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[Display omitted] • Self-folded honeycomb structure (SHS) was fabricated via stimuli-responsive materials. • Origami-inspired design for SHSs with energy-absorption properties was established. • Relationship of design, structure, and compression performance was elucidated. • Energy-absorption of 5-layered SHS was 6.67 times higher than that of 1-layered SHS. • Damage factor for protected object was successfully removed via pre-straining. The origami technique has been employed in the medical, space, and agricultural industries owing to its low cost and ease of use. In particular, the use of stimuli-responsive materials to automate origami fabrication has garnered interest. In this study, self-folded honeycomb structures (SHSs) were fabricated using the self-folding technique. A sheet of paper undergoes self-folding without human intervention via the physicochemical reactions between the paper and printing solution. Six SHSs with different mechanical properties were fabricated. The relationship between the design and structural parameters was examined. The energy-absorption performance of the structure improved by a factor of 15.2 on employing the optimal parameters. A consistent relationship between the design and compression performance was also discussed. By applying stacking technology, the energy-absorption performance increased by an average of 1753 N·mm per layer. The application of a pre-strain eliminated the compressive force peak that could damage the protected object, while maintaining 90 % of the energy-absorption performance. The proposed technology shows potential for the fabrication of tailored energy absorbers using stimuli-responsive materials, providing a groundbreaking technology for the packaging industry. [ABSTRACT FROM AUTHOR]

• A simple µPAD based on Griess chemistry is presented for rapid determination of iodate. • A wide linear range offers potential applications of this µPAD for determining iodate levels in different kinds of samples. • The device is easy to fabricate with rapid operation. We report a convenient microfluidic paper-based analytical device (µPAD) for the determination of iodate. The µPAD was fabricated using an ink-stamp with a simple circle design. Colorimetric detection of iodate employs the oxidation of hydroxylamine by the iodate to generate nitrite which reacts with the Griess reagent producing an intense magenta color. The images were recorded by a digital camera, and converted to a green scale color intensity by ImageJ. Calibration of iodate was linear in the range of 50–400 mg L−1 with a detection limit of 38.1 mg L−1. With such a wide linear range, the method can be applied to various kinds of samples with the entire process completed in 50 s. Good precision of measurement was obtained (<2 %RSD). Iodate levels were determined using the µPADs in table salt and irrigation water samples. The measured concentrations of the samples correlated well with the values as found by the standard iodometric titration (no statistical difference at a 95% confidence level). The developed device is simple with easy fabrication and rapid operation. It is portable and cost-effective and therefore suitable for quality control of iodate levels in the manufacturing and agricultural industries. [ABSTRACT FROM AUTHOR]

• Updated review paper on blockchain-based smart contract adoption in agriculture and food industry globally by the Governments and the private entities. • Comprehensive listing of the most popular smart contract platforms among the developer community and their notable features. • Overview of current obstacles and emerging trends of blockchain technology in the agriculture and food sector. Blockchain Technology has been finding industry-wide applications over the decade ranging from supply chain traceability to tamper-proof land registrations; facilitated by smart contracts and non-fungible tokens. The inherent immutability, transparency, and security of blockchain networks can transform the agriculture and food industry. Although several reviews have already been written, a complete in-depth analysis covering the popular smart contract platforms, current research progress concerning the agriculture and food industry, and applications of blockchain technology other than supply chain traceability has not been well documented. This paper discusses smart contracts-the computer programs that run on the blockchain, the smart contract life cycle, some of the most popular smart contract platforms among the developer community, and smart contact applications in the agriculture and food industry which includes a gist of recent developments in the Government and private sector across continents and the challenges and future trends associated with the use of this rapidly evolving technology. [ABSTRACT FROM AUTHOR]

• Agriculture-BERT is compared to other BERT models on agricultural term extraction. • With a few exceptions, Agriculture-BERT performs better than the other BERT models. • Embedding + encoder layers update scores best for extracting terms seen in training. • Embedding layer frozen + encoder layers updated scores best for extracting synonyms. • Embedding layer + top 4 encoder layers updated scores best for novel term extraction. This paper compares different transformer-based language models for automatic term extraction from agriculture-related texts. Agriculture is an important economic sector faced with severe environmental and societal challenges. The collection, annotation and sharing of agricultural scientific knowledge is key to enabling the agricultural sector to address its challenges. Automatic term extraction is a Natural Language Processing task that can provide solutions to text tagging and annotation towards better knowledge and information exchange. It is concerned with the identification of terms pertaining to a domain, or area of expertise, in text and is an important step in knowledge base creation and update pipelines. Transformer-based language modeling technologies like BERT have become popular for automatic term extraction, but limited work has been undertaken so far in applying these methods to agriculture. This paper systematically compares Agriculture-BERT to Sci-BERT, RoBERTa, and vanilla BERT, which were fine-tuned for the automatic extraction of agricultural terms from English texts. The greatest challenge faced in our research was the scarcity of agriculture-related gold standard corpora for measuring automatic term extraction performance. Our results show that, with a few exceptions, Agriculture-BERT performs better than the other models considered in our research. Our main contribution and novelty of the presented research is the investigation of the impact that different language model fine-tuning configuration scenarios had on the term extraction task. More specifically, we tested different scenarios related to the model layers kept frozen, or being updated, during training, to measure the impact they may have on Agriculture-BERT's performance in automatic term extraction. Our results show that the best performance was achieved by: (i) the "embedding layer updated + all encoder layers updated" scenario for the identification of terms also seen during training; (ii) the "embedding layer frozen + all encoder layers updated" scenario for the identification of terms being synonyms to those seen during training; and (iii) the "embedding layer updated + top 4 encoder layers updated" scenario for identifying terms neither seen during training nor being synonyms to those seen during training (novel terms). [ABSTRACT FROM AUTHOR]

The objective of this paper is to assess the readiness of Italian farms to actively engage in the journey of "Agriculture 4.0" (Agri 4.0). Specifically, the focus lies on analyzing the levels of knowledge and adoption of specific Agri 4.0 enabling solutions, while also considering the underlying business needs and the primary benefits of the paradigm. A descriptive survey was conducted involving 543 respondents associated with agricultural companies of varying sizes. The collected data was analyzed to address four specific research questions. The survey findings indicate that Italian farms are at different stages in their progression towards the Agri 4.0 paradigm, primarily influenced by their revenue and land size. Furthermore, notable similarities exist in both the benefits associated with adopting the Agri 4.0 paradigm and business needs that bring farmers in adopting such technologies. In terms of future research, conducting a similar study in other countries would be beneficial for comparative and benchmark analyses. Despite scholarly discussions regarding technology adoption and the benefits of the Agri 4.0 paradigm are present to the authors' knowledge few empirical surveys have been conducted thus far to evaluate the level of digital solution adoption in agriculture within a specific country. Specifically, this preliminary study follows research conducted two years ago, paving the way for a longitudinal comparison of the two datasets. [ABSTRACT FROM AUTHOR]

This paper examines the further question of whether water-related environmental innovations affect water stress in three main sectors such as agriculture, industry and services. The sample consists of 30 OECD countries for the period 2000–2019. This paper employs the method of moments quantile regression (MMQR) with fixed effects to analyze the effects of water-related innovative activities across different quantiles of water stress for all three sectors separately. The empirical results indicate that water-related innovations positively affect water stress in the agricultural sector in the lower and middle quantiles, while it has a negative effect in the middle and higher quantiles for the services sector and the higher quantiles for the industrial sector. These findings reveal nuanced effects of water-related innovations on water stress across sectors. Furthermore, the study suggests that while innovations in the industrial and services sectors can mitigate water stress beyond a certain threshold level, the agricultural sector appears to benefit comparatively less from such innovations. These findings underscore the importance of complementing water-related innovations with appropriate regulatory measures, to address informal practices such as losses and leakages in agricultural irrigation. Ultimately, this study provides valuable insights for policy makers to formulate targeted environmental policies and strategies, especially in the context of climate change adaptation, thereby enabling a more effective allocation of resources to mitigate water stress within each sector. • The relationship water-related environmental innovations affect water stress in three main sectors. • Water-related environmental innovations are closely related to water stress. • Environmental innovations has an important nonlinear role for water stress. • Environmental innovation has different impacts depending the level of water stress. [ABSTRACT FROM AUTHOR]

