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Agricultural and applied economists have maintained a public discourse at the Agricultural and Applied Economics Association (AAEA) meetings and subsequently published papers discussing the mission of land‐grant institutions and the role of AAEA members in that mission. With a content analysis of 4001 Invited Papers and Presidential Speeches, we find agricultural and applied economists questioned their profession's purpose and role within the land‐grant system. The reflective questions still apply to land‐grant institutions and the agricultural and applied economics profession. We argue that AAEA members are crucial in addressing the food and agricultural challenges connected to society's deepest needs today and into the future. [ABSTRACT FROM AUTHOR]

Detecting foodborne contamination is a critical challenge in ensuring food safety and preventing human suffering and economic losses. Contaminated food, comprising biological agents (e.g. bacteria, viruses and fungi) and chemicals (e.g. toxins, allergens, antibiotics and heavy metals), poses significant risks to public health. Microfluidic technology has emerged as a transformative solution, revolutionizing the detection of contaminants with precise and efficient methodologies. By manipulating minute volumes of fluid on miniaturized systems, microfluidics enables the creation of portable chips for biosensing applications. Advancements from early glass and silicon devices to modern polymers and cellulose‐based chips have significantly enhanced microfluidic technology, offering adaptability, flexibility, cost‐effectiveness and biocompatibility. Microfluidic systems integrate seamlessly with various biosensing reactions, facilitating nucleic acid amplification, target analyte recognition and accurate signal readouts. As research progresses, microfluidic technology is poised to play a pivotal role in addressing evolving challenges in the detection of foodborne contaminants. In this short review, we delve into various manufacturing materials for state‐of‐the‐art microfluidic devices, including inorganics, elastomers, thermoplastics and paper. Additionally, we examine several applications where microfluidic technology offers unique advantages in the detection of food contaminants, including bacteria, viruses, fungi, allergens and more. This review underscores the significant advancement of microfluidic technology and its pivotal role in advancing the detection and mitigation of foodborne contaminants. [ABSTRACT FROM AUTHOR]

This paper assesses the shifting locations and social significance of agricultural spaces through analyses of intensive pedestrian survey results, multi‐spectral remote sensing data, and Medieval Period inscriptional records around the site of Maski (Raichur District, Karnataka). In doing so, it challenges a longstanding historiographical trope about the social history and essential "fertility" of the Raichur Doab, a region of the central Deccan of southern India that was ostensibly contested for its rich agricultural resources by numerous imperial polities throughout the Medieval and Early Modern Periods. The results suggest that cultivation was extended into the region's more marginal production environments between the 11th and 14th centuries. Moreover, the process of agricultural expansion appears to have partly contributed to fomenting social concerns about the effects of temple patronage as many of the region's underclass farmers faced multiple modes of precarity, including those engendered by new labor and cultivation conditions in the semi‐arid Deccan. In that sense, the paper also expands on contemporary notions of precarity and highlights the significance of a variety of ways through which conditions of precarity might emerge in other historical contexts. [ABSTRACT FROM AUTHOR]

Background: An estimated two billion people do not have sufficient access to nutritious food, and nearly half are dependent on small‐scale and subsistence farming. Projections show that the global population is not on track to reach the Sustainable Development Goals. With this in mind, development actors are increasingly seeking to better integrate rural farmers into agricultural markets. This synthesis of the literature can help to inform policy decisions to improve outcomes for smallholder farmers in low‐ and middle‐income countries, and to enable the realization of the Sustainable Development Goals. This work is the most comprehensive and up‐to‐date review synthesizing evidence from 262 interventions. Objectives: The purpose of this systematic review is to appraise and synthesize evidence of the effects of five types of interventions facilitating farmers' access to output markets in low‐ and middle‐income countries. We examine how these effects vary across contexts and subgroups. We also identify evidence on program costs and evidence gaps in the literature. Search Methods: The search of included studies was based on nine major databases/search engines and 25 institutional websites, using a set of English search terms. We also conducted forward and backward citation tracking of literature, published a public call for papers, and contacted key experts. Selection Criteria: We included studies on the effects of five types of output market access interventions, focusing on participants residing in low‐ and middle‐income countries: (1) Farm‐to‐market transport infrastructure interventions; (2) Access to output market information interventions; (3) New marketplaces or alternative marketing opportunities interventions; (4) Contract farming interventions; (5) Improved storage infrastructure and technologies interventions. We included published and unpublished studies from 2000 onwards, with experimental and quasi‐experimental study designs focusing on relevant outcomes. Data Collection and Analysis: We screened 52,366 studies, identifying a total of 439 papers representing 289 unique studies on the effects of 262 interventions in 53 countries. Data extraction and risk of bias assessments were completed by two independent reviewers. Main Results: All five types of output market access interventions resulted in small‐to‐moderate positive effects on almost all measures of market participation, agricultural production, and welfare outcomes. These improvements occurred through a reduction in transaction costs, adoption of improved practices, greater farm investment, access to higher prices for farmers, greater volume sold, and increased farm income. Effects vary by intervention type. However, the body of evidence is comprised of a large share of included studies with a high risk of bias. Few studies have information on the cost of interventions, and there are gaps in the available evidence. Authors' Conclusions: Output market access interventions are effective in reducing transaction costs and addressing market failures, thereby leading to higher income levels. Evidence of effects on food security and nutrition is sparse and has not provided conclusive findings. We also found that multi‐component interventions are not necessarily more effective than single component interventions. The specific needs and dynamics of each context should inform the choice of the intervention and approach. Investments in additional research with low risk of selection bias and confounding effects will improve the evidence base, especially for outcomes that constitute gaps in the literature. For example, the effects on quality of agricultural products and group participation are under‐researched, and we did not find any included studies focusing on North Africa or the Middle East. Collecting and reporting information on interventions' cost‐effectiveness will help decision‐makers to prioritize limited resources. [ABSTRACT FROM AUTHOR]

Background and Aims: Two main problems the globe currently facing are migration and weather variation. Weather change has a significant impact on the agricultural industry, which affects the majority of poor people. There is a dearth of adequate methodological documentation when examining the relationship between weather variation, agricultural output, and migration. We aimed to identify methodological reporting difficulties by reviewing the quantitative literature on weather‐related migration through agricultural channels. Methods: A systematic evaluation was conducted using papers published between January 2010 and June 2022, indexed in the SCOPUS, PUBMED, and Google Scholar databases. Using inclusion/exclusion criteria, we selected 22 original research articles out of 18,929 distinct articles for review, in accordance with the PRISMA guidelines. We extracted data from each study to understand how various concepts, research designs, and investigative techniques influence our understanding of migration patterns related to weather in the agricultural sector. Results: The majority (64%) of the study's data consisted of time series data. In 50% of the studies, secondary data were used. Additionally, 55% of these studies did not state the sample size. In 40% of the studies, model assumptions were fully adhered to, whereas in 36% of the studies, they were not followed at all. The majority of the articles used the Ordinary Least Squares technique, while about 41% applied the Two‐Stage Least Squares technique. Various tests were conducted across these studies, such as robustness checks (59.1%), endogeneity tests (31.8%), omitted variable bias tests (22.7%), sensitivity analyses (22.7%), and weak instrument tests (13.6%), to name a few. In the research we selected, the methodology section had various shortcomings and lacked organization. Furthermore, the justifications for deviations from model assumptions were unclear, potentially affecting the study outcomes. Conclusion: This study has important indications for researchers in studying climatic (weather) migration through agricultural channels besides for policymakers by giving a thorough review of the methods and techniques. Key points: Providing narrative insights on how various issues, research designs, and analytical techniques shape our understanding of the association between weather variation and migration via agricultural production.Providing a broad overview of the pertinent literature, covering 22 articles, as a complement to earlier studies.Our study has important ramifications for researchers studying climatic (weather) migration through agricultural channels as well as for policymakers by giving a thorough review of the methods and techniques currently used in this sector.Future studies on weather variation, agricultural production, and migration should use prudent and comparable models that capture whole climatic (weather) impacts on migration through mediating factors like agricultural production. [ABSTRACT FROM AUTHOR]

