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The question of how agricultural knowledge and innovation systems (AKISs) can address the issue of sustainable management of natural resources (SMNR) is presented in this conference paper. This literature review, which collected published research from the Scopus electronic database, aimed to explore the value of AKISs in enhancing the sustainability of natural resources. Therefore, it examined and evaluated the roles of AKISs as either positive or negative overall. Moreover, it analyzed whether the use of AKISs supports the goal of creating a sustainable system that links agriculture with natural resources. Among its findings, this review presents the positive and negative outcomes of each element and potential future scenarios/suggestions if the current trends persist. [ABSTRACT FROM AUTHOR]

The paper introduces the analysis results over a selected number of small-scale farms in the Western Romanian agriculture, more precisely in the counties of Arad and Timis. The purpose of the investigation is linked to the assessment of need for advisory services input in solving the problems of the farmers, particularly for the ones operating in small farms. Analysing the returned answers in connection with the fields of interest or needed expertise, accounting for the forms of mutual or directional help, compiling any forms of advice inputs, including the specialised structures other than public in absence of a function Farm Advisory Service allow the development of a structured image in terms of current problems, the way of solving and the interactions among the farmers inside or outside their communities. The quantified findings can serve as base for a public policy recommendation in the field of farm advisory as part of the Agriculture Knowledge and Innovation System. [ABSTRACT FROM AUTHOR]

The interplay of machine learning (ML) and deep learning (DL) within the agroclimatic domain is pivotal for addressing the multifaceted challenges posed by climate change on agriculture. This paper embarks on a systematic review to dissect the current utilization of ML and DL in agricultural research, with a pronounced emphasis on agroclimatic impacts and adaptation strategies. Our investigation reveals a dominant reliance on conventional ML models and uncovers a critical gap in the documentation of methodologies. This constrains the replicability, scalability, and adaptability of these technologies in agroclimatic research. In response to these challenges, we advocate for a strategic pivot toward Automated Machine Learning (AutoML) frameworks. AutoML not only simplifies and standardizes the model development process but also democratizes ML expertise, thereby catalyzing the advancement in agroclimatic research. The incorporation of AutoML stands to significantly enhance research scalability, adaptability, and overall performance, ushering in a new era of innovation in agricultural practices tailored to mitigate and adapt to climate change. This paper underscores the untapped potential of AutoML in revolutionizing agroclimatic research, propelling forward the development of sustainable and efficient agricultural solutions that are responsive to the evolving climate dynamics. [ABSTRACT FROM AUTHOR]

The integration of the Internet of Things (IoT) has brought about transformative changes across diverse industries, and its application in agriculture, particularly in soil management, has become a focal point of research and innovation. This paper explores the paradigm shift enabled by IoT in detecting organic carbon in soil, with the overarching goal of advancing agricultural productivity and sustainability. Emphasizing the pivotal role of organic carbon in soil health, the research addresses the existing challenges associated with its detection and underscores the potential advantages offered by IoT-based solutions for precise and real-time monitoring. The study meticulously examines various IoT technologies, including sensors, data analytics, and wireless communication protocols, within the specific context of organic carbon detection. A thorough review of contemporary techniques, methodologies, and devices utilized in IoT-based organic carbon detection in soil is presented. The paper not only sheds light on the current state-of-the-art but also explores the advantages, limitations, and prospects inherent in the implementation of IoT-enabled systems in agriculture. The envisioned outcomes encompass enhanced soil management practices, heightened crop yields, and the simultaneous preservation of the environment. In essence, this research contributes to the expanding body of knowledge surrounding IoT applications in agriculture, specifically emphasizing the transformative potential of IoT-enabled organic carbon detection for revolutionizing farming practices and promoting sustainable agricultural development. [ABSTRACT FROM AUTHOR]

This paper firstly compares the structure of agricultural supply chain ecosystem from both internal members and external environment and analyzes the information transfer mechanism of information flow, capital flow, logistics and other energy and information in the supply chain. The importance of supply chain ecological coordination mechanism and its functional components are also discussed in depth. On this basis, the biosecurity strategy system of agricultural products supply chain management is constructed and the biosecurity strategy of supply chain management is proposed. Finally, the biosafety risk of agricultural products supply chain management in the e-commerce environment is assessed, and a multi-dimensional risk assessment index is proposed. Meanwhile, risk management theory is applied to provide a detailed analysis of the likelihood, loss, contagiousness, controllability and comprehensiveness of risks. The study showed that the risk indices were relatively high with the average values of 85% for transportation and storage technology risk, 76% for additive abuse risk, and 70% for agricultural input improper risk, respectively. The research in this paper provides new ideas and methods for biosafety management in the supply chain of agricultural products. [ABSTRACT FROM AUTHOR]