• Structural transformation via capital stock increases is enhanced by decreases in transaction cost. • Market policies should therefore complement production policies to facilitate optimal development in the context of structural transformation. • Zambia did not follow standard structural transformation, but successful agricultural led economic growth will be poverty-reducing. The Zambian economy does not follow the standard structural transformation pattern because agriculture's declining share in GDP corresponds to an increase in the share of services and not manufacturing. This paper establishes the relevance of capital as well as transaction costs in structural transformation using a computable general equilibrium (CGE) model. It is found that reducing transaction costs plays a significant role in aiding structural transformation through increases in value-added for all agricultural processing activities in the economy. When capital stock is increased in addition to the transaction cost decreases, the effects are enhanced. This highlights the importance of complementing production policies with market policies to achieve optimal development results. In the combined simulation labour moved out of agriculture to industry with the quantity of labour employed increasing relatively more for the agricultural processing subsector. The paper also confirms a well-known finding that agricultural led economic growth is poverty-reducing. [ABSTRACT FROM AUTHOR]

Preventing the impact of natural disasters on urban-rural income inequality helps to achieve shared prosperity. This paper uses the functional entropy weight method to calculate the level of natural disasters from 2004 to 2020. Then, this paper discusses the impact of natural disasters on the urban-rural income gap. The empirical results are as follows. (1) Natural disasters have expanded the urban-rural income gap. The regression coefficient is 0.2663, which is significant at the 1% level. (2) In areas with a high proportion of the rural population, the impact of natural disasters is more prominent. (3) Mechanism analysis indicates that natural disasters have widened the urban-rural income gap by restraining rural investment and agricultural production. Finally, this paper suggests strengthening investment in the agricultural sector to mitigate the negative impact of natural disasters. • This paper uses the functional entropy weight method to calculate the level of natural disasters. • This paper quantitatively measures the impact of natural disasters on the urban-rural income gap. • This paper examines the mechanism of the impact of natural disasters on the urban-rural income gap. • This paper provides policy suggestions for narrowing the urban-rural income gap. [ABSTRACT FROM AUTHOR]

Agritourism is known to play a pivotal role when providing diversification of farm activities, making in such way for sustainable regional and local development. However, it should be stated that in Ukraine agritourism has not received proper attention in the pre-war and current period. This paper explores the landscape of agritourism in Ukraine across pre-war and current periods, assessing its potential for the country advancement. The research involves the analysis of data on agriculture and tourism obtained from the World Bank, Ukrainian authorities, and agritourism association leaders. We also delve into 62 Ukrainian legislative and program documents to highlight institutional barriers and existing issues. The findings reveal that agritourism occupies minor position within robust agricultural sector in Ukraine, accompanied by notable regulatory gaps, nevertheless it possesses significant institutional and policy implications. We demonstrate that fostering agritourism in Ukraine can play a vital role in enhancing the sustainability of farms by broadening their range of activities. This holds particular importance in the context of the post-war economic recovery in Ukraine. Agritourism, operating at the intersection of agriculture and tourism, has high potential to generate positive effects in Ukraine not only on the agricultural sector but also on the country sustainable development. As a result of the investigation, the paper substantiates possible institutional changes (at the macro-, regional, and local levels) necessary to relaunch agritourism in Ukraine successfully. • Agritourism functions on the borderline between tourism and agriculture producing impact on sustainable development of local communities. • Agritourism demonstrates large potential for creating social networks, diversifying farms profit, boosting regional economies. • Ukrainian agriculture and food systems face dramatic challenges due to the Russian invasion and will require rebuilding after the war. • Agritourism activities can be a key element to ensure the economic and social viability of farms and regions in post-war Ukraine. [ABSTRACT FROM AUTHOR]

Abstract: To publish papers that have impact is indispensable for good scientists. It is frequently accepted that the impact factor (IF) of a journal reflects the likelihood of a paper to have impact. Many scientists may then attempt publishing their papers in journals with the highest possible IF. This is relevant for crop scientists as in many cases our hypotheses may be relevant to agronomy/agriculture but the product of our work may be published in the more basic plant science journals, which in general have higher IF than agronomic journals. To test whether agronomic journals may be better vehicles than plant science journals for crop physiological work, I did an analysis of my own publications (only “standard” papers, disregarding reviews) relating their annual citation rates against the IF of the journal in which they were published. The relationship was virtually inexistent, and my most frequently quoted papers were published in agronomic rather than in plant sciences journals. Conversely, restricting the analysis to the papers published within agronomic journals there was a relationship between the record of citations of the papers and the IF of the journals, particularly if the analysis is restricted to the most quoted papers in each journal. I then analyzed the cases of three other well-recognized crop scientists, to check whether the findings with my results were exceptional, and in the three cases results were remarkably similar. Therefore, it seems that the journal IF might be a valuable criterion for choosing the best journal in which to publish our best contributions only when comparing within agronomic journals, but not within combinations of agronomy and plant science journals. This should be also taken into account in evaluation processes when comparing scientists working in related but not identical fields. [Copyright &y& Elsevier]

• Adopting ecological agricultural technologies is an effective way to achieve sustainable agriculture. • The ecological effect of digital economy empowerment should be emphasized. • We analyze how farmers' participation in the digital economy affects their adoption of ecological agricultural technologies. • The treatment effect model is used to address the endogeneity issue. • Farmers' participation in the digital economy can promote ecological agricultural technologies adoption. Adopting ecological agricultural technologies (EATs) is an effective way to guarantee food security and protect the environment. With the advancement of the digital village strategy, the continuous integration of the digital economy with the rural economy has gradually become an emerging driving force for sustainable agriculture. However, few studies have examined the impact of farmers' participation in the digital economy in different links of the agricultural industry chain on EATs adoption from a micro perspective. Using data from 2,825 grain farmers from the 2020 China Rural Revitalization Survey, this paper applies the treatment effect model and the mediating effect model to empirically analyze the impact and mechanism of participation in the digital economy on farmers' EATs adoption from an ecological effect perspective. This paper characterizes farmers' participation in the digital economy in terms of digital production, digital sales, and digital finance. The results show that participation in the digital economy significantly promotes farmers' EATs adoption. The sub-dimensional test found that participation in digital production, digital sales, and digital finance significantly promotes farmers' EATs adoption. The above findings remain robust after a series of robustness tests, such as changing the estimation method and replacing the dependent variable. Mechanism analysis shows that participation in the digital economy, especially digital sales and digital finance, could promote farmers' EATs adoption by increasing the demand for agricultural machinery services, improving information availability, and enhancing food safety cognition; participation in the digital production could promote farmers' EATs adoption by increasing the demand for agricultural machinery services. Results of heterogeneity analysis show that the promotion effect of participation in the digital economy on EATs adoption is more substantial among farmers with higher digital literacy and larger cultivated land scales. The findings of this paper provide insights for China and other countries to effectively use digital technology to promote sustainable agriculture under the pressure of achieving sustainable development goals. [ABSTRACT FROM AUTHOR]

