 families. Because of the difficulties of starting new settlements and uncertainties about which crops settlers would produce, they recommended starting with a modest pilot project.” Among the scholars who have written about Sosúa, there exist slight discrepancies in the data including the size of the plot. Some scholars such as Bruman listed the size of the settlement at 27,000 acres, while others such as Kaplan and Wells have pegged the acreage at 26,000. For the sake of consistency we use the figure of 26,000 acres because it is the figure most often used. Joseph Rosen’s analysts had, in all probability, located better plots for the establishment of refugee settlements, however, the sway of Trujillo, and the fact that he had ownership of the Sosúa property, dictated that Rosen choose Sosúa as the site for the Republic’s first agricultural settlement of Jewish political refugees. The Sosúa site proved to have just a fraction of its land fit for cultivation. It had rocky outcrops and a lack of water, two obstacles to be dealt with should the settlement thrive. James Rosenburg, Rosen’s partner and the president of DORSA, incorporated in New York in December 1939, negotiated with Trujillo for the property. DORSA had as its mission the financing of the Jewish settlement at Sosúa. Together with other Jewish philanthropies such as the Joint, and the Agro-Joint, or the American Jewish Joint Agricultural Organization, DORSA collected funds and made studies of possible settlement sites. Rosenburg did not want to accept the property as a gift from Trujillo, insisting instead on purchasing it. The dictator claimed that he purchased the property from the United Fruit Company after the company had abandoned the former banana plantation. “Trujillo had allegedly bought the land from the United Fruit Company. He maintained that it had cost him $56,000…that he had put another $10,000 into it, but offered the land with buildings on any terms.”

The historian Allen Wells, in his monograph Tropical Zion, General Trujillo, F.D.R., and the Jews of Sosúa, has stated that Trujillo had purchased the property from the U.F.C. for the modest sum of $50,000. The international company had sold the property to Trujillo “in appreciation for the protection he afforded when he was head of the army.”However, Trujillo had no intention of turning the plot into agricultural land and looked to turning Sosúa into a cattle ranch.According to Metz, “Trujillo had originally obtained the lands that were to become Sosúa in an “irregular way.’ The foreign impression was that he donated lands to Jews at Sosúa, whereas, according to the ‘Dominican version,’ Trujillo had inexpensively purchased the properties under United Fruit Company pressure and then sold them at a significant profit in cash and stock to DORSA. What is certain is that Trujillo collected from DORSA one million dollars for this land.”However, in a letter from James Rosenberg addressed to ‘His Excellency, Rafael L. Trujillo’, dated June 25, 1951, more than a decade after its founding, Rosenberg gave thanks to the President for the gift of land at Sosúa. “Never, as long as I live, will I forget the day when I received your letter at Sosúa in which you gave our Association your land now occupied by the settlers. Faithfully yours, James N. Rosenberg.”This is not the first reference that Rosenberg makes regarding the Sosúa lands as being a gift from Trujillo to DORSA. In another piece of correspondence from Rosenberg to ‘His Excellency, Generalíssimo Rafael Leonidas Trujillo Molina, Commander-in-Chief of the Armed Forces of the Dominican Republic’ and dated February 8, 1957, Rosenberg praised Trujillo for his “noble gift of the Sosúa property.”The friendship that developed between Rosenberg and Trujillo began much earlier, as is evidenced in a letter to Trujillo from Rosenberg dated May 20, 1940, almost two years after the international conference at Évian les Bains. Rosenberg addressed Trujillo as “My Dear Generalíssimo,” and thanked him for “your service to the cause of humanity in these dark and tragic hours.”The two men were to become more than just collaborators; they became close friends and looked to each other for advice,plastic pots 30 liters diversion and guidance. The geographers Richard Symanski and Nancy Burley, in their 1973 paper published in the Annals of the Association of American Geographers; state that the purchase price of the land at Sosúa was $100,000 in stock in DORSA.10 Then again, Rosenberg and Rosen did not want to accept the lands at Sosúa as a gift, but preferred that Trujillo exchange the land for a fixed amount of stock in DORSA. It was agreed upon that the Trujillo would be given shares which had a value of approximately $100,000 U.S.D., in spite of his desire to present the land at Sosúa to DORSA as a gift without any strings attached. Rosenberg’s Diary I has details of the negotiations leading up to the signing of the contract that transferred the title of the property to DORSA in 1940.

The negotiations transpired over a period of weeks with some of them taking place over cocktails at one of Trujillo’s many parties. Indeed, Rosenberg’s diary is replete with personal observations of these lively assemblies. Reading it one is left with a mental picture of elegant balls, luncheons and official state dinners. Then again, Trujillo had a reputation as a social carouser and loved to be at the center of attention.Rosenburg wanted to avoid any negative perception that would certainly accompany any gift of Dominican property to DORSA. Both Rosen and Rosenberg wanted to foster an image of independence, that the Jewish refugees were not a charity case looking for free handouts and were able to stand on their own. It was widely believed that the Jew abhorred physical labor of any type, preferring the urban environs to the slow, seasonal rhythms of rural farms. Trujillo’s sale of the Sosúa property would give the Jewish refugees the opportunity to prove that they were a hardy folk who could withstand the privations that came with an agricultural and rural life. Long periods of isolation and hard work were preferable to the alternative of imprisonment and certain death at the hands of the hated Nazis. Again, Trujillo wanted to allow only those refugees with an agricultural background into the Dominican Republic. A consensus was reached between Trujillo and DORSA which called for only strong and able young males and couples to begin the settlement at Sosúa. Indeed, many of the refugees who sought visas to the Dominican Republic “had no interest in working on less than fertile land [and] lacked the skills, inclination or physical capacity for farm work. Most refugees could not transform themselves into plausible farmers.”El Generalíssimo Trujillo relaxed his previous stipulations which called for settlers with agricultural skill sets, writing that “no settler should become a financial burden on the state.”One refugee couple, who wished to immigrate to the Dominican Republic from their temporary residence in London, was told by an American, Solomon Trone, who “came to sign up people willing to settle in Sosúa that he could arrange for anybody willing to go to Sosúa to be released. In spite of their total lack of agricultural skills, the couple was told by one who had already made the journey to Sosúa that “Nobody in Sosúa knows anything. You just start applying for a place.”Rosen had a well-established track record regarding the founding of Jewish agricultural settlements, and the academic credentials to allow him access to the checkbooks of Jewish philanthropies and donors. Born in Moscow in 1877, Rosen came to America in 1903, landing in New York virtually penniless. Rosen worked at several different odd jobs to feed, clothe and house himself. He eventually went west in search of better opportunities, and found employment at a farm in Lansing, Michigan, where he worked for two years. In 1905, Rosen enrolled in the Michigan Agricultural College-now Michigan State University in East Lansing, as a special student. During his pursuit of an education at the school he worked as an assistant at the college library, and also wrote several articles on American agriculture for different Russian publications.

The respondent further underscores the need for precise models dealing with biology and living animals

Some respondents from the larger companies and cooperatives suggest that the attitudes might be affected by the perceived inconvenience that data gathering causes.They all believe that more farmers would have a positive view on it if it was made easier for them to collect it.However, there is also a sense that the data is not used optimally, partly because it is saved in different databases that are not interconnected.The responses from the respondents indicate that data is being gathered differently depending on the agricultural sector.For instance, many respondents in the dairy section state that there is a lot of data gathered, to a high degree on an individual level, on the farm animals.In contrast, arable farmers also collect data on almost all farms, but that data is not always as detailed.An arable farmer may collect remote sensing satellite data on its farm, but sometimes not with a resolution of square meters, but rather on a field or even farm level.The inputs, i.e.the resources added to the soil, are what would be interesting for the farmer to get decision support on, if one could see a beneficial correlation between input and output.One responding farmer with previous experience from the tech industry, believes that the problem with applying AI to arable farming is the lacking volume of interconnected data.The whole data chain is not connected today, he states.In practice, the input data taken during, for example, arable seeding is not properly connected to the output of the harvest.Additionally, the insights from the harvest are not used as a decision basis for the next seeding.Thus, the data loop is not closed, which it would need to be for AI to be efficient.This data gap combined with the large amount of uncertainty factors, such as unpredictable weather, is a technical hindrance to the learning of AI models.In the field of AI and machine learning, there is an important tradeoff between bias and variance.In the interviews, the respondents had different opinions on the matter.The concept was discussed with the respondents as ‘generalizability’ and ‘precision’ instead of their technical terms.Some respondents say that precision is extremely important since a technical solution that only predicts or detects something half of the time is useless.At the same time,hydroponic grow system other respondents say that as long as the predictions are slightly better than human predictions or detections then the model can be as general as one wants.