The continuous and close combination of artificial intelligence technology and agriculture promotes the rapid development of smart agriculture, among which the agricultural robot navigation line recognition algorithm based on deep learning has achieved great success in detection accuracy and detection speed. However, there are still many problems, such as the large size of the algorithm is difficult to deploy in hardware equipment, and the accuracy and speed of crop row detection in real farmland environment are low. To solve the above problems, this paper proposed a navigation line extraction algorithm for corn spraying robot based on YOLOv8s‐CornNet. First, the Convolution (Conv) module and C2f module of YOLOv8s network are replaced with Depthwise Convolution (DWConv) module and PP‐LCNet module respectively to reduce the parameters (Params) and giga floating‐point operations per second of the network, so as to achieve the purpose of network lightweight. Second, to reduce the precision loss caused by network lightweight, the spatial pyramid pooling fast module in the backbone network is changed to atrous spatial pyramid pooling faster module to improve the accuracy of network feature extraction. Meanwhile, normalization‐based attention module is introduced into the network to improve the network's attention to corn plants. Then the corn plant was located by using the midpoint of the corn plant detection box. Finally, the least square method is used to extract the corn crop row line, and the middle line of the corn crop row line is the navigation line of the corn spraying robot. From the experimental results, it can be seen that the navigation line extraction algorithm proposed in this paper ensures both the real‐time and accuracy of the navigation line extraction of the corn spraying robot, which contributes to the development of the visual navigation technology of agricultural robots. [ABSTRACT FROM AUTHOR]

The pine marten (Martes martes) occupies the northernmost extent of its distribution in Norway, where microtine rodents are an important food item. The relationship between microtine rodent abundance and pine marten population dynamics is not well understood. In this paper, we examined this relationship and tested if environmental factors (e.g. snow depth, elevation, mature spruce forest density and agricultural land density) modulate pine marten population dynamics. We calculated pine marten abundance indices using data collected from 593 unique snow transects surveyed between 2003 and 2014 in Hedmark, Norway. We employed a Partial Rate Correlation Function to identify potential cyclicity in pine marten populations. We did not observe any cyclical patterns in pine marten populations within our short time series. Instead, their population appeared to be directly density‐dependent. Although the population growth rate of pine marten tended to increase with increasing elevation, it was not affected by individual variables including a microtine rodent abundance index and snow depth. However, the annual growth rate of pine marten populations was positively affected by the interaction between the microtine rodent abundance index and increasing elevation. Pine marten abundance increased with microtine rodent abundance, elevation, snow depth and density of mature spruce forest, but decreased with increasing agricultural land density. Pine martens are opportunistic diet generalists that can switch between prey and cache food for later consumption. They are also strongly territorial with delayed implantation and are slow to respond to environmental changes due to their relatively low reproductive potential. These life‐history traits may mitigate the effects of fluctuating microtine rodent abundance on pine marten reproduction and survival. Nevertheless, our findings suggest that microtine rodents still serve as important prey which can influence the population dynamics of pine martens in higher elevation habitats where alternative prey may be less available. [ABSTRACT FROM AUTHOR]

How do we identify ancient fields and farming systems in areas where the same spaces of cultivation have been used repeatedly over thousands of years? In the limestone karst landscapes of northern Dalmatia, on the Adriatic coast of Croatia, drystone field walls, terraces, and cairns are common features that attest to generations of working the land for agriculture. While confounding archaeological objects due to complex histories of reuse, drystone terraced field systems throughout the Mediterranean are believed to have roots in ancient and prehistoric land use. Against this backdrop, this paper works to better understand the dynamic patterns and outcomes of field "recycling" through multiple lines of evidence for long‐term changes in cropping patterns and agroecology in multi‐millennial agricultural landscapes of northern Dalmatia. We compare archaeobotanical data from the Ravni Kotari plain to documents of preindustrial land use from the 1826 Franciscan cadastre. We also draw upon contemporary observations of traditionally managed, semi‐wild olive groves on the nearby Adriatic island of Ugljan to better understand the land‐use legacies inherent in the landscapes of northern Dalmatia today. These data show that, despite a relatively static agricultural built environment of field walls and terraces, Dalmatian communities held historically dynamic relationships with domesticated and wild plant ecologies. Prehistoric integration of cereal agriculture with wild forest resources appears to have shifted to commercial‐scale domesticated arboriculture in the Classical period, leaving a multifaceted legacy of commercial agriculture, traditional farming, and rewilding among the contemporary cultural landscapes of Dalmatia. [ABSTRACT FROM AUTHOR]

In this paper, we review current understandings of anthropogenic field systems, focusing on trends and variations in the chronology of field construction, use, and in some cases, abandonment, as well as labor organization of agrarian production across the Lake Titicaca Basin. These trends indicate that agricultural intensification increased both during the political centralization of the Tiwanaku state and during periods of political fragmentation. In contrast to prior work on fields in the region, we argue that there was no single cultural, environmental, or historical impetus that ignited the construction of any particular field type. Additionally, we present the results of pedestrian survey of terraces carried out in 2018 in the northern Lake Titicaca Basin. While there were regional commonalities across survey areas in the masonry design of terrace risers, presence of pathways and radiating walls separating vertical tracts of terraces, and a general absence of irrigation, we found deviations from each of these trends in individual terrace complexes. While preliminary evidence indicates that more terraces were built or cultivated during the Late Intermediate period (1100–1450 CE) than in other time periods in the northern Titicaca basin, some terraces were likely built earlier. Our findings point to the multiplicity of strategies that ancient farmers employed in the varied ecological settings of the Lake Titicaca basin under diverse sociopolitical programs. This contrasts with previous research on agrarian field systems, which is mostly single‐sited and tends to emphasize individual strategies over the quiver of agrarian options available to Andean farmers. [ABSTRACT FROM AUTHOR]

Almost 30 years ago, Naomi Miller and Katheryn Gleason edited the influential volume, The Archaeology of Garden and Field, a guide to the identification and interpretation of evidence for past agricultural practice inscribed within the landscape. Here we introduce a new collection of papers that advance both theoretical discourses and methodological approaches to the study of ancient field systems. Contemporary archaeological debates bring new urgency to explorations of relict agricultural features, as they offer powerful perspectives on the entanglements of humans with their environment in the Anthropocene, while also serving to decolonize the past through engagement with Indigenous and traditional ecological knowledge. Although many ancient fields are at dire risk of destruction or have already been lost to modern land‐use changes, an emerging suite of new technologies and innovative methods are now enabling archaeologists to find and interpret past agricultural systems as never before. Herein, we argue for the critical importance of archaeological investigations that prioritize discovery and interpretation of relict fields and their constitution within larger landscapes, both as a means to better understand people in the past as well as our role as a species in shaping global ecosystems. [ABSTRACT FROM AUTHOR]

During the mid-1990s, a banana river irrigation farm that was launched in Southwestern Burkina Faso by a returning emigrant refugee spread throughout the region as far as neighboring Ghana. With relative abundant fertile, arable farmland in Ghana, easy access to input and modest capital mobilization by a few Ghanaian University lecturers to clear farmland and construct ridges and lay pipes for irrigation, a new cash crop production was set in motion. This paper analyzes the implication of this innovative rural agricultural intensification in the Ghana side of the border by shifting the angle of analysis away from narratives of transnational African agricultural commercialization driven by foreign corporations to instead focus on the role played by the local elite. The paper demonstrates that the viability of this irrigated farming can be attributed to imported banana crop variety, local rural producers' entrepreneurial zest, and enhanced existing cross- border ties and commercial opportunities made possible by the construction of a strategic regional highway linking the farm sites with large urban and market centers in Burkina Faso. [ABSTRACT FROM AUTHOR]