In field robotics, particularly in the agricultural sector, precise localization presents a challenge due to the constantly changing nature of the environment. Simultaneous Localization and Mapping algorithms can provide an effective estimation of a robot's position, but their long-term performance may be impacted by false data associations. Additionally, alternative strategies such as the use of RTK-GPS can also have limitations, such as dependence on external infrastructure. To address these challenges, this paper introduces a novel stability scan filter. This filter can learn and infer the motion status of objects in the environment, allowing it to identify the most stable objects and use them as landmarks for robust robot localization in a continuously changing environment. The proposed method involves an unsupervised point-wise labelling of LiDAR frames by utilizing temporal observations of the environment, as well as a regression network, called Long-Term Stability Network (LTS-NET) to learn and infer 3D LiDAR points long-term motion status. Experiments demonstrate the ability of the stability scan filter to infer the motion stability of objects on a real agricultural long-term dataset. Results show that by only utilizing points belonging to long-term stable objects, the localization system exhibits reliable and robust localization performance for long-term missions compared to using the entire LiDAR frame points. [ABSTRACT FROM AUTHOR]

The agricultural sector plays a pivotal role in global economies, providing livelihoods and sustenance for billions. However, it faces numerous challenges, including low productivity, and inequitable supply chains that only benefit some of its stakeholders. The study investigates the potential of emerging digital technologies such as blockchain, the Internet of things, artificial intelligence, and machine learning, in promoting equity within agricultural supply chains. Using a scoping approach to Systematic Literature Review guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews, the study examines the extent of emerging digital technology deployment in various aspects of the agricultural supply chain. Emerging technologies have been found to focus heavily on some parts of the supply chain (such as transportation), with limited application in others, particularly cash crop supply chains. The evidence gathered informs innovation policies and prioritizes opportunities for future research and practices. Despite the promise of emerging technologies, further evaluation, re-development, and deployment considering the local context and innovation dynamics are necessary. The paper contributes by providing insights into the mediating role of emerging digital technologies in addressing equity issues within the agricultural supply chain emphasizing the need for continued exploration and refinement of these technologies. • Equitable supply chains support gender parity and equitable benefit distribution among smallholder farmers and marginalized communities. • Socio-technical systems theory emphasizes integrating technology within social contexts to ensure inclusive design and equitable use. • Blockchain technology ensures records are visible and unchangeable, promoting trust and fair access to information for all actors in the chain. • Artificial intelligence (AI) and big data analytics improve decision-making and resource allocation. • The Internet of Things (IoT) facilitates real-time monitoring, increasing supply chain efficiency and prompt interventions. [ABSTRACT FROM AUTHOR]

Triflumuron is an insect growth regulator belonging to the class of insecticides. It finds its primary application in the agricultural sector for the control of various pests, particularly certain beetles, aphids, locusts, and mites. In this paper, a Cu/Fe-BTC composite was synthesized through a straightforward solvothermal approach, subsequently employed as a precursor for the fabrication of an electrochemical sensor denoted as CuFe 2 O 4 @C. The latter exhibited a distinctive core-shell architecture achieved through annealing, and its application was focused on the sensitive detection of triflumuron. The electrochemical behaviour of CuFe 2 O 4 @C for the detection of triflumuron was evaluated by differential pulse voltammetry (DPV) under optimal conditions in wide concentrations from 1.0 × 10−4 to 1.0 × 10−12 mol·L−1, where there existed a superior linear relationship between the current and the concentration of triflumuron with R 2 being 0.995. Meanwhile, CuFe 2 O 4 @C had a low limit of detection (LOD) of 922 fM for triflumuron. The CuFe 2 O 4 @C/GCE exhibited remarkable sensitivity, long-term stability, excellent reproducibility, and repeatability, as well as effective anti-interference capabilities. Additionally, CuFe 2 O 4 @C demonstrated its applicability for the quantitative determination of triflumuron in diverse real samples with commendable recovery rates. In conclusion, the electrochemical sensor not only displayed exceptional performance in terms of stability, reproducibility, and anti-interference, but also showcased its practical utility in quantifying triflumuron across various real-world samples. [Display omitted] • Cu/Fe-BTC was calcined to form porous CuFe 2 O 4 @C with core-shell structure. • CuFe 2 O 4 @C/GCE was constructed for the detection of non-electroactive triflumuron. • CuFe 2 O 4 @C/GCE can quantify triflumuron in real samples. [ABSTRACT FROM AUTHOR]

In the realm of precision agriculture, accurate harvest prediction is vital, as any discrepancies between forecasted and actual yields can lead to significant commercial and logistical challenges. This paper presents a novel deep learning-based approach for detecting and counting tomato fruits using advanced computer vision techniques. Building upon our previously established framework for ultra-wide image acquisition, this approach focuses on a unique patch-cropping technique tailored to tomatoes. This method aligns with the natural clustering of tomatoes, significantly improving object detection in greenhouse settings and thereby enhancing the model's performance in identifying individual fruits. The detection results exhibit a precision of 0.85, a recall of 0.93, and an F1-score of 0.89. Our approach's efficacy is also demonstrated through a case study on harvest prediction in a tomato greenhouse. The proposed methodology exhibited a lower error rate than the agronomist's estimates and proved its practical applicability. These findings suggest that our methodology could substantially contribute to optimizing sustainable farming practices, offering a promising direction for future research and application in the agricultural sector. [Display omitted] • A generalized patch-cropping process for high-resolution images is proposed. • Our patch-cropping technique improves input data for object detection models. • Focus on tomato trusses enhances the identification of small and overlapping tomatoes. • Case study validates improved harvest prediction, better than human estimates. [ABSTRACT FROM AUTHOR]

There is limited data to baseline and track changes in farmer wellbeing. The aims of this study are to 1) review existing wellbeing assessment approaches, 2) identify key features of a farmer-focused wellbeing assessment, and 3) propose a farmer-focussed wellbeing assessment tool. We conducted a literature review of wellbeing assessment approaches within peer-reviewed literature and interviews with stakeholders to identify a wellbeing assessment approach for the agricultural sector. Key factors to incorporate into a farmer-focused assessment approach are: i) cultural health, which is especially important when measuring wellbeing amongst indigenous and recent immigrant farmers and workers; ii) farming-specific questions, using a combination of pre-existing and newly developed questions; and iii) ease of use, using a combination of short pulse and longer surveys depending on the survey context and aims. This paper contributes to the debate of how to measure wellbeing, which is useful for programme designers and developers. Furthermore, it provides a coherent review on wellbeing assessment approaches, which can be used to steer future research in this area. Despite the widespread focus on wellbeing, this is the first literature review for wellbeing approaches in the agricultural sector. • There are limited assessment approaches available to specifically assess farmer wellbeing. • Inclusion of questions on cultural health improves access to a variety of farmers. • Ease of use and a choice of language are key to enhance assessment completion. [ABSTRACT FROM AUTHOR]

The rise of organic chemistry in the 1800s quickly lead to the realisation that products previously derived from plants and animals could be derived synthetically from alternative organic sources. Although it slowly became clear that there were limitations to this technology, the goal of producing animal protein synthetically has remained a tantalising prospect for scientists, with new hopes being rekindled throughout the years as new knowledge emerged or technologies developed. The demonstration of synthetic meat (also termed in vitro meat) in 2013 revived this dream and, with the refinement of protein synthesis technologies, 31 start-ups are now working to become the first company to market synthetic animal protein. The potentially transformative nature of this technology make it essential to understand its potential to disrupt conventional agriculture at an early stage. This paper addresses this issue by examining historical substitutions that have lead to the decline or even decimation of agricultural industries, namely: alizarin (madder), indigotin (indigo) and vanillin (vanilla). Following an outlining of the historical cases themselves, it identifies substitution product complexity, ease of synthesis, compatibility with industrial processes, and contamination of the natural product as four key issues that affect the substitution transition. Analysis of the specific synthetic animal protein case suggests that, while there are many additional issues that could affect any transition, three aspects are key: development of transferrable technologies in the medical sector, potential environmental advantages, and a lack of consumer resistance to its "unnatural" nature. Finally, the paper argues that rather than a complete substitution (e.g. alizarin & indigo) a furcated market (e.g. vanillin) with various classes of protein production is likely to emerge – within which industrial livestock production will struggle to compete against cheap synthetic alternatives. • Synthetic animal protein products will be available in the next decade. • Historical substitutions provide lessons for the future protein transition. • Intensive livestock production will ultimately struggle to compete with biosynthetics. • Market furcation is the likely future of the animal protein market. [ABSTRACT FROM AUTHOR]