In fact, many respondents claim that there is a much larger market for standardized models than the ones that are too adapted after local needs.There is a tendency among arable farmers and corporations that they tolerate a higher degree of generalizability while livestock farmers need more precision.A respondent in the livestock farming sector claims that a farm would never really benefit from a technical solution that could only detect rut among the animals one out of three times.Of course, many respondents bring up that there is a need for balance between generalizability and precision, and that it would be optimal if there was some degree of customizability in that aspect so that each solution can fit each farm.One key concern for the development of smart farming technologies is ownership of the data.Most smart farming systems are created as closed technological ecosystems, with limited possibilities of sharing data in between each other.This technological segregation hinders the systems to share data with each other and is thereby an obstacle to the interconnection between systems.Descending from the rivalry between the major transnational agricultural technology companies, including the quest to both pin the users to their specific technological ecosystems and avoid giving their rivals a chance to create competitive technology, this structure is difficult to change.With that said, two respondents note a tendency for transnational agricultural technology companies to move away from technology that ensnares the user to their ecosystem, to more open data flow.Such open data flow is believed to create more value for the businesses and their users.Consequently, a higher degree of data is expected to be on open standards.Even if the companies providing the technology make some progress towards open data sharing, a couple of projects are created to facilitate the data sharing compatibility.GigaCow, a research project by the agricultural university SLU on data for dairy farms, aims to enable data sharing by automatically exporting the data from different milk robots over time.Such initiatives are welcome to most farmers.However, this is a third-party work-around solution and not as straight-forward as if all machines would automatically be open for data sharing.

Some respondents lift the potential threat towards online IT systems as a risk when implementing new smart farming technology.The risk of being hacked poses a threat both to farmers and to society at large.Focusing on society at large, a respondent from a governmental agency describes cyber security as a particularly important aspect of digitalization in agriculture.This respondent believes that such a data platform probably would be classified with an extremely high security and secrecy label and be managed by the Swedish Security Service SÄPO.Therefore, this could be regarded as a clear barrier for the development process of a common data platform.Nevertheless, the respondent adds that in case of potential cyber-threats it would be better to have the data stored on a common platform than with individual farmers, since people would be managing and looking after the platform to a much higher degree than farmers currently are securing their data.Even though these issues are mostly raised by the larger organizations and authorities, the threat is also acknowledged by some farmers.They believe that connected data platforms with weak security make the farm quite vulnerable to threats.However, one farmer commented that “it is not worse than having all money in a bank account, and that I trust today.”.Other respondents, both governmental agencies and farmers, recognize the IT systems as possibly vulnerable but are not necessarily worried.Instead, they reject the belief that lacking cyber security would pose a greater threat to agriculture than to any other sector in society.When it comes to digitalization of such a fundamental societal system such as the agricultural sector, many strategic decisions are of nationwide interest.Some of the interviewed respondents from larger organizations and authorities believe that there is a wide interest that the agricultural sector becomes smarter.However, farmers are themselves accountable for making this technological transition.Two respondents argue that there is a lack of initiatives from the state or from the large organizations to drive the propagation of digitalization forward in a structured manner.One respondent, working at a governmental authority, addresses the topic of nationwide interest in digitalizing the agricultural sector , stating that AI in agriculture is a natural step moving forward.The respondent says that there are a lot of internal discussions in governmental agencies regarding if and how they should take a more active leadership role in the digitalization of Swedish agriculture.The governmental official thinks that Sweden is behind with its digital development compared to other countries with weaker economic conditions and budgets for agriculture.

A natural first step, according to this respondent, is to create a common national data platform for all agricultural data to be compiled on.Still, this respondent sees no clear political ambition driving this change, while this could speed up the digital transition tremendously.Although there is no wish to ‘force’ farmers into using agricultural technology and digitalizing their businesses, it is a likely progress if there is a nationwide and political interest in going in that direction.As in any other industry, the agricultural sector is driven by the quest for increased profit.Money is a motivator, not only for larger agricultural enterprises but also for farmers.Therefore, the general low profitability in agriculture is a major problem for farmers.Optimization plays an important role for the often unprofitable Swedish agricultural farms to be competitive on the world market.Even though there are lots of subsidies connected to food in the European agricultural system, no farmer respondents recognize any subsidies for investments in new technologies at a farm-level.Instead, the technological transition that is supposed to lead to more sustainable food production or larger output is financed by the individual farmer.different farmers have distinct economic incentives to implement smart farming technologies in their work.Generally, there is one group of farmers that have less reason to care about implementing new technologies since they will have structures in place to reach their revenue in any case.This group often owns their own property and farmland.On the other hand, there are farmers that lease their farmland and therefore constantly must become more and more effective.It is not only a matter of farm ownership though, also the size of the farm affects the probability that smart farming technologies will increase profitability.With a small farm, farmer respondents believe it is difficult to profit from smart farming techniques.A farmer with a small farm describes that he cannot afford buying new equipment, such as a new tractor, himself.Upgrading the machine park is necessary for smart farming technologies to gather enough useful data.This can be linked to the major macro trend of consolidation of farms.Basically, this means that smaller farms cannot afford to compete with the larger ones that can use their competitive advantages of being larger.There is simply not enough profit in managing most small farms, a problem which forces many farmers to merge with neighboring farms.Another trend that impacts the agricultural sector is how technologies are sold and distributed.Today, indoor garden most technology is bought as a hardware which is often a huge expense for the farmer.However, slowly things are changing.There is a transition happening towards services being bought as ‘Software as a Service’ solutions.This allows for business models in which the sold hardware is much cheaper than today or even provided at no cost, while the farmer pays a fee to subscribe for using the set of hardware and software.One respondent from an agricultural cooperative foresees that this change will have major implications and wonders whether, in ten years from now, tractors will be sold solely as a rental service instead of as a product.To enable this, an enormous amount of data will be needed.

One communicated and discussed concern about implementation of smart farming technologies is the dependency it might create towards technology.Dependency on technology refers to a system that relies on automated or semi-automated activities based on often incomprehensible software, a constant power supply or Internet-access.The system itself is not problematic to any of the respondents.However, there are some concerns regarding the cases when this type of system fails.One respondent, from an organization, states that the usefulness of the system would be compromised if the communication infrastructure would somehow break.The concern is expressed in different ways and with different urgency.Livestock farmers express their concern about this since their activities revolve around living beings, whose comfort and health rely on the technological systems continuing to operate.Also, when it comes to dependency on technology, another aspect that several respondents mention is that some practical knowledge among farmers and advisors might be forgotten.One responding farmer believes that if he applies too much technology to his farm he would risk losing some of the local, tacit knowledge of the farm.Particularly, some local variations of the farmland he finds difficult to represent correctly with data.Since there are a vast number of connected parameters affecting how a crop at a specific place will grow, he fears that a program could miss some critical aspects.This may be linked to a certain expressed mistrust towards technology, that it needs to be double checked to make sure it is doing the right thing while working autonomously.In general, there is a positive attitude towards smart farming and what it could mean, to the agricultural sector as a whole and to farmers specifically.Incorporating smart farming technologies could mean that time and costs for activities, such as irrigating and fertilizing, are reduced.Therefore, farmers can better manage their time when using well-functioning new technology.One positive side effect of this is an improved work environment for the employees.With that in mind, researcher respondent R2 states that farmers are generally bad at valuing their time spent compared to the economic return.