Smallholder farmers in developing nations face multifaceted challenges as they strive to secure fair prices for their agricultural products. With a primary focus on bolstering sustainable agricultural value chains (SAVC), this conceptual paper investigates the transformative potential of Financial Technology (FinTech) solutions. The study synthesizes insights from prior research on SAVC, hurdles faced by smallholder farmers, conventional strategies, and the untapped prospects offered by FinTech solutions in the agricultural sector. Utilizing the PRISMA strategy for comprehensive documentation retrieval, the study underscores the significance of creating a robust SAVC to empower smallholder farmers within the broader value chain landscape. It is found that Agri‐FinTech solutions represent a pivotal avenue for advancing living standards and cultivating agricultural sustainability in developing nations. The integration of FinTech solutions for agri‐credit mechanisms and product market facilitation catalyzes enabling pre‐production financing and ensures fair prices for smallholder farmers in the post‐production phase while neutralizing the value chain's exploitation potential. The study advocates for the expeditious adoption of information technology in developing countries, spotlighting the transformative role of Mobile Financial Services (MFS), which fortifies the agriculture sector, ensuring its resilience and responsiveness to the evolving demands of a globalized market. Drawing upon an evaluation of existing literature on FinTech‐enhanced agricultural initiatives in developing nations, the study outlines directions for future research and creates a path for a more nuanced understanding of the strategic enhancements necessary to fortify the SAVC, fostering a sustainable and equitable ecosystem for smallholder farmers. [ABSTRACT FROM AUTHOR]

A sustainable transition in the agri‐food system holds society‐wide implications. Farmers play central roles in responding to climate change, environmental degradation and sustainable food production. Still, factors underlying how farmers make decisions and manage their farms are often marginalised in efforts to develop policies to tackle these issues.The concept of relational values, defined as preferences, principles and virtues based on human–nature relationships, recently emerged to expand understandings of environmental decision‐making in general and that of farmers specifically. As agricultural landscapes are dynamic and characterised by the interaction of various actors with diverse values and interests, how these interactions influence farmers' decisions remains underexplored.This paper engages with these issues by using qualitative data on Norwegian horticultural farmers' motivations, opportunities and challenges in farming. We find that their relational values (a) are influential in shaping farmers' decisions about farm management and (b) are continually unfolding and embedded within a web of other actors, including grocers, retailers, consumers, farm advisors and policymakers, which shapes farmers' enactment of their relational values.In the context of agriculture, this research underlines the utility of an in‐depth understanding of relational values as embedded in wider social systems to enrich analyses of farmer decision‐making. How farmers' relational values are shaped and realised through interactions with other actors holds important implications for policy and programming to navigate tensions between different interests and actors for sustainable and long‐term change. Read the free Plain Language Summary for this article on the Journal blog. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Agricultural markets remain major issue downgrading root and tuber crop farmers who form the mainstream of the agricultural producers in Malawi. Recent evidence however reveals that orange‐fleshed sweet potato (OFSP) (Ipomea batatas) is currently being sold in produce markets along with the non‐orange varieties, sometimes in differentiated form in Malawi. The main objective of this study was to examine factors affecting market participation of sweet potato farmers in southern region of Malawi. Using a double‐hurdle model, this paper analyzed both the factors affecting farmer decision to participate and the extent/intensity of participation in market. The first tier of the double hurdle focused on decision to participate in the market using probit model and the second tier addressed factors affecting intensity of participation using truncated normal regression model. The paper used data collected from 360 farmers in southern districts of Malawi. Out of 360, 146 farmers had grown OFSP in the season preceding the survey. Double hurdle results indicate that farm size, output, age of a farmer (household head), and early maturing trait significantly determined decision to participate in the market. Further, results on intensity of participation indicate that access to market training, farm size, asset value, and output positively determined the intensity and negatively determined by distance to main market and gender of a farmer (household head). Based on the research findings, higher output levels and early maturing trait were found to increase smallholder farmer market participation. It is therefore recommended that strategies aimed at increasing household capacity to produce surplus produce through market tailored extension messages and productivity enhancement technologies could be highly effective in fostering smallholders' participation in commercial markets. Again, enhanced capacity building of research institutions to breed sweet potato varieties based on market demand is pivotal for increased market participation. Furthermore, research suggests that improving smallholder farmers' access to market price information, asset value, and farm size can help increase their intensity in the market. Therefore, it is critical for policymakers to holistically comprehend these socioeconomic factors in order to address the issue of smallholder farm households' decisions about market participation and the degree to which they participate. Core Ideas: Orange fleshed sweet potato is currently being sold along with non‐orange varieties, sometimes in differentiated.Decision to participate in market is significantly influenced by output, farm size, age early maturing attribute.Market intensity is determined by access to training, distance to market, farm size, gender, asset value and output.Breeding programs should integrate both sensory and agronomic traits such as early maturity and good taste. [ABSTRACT FROM AUTHOR]

Aim: As climate change increases the frequency and severity of droughts in many regions, conservation during drought is becoming a major challenge for ecologists. Droughts are multidimensional climate events whose impacts may be moderated by changes in temperature, water availability or food availability, or some combination of these. Simultaneously, other stressors such as extensive anthropogenic landscape modification may synergize with drought. Useful observational models for guiding conservation decision‐making during drought require multidimensional, dynamic representations to disentangle possible drought impacts, and consequently, they will require large, highly resolved data sets. In this paper, we develop a two‐stage predictive framework for assessing how drought impacts vary with species, habitats and climate pathways. Location: Central Valley, California, USA. Methods: We used a two‐stage counterfactual analysis combining predictive linear mixed models and N‐mixture models to characterize the multidimensional impacts of drought on 66 bird species. We analysed counts from the eBird participatory science data set between 2010 and 2019 and produced species‐ and habitat‐specific estimates of the impact of drought on relative abundance. Results: We found that while fewer than a quarter (16/66) of species experienced abundance declines during drought, nearly half of all species (27/66) changed their habitat associations during drought. Among species that shifted their habitat associations, the use of natural habitats declined during drought while use of developed habitat and perennial agricultural habitat increased. Main Conclusions: Our findings suggest that birds take advantage of agricultural and developed land with artificial irrigation and heat‐buffering microhabitat structure, such as in orchards or parks, to buffer drought impacts. A working lands approach that promotes biodiversity and mitigates stressors across a human‐induced water gradient will be critical for conserving birds during drought. [ABSTRACT FROM AUTHOR]

The Complete Coverage Path Planning (CCPP) problem is a subfield of industrial motion planning that has applications in various domains, ranging from mobile robotics to treatment applications. Especially in precision agriculture with a high level of automation, the use of CCPP techniques is essential for efficient resource utilization, reduced soil compaction, and increased yields. This paper reviews the CCPP problem in the context of machines operating in agricultural fields and proposes a methodological approach consisting of three steps: Generating the Guidance Tracks (i.e., the track system along which the path should be oriented), determining the traversing sequence through these tracks, and planning a smooth and drivable path. This paper provides an in‐depth review of optimization‐based approaches that deal with the first step, the generation of the guidance track system. Thereby, a comprehensive and pedagogical approach for the generation of guidance tracks for arbitrarily shaped two‐dimensional regions of interest is provided, along with an overview and detailed elaboration on different exact cellular decomposition techniques found in literature. Furthermore, cost functions are outlined for the different approaches presented in this work, which are utilized to generate optimal guidance tracks. Finally, this survey serves as an introductory guide for research and practitioners to solve the CCPP problem effectively and efficiently. [ABSTRACT FROM AUTHOR]