Highlights • Inclusive Businesses are complex, composite organisational structures, combining standard instruments into unique set-ups. • Resource dependency, transaction cost and agency theory plus failings of individual instruments determine the IB set-up. • Multi-instrument IBs achieve inclusion of smallholders but power imbalance and corporate control over resources remain. • A conducive policy framework and third parties are important to shape dependencies, instruments and to balance power. Abstract Inclusive Businesses (IBs), signifying sustainable and equitable commercial operations linking low-income communities and smallholder farmers with agri-businesses in order to facilitate the former's market integration, are considered to comprise an essential tool for raising smallholders, across the developing world, out of poverty and for stimulating overall rural development. Although often promoted based on anecdotal evidence, IBs are little analysed and understood from a conceptual perspective, nor are they scrutinised when implemented in the field. This paper aims to provide a more precise insight into IBs, from a conceptual perspective and from a more practical one when implemented. Based on extensive fieldwork and assessments of 14 IBs, this paper proposes a new, flexible typology for the institutional set-ups of IBs, which accommodates the complex structures observed in the field. These innovative and hybrid arrangements, explained by a holistic framework that combines aspects of Resource Dependence Theory, Transaction Costs Economics and Agency Theory, are presented as unique combinations of the standard instruments of collective organisation, equity, lease/management contracts, mentorships, and supply contracts. Results show that whereas multiple-instrument IBs do obtain improved inclusiveness of low-income communities and smallholder farmers in commercial value chains, issues related to corporate control over resources, lack of knowledge transfer and marginal benefits remain. The assessed IBs are dynamic in their set-up, however, and allow for adaptations to overcome these issues. The State, which plays an important role through establishing a stimulating policy framework and financial contributions, together with third party engagement, can counter the potential corporatisation under IBs – emphasising that IBs alone cannot constitute the expected panacea for agricultural transformation and rural development. [ABSTRACT FROM AUTHOR]

Increasing the efficiency of agricultural production is a very important task. To solve this problem, it is proposed to use the "Smart Farming" cloud system for precision farming management. The novelty of the proposed approach lies in using the knowledge base and multi-agent technology to develop coordinated decisions on management of agricultural enterprises. The paper focuses on development of the knowledge base in the "Smart Farming" system on precision agriculture. Information storage is organized in the form of a semantic network of concepts and relations on the "All about the concept" principle in a single repository, which facilitates the work of farmers with this resource. The paper covers storage, editing, verification, and visualization of knowledge representation about the domain of crop production, production resources, agricultural machinery, equipment and other material resources, as well as peculiarities of the tasks of precision farming. The knowledge base of plant production, built on ontological principles, will be useful to enterprise managers, agronomists, machine operators, planning services and other specialists of large, medium and small farms, as well as to individual farmers. [ABSTRACT FROM AUTHOR]

Highlights • We present a systematic review of the literature on FMISs since 2008. • We reviewed 38 papers out of 1051 identified studies. • We identified 81 unique features of FMISs. • We identified 53 unique obstacles for FMISs. • We ranked the features and obstacles and discussed the key lessons learned. Abstract Various Farm Management Information Systems (FMISs) have been developed to support the management of the farm businesses. These FMISs typically support the different domains of the agricultural sector, such as arable and dairy farming; and include different set of features, such as crop, field, and financial management. These FMISs also have to deal with diverse obstacles during their development and adoption, such as lack of standardized data, cost and usability. Though several papers have been published in the past several years on this topic, there has been no explicit attempt to systematically review these papers to identify and characterize the features and obstacles. The objective of this study is to identify and describe the state-of-the-art of FMISs and as such pave the way for further research and development of FMISs. We applied a systematic literature review protocol in which we included the literature published from 2008 to 2018. We found 1048 papers of which 38 papers were selected as primary studies that we analyzed further in detail. From the detailed analysis, we identified 81 unique FMIS features and 51 unique obstacles of FMISs. We have systematically ranked the identified features and obstacles and describe the key associated aspects. These aspects include the agricultural domains, modeling approaches, delivery models, and identified stakeholders. [ABSTRACT FROM AUTHOR]

This paper presents the methodological assumptions of a logistic regression model and presents an example of the use of this type of models to assess the factors determining investment decisions of agricultural enterprises. The aim of the study was to identify and evaluate the factors influencing the decisions of agricultural enterprises in Central Pomerania with respect to tangible investments using the logistic regression model. The results of the research proved that the probability of making tangible investments by agricultural enterprises in Central Pomerania is influenced by financial factors: the structure of the use of capital expenditure (x 1 , x 4); use of traditional sources of financing (x 5 , x 6 , x 8); use of alternative sources of financing (x 13); variable combining the use of traditional and alternative sources of financing (x 14), as well as non-financial factors: characteristics of the enterprise (x 17) and behavioral aspects (x 18). It was also established that financial factors have a greater impact on the development of tangible investments in agricultural enterprises in Central Pomerania than non-financial factors. [ABSTRACT FROM AUTHOR]

Wireless Sensor Network (WSN) are in huge demand since last few years, we have seen a wide growth of wireless devices in many applications ranging from agriculture to aviation industry are few of them. It comprises of the number of sensor nodes (SN), which sense the physical phenomena from the environment and send this sensed information to the base station (BS) for further processing. Here, energy of the SN play an important role for lifetime of the overall network and to maintain security during the process of communication between each SNs is also crucial. Considering the aforementioned points, there is need to design a routing algorithm, which reduces the energy consumption as well as maintain the security. In this paper, a brief overview of routing challenges in WSN along with energy efficient cluster-based protocol named LEACH with its vulnerabilities are presented. The primary objective of a cluster-based protocol is to reduce the delay in the system and also consumption of less energy. It achieves scalable routing and energy proficient and fair access for nodes. This protocol has quite a few deficiencies with respect to security, which can be solved by extending it. This paper also highlights improved version of LEACH protocol with its advantages and limitations as compared to the Sec-LEACH protocol. We have compared the LEACH and Sec-LEACH protocols by varying the number of nodes per round. The Sec-LEACH protocol is used to reduce the security attacks from the outsider intruders in a cluster, increases the lifetime of the network, and reduces the number of compromised nodes and energy consumption, thereby improving the overall performance of LEACH protocol. [ABSTRACT FROM AUTHOR]

Clarifying the relationship between new energy and economic growth is an essential prerequisite for achieving the goal of carbon peaking and carbon neutrality. This paper utilizes a combination of nonlinear analysis methods, including transfer entropy, Bai–Perron (BP) structure point breakpoint detection, and complex network theory, to examine the coupling relationship between China's new energy and economy across different stages and sectors. An analysis of the network's topological properties shows that a complex coupling driving relationship exists between the new energy industry and the other 11 economic sectors. In particular, the agricultural sector exerts a significant driving force on the new energy industry, with the most extended duration of influence. Besides, the IT and construction industries also play a driving role in the new energy industry, and the latter's impact is earlier than that of the IT industry. The empirical results can guide the government and makers to formulate long-term sustainable action plans for different economic sectors. • Transfer entropy, BP structure break point detection and complex network are used. • 33 net transfer entropy symbol mode complex networks are constructed. • The coupling relationship between China's new energy and economy is complicated. • The agriculture industry has a large driving force on new energy industry. [ABSTRACT FROM AUTHOR]