The specific transformation pathways that farms take can be conceptualised in terms of resilience

Resilience refers to the capacity of social-ecological systems to fulfil their function in changing conditions, thus withstanding disturbances and being able to adapt and transform while delivering on their main goal . Although resilience is sometimes portrayed as stability, resilient systems can—and should be able to—transform. The strategies through which a social-ecological system may retain its resilience can be characterised in terms of persistence or robustness, adaptability, and transformability . Robustness refers to the capacity of the system “to withstand stresses and anticipated shocks” . Adaptability, in turn, entails “the capacity of actors in a system to influence resilience” by, for example, changing “the composition of inputs, production, marketing and risk management in response to shocks and stresses but without changing the structures and feedback mechanisms of the farming system” . Lastly, transformability is about “the capacity to create a fundamentally new system when ecological, economic, or social structures make the existing system untenable” . Such changes can imply a changing function of the farming system . A farm system may employ different resilience strategies over time. The food system and the embedded farm systems are in a flux of constant interaction: the dynamics on both levels condition each other. The employed resilience strategy depends on the transformative capacities of the farm and the farmer—what they can do with the resources they have. This makes resilience a question of agency and power. In a situation where the regime is strongly locked-in, farmers’ choice space becomes substantially limited .

The pressures are manifest in how farmers are acting mostly as price-takers and carry the responsibility for mitigating environmental impacts in the food system . However,flower pot not all farmers are similarly affected by transition processes, which calls for analyses of the transformation pathways accessible to farms. Agency and power are longstanding areas of research in social sciences. Agency can be seen as the actors’ capacity to act, and it constitutes power, intentionality, freedom of choice and reflexivity . Power, in turn, is understood here as “the capacity of actors to mobilise resources and institutions to achieve a goal” . When resilience is understood as the capacity of a system to achieve its goal, the notion of power in achieving that goal is central to the analysis of resilience. Resilience requires adaptive capacity, which refers to the potential of system agents to fulfil their goals, act independently, and exert their own agency . As such, the concept of adaptive capacity is practically identical to the concept of social power. Analyses of resilience and adaptive capacity at the level of farm systems require identifying the kinds of goals farmers hold regarding food production, the resources available, as well as the capacities to utilise them to achieve those goals . Thus, even though the concept of resilience has sometimes been used without being attentive to the societal context, questions of regime reproduction, or social power , it holds potential in analysing questions of agency, power, and social justice related to systemic transformations As systems may employ very different strategies to retain their resilience, it is presumed that system actors also employ different capacities in accordance with their resilience strategy. Avelino argues that transformative capacities are different from capacities that reproduce the existing structures, as in the case of persistent or adaptive versus transformative types of resilience.

According to Patterson et al. , “Transformative adaptation approaches take as a starting point that power relations condition the options available to marginal and vulnerable groups to shape their own desirable futures, thus requiring keen attention to issues of social difference, power, and knowledge.” Tribaldos and Kortetm¨ aki see capacity development as a criterion for a just transition in the sense of whether food system actors can respond to transition pressures. Thus, resilience capacities depend on what people can do and be with those resources and goods they possess or have access to . How farmers as system actors employ their capacities is a function of their internal goals and the external conditions defined by the food system . When the distributive effects of external conditions fall unequally upon the food system actors, restorative justice can reveal new perspectives on mitigating these effects. Restorative justice approach is traditionally understood as a non-adversarial response to harm and conflict that derives from violations of law, rules, ethics, or a general sense of moral obligation . The concept originates from criminal justice studies seeking to repair the damage and restore the dignity and well-being of all those involved in causing harm . However, restorative justice has increasingly been acknowledged in the field of sustainability, particularly from the perspective of energy transition, nature conservation, food transition and human rights . The common characterisations of restorative justice emphasise face-to-face dialogue between different parties configured as offenders or perpetrators of harm and the subjects-of-harm . The latter is often conceptualised as a “victim”, a condition under which agency and relationship with offenders are to be transformed. The process of restorative justice involves a reactive mechanism to address the damage already done. In other words, the process seeks to restore justice within the structures of the existing system. Accordingly, the individual is expected to undergo a transformation process while the surrounding system does not change.

Recent proactive approaches to restorative justice have emphasised more anticipatory elements of restorative justice. This means involving a range of actors and adopting a forward-looking approach that is both preventive and strategic . However, to be genuinely proactive and transformative, justice cannot be achieved by restoring the status quo ex ante . We further argue that the main challenge of restorative justice during systemic changes is that the transformation is not only about individuals but the system itself. Thus, individuals cannot be easily ‘restored’ with the logic of a system on the move. In systemic transitions, this would mean that those at risk of becoming ‘transition victims’ should also have the opportunity not to become ones. However, the application of the restorative approach to sustainability transition is not unproblematic, as the actors who fall victim to the transition processes have at the same time contributed to the problems that call for a transition in the first place. To what extent this contribution can be credited to the deliberate choices of the actors or just to them operating by the rules of the game remains debated. However, the current financial position of farmers suggests that the system itself is the most crucial factor in delimiting their choice space. The just food transition poses a fundamental challenge to restorative justice; the food system itself is enduring a major transformation which is also expected from the actors within the system. We argue that a genuinely transformative and proactive approach to restorative justice should aim at resilience and capacity building not only in terms of the existing system, but also in terms of the systemic transformation. We now move on to examine farmers’ transformative capacities and then discuss our findings from the perspective of restorative justice. The research area in Eastern Finland comprises three provinces: North and South Savo and North Karelia . The area is characterised by a sparse settlement structure and rather unfavourable socio-economic development patterns. The area adds up to 18% of the total area in Finland and 10% of the total population, with 557,000 inhabitants.

On average, the farms in Eastern Finland are smaller than the national average, and the fields tend to be fragmented into small plots. The share of utilised agricultural area in Eastern Finland is 5% of the total area in comparison with the Finnish average of 7.4% . The climatic conditions and soil properties are particularly suitable for grass production, and consequently, the role of cattle production is pronounced with 33% of all farms in Eastern Finland being cattle farms in comparison with the Finnish average of 20% . A significant share of the yields produced on crop farms are used for feed on cattle farms in the area . Regarding farm sales,berry pots in Eastern Finland 68% comprises animal products in comparison with the 58% average of mainland Finland . This study is based on survey data collected during the mid-term evaluation of the 2014–2020 Rural Development Program of Eastern Finland . The programme addresses a wide range of social, economic, and environmental issues of farms and rural areas by channelling the funds of the second pillar of the EU’s Common Agricultural Policy for farmers, rural firms, and non-profit organisations. A survey request was sent to all farmers in Eastern Finland who had received agricultural support from the programme and who had registered an email address in the IACS farm register . All active farmers in Eastern Finland with at least 5 hectares of arable land are entitled to LFA support, and in Finland, the support encompasses nearly all agricultural land . As a result, 577 responses were retrieved, with a response rate of 9% despite several requests to fill out the questionnaire. The low response rate was partly due to unfavourable timing of the survey at the beginning of spring but is in line with many recent farmer surveys conducted in Finland. The survey addressed issues related to the farm and its production activities, the farmer and the farming family, farming as a livelihood, environmental aspects related to farm management, and the main types of subsidies received and their perceived effectiveness. The basic characteristics of the surveyed farms are presented in Appendix 1 in comparison with all farms in Eastern Finland and all farms in mainland Finland. The survey respondents farmed slightly larger farms than farmers in the area on average but were broadly representative of farmers in the area.