Summary: Maize grain is deficient in lysine. While the opaque2 mutation increases grain lysine, o2 is a transcription factor that regulates a wide network of genes beyond zeins, which leads to pleiotropic and often negative effects. Additionally, the drastic reduction in 19 kDa and 22 kDa alpha‐zeins causes a floury kernel, unsuitable for agricultural use. Quality protein maize (QPM) overcame the undesirable kernel texture through the introgression of modifying alleles. However, QPM still lacks a functional o2 transcription factor, which has a penalty on non‐lysine amino acids due to the o2 mutation. CRISPR/cas9 gives researchers the ability to directly target genes of interest. In this paper, gene editing was used to specifically target the 19 kDa alpha zein gene family. This allows for proteome rebalancing to occur without an o2 mutation and without a total alpha‐zein knockout. The results showed that editing some, but not all, of the 19 kDa zeins resulted in up to 30% more lysine. An edited line displayed an increase of 30% over the wild type. While not quite the 55% lysine increase displayed by QPM, the line had little collateral impact on other amino acid levels compared to QPM. Additionally, the edited line containing a partially reduced 19 kDa showed an advantage in kernel texture that had a complete 19 kDa knockout. These results serve as proof of concept that editing the 19 kDa alpha‐zein family alone can enhance lysine while retaining vitreous endosperm and a functional O2 transcription factor. [ABSTRACT FROM AUTHOR]

Societal Impact Statement: Lavaka, large gullies in Madagascar, can cause problems for farmers and for infrastructure, but these features also have beneficial aspects that have generally been overlooked. They provide plant refugia, and commonly host species that would otherwise not thrive on the grassy uplands. Farmers sometimes make use of lavaka to plant crops that require more protection or soil moisture. Colonial narratives blame lavaka erosion on poor land management but ignore their pre‐human‐settlement existence on the landscape and the ecological functions they serve. The knowledge and wisdom of Malagasy farmers are key to better understanding the complex roles that lavaka plays in the landscape. Summary: This paper combines a review of lavaka—erosional gullies in Madagascar's grass‐covered highlands—with new observations of their importance as ecological patch environments for a wide range of plants not seen elsewhere within the grassy biome. Lavaka play a role as a natural refugia for flora that would otherwise not thrive on the exposed and infertile hillslopes, and local farmers exploit their topography and sediment deposits to grow a variety of crops. We provide a classification scheme for lavaka based on the extent to which they have been colonised by vegetation. Our analysis is based on observations made over many field seasons in the highlands as well as interviews with Malagasy farmers living with lavaka on their land. We emphasise the importance of local knowledge and environmental wisdom in the analysis of landscape evolution, and we conclude that lavaka, while certainly an erosional problem in many places, can nonetheless provide valuable ecosystem services and agricultural opportunities that should not be overlooked. [ABSTRACT FROM AUTHOR]

Stakeholders require transparency that companies are conducting business sustainably, which can be provided through non‐financial disclosures. Businesses that act on environmental, social, and governance (ESG) matters can attain a competitive advantage. ESG has become necessary in the agricultural sector as agribusinesses are considered high‐impact companies. The lack of uniformity in reporting guidelines leads to inconsistent and overloading of information. The objective of this paper is to conduct an evaluation and comparison of the current ESG reporting practices of listed agribusinesses in South Africa, Australia, and Chile. To support the quality and quantity of reporting, the concept of materiality is addressed by recognising what is material to be disclosed to stakeholders. The study evaluates how agribusinesses have incorporated the proposed material topics of the new GRI 13 sector standard into their current reporting practices. A qualitative content analysis was done to identify the presence or absence of the 34 proposed material topics in their reports. The findings indicate a distinct lack of harmonisation in the agri‐food sector disclosures. Topics hardly mentioned included the rights of indigenous people, living income, and climate adaptation. Low disclosures of the keywords Climate adaptation with 3.3% and Climate resilience with 7.0% on average, for all three countries, were reported. It is recommended that the newly proposed GRI 13 sector standard must be implemented as companies can seize this opportunity for increased transparency and gain a strategic advantage. Emphasis on the materiality concept is needed as it connects with the stakeholder theory to disclose only important information. [ABSTRACT FROM AUTHOR]

This paper proposes a new method for evaluating green growth in agriculture (GGA) based on a set of key performance indicators and a synthetic index. To this end, we used the zero unitarisation method. The objects of study were seven countries/groups of countries with the largest share in agricultural production in 2020. This paper attempts to answer the following questions: (1) Has there been any progress in fulfilling the assumptions of the green growth concept implemented in the agricultural sector of the examined countries? (2) Which countries do better, and which do worse in that respect? (3) What are the challenges respective countries need to face? In the analysed years, the mean GGA index increased from 0.3287 to 0.3342, which means that the overall level of 'greening' in agriculture grew insignificantly. Out of the seven analysed countries/regions, China did the best in handling the challenges of GGA, while India did the worst. The paper discusses the reasons for this state of affairs, simultaneously making recommendations for improving the existing situation. [ABSTRACT FROM AUTHOR]

This paper highlights the relevance of Marxian class analysis to understand the changing nature of agrarian classes under capital‐intensive agriculture. It is a methodological exercise that builds on Patnaik's labour exploitation index (E‐criterion) in three major respects to construct a new index, namely, the Modified Labour Exploitation Index (MEI), to differentiate peasant classes. First and most important, it incorporates the role of mechanisation, which, so far, has been ignored in the methodological attempts to differentiate within the peasantry. Second, it underscores the importance of non‐agricultural (and non‐rural) bases of simple reproduction in the countryside by incorporating hired‐out labour by agricultural households to the non‐agricultural sector into the classification criteria. Finally, it makes surplus labour exploited through land leasing empirically testable by using Marx's differential and absolute rent to differentiate between subsistence and commercial leasing. The new index is then empirically tested using primary data collected from rural Haryana, India. The paper argues that MEI is an effective criterion for understanding changing class dynamics, the shifting modes of the livelihood of the poor peasantry and the largely hidden accumulation processes in agrarian societies. [ABSTRACT FROM AUTHOR]

Current soil‐ and land degradation seriously challenge our societies; it contributes to climate change, loss of biodiversity and loss of agricultural productions. Yet, soils are also seen as a major part of the solution, if maintained or restored to provide ecosystem services. Climate‐smart sustainable management of soils can provide options for soil health maintenance and restoration. In the European Union, the resource management and sustainability challenge are addressed in the Green Deal that, among other goals, aspires towards a healthy climate‐resilient agricultural sector that will produce sufficient products without damaging ecosystems and contribute to better biodiversity and mitigate climate change. The European Joint Programme (EJP) SOIL was set up to contribute to these goals by developing knowledge, tools and an integrated research community to foster climate‐smart sustainable agricultural soil management that provides a diversity of ecosystem service, such as adapting to and mitigating climate change, allowing sustainable food production, and sustaining soil biodiversity. This paper provides an overview of the potential of climate‐smart sustainable soil management research to the targets of the Green Deal that are related to soils most directly. The EJP SOIL EU‐wide consultation (interviews and questionnaires) and literature analysis (national and international reports and papers) done in the first year (2020–2021) generated a wealth of data. This data showed that there are specific manners to do research that are essential for it to be effective and efficient and that can actively contribute to the Green Deal targets. We concluded that research needs to be: (i) interdisciplinary, (ii) long‐term, (iii) multi‐scaled, from plot to landscape, (iv) evaluating trade‐offs of selected management options for ecosystem services and (v) co‐constructed with key stakeholders. Research on climate‐smart sustainable soil management should be developed (1) on plot scale when mobilizing soil processes and on landscape scale when addressing sediment and water connectivity and biodiversity management; and (2) address the enabling conditions through good governance, social acceptance and viable economic conditions. [ABSTRACT FROM AUTHOR]