This paper aims to demonstrate the feasibility, regarding environmental and economical point of view, of a local tomato farm powered by an offshore wind farm for Romanian Black Sea coast, where there are no such projects implemented and just one is foreseen so far. In this regard, both the agricultural farm and the offshore wind farm were dimensioned and using a new methodology proposed in the year 2023 by the World Bank, an environmental analysis of the project was made with estimating the positive effects that occur in the GHG emissions at the implementation of this project. The relationship between energy inputs and farm yields is analysed for two cycles of tomato crops and a comparative evaluation is conducted to emphasise the favourable influence that the implementation of the proposed solution would exert on the carbon footprint of Romania's agriculture sector. The two scenarios considered are Scenario 1 - S1 with tomato farm in the Schitu area (in greenhouses powered by an offshore wind farm, Cycle 1 and in open field, Cycle 2) and Scenario 2 - S2 when the tomatoes are imported from proximate regions. For both cycles, the energy ratio and energy productivity values were calculated, obtaining 0.11 and 0.13 for cycle C1, and 0.67 and 0.84 for cycle C2, respectively. The benefits of the proposed solution presented in S1 are represented by a) enhancing agricultural production by exploiting a renewable energy source with a yearly production of 45.07 GWh; b) reducing the transport distance of tomatoes by 324,057 km; c) promoting the local economy by employing an average of 124 people; d) improving the carbon footprint of Romania's agricultural sector with a reduction of CO2e per year of 43.13%. [Display omitted] • Local tomato farm located in Romania, powered by an offshore wind farm. • Improving the safety and resilience of the food system. • Reduction of the carbon footprint of Romania's agriculture sector. • Boost of local economy. • Relatively quick return of investment. [ABSTRACT FROM AUTHOR]

In the recent explosion of attention given to the land grabbing phenomenon, contract farming has been identified as a potentially inclusive alternative for smallholders to outright acquisition of farm land by agri-business capital. This paper responds to these claims by resituating contract farming as an equally important form of land control. The focus of the paper is a case study of potato contract farming in Maharashtra, India. While there is ‘nothing new’ about contract farming as a mode of agriculture production in India, its influence on patterns of agrarian change is poorly understood. Adopting an agrarian political economy-informed livelihoods approach, the paper argues that rather than an inclusive alternative to land grabbing, contract farming in the study site represents another way that capital is coming to control land in rural India, with just as important implications for agrarian livelihoods. While some individual households have improved their livelihoods through participation, the contract scheme acts to reinforce already existing patterns of inequality. In particular, the unequal power relations between firm and farmer skew the capture of benefits towards the firm, and render participating households vulnerable to indebtedness and loss of autonomy over land and livelihood decisions. [ABSTRACT FROM AUTHOR]

This paper investigates the decoupling of carbon dioxide (CO 2 ) emissions from agricultural economic growth in 30 Chinese provinces from 1997 to 2014. First, CO 2 emissions from agricultural production activities, farming, and livestock husbandry are computed. Then, this paper explores the spatial and temporal heterogeneity of CO 2 emissions and their intensity in China’s agricultural sector. Finally, this paper compares decoupling of China’s agricultural CO 2 emissions from agricultural output value across different regions and years. The results indicate that fertilizer, in-season rice cultivation, and cattle generated the most CO 2 emissions in the categories of agricultural production activities, farming, and livestock husbandry, respectively. The results also show that East China covered more periods of the strong decoupling of CO 2 emissions from agricultural output value between 1997 and 2014. To decrease CO 2 emissions, this paper suggests imposing a higher value-added tax on fertilizer producers, while waiving value-added tax for organic fertilizer and substituting animal manure for conventional fertilizers where possible. [ABSTRACT FROM AUTHOR]

Rapid expansion of agrarian capitalism in China has commanded much attention. This paper situates the rise of agrarian capital in the context of fear regarding “Who will feed China?”, demonstrating how the pursuit of grain self-sufficiency in the country has fueled the expansion of agribusiness enterprises and large farms. The policies to increase grain production, including the grain crop subsidy program, the incentive scheme for grain-producing regions, and the policy of nurturing new agricultural units, provide favorable conditions for agrarian capital of both domestic and foreign origins to take root and expand. As a result, the emphasis on self-sufficiency has strengthened the alliance between the state and large capital, and placed small farming households at a disadvantage. The paper draws attention to the interconnections between food politics and rural transformation, and offers an alternative perspective on agrarian capitalism in China. [ABSTRACT FROM AUTHOR]

Why should a parcel of agricultural land be abandoned when there is a scarcity of food? In this paper, we address this question in relation to the hills of Nepal, where agricultural land is being abandoned at an unprecedented rate, despite looming food scarcity. Responding to studies that have highlighted land abandonment trends, we conducted in-depth case studies in two of Nepal's hill districts to understand how land abandonment is taking place, and under what circumstances. Using an interdisciplinary lens and transcending linear models of agrarian change which attribute land abandonment to one or more prominent factors, our study unravels complex, cross-scalar processes, involving the interaction among social forces and environmental factors which lead to land underutilisation. The paper shows that land underutilisation happens through what we term ‘socio-environmental pathways’, which operate across scales, yet are deeply rooted in local dynamics of agrarian change. These pathways are triggered by, and embroiled within, three wider socio-economic and political dynamics in contemporary Nepal, namely: socio-cultural changes that favour out-migration; evolving economic opportunities that make farming less profitable; and a policy context in which the gravity of the land abandonment challenge goes unrecognised. The framework of ‘socio-environmental pathways’ applied here also advances a theoretical lens to explain agrarian change in a way that integrates multiple scales and multiple sectors, emphasising a thoroughly empirical approach. Finally, we identify key policy implications of this research on livelihoods and sustainable development. [ABSTRACT FROM AUTHOR]

This paper attempts to ‘put in their place’ (Sum and Jessop 2013) some key issues that frame the question of ‘the more-than-economic dimensions of co-operation’. In particular, it asks why capitalism deconstructs socio-natural reality into the ‘common-sense’ and discrete institutional spheres of ‘economy’, ‘society’ and ‘environment’, an institutional constellation in which the ‘economy’ is usually afforded pre-eminence. Building on this, the paper further asks: why does the organization of society around the commodity form, and specifically around the generalization of the commodity form to labour-power that is the defining feature of capitalism, have the tendential effect of fragmenting, atomizing, and marginalizing social collectivities and cooperative behaviour? This question is answered through examination of the work of Polanyi and Marx, arguing that it is the latter who is best able to explain the nature and dynamics of capitalism, and its relationship to cooperative activity. The paper elaborates the Marxian approach and suggests strong linkages with the ‘radical’ fraction of the food sovereignty movement. The latter, like Marx, appears to invoke unconstrained cooperation as ‘actual’ autonomy; the paper asks what the political and ecological prerequisites for the realization of this social imaginary might be. [ABSTRACT FROM AUTHOR]

This paper uses pork as a lens on China's rural transformations. Taking the industrialization of pig farming in the reform era as a trace on broader processes of social and environmental change, it advances three arguments. First, the massive increase in pork production and consumption since 1978 has been propelled by an industrial meat regime. A party-state led and agribusiness-operated regime, it articulates modernist notions of meat-as-progress with the relentless drive for capital accumulation. Second, using Marx's concept of metabolic rift, the paper examines how processes of concentration in the industrial meat regime are at the same time processes of separation. This dialectical approach highlights the contradictions inherent in ongoing attempts to disembed capitalist production from biological and social relations. Finally, while official party-state discourse conceptualizes "the rural" as a production base for surplus value, and/or as a site for preserving environmental integrity, the paper's analysis reveals a further unofficial recasting of the rural: in the process of agroindustrialization, the rural is also a sink for offloading capitalist crises. Between the rivers of manure that flow from industrial livestock operations and contaminate rural waterways; the loss of soil nutrients and food calories in the inefficient conversion of grains and oilseeds into industrial meat; the erosion of agricultural knowledge and practice that accompanies the dispossession of China's farmers; and the shifting values of pigs, pork, and manure, this is a system that "wastes" the rural in service of capital. [ABSTRACT FROM AUTHOR]