Most of the survey respondents were cattle farmers , followed by other crops and cereal production . Garden crops, especially strawberry and currant, are typical crops in eastern Finland and had a share of 9% in the dataset. We operationalised the concept of resilience according to the three dimensions of resilience: persistence, adaptability, and transformability. In addition, we also identified a non-resilient group. The operationalisation strategy was based on three variables: 1) the future strategic orientation stated by the farmer , 2) an additional open question related to the farmer’s strategic orientation asking the respondent to specify his or her plans, and 3) freely expressed goals for farming . Out of the 577 responses, 575 were analysable in terms of resilience; thus, the final dataset consisted of 575 responses. Coding farm resilience was an iterative process between the three variables. Table 1 presents the coding principles for each resilience group. In short, a farm was coded as persistent when the farmer aimed at business-as-usual and did not indicate development intentions. Those farms that aimed at developing the farm within the existing operations were coded as adaptable. Transformable farms indicated a deliberate search for a new direction for the farm business by diversifying the farm operations or doing something new in comparison with the existing operations. Non-resilient farms aimed to quit farming by retirement or moving into another business; they did not have successors and their intention was to lease or afforest the fields. The resulting four farm groups with diverging resilience orientations were profiled in terms of variables concerning the farm and its production activities , the farmer and the farming family , farming as a livelihood , environmental aspects related to farm management , and the main types of subsidies received and their perceived effectiveness , adoption of agri-environmental contracts, investment support, organic farming, extension support. These variables reflect the availability of resources, as well as how farmers make use of them and how they relate to environmental management at the farm level, reflecting the mobilisation of environmental values and motivations. A complete list of the variables included in the analysis is given in Appendix 2. To determine whether the differences between the resilience groups were statistically significant, ANOVA tests were performed for continuous variables for the comparison of means, and contingency tests were performed for categorical and dummy variables for comparison of the distributions.

Reproduction control is another important tool for flock management in dairy sheep

With average costs of roughly 1.50€ per each tag, it is the cheapest method among the three. However, it suffers from one disadvantage which could lead to several problems. Its application to the ear lobe of the sheep increases its possibility to be lost due to entanglement in bushes, trees fences, etc. Another problem has to do with the ease of removal of the tag, a practice used in various fraudulent activities regarding animal identifications and could be avoided using irremovable animal tagging systems. In case of tag losses, new tags are to be applied, which not only causes additional administrative work but also impacts the welfare of the sheep which have to undergo another piercing of the ear.In this case, the EID is enclosed in a ceramic bolus, which is then inserted into the sheep’s rumen using a designated tool . Although having a slightly higher cost of about 4–5€, its main advantage is its permanence and very low malfunction and loss rate. Boluses have widespread use and are currently applied routinely in many commercial farms. It is however a more complicated EID to insert, with sheep needing to reach a certain age in order to safely receive the bolus. Size reduction and proper insertion by trained personnel mitigate these problems, with the bolus total size and length being a key factor. As shown by Hentz et al. , smaller boluses could be inserted safely and efficiently to smaller ewes while retaining the internal positioning and reliability.Widely used in house pets and horses for animal identification, its use in livestock although permitted is very limited . The main reason for its limited use is the difficulty to remove the EID in the abattoir,and the tendency of early models to migrate from the original region of injection.Different studies however show limited migration patterns of modern glass and silicone enclosed injectable EIDs during their use in field conditions.A particular advantage of injectable EID is the possibility of it being used not only as passive information storage but also as a sensor for physiological parameters.

The use of temperature detecting injectable passive RFID/ EIDs is widespread in the management of smaller laboratory animals and was tested on bigger farm animals under different conditions . Its use in sheep has been shown to provide highly correlating data to that of core temperature measured via rectal thermometry. This concept is, however, stackable flower pots still in the experimental stage and its future applications are uncertain.Sensors applied on the individual animal are one of the key principles of PLF with tools such as pedometers and rumination tags are well known to dairy cattle farmers. They provide information on animal’s physiological conditions whether in real time or via data loggers downloading in key passages . These sensors collect data from the animal and translate it into physiologic status such as ovulation or lameness relevant to farm management . In case of extensive sheep farming, wearable sensors have been experimented in small-scale-controlled conditions as well as experimental farms . The main objectives of these sensors are to evaluate grazing and resting behaviours, which provide information regarding grazing patterns and feed intake as well as animal position and movement of the flock . Currently, two main types of technology are being tried in this field: accelerometers, especially the tri-axial type, and GPS systems. The third use of active sensors is in the case of social networks and behaviour such as heat and mating identification. Being a seasonal breeding species, a big focus in Mediterranean production is dedicated to out of the season mating in order to maintain constant milk production in contrast to the sheep’s natural cycle . Currently, a common practice is the use of a harness on the flock rams with colour for visual identification of covered ewes; however, the use of electronic activity logger is being tested .A system that measures movement in terms of the direction and speed of the sensor is attached to the foot, neck or head of the sheep. Evaluated by the software first, data are provided to the producer to assist in decision making .

The most useful data come from three axial accelerometers which record movement in a three-dimensional pattern. Field trials confirm the ability of such accelerometers to register movement patterns linked to behaviours such as resting, grazing, moving and running/playing or lameness . Even though accelerometers could be considered technologically matured, data interpretation and validation is still a subject for field research . Meanwhile, the collection and management of the data as well as energy supply to systems in the field present a big challenge for a widespread application. In recent years, the amount of research put into this system is growing increasingly especially in attempt to take a research ready prototype into commercial production . Therefore, accelerometers could represent in the near future a viable product.Especially when paired with geographic information system , it provides information on animal movement and disposition in certain geographical areas. Such a system could help evaluate the movement of sheep in a vast grazing area, between water sources, low and high land and in response to the presence of predators or wild herbivores . In the work of de Virgilio et al. , combined use of accelerometers and GPS/GIS was proposed as a PLF option for sustainable range land management. Such systems, however, are not yet operational in commercial farming due to relative high cost of each sensor and the need for high energy supply . Also, information gathered by the systems still needs interpretation and given the right value in a decision-making process.In a recent study by Mozo et al. , tri-axial was used accelerometer with specific software to detect rams’ mating activity providing a possible tool to measure service capacity of rams. A more mature system is the electronic Alpha-Detector which includes a harness for the ram with an active reader and transmitter which detects the ewes’ EID and transmits the data to a centralized computer. The transmitted data could be interpreted for frequency of mating, true and false coverings and the number of ewes covered. This system has currently passed the research phase and is being tried in field conditions for commercial production .

Other technologies include a concept produced by Laca regarding extensive management of animals which incorporates GPS, satellite communication of data from ‘mother collars’, short distance communication between the animals’ collars and feed management based on the elaborated data. The system is very complex and requires both costly technologies and knowledge of the herd dynamics for the identification of key individuals in their respective groups . The feasibility of such system is becoming widespread in Mediterranean dairy sheep farming due to cost and complexity, but may be relevant for other types of extensive farming that use larger grazing areas , or less contact with the animal . Other sensors include microphone and sound analysis of chewing sheep and monitoring urination in sheep and cattle in order to determine liquid and nitrogen emissions. However, the systems were only described as an experimental process and not yet ready for field implementation.Stationary sensors are another key element in the PLF concept, with different types of sensors such as temperature sensors, cameras, weights and automatic feeders are placed in key locations of a barn . These sensors collect data and usually communicate with the animals’ EIDs, providing real-time data for each single animal to feedback systems . In extensive sheep farming, there are several stationary tools such as AD, weighting crates or a walk over weight system. Although the systems are extensively tested and reached advanced stages of development, they are not yet accepted by dairy sheep farmers for widespread commercial use .An AD, in simple terms, is an automat system centred around a selective gate with the ability to distinguish and direct the passage of animals. Most of the AD systems are based on the recognition of animals’ EIDs as the selective criteria. In extensive sheep farm, ADs and EIDs could be used together not only for data collection and feeding control but also as a tool to reduce manual labour for the flock . Animal selection is one of the most labour intensive activities on the farm, especially in events such as sheering, parasite treatments and selection for sale.