Societal Impact Statement: A diverse portfolio of genetically engineered food crops, as well as animal livestock and fish, are currently being developed and commercialized. To ensure their contributions to long‐term sustainability, a broad range of environmental, health, ethical, and societal parameters should be used in their evaluations. This paper proposes a set of parameters to evaluate the sustainability of genetically engineered food and agriculture products and discusses mechanisms to improve their governance and oversight. With such holistic evaluations, genetic engineering applications that are deemed beneficial to sustainable agriculture could be identified in an effort to foster sustainability. Summary: To achieve international sustainable development goals, food and agricultural production need to rely on sustainable and resilient practices. Traditional breeding as well as the use of new agricultural technologies, including genetic engineering and gene editing, have the potential to help achieve sustainable agrifood production. Although numerous oversight mechanisms exist to guarantee the secure and sustainable advancement and utilization of genetically engineered agrifoods, the majority of these mechanisms heavily depend on a narrow set of parameters to assess risks and safety concerning human health and nontarget organisms. However, a more comprehensive range of parameters should be considered to promote environmental and social sustainability in a more holistic manner. This Opinion article argues that to achieve a more sustainable agrifood production that relies on genetic engineering, governance systems related to new agrifood biotechnologies should incorporate a broader array of environmental, health, ethical, and societal factors to ensure their sustainability in the long‐term. To facilitate this process, we propose a set of parameters to help evaluate the sustainability of agrifoods that rely on genetic engineering. We then discuss major challenges and opportunities for formalizing sustainability parameters in US governance policy and decision‐making systems. Overall, this work contributes to further developing a more comprehensive assessment framework that aims to minimize potential risks and maximize potential benefits of agrifood biotechnology while also fostering sustainability. [ABSTRACT FROM AUTHOR]

The integrated farming system (IFS) is a holistic farming approach specially designed for small/marginal farmers to enhance the system productivity, profitability, and employment generation of their farm, ultimately ensuring their food and nutrition security for their livelihood. The mechanism of IFS offers various ecosystem services making farms environment‐friendly, sustainable, and climate‐resilient. IFS is characterized by the allocation of different agricultural components systematically in a single farm performing synergistically among themselves making the farm more productive, healthy, biodiversity enriched, and eco‐friendly than simplified farms. Therefore, this review paper represents an extensive analysis of existing literature on IFS exploring its concept, components, and need, and emphasizing its potential for higher system productivity, profitability, and employment generation in a sustainable manner. Moreover, it develops a conceptualization of the relationship among different agricultural components in a single farm exploring its role in ecosystem services (reducing greenhouse gases, carbon sequestration, nutrient recycling, improving soil health, and biodiversity conservation). [ABSTRACT FROM AUTHOR]

In Senegal, agriculture is an important sector underpinning the socioeconomic fabric of the populace. Notably, the agricultural production in this region exhibits heightened sensitivity to climatic perturbations, particularly droughts and heat waves. This study aims to determine the resilience of different agronomic interventions for farmers practicing mixed farming that produce both crops (i.e., groundnut (Arachis hypogaea L.) and pearl millet (Pennisetum glaucum (L.) R. Br.)) and raise animals in the Groundnut Basin in Senegal, which holds historical and socioeconomic significance. To understand the current situation regarding demographics, economics, consumption behavior, and farm operations for smallholder farmers, data were comprehensively collected from government and nongovernment organizations (NGO) reports, scientific papers, organization databases, and surveys. Additionally, the Agricultural Production Systems sIMulator (APSIM) was used to understand how combinations of three planting dates, three plant densities, and six urea nitrogen (N) fertilizer rates affected the yield of pearl millet, which were used as the alternative scenarios to the baseline in the farm modeling and analyses. All the collected and generated data were used as inputs into the Farm Simulation Model (FARMSIM) to generate economic, nutritional, and risk data associated with mixed farming systems. The generated data were then used to determine the resilience of the alternative scenarios against the baseline. Initially, a multi‐objective optimization was employed to meet nutritional needs while maintaining a healthy diet at the lowest cost. Then, the scenarios that met the population's nutritional requirements were evaluated based on four economic indicators: net cash farm income (NCFI), ending cash reserves (EC), net present value (NPV), and internal rate of return (IRR). Lastly, those that passed the economic feasibility test were ranked based on risk criteria certainty equivalent (CE) and risk premium (RP). The analyses found N fertilizer rates of 0, 20, and 100 kg N ha−1 were generally economically not feasible. Additionally, medium (early‐July to late‐August) and late (late‐July to mid‐September) planting dates generally performed better than early (early‐June to late‐July) planting dates, while plant densities of 3.3 and 6.6 pL m−2 performed better than 1.1. The robust resilience approach introduced in this study is easily transferable to other regions. [ABSTRACT FROM AUTHOR]

Growing recognition of the potential vulnerabilities of major crop systems has spurred a growing interest in the potential of alternative crops which may be resilient to climate change and also help mitigate its effects. In Indonesia, such issues are particularly pertinent given that country's particular vulnerability to climate change impacts high dependence on agricultural livelihoods and varied topographies and growing conditions. Cyrtosperma merkusii (giant swamp taro) is a wetland plant which has historically formed part of food systems in the eastern Pacific. The plant has the potential to be cultivated as a source of starch on marginal coastal land and on peatlands with high water tables. The aim of this paper was therefore to determine site conditions that promote growth of C. merkusii and the macro and micronutrient status of the corms. Naturally, the size of the plants varied substantially among sites, with a neutral pH, and low redox and conductivity being strong edaphic predictors of corm size. Despite substantial differences in the soil properties of the different study sites, there were no significant differences in the macro and micronutrient content of the corms. Field trials showed that although the plants grew under dry land conditions, the plants grew bigger and yielded corms with greater concentrations of Fe, Mn and K under waterlogged conditions, indicating that a high‐water table is the best cultivation environment for C. merkusii. The nutrient content of the corms suggests that, although primarily a starch crop, C. merkusii could also increase the intake of Fe in populations where Fe deficiency is pervasive. We conclude that the wetland plant C. merkusii has considerable potential as a paludiculture crop in low‐lying areas of SE Asia as it was tolerant of a wide range of soil conditions and performed well when cultivated under waterlogged conditions without additional fertilisation. [ABSTRACT FROM AUTHOR]

This paper highlights the significance of nurturing and safeguarding minor crops as a means of achieving regional sustainable development, preserving biodiversity, and ensuring food security. Minor crops play a critical role in addressing various environmental challenges like climate change, biodiversity loss, desertification, and soil salinity. Simultaneously, they offer local farmers economic opportunities by providing income stability and resilience. To demonstrate the potential of minor crops in promoting sustainable development, a case study from Greece is presented, focusing on three crops: blackcurrant, rice, and sunflower, which bring substantial economic and environmental benefits to the region. The study assesses the economic and environmental impact of these crops across three different rural territories in Greece. Despite covering less than 4% of total agricultural land, these crops are predominantly grown in marginal, mountainous, and insular regions. By analyzing the farm‐level and broader economic effects, the study determines their potential for agricultural and regional development. The results indicate that these crops are more profitable and environmentally friendly compared to their counterparts in all three cases. Additionally, they make significant contributions to the regional economies relative to their cultivated land area, supporting economic growth while conserving and enhancing agricultural land. In conclusion, this article emphasizes the crucial need to promote the cultivation and preservation of minor crops to support sustainable development, biodiversity conservation, and regional economic growth. Policymakers and agricultural practitioners should prioritize the cultivation and preservation of regional minor crops to safeguard biodiversity at the regional level and at the same time sustainable regional development. [ABSTRACT FROM AUTHOR]