Smart agriculture offers the potential to analyse agricultural data at a scale not previously possible. Researchers argue that the combination of rich data and intelligent decision support has the potential to improve productivity and profitability in agriculture, whilst also improving sustainability. We argue that achieving this potential requires not just on technological advancement, it also requires a detailed understanding of factors that impact technology acceptance in smart agriculture. Acceptance is necessary if technical advances are to translate into real-world impact. However, technology acceptance is complex and often poorly understood. This systematic review focuses on technology acceptance in prediction and decision support systems in crop production. Major databases were searched to identify papers that formally address technology acceptance and include detailed data. 16 papers met the inclusion criteria and were included in the final analysis. Common facilitators and barriers are identified, and papers are mapping against the Theoretical Framework of Acceptability. This analysis showed that constructs including perceived effectiveness are addressed frequently, but others such as opportunity costs and burden have received less attention. The findings suggest the necessity for greater application of formal methods and the need for standardized, domain-specific methods to support this assessment. • Presents a systematic review of technology acceptance in smart agriculture, focusing on decision support in crop farming. • Increased productivity, access to information, and support for training are amongst the most common facilitators of acceptance. • Complexity, infrastructure requirements, increased burden, and not directly addressing farming needs are common burdens. • While effectiveness has been widely addressed, issues such as burden, opportunity costs and ethicality have received limited attention. • The development of a validated models of technology acceptance, and associated instruments, should be prioritised. [ABSTRACT FROM AUTHOR]

This study investigates the potential use of magnesium based phosphate cement prepared from a heavy magnesium oxide and monopotassium phosphate as a binder for the production of composite panels using bio-based industrial residues such as bagasse, hemp hurds, pine sawdust, paper mill sludge and wastepaper as raw materials. These residues were used to produce light-weight and durable materials that can compare with current Portland cement based products. The phosphate binder is fast setting, cold curing and has a low carbon footprint compared to its Portland cement counterpart. The development of phosphate bonded board products promises to reduce the energy requirements in the manufacturing process of board products, and also provides an alternative route for disposal or value addition to bio-based residues by developing environmentally friendly products. The board manufacturing process was laid out on a central composite design (CCD) to model the response variable, utilizing as much residues as technically feasible. The design allowed for the production of low and medium density boards that can be used for non-structural interior finishes and partition boards. Response surface methodology (RSM) was used to show the relationships between the production variables and predict the board property by variable optimisation. Tests of mechanical and physical properties were conducted on the boards. The density of hemp boards ranged from 0.59–0.83 g/cm 3 , bagasse boards ranged from 0.54–0.78 g/cm 3 , pine boards ranged from 0.58–0.84 g/cm 3 , paper sludge boards ranged from 0.68–0.81 g/cm 3 and wastepaper boards ranged from 0.67–0.81 g/cm 3 . The study has shown that it is feasible to produce phosphate based board products using bio based industrial and agricultural residues. The physical properties of the products met the minimum requirements for cement bonded particleboard (EN 634:2007) and LD-1 grade particle board (ANSI 208.1:1999). [ABSTRACT FROM AUTHOR]

Achieving greenhouse gas emission reductions to meet the 1.5 °C target by 2050 is particularly challenging for the agricultural sector. Cleaner Growth Mitigation Measures (CG-MM) are practices and technologies which balance food production with greenhouse gas abatement and are also identified as being economically acceptable. This paper explores a large number of CG-MMs to assess their feasibility using a novel participatory filtering process. Each measure is explored through a series of mapping exercises with supply chain actors to identify the impact on greenhouse gases and their applicability to different farming systems. These are then refined in a series of farmer workshops to identify which measures were considered feasible. Results show that acceptance of CG-MMs by the industry and the farmers themselves is limited. A pessimistic estimate of 50–60% of potential abatement could be lost due to lack of acceptance of currently available CG-MMs within farming. This impacts expectations on decarbonisation trajectories for the agricultural sector to reach net zero by 2050. This also argues for targeted approaches in order to capture some of the lost abatement. • Cleaner growth mitigation measures are assessed at farming systems level. • Half of the potential abatement from cost-effective measures is considered feasible for farmers. • Agricultural support needs to be targeted to capture lost abatement from cleaner growth measures. [ABSTRACT FROM AUTHOR]

Much of the existing literature on greenhouse gas peaking focuses on carbon dioxide (CO 2) emissions, however there is a lack of research on peaking methane (CH 4) emissions, the second-largest greenhouse gas. This paper attempts to determine and classify the peaking status of anthropogenic CH 4 emissions in 188 economies over the period 1970–2021 using a trend analysis model and a decoupling model. Fifty-eight economies achieved a peak in total CH 4 emissions, and 125 economies achieved a peak in CH 4 emissions per capita, showing marked spatial-temporal variation. Emissions generated by the agricultural sector peaked in 84 economies, followed by the energy sector in 63 economies, and the waste sector in 34 economies. Of these, the most volatile was the peak in emissions in the energy sector. There were 45 benign peaking economies and 13 pseudo-peaking economies. The majority of developed economies showed strong decoupling after reaching their peaks. The agricultural sector had the most peak economies which achieved strong decoupling. Among the factors influencing national pathways to peak CH 4 emissions, technological progress driving CH 4 emissions reductions in benign peak economies is the most important. This study provides targeted strategies for global and national CH 4 emissions reduction, particularly given the historical trend and current profile of economies at different levels of emissions evolution. • Peaking status of CH 4 emissions in 188 economies during 1970–2021 is evaluated. • 58 economies peaked in total CH 4 emissions and 125 in per capita emissions. • Agriculture-, energy- and waste-related emissions show various peaking patterns. • There are 45 benign peaking economies and 13 pseudo-peaking economies. • Factors influencing national pathways to peak CH 4 emissions are identified. [ABSTRACT FROM AUTHOR]

The eradication of illicit drug crops in developing countries through international agricultural cooperation in alternative livelihoods is a new mode of clean production. This paper examines the market-oriented alternative livelihood (AL) model implemented by Chinese agricultural companies in Laos, focusing on land-based cooperation between these companies, local authorities, and communities. It aims to reveal the conditions for successful land-based cooperation and mutual trust building with local communities and government agencies. Three Chinese companies involved in alternative cultivation projects in Laos are selected as case studies. The findings highlight the market-oriented AL model as a beneficial approach to transition from illicit crop cultivation to clean production. The study emphasizes the importance of land-based cooperation and trust building for the sustainable operation of market-oriented alternative livelihoods. Challenges faced by the companies include managing international market risks and developing locally-led technical and management teams. The research underscores the need for inclusive innovation in land-based cooperation and alternative livelihoods in the Global South. It calls for further exploration of innovative approaches to inclusive cooperation, local empowerment, and capacity building. The study contributes to understanding the potential of international agricultural cooperation in promoting alternative livelihoods and sustainable development in illicit crop-growing regions. [ABSTRACT FROM AUTHOR]

• Detailed review of over 300 research papers. • Object Detection and Tracking are suitable techniques to enhance Precision Farming. • Critical discussion regarding the challenges of Object Detection and Tracking. • Potential research lines to improve Object Detection and Tracking are identified. Object Detection and Tracking have gained importance in recent years because of the great advances in image and video analysis techniques and the accurate results these technologies are producing. Moreover, they have successfully been applied to multiple fields, including the agricultural domain since they offer real-time monitoring of the status of the crops and animals while counting how many are present within a field/barn. This review aims to review the current literature on Object Detection and Tracking within the field of Precision Farming. For that, over 300 research articles were explored, from which 150 articles from the last five years were systematically reviewed and analysed regarding the algorithms they implemented, the domain they belong to, the difficulties they faced, and which limitations should be tackled in the future. Lastly, it examines potential issues that this approach might have, for instance, the lack of open-source datasets with labelled data. The findings of this study indicate that Object Detection and Tracking are critical techniques to enhance Precision Farming and pave the way for robotization for the agricultural sector since they provide accurate results and insights on crop and animal management, and optimize resource allocation. Future work should focus on the optimal acquisition of the datasets prior to Object Detection and Tracking, along with the consideration of the biophysical environment of the farming scenarios. [ABSTRACT FROM AUTHOR]