Automatic drafters could also be coupled with weighting systems in order to measure the condition of a single sheep, directing lower weight animals towards supplemented feeding areas accordingly .Originally developed for grazing cattle, both systems were consequently adopted and modified of sheep farming as well. The WOW was tried in field conditions where it proved its efficiency, consequently expanding its use to sheep management . The system includes a one-way passage leading to a key stimulant which the animals are forced to pass through. The weighting platform is placed in this corridor, and it communicates with the animals’ EIDs on each passage. Data regarding each single sheep are stored and could be matched against similar passages in a single day creating a more reliable result. When used by itself, the WOW system helps to reduce labour with fewer personal needed for animal sorting activity while pairing it with AD systems can allow better control on supplementation feeding . This combination has been proven to be efficient in several studies as presented by a recent review by Rutter and by Gonzalez-Garcia et al. , making it a viable instrument for farm management. The WC on the other hand is used by actively separating single animal by operator closing doors in a passage corridor. This way, each animal is weighted standing still and isolated from others. In the WC, the RFID identification could be done both by handheld transponders or by fixed reading antennas,flower pots for sale consequentially allowing the analysation of data in real time. Commercial models are already available on the market . The collected data could be used for various purposes such as ensuring lambs are ready for sale or anthelmintic treatments. The last use is of particular importance considering the growing awareness to the amount of anthelmintic resistant parasites in grazing sheep and the health implications derived from it . For this purpose, coupling the WC with a self-dosing fluid dispenser is a currently viable option with commercial products already on the market such as Te Pari fluid dispenser .

Virtual fencing is an innovative method for extensive animal management that replaces physical barriers with electronically placed boundaries. Animals are prevented from passage by a system of visible and/or audible cues combined with electric stimulus. Although VF is not able to provide a full sealing of an area, its flexibility and potential applications has attracted a growing amount of researches as well as stimulating commercial development with products such as BoviGuard, NoFence and eShepherd™. The main advantage of such a system is not the complete exclusion of animals from certain areas, but rather the possibility VF provides to guide and move the animals according to pasture availability . However, VF cannot completely replace all fences, as the hermetic exclusion of animal is impossible without physical barrier. Therefore, due to security reasons and property rights , the external fences of the pasture remain necessary. By using visible and audio cues prior to the electric stimulus VF systems are aiming to condition the animals to understand the limits of their area. Although there is a variability among the individual animals in understanding these limits, as a group the herd maintains its position . There are several factors however, which limit the adoption of VF systems on commercial farms. The first is its cost, although the cost of the system was estimated in 200 000 £ for 100 animals in UK, its difference is not as big in comparison with traditional fencing costs in the same country . However, VF cannot completely replace traditional fencing and a combined use will be always needed . Another weakness is the lack of technological infrastructure in sheep farms ; this includes network coverage and IT-related skills and understanding. Without this, farmers may find it difficult to trust hi-tech systems .

The need for labor for instance depends on the level of automatization in agriculture

This is why after assessing critical thresholds, participants should also be stimulated to think about adaptations to improve their system to desired sustainability and resilience levels . Be it by steering away or actual exceeding critical thresholds to arrive at higher sustainability levels. Paas et al. suggest a back-casting approach, but other solution-oriented methods such as participatory multi-criteria decision analysis may also be appropriate . In any case, starting with a threshold assessment before solution-oriented participatory methods may create path-dependency, resulting in adaptations that lead to a reconfirmation of the current system where a transformation might actually be more appropriate. This path-dependency is likely to be reinforced by only inviting participants from within the farming system. Farming system actors are for instance probably biased regarding depopulation and a loss of attractiveness of the rural area, as it is related to farm closure. Considering the possibility that the closure of individual farms could be good for the farming system as a whole might go beyond the mental models of some farming system actors. Participatory methods involving so-called “critical friends” that have no direct stake in the system might help to overcome this obstacle . Involving external actors is especially required in unsustainable systems that persist through the agency of only a subset of stakeholders. It should be noted that critical thresholds are never static as they depend on the context .Critical thresholds may change because of slowly changing variables , which is also acknowledged in this study by presenting interacting thresholds across levels and domains in multiple case studies. Different domains could be addressed by including a variety of social, dutch bucket hydroponic economic, institutional and environmental challenges, function indicators and resilience attributes.

Using the framework of Kinzig et al. forced in particular researchers in some case studies to reflect on critical thresholds in the social domain, while focus of participants was more on economic and environmental processes. The framework of Kinzig et al. can hence show where knowledge of stakeholders is limited. This is an asset as exposing the limits of local knowledge is often lacking in participatory settings . Explicitly adding the institutional domain and a level beyond the farming system to the framework of Kinzig et al. may further reveal the limits of knowledge and improve the understanding of farming system dynamics. To further stimulate co-production of knowledge, the figures with interacting thresholds could be fed back to farming system stakeholders in a follow-up workshop. In addition, farming system actors could be stimulated to think about representative indicators for resilience attributes. These representative indicators could add local meaning and thus improve stakeholders’ understanding and assessment of the resilience attributes and resilience mechanisms . Becoming aware about a threshold can help reducing the likelihood of exceeding one . Indeed, assessing critical thresholds may bring the awareness that is needed to move away from the conditions that have caused them. Participatory methods that are more specifically aimed at social processes could bring about awareness of system actors. However, interrelatedness with processes in other domains are consequently likely to be lost out of sight. Still, specific attention for social processes in the conducted workshops can improve the integrated nature of the assessments, for instance by pre-selecting at least one indicator related to a social function and a resilience attribute related to social conditions.

For some case studies in this study, this would imply a suggestion that new functions and system goals are needed. Although top-down, this could initiate the process of system actors picking up this signal as being valuable and the process of redirecting the system as a whole to an alternative state . The study presented in this paper is a resilience assessment that is partly objectively and partly subjectively defined: we worked with a set of function indicators and resilience attributes selected in a previous workshop by stakeholders based on lists prepared by researchers . Such an approach may not be feasible at EU scale, but has proven effective for postulating candidate indicators for monitoring frameworks such as the CMEF. More participatory workshops in a diverse range of EU farming systems are advised to find more of these indicators that can enrich those monitoring frameworks. It should be noted however, that assessments inclining towards a subjective definition and evaluation of resilience are poorly researched and that translation issues and cultural biases can limit these kind of assessments . Further elaboration and study of participatory methodologies is therefore necessary to improve its use for evaluating sustainability and resilience at farming system, national and EU level. Specifically the desired or acceptable degree of objectivity vs. subjectivity in assessments across different levels and domains should be discussed. Low-carbon societies and carbon neutrality have become key goals in combating climate change . Carbon neutrality is expected to both contribute to climate change mitigation and require adaptation in the agricultural sector. Developing the systems required by a low-carbon society is a process based on natural and agricultural sciences. For example, carbon neutrality needs changes in land use practices in farming. However, as it also involves political, social, and economic processes, the systemic change required in its implementation is extensive. The inclusion of farmers in the transition process and an understanding of their perspectives on the change are required, in part, to achieve carbon neutrality. Studies on farmers’ climate change perceptions have predominantly reported a majority of them being skeptical of both the anthropogenic nature of climate change , and its risks to their livelihoods . Consequently, it seems unlikely that farmers would be willing to proactively make considerable investments in carbon-neutral farming methods.

To improve the acceptability and adoptability of low-carbon policies and to better acknowledge their unwanted consequences, especially to vulnerable groups, the concept of a “just transition” has emerged and gained momentum. An example is the European Union’s Green Deal program . This concept, as the name suggests, focuses on the fairness of the transition towards low-carbon societies . The concept, which could be an important tool in improving low-carbon policies and policy-making processes, has expanded and become both more theoretically robust and academically interesting . However, it has been insufficiently utilized in the agricultural sector, although there is growing interest therein . Conversely, consideration of private companies’ perspectives, for both the agricultural and transitional processes, is also important. Private companies operate dairy chains, and dairy farms are an essential part of these chains. Dairy production currently faces many challenges, majorly in relation to discussions about its environmental impact. Demands for decreasing meat and milk production have increased , while the legitimacy and continuity of dairy farming; practices, livelihoods, and the entire sector have been disputed. In Finland, the combined agricultural emissions from the EU’s effort sharing sector and land-use are about 20% of the total carbon emissions . Much of the agricultural emissions come from the use of peatlands, which are strongly connected to dairy production . The level of the agricultural emissions has remained stable and there is a pressing need to find ways to reduce these emissions. Within this challenging situation, we scrutinize the transition towards carbon-neutral dairy farming in Finland. The aim of this study is to clarify how to shift towards carbon-neutral dairy farming in Finland, such that dairy farmers can see the systemic change as equitable. The study focuses on Valio’s carbon-neutral milk program. We acknowledge that the environmental measures promoted by the program are produced in this context. These measures are geared towards improving the practices and the profitability of the dairy sector. The program does not involve critical elements such as promoting the reduction of dairy consumption or limiting the number of livestock, although these would have beneficial climate impacts. This study does not aim to analyze the environmental impacts of the program but focuses on understanding farmers’ perspectives on the role of such private sustainability initiatives for the promotion of a just transition. We used a case study methodology to answer these research questions. First, we outline the theoretical framework of the study. Second, we describe our research data and the methods used. Third, we present the results of the study.