Crop disease detection is important due to its significant impact on agricultural productivity and global food security. Traditional disease detection methods often rely on labour‐intensive field surveys and manual inspection, which are time‐consuming and prone to human error. In recent years, the advent of imaging technologies coupled with machine learning (ML) algorithms has offered a promising solution to this problem, enabling rapid and accurate identification of crop diseases. Previous studies have demonstrated the potential of image‐based techniques in detecting various crop diseases, showcasing their ability to capture subtle visual cues indicative of pathogen infection or physiological stress. However, the field is rapidly evolving, with advancements in sensor technology, data analytics and artificial intelligence (AI) algorithms continually expanding the capabilities of these systems. This review paper consolidates the existing literature on image‐based crop disease detection using ML, providing a comprehensive overview of cutting‐edge techniques and methodologies. Synthesizing findings from diverse studies offers insights into the effectiveness of different imaging platforms, contextual data integration and the applicability of ML algorithms across various crop types and environmental conditions. The importance of this review lies in its ability to bridge the gap between research and practice, offering valuable guidance to researchers and agricultural practitioners. [ABSTRACT FROM AUTHOR]

This paper introduces a novel wearable flexible gas sensor designed specifically for the detection of d‐limonene. The sensor utilizes materials recognized for their high efficiency‐to‐cost ratio, notably polyaniline (PANI) combined with carboxylated multiwalled carbon nanotubes (MWCNT) and graphene oxide (GO) as sensing layers. The study conducts a comprehensive analysis of the nanocomposite layers, examining their functional groups, morphology, topography, thickness, crystallinity, thermal behavior, surface area, as well as the size and volume of their pores. This examination showed distinctions among the nanocomposite layers. PANI/GO exhibited larger pore size and thickness, while PANI/MWCNT_COOH demonstrated a higher surface area. The analysis of thermal stability demonstrated that the film employing the DBSA dopant exhibited the lowest stability. Morphological characterizations showed a globular structure for PANI, tubular characteristics for PANI/MWCNT_COOH, and a flat nature for PANI/GO. When detecting d‐limonene, nanocomposite films doped with HCl demonstrated notably superior response levels. The gas sensors exhibited high sensitivity (>2.24 mV/ppm), a narrow range for the limit of detection (0.12–0.52 ppm), and excellent reversibility, stability, and selectivity. These findings suggest the possibility of broadening the application of gas sensors to monitor additional volatile compounds, with a particular emphasis on the online monitoring of agricultural products. [ABSTRACT FROM AUTHOR]

The Later Iron Age in Britain was a transformative period: material culture, settlement patterns, technology, trade networks, and the structures of power changed, ultimately leading to the Roman invasion. This paper examines the significance of investigating animal economies in this period within the broader context of socio‐economic developments. It reviews the available evidence regarding animal economies in this period, integrates new osteometric analyses, and discusses diachronic changes using the Roman evidence on a comparative basis. The investigation shows a broad pattern of continuity of practice, with relatively uniform livestock types and management strategies until the very end of the Iron Age. This suggests that the trajectory of local farming practices was largely independent from Mediterranean developments. This study contributes to a deeper understanding of Iron Age societies and their response to external influences, while also informing future research directions in archaeology. [ABSTRACT FROM AUTHOR]

Coffee is an important crop with economic and social importance in several countries. With a daily consumption estimated at 2.2 billion cups, its sustainability is facing critical challenges given the projected climate changes. Coffea arabica, which represents ∼60% of the global market coffee is a delicate crop, quite susceptible to diseases and biotic stresses. Developing climate‐resilience cultivars is necessary, and it includes coffee plants adapted to new farming conditions that can meet the demand for biotic and abiotic tolerance and quality. In this context, Coffea canephora emerges as a potential candidate if the crop combines plasticity and cupping quality. Plant plasticity refers to adjusted phenotypic performance when grown in different environments, a fact that may help mitigate the detrimental effect of climate changes. In this study, using a multiple environment trial, we combined genomic and genotype‐by‐environment analyses to answer the following main question: How the climate effects may affect the phenotypic plasticity in C. canephora? Our contributions in this paper are fourfold: (i) we draw attention to the cupping quality and yield performance of C. canephora cultivars when evaluated in high‐altitude and cold weather, (ii) we compared C. arabica and C. canephora phenotypic plasticity and highlight genotypes with broad and specific adaptation to certain environmental conditions, and finally, (iii) using stochastic simulation, we emphasize the potential of molecular breeding in the long term in coffee. Altogether, we present an emerging view on how C. canephora could be a valid alternative for climate‐smart cultivars in a projected scenario of altered climatic conditions. Core Ideas: Coffee sustainability is facing critical challenges given the projected climate changes.Inference on plant plasticity can identify plants more subjected to genotype‐by‐environment interaction, and therefore mitigate the detrimental effect of rapidly changing climate.Analyses of Coffea canephora phenotypic plasticity highlighted genotypes with broad and specific adaptation to certain environmental conditions.Results shed new light on the use of C. canephora as an alternative for climate‐smart coffee cultivars. [ABSTRACT FROM AUTHOR]

Highly fragile small island states experience disproportionate climate impacts given their limited capacity to implement cost‐effective tools for detecting emerging signals of drying conditions and monitoring systems for sensitive sectors such as agriculture, especially for uncertain, 'creeping' events such as droughts. Despite the existence of open‐source Google Earth Engine datasets, untapped potential remains for their full deployment in disaster management infrastructure. Given this gap, this paper explores the utility of the Enhanced Vegetation Index (EVI) for detecting spatio‐temporal variations of Mid‐Summer Drought (MSD) impacts on vegetation in the small island of Jamaica, with emphasis on major historical drought events. Geospatial analyses of EVI datasets from the Terra Moderate‐Resolution Imaging Spectroradiometer (MODIS) between 2000−2015 archived by the United States Geological Survey (USGS), were computed, and validated by station‐based precipitation and production data for selected parishes for historical case study MSD events. Results revealed highly asymmetrical drought impacts, with Jamaica's agriculturally intense Southern coastline displaying the most stressed vegetation (EVI < 0.5). North‐Western and North‐Eastern regions had the healthiest vegetation during the MSD (EVI > 0.6). A 'fair' to 'moderate' concurrent correlation was found between EVI and precipitation (R > 0.6), with lower correlations vis‐a‐vis agricultural production (R = 0.2–0.4). The results provide evidence of EVI's utility as a drought monitoring tool in a small island context. [ABSTRACT FROM AUTHOR]

Growth in agricultural total factor productivity (TFP), which explains most of the long‐term growth in U.S. agricultural output, may be slowing. The Economic Research Service (ERS) of the USDA is confident that current levels of below‐average growth will eventually regain the long‐term trend line. Others disagree, arguing instead that due to declining public expenditures on agricultural research, TFP growth experienced a downward and seemingly permanent structural shift about 30 years ago. In this paper, I argue that neither perspective is accurate since agricultural TFP is best modeled as a random walk with drift and thus not governed by a deterministic trend line. When I use a first difference model to accommodate the unit root, I do not find a structural break in the rate of drift. However, I acknowledge that this finding may not be general because I show that my test for a structural break has low power. To add theoretical relevance, I develop a simple model of stochastic innovation and farm technology adoption, and then use simulation results from my model to explain why a random walk for agricultural TFP is a theoretically sound proposition. [ABSTRACT FROM AUTHOR]