• Ethiopia implemented widespread agricultural inteventions in the past decades. • We estimate the yields and food security impacts of the interventions implemented by the Ethiopian Agricultural Transformation Agency (ATA) between 2011 and 2016. • We combine project and remote-sensing data with a nationally representative household panel survey. • Our identification strategy exploits the temporal and geographic variation in the roll-out of the ATA interventions. • Results show that large-scale agricultural interventions are associated with higher agricultural yields and better food security outcomes. In the past decades, the Government of Ethiopia implemented widespread interventions with the objective of modernizing the agricultural sector and stimulating transformative growth. This paper assesses the agricultural yields and food security impacts of those interventions. Combining project and remote-sensing data with a nationally representative household panel survey, we identify impacts by exploiting the temporal and geographic variation in the roll-out of the interventions implemented by the Ethiopian Agricultural Transformation Agency from 2011 to 2016. Results show that large-scale agricultural interventions are associated with higher agricultural yields and better food security outcomes. These outcomes underscore the linkages that persist between agricultural development and food security for rural households living in mostly agrarian economies and the potential for systems-wide interventions to catalyze agricultural transformation. [ABSTRACT FROM AUTHOR]

This paper presents a study focused on the analysis of phytosanitary treatment sales in the Souss Massa region of Morocco. The objective of the study is to predict the sales of agricultural products, particularly crop protection solutions, aiming to optimize supply chain operations and meet customer demand effectively. Data for this study are collected from multiple sources, including the Enterprise Resource Planning (ERP) system called Microsoft Dynamics AXAPTA used by a leading agricultural company operating in the region. Information such as the date of sale, farming type, climate, and specific sales locations within the Sous Massa region is gathered. Machine learning techniques are applied for forecasting. Various regression models, including the Gradient Boosting Regressor algorithm, are employed to determine the most accurate predictor. Evaluation of the models reveals promising results, with a Mean Absolute Error (MAE) of 0.0035 and a Root Mean Square Error (RMSE) of 0.0066. The results obtained by applying various regression models, including the Gradient Boosting Regressor algorithm, demonstrate promising prediction scores. These findings contribute to the field of sales prediction in the agricultural industry while considering the impact of climate conditions, farming practices, and regional factors. [ABSTRACT FROM AUTHOR]

Agricultural production struggles with low efficiency and high emissions. This urgently calls for a collaborative effort between government and non-government organizations in environmental governance and policy implementation. In order to explore the supply-shock, demand-induced or superposition effects of the formal and informal environmental regulations to agricultural total factor productivity, using listed Chinese agricultural enterprise data from 2003 to 2018 as a sample, this paper employed a two-way fixed difference-in-difference model to analyze from supply and demand perspective. The results indicate that, (1) formal environmental regulations and environmental non-governmental organizations not only drive total factor productivity caused by dynamic changes on the supply and demand sides respectively, but also exhibit strong policy superposition effect. (2) The Analysis of policy intensity heterogeneity illustrated that the intensity of command-control and market-incentive environmental regulations could exert impact on the direct dual policies' effects. (3) The mechanism test found that green innovation and market forces play a mediating or regulating role. This paper provides empirical evidence for strengthening the policy orientation of synergistic governance, and has certain reference significance to realize the rise of green agriculture-supporting economy. [Display omitted] • Analysis is based on the supply and demand sides, with DID method mainly. • Heterogeneous environmental regulations respectively stimulate total factor productivity. • Dual regulations could generate a superposition effect. • Policy effects are affected by the heterogeneity across policy intensity. • Green innovation and market forces have regulating or mediating effects. [ABSTRACT FROM AUTHOR]

Using China's province-level panel data from 2001 to 2019 and the unexpected super efficiency MetaFrontier-Malmquist model (MinDS) to compute the super efficiency MinDS index for the green total factor productivity of China's agricultural sector, the paper analyses the temporal evolution in the agricultural sector's green total factor productivity across China's three economic regions by kernel density estimation. The effects of general climate factors and extreme weather events on the agricultural sector's green total factor productivity are empirically tested. The results show that precipitation, temperature, and humidity significantly impact agricultural green total factor productivity. The semi-parametric panel estimation method fits the nonlinear relationship between climate change and agricultural productivity. In addition, the impacts are found to vary across grouping levels. The mechanism test shows that climate change affects agricultural green total factor productivity through output, input, and structure effects. The test of the synthetic control method based on counterfactual thought shows that extreme weather has a significant negative impact on agricultural green total factor productivity in severely affected areas and is shown to display spatial and dynamic sustainability. The paper's results encourage policymakers in China to actively promote the coordinated and high-quality development of regional green agriculture under the condition of climate change. • Precipitation, temperature, and humidity are shown to have a significant impact on the total factor productivity of green agriculture. • The mechanism test shows that climate change affects the total factor productivity of green agriculture through outputs, inputs, and structural effects. • Extreme weather has a significant negative impact on Green TFP in the regions that were severely affected by such events and is shown to display spatial and dynamic sustainability. [ABSTRACT FROM AUTHOR]

The aim of this paper is to improve our understanding of the roles of individuals and the importance of their social contexts in shaping the dynamics of technological diffusion in the agricultural sector. When justifying the different rates of innovation adoption, existing literature reviews overemphasize either the drivers of technological changes enacted by farmers' agentic behaviour or the cognitive processes of individual farmers and their social contexts (structures). However, they continue to have a fragmented view of how local social systems and the agentic behaviour of individual actors influence the evolution of technological regimes, and they lack the ability to describe a purposeful interplay between agency and structures. We present an integrative review of the most relevant papers published in the last 20 years and discuss the impact of structures and agency emerging from local social systems on the local innovation process and, as a result, the evolution of technological regimes. The identified macro categories describe the main processes affecting individuals' abilities to mobilize and manage local resources for innovation, allowing us to critically assess the stock of previous developments from a new perspective and identify novel research avenues. • The last two decades of innovations in the agricultural sectors are reviewed. • Three macro categories emerged. • Agency, structure, and their interplay constitute the core of the integrative review. • A future research agenda is proposed. [ABSTRACT FROM AUTHOR]

Considering global water scarcity, especially in the agricultural sector, many attempts are being made to improve water productivity and save more water. Changing irrigation systems from surface to pressurized has been one of the considerable actions in this regard. However, any attempts to do so must be evaluated in an integrated perspective at the basin level by means of relevant agro-hydrological models before making them operational. This paper aims to address this issue by using the soil and water assessment tool (SWAT). Zarrineh Rud River, the main feeding river of northwest Iran’s Lake Urmia, is selected as the case study for exploring this methodology. This lake has been shrinking since 1995, and to save water and increase the basin’s water productivity, improvement of pressurized systems is considered as a solution. SWAT cannot directly simulate changing the irrigation system from surface to pressurized. In this study, we use the innovative approach of applying the model to simulate different irrigation systems considering real irrigation management variables such as depth and date of each irrigation event. Also, in order to improve its performance in simulation of such systems, a comprehensive calibration procedure was used based on a wide range of data for hydrological and agricultural variables. The results showed that changing the current irrigation to a pressurized system can increase water productivity up to 15% due to increases in crop yield, better water distribution and greater actual evapotranspiration. However, pressurized irrigation results in no significant change in total inflow to the lake. Notably, these systems can intensify drawdown of the basin’s water table up to 20%. So, any significant “real water saving” program in the basin must be associated with reduction of evapotranspiration by adopting measures like reducing cultivated areas, changing cropping patterns to less water consuming plants, or applying deficit irrigation. The applied methodology of this paper as well as the comprehensive calibration and setup of the SWAT model with the readily available hydrological and agricultural variables can be a good sample for similar works. However, further work is still needed to more broadly test this approach in areas with intensive irrigation systems. [ABSTRACT FROM AUTHOR]