The results are divided into three sections according to the three main themes that arose in the interviews: 1) the profitability of farming, 2) concerns and blame in the context of dairy farming, and 3) use of agricultural peatlands. Finally, we discuss the results in terms of the two research questions and draw meaningful conclusions. The concept of a just transition has evolved in relation to sustainability transition studies and various interlinked conceptualizations, such as environmental, energy, dutch buckets system and food justice . In the environmental justice literature, it is common to consider a just transition in terms of a set of justice dimensions. The most commonly used dimensions include distributive, procedural, and recognitive justice . As compensation for injustice may be required, the dimension of restorative justice is also relevant. Distributive justice focuses on the distributive impact of a transition. Traditionally, at the core of sustainability discourse, there has been an interest in intergenerational equity: that is, a concern for the needs of future generations. However, distributional concerns need to account for intragenerational equity too , aiming for a balanced distribution of drawbacks and benefits among different actors in contemporary society . If an unjust distribution cannot be avoided, restorative justice can be used to compensate for the harm caused. For farmers, this could mean subsidies for changing farming practices or production lines. Procedural justice highlights the decision-making procedures used to reach and implement a sustainability transition in which every party should have an equal opportunity to participate. Finally, recognitive justice is related to procedural justice, but extends towards the recognition of different livelihoods and ways of knowing and being in society. In particular, this means the equal valuing of different cultures, with particular attention paid to vulnerable groups and elements of society, such as indigenous peoples . While farmers are not generally recognized as a group potentially at risk, owing to climate-related policies , their vulnerability in the food system has been acknowledged . As climate policies are shifting from a focus on energy to other key emission-producing areas, it is important to consider farmers and other workers in the land use sector.

Despite the recent interest in the concept of a just transition, empirical studies have largely focused on energy justice and the transition from coal in the context of coal mine closures . While farmers have not been studied previously in the context of a just transition, their perspectives on agri-environmental policies, climate change, and associated justice issues have been widely studied, providing important insights. The changes required in agricultural production also raise questions related to regional viability and livelihoods, which are at the core of current EU agricultural policies. Despite efforts to provide sufficient livelihoods from agricultural production and to support investments in and changes to production lines, farmers may perceive the support system as unjust. In particular, this relates to gaining a livelihood from food production, versus so-called quasi-farming, where fields are maintained without productive goals. Another distributive justice issue for farmers relates to profit distribution among food system actors, visible in the food sovereignty movement , and the emergence of diverse alternative food systems, which farmers may see as a way of obtaining equal payment for their work . The transition literature discusses restorative justice as a means of compensation for or alleviation of the distributive harms caused to particular groups, owing to transition or related policies . Restorative justice involves means, such as adjustment periods, education, and direct subsidies, to support structural changes. In the EU, agri-environmental subsidies follow the logic of compensation for the additional costs that implementation of environmental measures incurs. Undoubtedly, subsidies can also serve as a basic income. However, the changes required to reduce the climate impact of food production are likely to require more than mere adjustments to farming practices. Thus, the measures required for just compensation may also need to be wider in scope. Farming generally means more than just gaining a livelihood. It is a way of life, intertwined with one’s family, home, and local environments . These issues can be considered in the light of recognitive justice. For instance, similar to farmers, for mine workers and the mining community, the coal mine represents more than just a job.

Mountain farming faces several natural and technological limitations

A final element to consider in creating smart farming innovation processes that yield more effective configuration comes to light from actions in India. Over the last few years, a team of Berkeley University technologists, economists, and development practitioners has worked with the government in Andhra Pradesh to create ‘smart villages’ . Reflecting the vision that innovation processes can deliver effective results when they are open, as argued by Chesbrough in particular, the plan was to bring the team together to produce new sociotechnical arrangements in one village, Mori, that would empower villagers, improve their material situations, and yield insights about how to ‘scale up’ the interventions across the entire state. There is no evidence to suggest that people in Mori wanted their village to be ‘smart’ prior to the intervention, but from the outset the process was designed to tap the Mori crowd for insights in a form of co-design that identified specific problems that might be addressed by new technical fixes. One such problem involved the condition of textile weavers within value chains, which the ‘smart village’ initiative tried to address by creating a new ‘virtual village mall.’ Another problem concerned the structural relationship between farmers and the suppliers of agricultural inputs. To make the village ‘smart,’ the apparent solution was to create more direct connections between farmers and retailers. A partner on the project was the Indian agricultural e-commerce startup firm BigHaat. So long as farmers could access the Internet – as was facilitated by Google, one of the project partners – they could consider purchasing inputs directly from BigHaat and for a lower price than if they had to rely on various intermediaries. In this smart village, tapping the crowd informed and then guided a tech firm to create a ‘win-win’ solution: Mori farmers paid less for inputs, while BigHaat made new sales and,gutter berries crucially, created opportunities to learn from analysing data generated by the new flows of information when farmers tapped screens on their devices and communicated with BigHaat’s servers.

Writ large over the entire state – ‘scaled up’ – this new type of ‘smart’ engagement would conceivably lay the ground for further innovations based on tapping the crowd for insights. The smart village envisioned by this project would play a new role in expanded open innovation ecosystems designed to upgrade the technical sophistication of rural life and address societal challenges. Yet, the technical dimensions of all this action deserve critical scrutiny. Initiatives such as the smart village might empower some or indeed many villagers and they could improve their material situations. However, based on what we know about digital life in general, what seems much more likely is that these initiatives will generate significant scope for tech firms to create new assets and value from data flows ; assets and value, moreover, that they will not share with the users of their technologies. Whether framed as a matter of surveillance capitalism or data colonialism , an important dynamic of digital life concerns the maldistribution of opportunity to convert data curation into profits. The asymmetries of digital life mean firms such as BigHaat stand to gain the most from smart village projects. In this context, then, it is worth remembering some pertinent lessons from the green revolution. Consider that when India embraced green revolution practices in the 1960s, the government redirected scarce resources toward importing fertilizer needed to support the planting and growth of new green revolution wheat varieties . Part of the issue was a realization in India that, although the country had “doubled its output of machinery, chemicals, and power […] ‘you can’t eat steel’” . In the contemporary context – when investment in smart cities, villages, and farming is bound up with the notion that “data is the new cash crop” – the refrain ‘you can’t eat data’ might have some purchase, especially given India’s rush toward smart technologies despite malnutrition currently affecting around one-seventh of the population . The stark difference now, though, is that some of the lead actors in the production of smart life in India do eat data, albeit by virtue of their ability to convert data into profits.