Food security, a vital determinant of overall health and well-being, hinges on the simultaneous achievement of four dimensions: physical availability of food, economic and physical access to food, utilization of nutrients, and stability over time. This paper explores the complex and multi-faceted food security situations in Kenya and Zambia, emphasizing key factors such as agricultural production, government policies, and socio-economic conditions. [ABSTRACT FROM AUTHOR]

This document discusses the applications of machine learning in national territory spatial planning. National territory spatial planning is important for solving issues such as human-land conflict and regional development imbalance. Machine learning technology is being used to improve national territory spatial planning, but there is still a need for further exploration and research in this area. The document highlights research papers that focus on topics such as urban spatial environmental monitoring, food security and agricultural development, and methodological innovation in territorial spatial planning. The authors note that there are challenges and difficulties that need to be addressed in the future, including data mining, small-scale research, and practical case studies. [Extracted from the article]

To advance understanding about the way endogenous knowledge on mangrove swamp rice (MSR) farming is transmitted, reinvented and negotiated between generations and highlight the implications this has for R4D. Long-term qualitative research using an ethnographic approach, technography and biographies of farmers. The endogenous Agricultural Knowledge and Innovation System (AKIS) is dynamic but faces shortcomings owing to socio-environmental changes. This highlights the relevance of knowledge exchanges from multiple sources, eroding the divide between endogenous and exogenous from the farmers' point of view. For positive exogenously induced socio-technical change to occur, external actors must fully understand the conditions under which (a) endogenous knowledge is produced and reinvented and (b) endogenous innovations flow among farmers. This will then allow the co-production of innovations adapted to each specific agro-ecological, cultural and socio-economic context, leaving them to be further transformed and refashioned by smallholders to meet their individual 'dispositions' and generate the roots necessary for a strong AKIS. This paper highlights the importance of locally embedded processes of learning and innovation, the better understanding of which can provide a more solid basis for the co-production of technologies and the establishment of an AKIS. This paper improves understanding of socio-technological change in smallholder agriculture by focusing on endogenous processes of learning and innovation. This paper advances the knowledge on endogenous processes of learning and socio-technical change in smallholder agriculture. [ABSTRACT FROM AUTHOR]

The long-term and stable development of agriculture is the key to China's economic development and social stability. Agricultural total factor productivity and the digital economy have become new kinetic energy and new engines driving agricultural high-quality development. It is of great significance to verify whether there are significant spatial and threshold effects in the process of high-quality development of agriculture and to explore the intrinsic relationship between high-quality development of agriculture and agricultural total factor productivity and digital economy. This paper takes 31 provinces in China from 2011 to 2020 as the research object. The coefficient of variation method is used to estimate the comprehensive evaluation index of agricultural high-quality development and digital economy. And Dea-Malmquist index method is used to estimate agricultural total factor productivity. On this basis, the spatial Durbin model and threshold regression model are constructed to explore the spatial and threshold effects of agricultural total factor productivity, digital economy and other factors and high-quality agricultural development. The conclusion is as follows: the high-quality development of agriculture has significant spatial autocorrelation. Agricultural total factor productivity and digital economy have significant direct effect and indirect spillover effect on the high-quality development of agriculture. Agricultural total factor productivity has stage differences in each range of digital economy level, but its influence on agricultural high-quality development shows a positive state. Based on this, the paper puts forward some countermeasures to promote the high-quality development of agriculture. [ABSTRACT FROM AUTHOR]

Monitoring the agricultural production environment is crucial for optimal crop growth and resource efficiency. Cloud Computing, Artificial Intelligence (AI), and Big Data have revolutionized traditional agriculture, promising improved output and product quality. The popularity of these technologies drives their application in safety monitoring. This system facilitates data collection and transmission among equipment, overcoming challenges of traditional systems like investment, costs, and maintenance. In this paper, cloud computing-based AI optimization technology and big data network were proposed to monitor the safety of the agricultural production environment, and the shortcomings of traditional distance vector hop (DV hop) positioning algorithms were analyzed in depth. RSSI (Received Signal Strength Indication) technology improved the traditional DV Hop location method. The paper analyses direct and indirect transmission for data transmission between WSN and cloud nodes and favors indirect transmission because it consumes less invalid energy. Finally, the article compares several evaluations of alternative algorithms for monitoring system performance, including data transmission reliability, data reception rate, and data delay. The experimental results in this paper showed that in the data reception rate test, the data reception rate of System 2 was 97% at the lowest and 99% at the highest, both exceeding 95%. [ABSTRACT FROM AUTHOR]