Agriculture sector in India is diminishing day by day which affects the production capacity of ecosystem. There is an exigent need to solve the problem in the domain to restore vibrancy and put it back on higher growth. The paper proposes an e-Agriculture Application based on the framework consisting of KM-Knowledge base and Monitoring modules. To make profitable decisions, farmers need information throughout the entire farming cycle. The required information is scattered in various places which includes real time information such as market prices and current production level stats along with the available primary crop knowledge. A knowledge dataflow model is constructed connecting various scattered sources to the crop structures. The world around is getting automated replacing manual procedures with the advancement of technology, since it is energy efficient and engross minimal man power. The paper proposes the advantages of having ICT in Indian agricultural sector, which shows the path for rural farmers to replace some of the conventional techniques. Monitoring modules are demonstrated using various sensors for which the inputs are fed from Knowledge base. A prototype of the mechanism is carried out using TI CC3200 Launchpad interconnected sensors modules with other necessary electronic devices. A comparative study is made between the developed system and the existing systems. The system overcomes limitations of traditional agricultural procedures by utilizing water resource efficiently and also reducing labour cost. [ABSTRACT FROM AUTHOR]

This paper assesses the capacity of Whitehouse, Jamaica to adapt to climate change. A community-based vulnerability assessment was conducted that employed semi-structured interviews with community members within or related to the tourism, fisheries and agricultural sectors. The results were analysed using the Local Adaptive Capacity (LAC) framework, which characterises adaptive capacity based on five elements: asset base; institutions and entitlements; knowledge and information; innovation; and flexible forward-looking decision-making and governance. This paper contributes to the literature in three ways. First, it argues that many elements of the LAC framework correspond with an evolutionary perspective on adaptive capacity. Second, it offers an in-depth case study of the capacity of Whitehouse to adapt to climate change. Third, it offers a critical assessment of whether the LAC framework fully captures the important elements of adaptive capacity. [ABSTRACT FROM AUTHOR]

The practices and decision-making of contemporary agricultural producers are governed by a multitude of different, and sometimes competing, social, economic, regulatory, environmental and ethical imperatives. Understanding how they negotiate and adapt to the demands of this complex and dynamic environment is crucial in maintaining an economically and environmentally viable and resilient agricultural sector. This paper takes a socio-cultural approach to explore the development of social resilience within agriculture through an original and empirically grounded discussion of people–place connections amongst UK farmers. It positions enchantment as central in shaping farmers' embodied and experiential connections with their farms through establishing hopeful, disruptive and demanding ethical practices. Farms emerge as complex moral economies in which an expanded conceptualisation of the social entangles human and non-human actants in dynamic and contextual webs of power and responsibility. While acknowledging that all farms are embedded within broader, nested levels, this paper argues that it is at the micro-scale that the personal, contingent and embodied relations that connect farmers to their farms are experienced and which, in turn, govern their capacity to develop social resilience. [ABSTRACT FROM AUTHOR]

Cellular food technologies aim to decouple animal protein production from animal bodies and address the negative environmental, ethical, and human health implications of animal agriculture through its substitution. This marks a major rupture with previous expectations for agricultural biotechnology. If technically and commercially successful cellular agriculture could have far reaching effects that have yet to be the subject of concerted public or political discussion. These include, fundamentally altering human-nature relations, disrupting existing food systems, patterns of land use, rural economies, drivers of environmental change and biodiversity in terrestrial and aquatic ecosystems. In this paper we explore the environmental and rural visions of cellular agriculture in mainstream news and industry media, their contestation and the narrative silences. These silences represent the under- and un-explored questions, contingencies, and eventualities of envisioned developments. Our analysis highlights how anticipated efficiency gains are central to the realisation of several interlinked but separate positive environmental visions. Notably, that cellular agriculture will be able to replace conventional agriculture and feed the future whilst reducing environmental burdens and land use pressures. However, these visions leave many potential consequences unaddressed. We therefore explore these narrative silences. In doing so we explore the creative and destructive potential of these technologies with a specific emphasis on their environmental, rural, and spatial implications. In conclusion, we identify and anticipate environmental and rural policy implications stemming from these technologies that require further consideration, public and political discussion. • Cellular agriculture aims to replace livestock farming and radically alter land use. • Analysis of promissory narratives explores creative destructive consequences. • Expected efficiency gains and substitution of livestock farming key to promised future. • Attention to narrative silences highlights underarticulated implications. • Implications of cellular agriculture needs further policy and public discussion. [ABSTRACT FROM AUTHOR]

The UK has had a Temporary Migrant Worker Programme (TMWP) for agricultural ‘guestworkers’ since 1943. Most recently referred to as the Seasonal Agricultural Workers Scheme (SAWS), SAWS accommodated 25,000 workers per annum by its 2004 peak. However, the UK government then announced the scheme's closure (initially for 2011, but then delayed until 2014). This paper examines employers' response to this closure and, specifically, juxtaposes the academic critiques of TMWPs with the very strong employer preference for them. This preference, the paper concludes, is about the way in which TMWPs allow labour to be more readily and more extensively controlled, and, also allow employers access to ‘better quality’ workers. Considering these benefits of quality and control, alongside the academic critiques, the paper concludes that SAWS should be retained, but with major changes and safeguards. [ABSTRACT FROM AUTHOR]

Lignocellulosic crops like kenaf, flax and hemp have been extensively studied the last years with the help of new technology and many new products fabricated with them are ready for the market or have already been marketed. Both the core material and the bast fibers of these crops are ideal feedstocks for the production of yarns and paper of high quality, for rendering flame retardant properties to composites reinforced with them, for the production of energy via a sustainable way without polluting the environment and for use as alternative materials to wood for the manufacturing of panels like particleboards and fiber boards (MDF, HDF, etc.). The investigation of lignocellulosic feedstock as potential source for the sustainable production of materials, products and energy has resulted in promising solutions for the successful replacement of their counterparts made from fossil raw materials. However, the related industries still have some challenges to face, like the cost of materials from lignocellulosic plants in comparison with those derived from fossil sources and the availability of the feedstock throughout the year. [ABSTRACT FROM AUTHOR]

Ammonia emission in the atmosphere is a major concern in EU countries. In 2005 it was reported by European Environmental Agency (EEA) that 93% of the EU15 countries come from agricultural sector. This paper reported an open-path differential optical absorption spectroscopy (DOAS) system to monitor ammonia emission in the agricultural sector. In the initial stage, analysis of the absorption lines for ammonia in the ultraviolet region was performed and the optimum wavelength for ammonia measurement was selected at 212 nm. A few tests were conducted to verify the detection system reliability and this DOAS system was able to detect various ammonia concentrations from 0 to 100 ppm. It is also shown that this DOAS system has better response and recovery time than a chemisorption sensor. In this paper, ammonia levels measurement in a cattle barn for initial monitoring purpose is also reported. The DOAS system is able to measure ammonia concentrations of 2 ppm with fast response time (4 s). [ABSTRACT FROM AUTHOR]

Economists have touted partnerships between smallholders and agribusiness firms that cultivate high-valued export crops as a means of raising smallholder incomes and achieving rural development. However, some case studies show that such partnerships can deny smallholders the ability to benefit from their lands. This essay examines how this dynamic occurs by comparing the experiences of agrarian reform beneficiaries (ARBs) in the Davao Region of the Philippines. The paper finds that contracts which deny ARBs the benefit of their holdings are those that deprive them of key abilities such as determining who can use land and withdraw it from a partnership. Such contracts arise when ARB groups lack attributes that enhance their capacity for collective action, information gathering, and legal advocacy. • Illustrates how agribusiness partnerships result in adverse outcomes for smallholders despite legally enforceable property rights to land. • Relates the theory of access (ability to benefit from land) and exclusion (ability to prevent others from access) to abilities held in a contract. • Uses field work among of Agrarian Reform Beneficiaries in the Southern Mindanao Region of the Philippines. • Social relations as well as economic considerations determine access and exclusion. [ABSTRACT FROM AUTHOR]