In a place such as Mori, it is not so much that villagers can’t eat data but rather that the current rush toward using digital technologies is underpinned by approaches and economies that mean Mori’s villagers are unlikely to share in the harvest. The Mori smart village project yields a unique but striking type of misconfigured innovation. Given the growing number of similar digital initiatives rolling out in the shadow of high-level belief that digital technologies can “play an increasingly important role in achieving global food security and improving livelihoods especially in rural areas” , it is necessary to ask whether an emancipatory version of smart farming could do any better. What might be the intricacies of building innovation processes that reconfigure the sociotechnical relations of smart farming within the ‘planetary cognitive ecology’ to enable all food producers, not only those in the global north heartlands of smart farming, to eat data? In the context of significant inequalities in the ability of digital pioneers and laggards to take advantage of smart life, a minimum insistence of an emancipatory version of smart farming should be that adopting digital technologies works from the ground up to create incremental adjustments via information-intensive iterative processes that target systemic or structural change. In effect, the task should be to find models of emancipatory smart farming that use algorithmic affordances to pursue ‘productive resistance’ to dominant formations, such as the corporate food regime. The point here is, plainly, that new and potentially radical arrangements of digital platforms, devices, and software are waiting to be established. Thus, as outlined in the final column of Table 1, arrangements of devices, software, and practice that lead to something akin to emancipatory smart farming are at least conceivable. Departing from the mainstream model of smart farming, emancipatory smart farming arrangements will use technology to support agroecological and regenerative food production in a food sovereignty framework. Such arrangements would need to consist of hackable devices that users can repair. Open source software would be a requirement. If digital platforms are involved, for example to pool computational resources, they would be run as platform cooperatives. Users’ privacy would be built-in by default.

To the extent that data emerging from emancipatory smart farming arrangements will have value, it will be shared and held according to principles of data sovereignty. In all of these respects, therefore, emancipatory smart farming would depart significantly from mainstream practices. Further, striking differences pertain to innovation processes. An emancipatory smart farming arrangement would need to be constructed from the bottom-up in a participatory approach that empowers food producers to remain independent of ATPs. Ultimately, its aim would be to undermine, resist and overcome systemic challenges facing food producers. The point here is that, with novel innovation processes, it should be possible for even the most oppressed food producers to participate in the creation of emancipatory smart farming practices that engage digital technology in transformative ways. A key concept introduced by the European Commission’s “The future of food and farming” communication is that the next common agricultural policy post-2020 reform must foster a smart agricultural sector. As pointed out by the EC, “smart farming” or “smart agriculture” represents the application of modern information and communication technologies to agriculture, leading to what can be called a “Third Green Revolution” . ICTs include products and services that allow entrepreneurs to store, process, transmit, convert, duplicate, or receive electronic information. Among the ICTs for smart agriculture, farmers can adopt software and hardware solutions, such as professional applications and operating systems, mobile phones, remote sensors, and multimedia products . These technologies provide farmers with updated information, such as farms’ input and yields and agricultural markets, promoting an increase in the efficiency of the farm production process through evidence-based managerial decisions . Moreover, as reported by the FAO , ICTs can promote learning and therefore facilitate technology adoption among farmers. Despite the advantages provided by these technologies, in the last decade in the European Union ,strawberry gutter system only one out of four farmers adopted ICTs . Furthermore, despite Italy being the first-ranked European country in terms of agricultural value added and the second-ranked in terms of production value , grow strawberry in containers the last agricultural census showed that only 76,000 out of 1.6 million farms adopted organizational innovations such as ICTs . According to the European Innovation Scoreboard analysis , Italy has moderate innovation performance compared to the other EU member states.

In the agricultural sector, structural and cultural factors surely affect the innovation process, which is not uniform within Italy . Although the fostering of smart farming appears to be even more important for increasing the competitiveness of mountain farming, these mountainous areas show the highest aversion towards innovation .For instance, climatic conditions limit the length of the growing season and lead to the scarce accessibility of lands, the presence of slopes impedes the use of machinery , and poor mobile network coverage can hamper the use of ICTs . Such limitations imply some difficulties in the development of economies of scale and thus have a great impact in terms of increased costs and lower productivity compared to lowland agriculture. Despite these constraints, mountain farming’s persistence and prevention of land abandonment are essential for protecting landscapes and ecosystems, reducing erosion and natural hazards , supporting the local economy and preserving local traditions . Considering the crucial role of mountain farming in the provision of public goods to society, special support programmes for mountain farmers have been developed in the CAP since the early 2000s, and the current public policies increasingly support innovative practices in these areas, encouraging farmers to adopt ICTs to ensure agricultural sustainability . Despite all these efforts to promote ICT application in mountain farming, these technologies remain scarcely used in these areas .

Scholars and institutions have widely recognized the importance of fostering smart farming for improving mountain farming competitiveness ; nonetheless, to the best of our knowledge, no previous studies on ICT adoption have been developed focusing on a sample of mountain farmers. By means of the clustering analysis method, the present study examines how attitudes and the characteristics of farmers and farms influence the use of ICT devices . To the best of our knowledge, this is the first study clustering mountain dairy farmers based on their attitudes towards technologies. The results from this study are especially important considering the limited adoption and diffusion of ICTs among mountainous farmers. In fact, understanding the factors that affect the adoption of these technologies is fundamental for the development of tailored policies in support of different types of mountain farmers. Our results can also help service providers indicate future directions for the design of their products. The remainder of this article is structured as follows. Section 2 presents a literature review focused on farmers’ adoption of technologies and their attitudes towards innovation. Section 3 describes the methods and procedures that were implemented in the analysis, including the conceptual framework , the case study , sample and data collection and the data analysis . Section 4 describes the results, while Section 5 provides a related discussion. Finally, Section 6 provides a summary of the research and some conclusions. Most of the literature on the factors affecting farmers’ adoption of technologies and innovation in developed countries seems to be related to specific types of technologies . For instance, Wheeler focused his study on the adoption of organic farming and genetic engineering practices in Australia. Additionally, in the Australian context, Sneddon et al. investigated farmers’ adoption of new agricultural technologies in the wool sector. A number of studies have investigated the adoption of specific sustainable and pro-environmental agricultural innovations within the wine industry and more generally in land management . Tey and Brindal and Pierpaoli et al. investigated the factors influencing the adoption of precision agricultural technologies by summarizing the findings of past studies. In Italy, Cavallo et al. analysed the innovative attitudes of farmers towards the technological innovation of agricultural tractors.

Vietnam is among the most vulnerable countries in the world in regard to climate change

Our results demonstrate experimentally what has long been argued anecdotally, that farmers respond to price incentives . For organizations looking to provide contracts to farmers, this result is encouraging because it implies that they can provide strong incentives to farmers without undertaking the costs of providing training and input loans. By far the most binding constraint to expansion for ESOP is the need to raise sufficient capital to provide input loans to farmers at planting. Our results demonstrate that much of this expense may be unnecessary and ESOP could potentially expand the number of farmers it contracts with, and thus its throughput, by offering farmers a guaranteed price. With a price guarantee delivering secure market access, farmers can use the contract as collateral to rent in more land and obtain loans for inputs, improving outcomes for both parties and contributing to more rapid rural transformation.Since the plastics industry first flourished in the 1950s, global plastic production has steadily increased, reaching 368 million tons in 2019 . However, poor management of plastic waste means that it is frequently washed into the oceans, where it accumulates and disperses on a global scale, showing a great resilience . Studies estimate that the amount of plastic floating on the sea surface is between 93,000 and 236,000 tons, representing approximately 5000 to 50,000 billion fragments, 92% of which are micro-particles of plastic , also called “micro-plastics” . These micro-plastics can enter the marine environment by several pathways .

The majority of MP found in the oceans are secondary MP produced by the fragmentation of larger plastic debris under a combination of environmental factors . Primary MP, in contrast, are those directly released into the environment as micro-sized particles . Micro-plastics have been reported in all major oceans and seas including the Pacific , Atlantic and Indian Oceans , as well as the Southern Ocean , Arctic polar waters , Antarctica , and the Mediterranean and North Seas . They have been found everywhere, from populated coastal environments to the most remote areas . Their ubiquitous nature in all environmental matrices, from surface water,down through the water column to the sediments,grow table including in marine biota,as their small sizes make them easily taken up by a wide range of organisms . In French Polynesia , pearl-farming is the second most important economic activity, based on the trade of pearl and mother-of-pearl . It also contributes to the social development of the territory by being widespread across 23 remote islands and atoll lagoons. However, pearl-farming is associated with a specific source of plastic pollution. The inventory carried out by Andr´efou¨et et al. in the atoll lagoon of Ahe revealed thousands of tons of plastic pearl-farming gears . Rearing structures and equipment of these types are accumulating over time in pearl-farming lagoons. They may fragment into smaller particles, which then add to MP entering the lagoons from other anthropogenic pressures and from the South Pacific subtropical gyre . This situation is worsened by the semi-enclosed environments of some of these lagoons, which could favour MP accumulation.Pearl-farming could thus be causing a risk to itself through plastic pollution, with a potential impact of MP on the suspension filter-feeding pearl oyster Pinctada margaritifera. Indeed, exposure using polystyrene microbeads demonstrated a dose-dependent effect on the energy balance and dose-specific transcriptomic disruption to gene expression in P. margaritifera. However, these effects were only observed in experimental controlled conditions that do not properly represent the complexity of the environment.