With its focus on the species level of the Anthropos, there is growing concern that the Anthropocene analytic lacks the conceptual nuance needed to grapple with the unevenly distributed harms and responsibilities tied up with issues of biodiversity loss, global warming, and land use change. Conceptual variants like the patchy Anthropocene have been proposed to better capture the justice implications of these socio‐ecological crises, directing attention to their spatially ubiquitous yet context‐specific character. The figure of the plantation has come to play an important role in this scholarship due to the contribution intensive agriculture had made to these interlinking crises. Through empirical study of the regenerative agricultural movement, this paper reflects on how regenerative farmers use different sites (fields, soils, livestock stomachs) to apprehend their agro‐ethical responsibilities to more‐than‐human actors both near to and far from the landscapes they manage. Our aims here are two‐fold. First, we provide a more affirmative account of agricultural management than is currently offered by plantation farming: a model of food production that is not just 'in' the Anthropocene, but 'for' it. Second, we contribute to ongoing discussions unfolding in the social sciences around the tools needed to conceptualise the interlinking spatial and justice aspects of the Anthropocene transition. By bringing the patchy analytic into conversation with more established geographic writing on scale, volume, and horizontal connections, we show the merit of juxtaposing multiple models of spatial relation as a way of gaining ethical and conceptual traction on complex socio‐ecological issues. We argue that the 'polymorphic' spatial imaginaries of regenerative agriculturalists can offer some guidance on the tools needed to attend to the specificity of local Anthropocene outcomes in relation to socio‐ecological forces actuating the world at much greater spatio‐temporal scales. [ABSTRACT FROM AUTHOR]

This paper investigates four different mobile robots with respect to their driving characteristics and soil preservation properties in an agricultural environment. Thereby, robots of classical design from agriculture as well as systems from space robotics with advanced locomotion concepts are considered to determine the individual advantages of each rover concept with respect to the application domain. Locomotion experiments were conducted to analyze the general driving behavior, tensile force, and obstacle‐surmounting capability and ground interaction of each robot. Various soil conditions typical for the area of application are taken into account, which are varied in terms of moisture and density. The presented work covers the specification of the conducted experiments, documentation of the implementation as well as analysis and evaluation of the collected data. In the evaluation, particular attention is paid to the change in driving characteristics under different soil conditions, as well as to the soil stress caused by driving, since soil quality is of critical importance for agricultural applications. The analysis shows that the advanced locomotion concepts, as used in space robotics, also have positive implications for certain requirements in agricultural applications, such as maneuverability in wet conditions and soil conservation. The results show potential for design innovations in agricultural robotics that can be used, to open up new fields of application for instance in the context of precision farming. [ABSTRACT FROM AUTHOR]

Economic sanctions are more popular than ever. But do they affect agricultural trade? Combining two new datasets and capitalizing on the latest developments in the empirical structural gravity literature, we investigate the effects of sanctions on international trade of agricultural products. We find that trade sanctions impede agricultural trade, whereas other sanctions do not show any significant impact. Complete trade sanctions have led to about a 67% decrease in the agricultural trade between the sanctioned and sanctioning countries, or a corresponding tariff equivalent of 25%, and we also obtain significant estimates for partial sanctions. At the industry level, we find substantial heterogeneity depending on the sanctioning and sanctioned countries, the type of sanctions used, and the direction of trade flows. The 2014 sanctions on Russia substantially decreased Russia's agricultural trade, mainly due to reduced trade with the EU but also due to reduced trade with other countries. Although no definitive evidence exists that sanctions alter the actions of governments of receiving countries, this paper provides broad evidence that sanctions hamper agrifood trade and hurt producers, consumers, and real output. [ABSTRACT FROM AUTHOR]

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Agriculture has been considered an important source of food for humans throughout history. Plant pests cause significant damage to crops and reduce the productivity of global crop yields. Therefore, it is important to identify the plant pest at an earlier stage in order to minimize crop losses and use pesticides optimally. This paper develops the MobileENet deep learning architecture for accurate plant pest identification with less computational effort. The input images are pre‐processed, and the features are extracted using a deep convolutional encoder–decoder network (DCEDN). The proposed classification approach solves the problems of over‐fitting regularization, batch normalization, and dropout layers. Due to the minimum computing size and factorization process, the classification performance is increased. It extracts discriminatory feature information by eliminating redundant background information. The performance of the proposed approach is evaluated on the IP102 dataset, and the performance is compared with existing deep learning‐based approaches. The performance metrics, such as accuracy, precision, recall, and so forth, are considered to evaluate the performance of the proposed plant pest identification approach. The accuracy performance of the proposed approach is improved to 98.83% with less information loss. [ABSTRACT FROM AUTHOR]

Summary: Smart Farming has become a cornerstone of modern agriculture, offering data‐driven insights and automation that optimize resource utilization and increase crop yields. The use of cutting‐edge technologies in agriculture has given rise to Smart Farming, which has transformed traditional farming practices into efficient, data‐driven operations. This paper explores the synergy between high‐performance computing (HPC) systems, Kubernetes orchestration, GoogleNet architecture, and containerization to redefine the future of farming. At the heart of this transformation lies the GoogleNet architecture, a deep learning powerhouse recognized for its efficiency and accuracy in image recognition tasks. The orchestration capabilities of Kubernetes, a versatile tool for managing containerized workloads efficiently on HPC clusters. Hence, in this work, we investigate the intricacies of deploying GoogleNet‐based deep learning models within containerized environments orchestrated by Kubernetes on HPC infrastructure. It explores resource optimization, scalability, security, and adaptability, all tailored to the unique demands of the agricultural domain to evaluate the effectiveness of the given technique it is compared with the existing techniques namely Hermes, Horus, CYBELE, and RZ‐SHAN. The attained ranges of proposed method of various measures of accuracy, precision, recall, and F1‐score are 98.65%, 97.45%, 97.87%, and 98.12% for the Pilot Wheat Ear dataset. Also, the processing time for the proposed approach is 181.50 and 120.2 m for the Pilot Wheat Ear Dataset and the Pilot soya bean farming dataset. The latency of the proposed approach attains a lower value of 1.5 and 1.1 s pilot soya bean farming dataset and Pilot Wheat Ear dataset. The experimental outcome demonstrates the efficiency of the proposed approaches to improve Smart Farming agriculture. [ABSTRACT FROM AUTHOR]

Issue Addressed: Farmers experience skin cancer and die from melanoma at significantly higher rates than the general Australian population. This study examined Australian farmers' engagement with self‐skin examinations (SSE), participation in clinical skin examinations (CSE) by a health professional, and self‐reported barriers to engagement with these important skin cancer detection practices. Methods: A cross‐sectional, mixed‐methods design was used. Australian farmers were recruited through an industry‐based organisation representing livestock farmers. Farmers (N = 498; 22–89 years; 83.1% male) responded to a paper‐based survey that included closed‐ and open‐ended questions. Results: Farmers reported engagement with self‐conducted SSE and routine CSE that was comparable to findings in the general population, but 29.4% of farmers reported that they had not sought a CSE as soon as possible after noticing changes to their skin. Farmers reported a range of barriers to SSE, including physical difficulties examining their skin, difficulties identifying changes in their skin, forgetfulness, and lack of motivation. Barriers to CSE included accessibility, cost, difficulties finding the right doctor, and avoidance and complacency. Conclusions: There is a need to make clinical skin cancer detection more accessible to farmers, in addition to promoting self‐skin examination and help‐seeking behaviours within this at risk population. So What?: Novel approaches are needed to address systemic barriers faced by Australian farmers. These may include the use of teledermatology or artificial intelligence to assist with CSE. Remote training delivery methods may be also utilised to teach SSE skills to farmers who may be otherwise unable to access such opportunities. [ABSTRACT FROM AUTHOR]

The lack of research in farm animal welfare governance is noticeable given how political science traditionally describes the agricultural field as politicized, i.e., subject to private and public regulations and governance. This paper shows how this issue is making its way into social and political science by using a scoping review methodology to map and analyze what exists in the research literature on farm animal welfare governance from 2000 to 2021. In evaluating drivers in farm animal governance, the literature points to increasing public concern. This is not necessarily because it changes the public's actions, but rather give legitimacy to actors to drive change in other domains such as research and the market. This review identifies retailers and animal welfare organizations as key actors in private farm animal welfare governance. Public government and political parties are perceived as "slower drivers," thus leaving room for private governance. [ABSTRACT FROM AUTHOR]

Honeydew, a sugary excretion produced by sap‐feeding insects, plays a pivotal role in shaping intricate interactions between insects and plants. This review explains the multifaceted aspects of honeydew, beginning with an overview of its production mechanisms and factors influencing its variability across insect species and plant hosts. Exploring its composition, we examine the chemical components and nutritional aspects, highlighting variations based on insect species and plant sources. The impact of honeydew on microbial communities is explored, shedding light on its role in influencing the diversity and abundance of microorganisms. Furthermore, the review investigates how honeydew affects pest behaviour and population dynamics, elucidating plant responses to honeydew deposition. In the realm of biocontrol, we examine the intricate relationships between honeydew and natural enemies, considering potential implications for integrated pest management. Beyond these individual components, the paper discusses the broader ecological consequences of honeydew in ecosystems, emphasizing the interconnected relationships between insects, plants and microorganisms. The review concludes by identifying research gaps and suggesting future directions, recognizing the need for further investigation into areas with potential applications for agriculture and ecology. This review provides a comprehensive synthesis of the current understanding of honeydew's significance in insect–plant interactions, offering insights for both researchers and practitioners in the field. [ABSTRACT FROM AUTHOR]

This paper explores the concept of community engagement, aligned with President Jokowi's mission to promote social enterprises, as a means to support the development of a re‐generative circular green economy in Tarumajaya, West Java. The primary focus is on enhancing farming, fishing, and forestry activities with villagers. The Covid‐19 pandemic presented significant challenges for the villagers, particularly in marketing their goods, resulting in financial hardships and an increased vulnerability to debt traps, particularly affecting women. Additionally, a major obstacle to achieving regenerative living is the limited access to land, with approximately 80% of the villagers either landless or owning small plots. Moreover, fishing restrictions imposed by the military to protect the Citarum River have further curtailed access to common grazing land for cattle. Preliminary analysis indicates that adopting intensive farming methods, such as rabbit breeding, mushroom cultivation, and fertiliser production, holds promise for reducing the community's carbon footprint. Overcoming these challenges and mapping pathways towards regenerative living are central objectives of this case study, providing insights and practical strategies to foster sustainable economic and environmental progress in Tarumajaya. Key components of the approach include finding markets for village products, extending access to common resources such as rivers, forests, and hillside terraces to villagers, and providing mentorship to women for supporting their small enterprises. The ongoing partnership with the village involves a community of practice consisting of universities and nongovernmental organisations, while private sector entities, including a gas company and tea and coffee plantations, are engaged in negotiations with the village head to secure additional land access. This study highlights the combination of challenges arising from the lack of access to common resources, limited market opportunities, and the influence of predatory financial institutions during the pandemic. By working closely with the villagers, the case study aims to identify opportunities and support the transition towards a green circular economy that moves away from business as usual and promotes regenerative living. [ABSTRACT FROM AUTHOR]

Carbon cycling in boreal regions is controlled naturally by fire disturbance, climate, hydrology, snowmelt, soil heterogeneity, acidity, low nitrogen and phosphorus availability, mycorrhizal distribution, plant cover, and cryoturbation/permafrost at the northern edge. It is primarily altered by human management via and following land clearance. Each factor interacts with others in complex ways, creating a system characterized by high carbon storage and shaped by natural and anthropogenic disturbance. This paper examines boreal research to answer the question: 'what are the primary factors controlling boreal carbon cycling?' Though climate change threatens boreal systems, they may yet be resilient given many natural feedback loops that resist massive carbon loss. Perhaps the greatest danger is land conversion, which causes permanent losses and drastic alteration of certain carbon pools. Accordingly, it might be argued that it would be overall better to implement policies that keep these lands as forests, including managed forests, rather than convert to agriculture. Conversely, farming of marginal boreal soils might be managed to enhance carbon storage while satisfying local food security needs. However, the impact of agriculture on soil carbon storage is yet to be effectively quantified and initial results offer inconsistent assessments, reflected in the as‐yet natural sciences data‐scarce policy development. Research targeting long‐term carbon cycling, land conversion practices, agroforestry, and communication between boreal scientists and other groups (climate scientists, policymakers, public, and farmers) must be addressed through creation of long‐term experiments. [ABSTRACT FROM AUTHOR]

BACKGROUND: Faced with the need to develop new herbicides with modes of action different to those observed for existing agrochemicals, one of the most promising strategies employed by synthetic chemists involves the structural modification of molecules found in natural products. Molecules containing amides, imides, and epoxides as functional groups are prevalent in nature and find extensive application in synthesizing more intricate compounds due to their biological properties. In this context, this paper delineates the synthesis of N‐phenylnorbornenesuccinimide derivatives, conducts biological assays, and carries out in silico investigation of the protein target associated with the most potent compound in plant organisms. The phytotoxic effects of the synthesized compounds (2–29) were evaluated on Allium cepa, Bidens pilosa, Cucumis sativus, Sorghum bicolor, and Solanum lycopersicum. RESULTS: Reaction of endo‐bicyclo[2.2.1]hept‐5‐ene‐3a,7a‐dicarboxylic anhydride (1) with aromatic amines led to the N‐phenylnorbornenesuccinic acids (2–11) with yields ranging from 75% to 90%. Cyclization of compounds (2–11) in the presence of acetic anhydride and sodium acetate afforded N‐phenylnorbornenesuccinimides (12–20) with yields varying from 65% to 89%. Those imides were then subjected to epoxidation reaction to afford N‐phenylepoxynorbornanesuccimides (21–29) with yields from 60% to 90%. All compounds inhibited the growth of seedlings of the plants evaluated. Substance 23 was the most active against the plants tested, inhibiting 100% the growth of all species in all concentrations. Cyclophilin was found to be the enzymatic target of compound 23. CONCLUSION: These findings suggest that derivatives of N‐phenylnorbornenesuccinimide are promising compounds in the quest for more selective and stable agrochemicals. This perspective reinforces the significance of these derivatives as potential innovative herbicides and emphasizes the importance of further exploring their biological activity on weeds. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Environmental conditions significantly affected development in the Asian tropics. This paper investigates the relationship between weather risk and agriculture in four regions with distinct climatological features. Using new data, we estimate the scale of crop output sensitivity to rainfall shocks across ecological zones. Output was sensitive to shocks in regions with low levels, concentrated spells and high volatility of rainfall. Canal irrigation protected some districts while unirrigated regions remained vulnerable. Regions with high rainfall levels and long seasons remained protected. Regions with large interruptions deterred investment and were underdeveloped while regions with small interruptions invited investment‐led growth. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel paradigm for disease detection. We build an artificial intelligence based system where various biomedical data are retrieved from distributed and homogeneous sensors. We use different deep learning architectures (VGG16, RESNET, and DenseNet) with ensemble learning and attention mechanisms to study the interactions between different biomedical data to detect and diagnose diseases. We conduct extensive testing on biomedical data. The results show the benefits of using deep learning technologies in the field of artificial intelligence of medical things to diagnose diseases in the healthcare decision‐making process. For example, the disease detection rate using the proposed methodology achieves 92%, which is greatly improved compared to the higher‐level disease detection models. [ABSTRACT FROM AUTHOR]