Furthermore, concentrations tested were not ecologically relevant since no environmental surveys had been performed in pearl-farming lagoons. To date, only one study has demonstrated the presence of MP in French Polynesia waters, using a 50 µm-plankton net in front of a public beach in Moorea, where they reached 0.74 MP m–2 . There was, therefore, a strong need to evaluate and characterize MP pollution in pearl-farming lagoons. The aim of the present study was to evaluate MP contamination in pearl-farming atoll lagoons of French Polynesia with low population and tourism. We investigated MP concentration, composition and spatial distribution in surface water and the water column , as well as in the tissue of cultivated pearl oysters. Our study addressed two main aspects: the distributions and concentrations of MP in the compartments investigated; the identification of polymer types and relative abundance, in so far as the main characteristics of MP contamination could be related to those of local macroplastic pollution sources such as the widely distributed pearl-farming gears. The data produced should facilitate decision making for local government policies to assess and anticipate this emerging risk for pearl-farming sustainability in French Polynesia.Its agricultural sector is particularly susceptible to various damages caused by climate change . Close to 40 percent of the country’s total land area is agricultural land. The agriculture sector accounts for 24 percent of Vietnam’s GDP, 20 percent of total exports, and over 70 percent of total employment . Using integrated or multi-sector modeling, Arndt et al. estimated the economic cost of climate change in Vietnam and concluded that the annual GDP growth rate would decline by about 1%–2%. Even so, they found that the negative impacts on agriculture and roads would be modest by 2050. They further showed that adopting appropriate preemptive actions to climate change would bring positive results. Agriculture is an important pillar of the Vietnamese economy. Rice farming, which uses two-thirds of the country’s rural labor, produces 30 percent of the country’s total agricultural production value . Vietnam is also one of the largest rice exporters in the world .

More than half of Vietnam’s rice production and about 90 percent of the rice exports come from the Mekong River Delta.However, this low-lying area faces some of the worst impacts of climate change and is therefore seen to ‘‘severely compromise’’ the country’s future rice production . Recent studies have shown that ongoing climate change has had significant impacts on rice production and the livelihoods of farmers in the region. The most serious effect is caused by saltwater intrusion during the Winter– Spring crop season . In the 2015/16 W-S crop season, MRD farmers suffered great losses from saltwater intrusion as rice paddy production fell by 11.2 percent in comparison with the 2014/15 W-S crop season . The problem is likely to continue in the future. The sea level in 2050 is projected to be between 25 cm and 30 cm higher than the 2000 level, which will likely result in salinity intrusion of >4g/l up to 50–60 km from the mouths of the Mekong River affecting about 30,000 hectares of agricultural area . Local authorities have intervened to protect MRD farmers against drought and salinity intrusion. Assistance includes adjusting seasonal schedules, managing water resources, adjusting cultivation techniques, diversifying and changing crops, applying new varieties, and self-learning to protect crops and cut economic losses . Previous studies provided empirical evidence on the effectiveness of adaptation strategies as well as the factors that influence the rice farmers’ choice among various adaptation strategies . However, the benefits of such solutions were not properly controlled in the past comparative studies. Specifically, the following problems can be cited. First, studies that used a binary indicator to measure the cope-with climate-change solutions failed to quantify the costs or control the farmer’s response process. Second, the impact of each strategy on income and productivity could not be separated as the studies aggregated many coping solutions. Third, the use of annual outcome indicators such as costs, profits, and productivity could not identify the effect of a single-response strategy in each crop season since the seasonal weather factor is not controlled.

To avoid these problems, we investigate the role of an adjusted cropping calendar in the rice production of MRD farmers facing saltwater intrusion. We focused on the relationship between early planting and the production and welfare of MRD rice farmers during the 2019/20 W-S crop season. This strategy is based on the following considerations. First, Nguyen and Ho , Nguyen et al. , and Nguyen and Nguyen found that farmers’ adaptation strategies against climate change significantly affect their farm income. Because farmers are highly resource conscious when making climate adaptation decisions, a comparative study is required to gauge the change in farmers’ welfare under different adaptation strategies. Second, Lu et al. argued that the timing of sowing needs to be predicted appropriately to avoid risks and achieve maximum yields. In 2018, the Ministry of Agriculture and Rural Development of Vietnam instructed the provinces in the MRD coastal areas to apply Climate-Smart Maps and Adaptation Plans 1 to adjust the rice planting calendar during the 2019/20 W-S crop season to minimize saltwater intrusion brought by the 2019 El Niño . In 2019, ebb flow table experts predicted that saltwater intrusion in the MRD would start earlier and that the salinity level would be higher than those in the 2015/16 dry season. The Department of Crop Production issued Official Document No. 1252/TT-VPNN directing the MRD to adjust its planting calendar in the 2019/20 W-S crop season. Coastal areas of the MRD, including Long An, Kien Giang, and Soc Trang provinces, were advised to plant rice from early October to early November in 2019. This created an opportunity for a natural experiment for the current study. To the best of our knowledge, this is the first study to examine the impacts of the adjusted cropping calendar on the welfare of rice farming households in the 2019/20 W-S crop season.

To determine the effect of early planting in response to saltwater intrusion, a total of 1176 rice farmers in three MRD provinces were randomly selected as research participants. Then propensity score matching was applied to match 412 early-planter farmers with 764 non early planters ,comparing the rice farming income and rice yield of the two groups. We found that early planting increased rice farming income by VND 8.62–8.77 million per hectare and rice production by 2.51–2.59 tons per hectare during the 2019/20 W-S crop season. Our findings suggest that during salinity years, advancing the rice cropping calendar to early planting can increase the production and income of rice farmers. This confirms the significant benefits of crop calendar adjustment in areas exposed to the risk of saltwater intrusion. The result also corroborates the robustness of a ‘‘planned’’ response to climate change risks in agricultural production . It is also consistent with the framework for agricultural climate change adaptation advocated by Ozor et al. and the process model of private proactive climate change adaptation presented by Grothmann and Patt . The paper proceeds as follows. Section 2 presents an overview of the study site and rice cropping practice in the MRD. Section 3 describes the sample and the methodology. Section 4 reports and discusses the results. Section 5 concludes the paper. MRD farmers practice either two or three rice cropping systems. Normally, the Winter–Spring crop season is from November to February, the Summer–Autumn rice season is from April to July, and the Autumn–Winter rice season is from August to November. In normal years with no drought or high salinity, MRD rice farmers start planting in middle to late December for the W-S crop season. Rice farmers can move the planting calendar forward, particularly for the W-S season, whenever unfavorable environmental conditions such as drought and high salinity necessitate it Nguyen . For early planting, the DCP calendar recommends planting within the month of October during the W-S season, which is the season most affected by drought and salinity. Nguyen found that rice farmers in Long An, Kien Giang, and Soc Trang, especially those practicing the two-cropping system, define ‘‘early planting’’ as starting the planting period by mid-November. Considering this, we define early planting for the 2019/20W-Scrop season as planting rice by 15 November 2019 at the latest provided that this is the last cropping of the 2019/20 crop year. If the farmer planted before 15 November 2019 but had another cropping extending from late November to February 2020, he or she was considered a non-early planter for the 2019/20 W-S crop season.The target sample size of the treatment group was 384.