With the new challenges and crises facing agriculture, digitalization and green transformation have become important ways to solve the problems. This paper uses an international economics perspective to chart a new path for sustainable agricultural development. Specifically, it analyzes whether two-way international direct investment (FDI) can facilitate agricultural digital-green fusion(DGF)? Using a sample of 31 provinces (autonomous regions) from 2012 to 2021, this study finds: (1) Two-way FDI can significantly contribute to agriculture's DGF. (2) In the mechanism test, it is proved that two-way FDI can promote agriculture's DGF level by promoting green technology innovation capacity and overall regional technology innovation capacity. (3) The positive effects of two-way FDI are prominent in the eastern and central regions, coastal regions, and economically developed areas. (4) In the spatial Durbin model, the local two-way FDI growth improves agriculture's DGF level in the surrounding areas to a certain extent. The government is advised to prioritize openness, foster an environment for technological innovation, leverage spatial radiation for agricultural DGF, and advance digitally empowered agricultural modernization. [ABSTRACT FROM AUTHOR]

The coupling coordination of agricultural technology innovation with food security is of great significance for high-quality agricultural development. By identifying the coupling coordination relationship between the two systems and the influencing factors, this paper aims to promote the virtuous cycle of coordinated development between regional agriculture and technology, as well as accelerate the realisation of high-quality development of Chinese agriculture. Therefore, this paper explores the spatial and temporal coupling characteristics of the two using the entropy value method, coupling coordination degree model, and exploratory spatial data analysis, and it screens for important influencing factors using the grey correlation model. The main results show that ① the coupling coordination relationship between agricultural technology innovation and food security in China is at a dissonant stage, but the value of the coupling coordination degree increases from 0.2076 to 0.3437 during the period of study, and the level of coordination gradually improves. ② The degree of coupling coordination in the provincial space exhibits a distribution pattern of "high in the east and low in the west". The areas of high value are primarily situated in the provinces of Shandong, Jiangsu, and other provinces along the southeastern coast of China, while the areas of low value are mainly located in the provinces of Qinghai, Ningxia, and other provinces in inland northwest China. ③ The Moran's index of provincial coupling coordination is greater than 0, showing a certain positive correlation, and there is a significant pattern of spatial aggregation. ④ The correlation coefficients between the influencing factors and the degree of coupling coordination are all greater than 0.35, indicating a moderate or high correlation, but the significance of technological support capacity and food distribution security increased over time. [ABSTRACT FROM AUTHOR]

Advancing the construction and application of new quality productive forces is an essential prerequisite for achieving high-quality agricultural development and expediting the establishment of agricultural powerhouses. This study aims to elucidate the internal mechanisms through which new quality productivity contributes to high-quality agricultural development and to explore practical pathways for enhancing agricultural quality through its promotion. Utilizing panel data spanning 2012 to 2021 from 30 provinces and municipalities in mainland China, the entropy method is employed to gauge levels of new quality productivity and high-quality agricultural development. Additionally, employing research methodologies including SYS-GMM and threshold effect models, this study empirically investigates how the advancement of new quality productivity influences high-quality agricultural development. Our research reveals the following key findings: (1) The development of new quality productive forces significantly enhances high-quality agricultural development, exhibiting a heterogeneous distribution pattern favoring the "eastern region > western region > central region" and "northern region > southern region". (2) New quality productive forces can bolster the level of high-quality agricultural development by fostering innovation, coordination, openness, and shared development within its subsystems. However, they may impede progress by inhibiting improvements in green development within the subsystems. (3) The results of the threshold effect test demonstrate that the promotion effect of the development of new quality productive forces on high-quality agricultural development escalates with the level of high-quality agricultural development. Specifically, as the level of high-quality agricultural development exceeds the first threshold value of 0.1502, the promotion effect becomes significant; crossing the second threshold value of 0.2010 further amplifies this effect. This paper's primary marginal contribution involves empirically analyzing the potential nonlinear effects of advancing new quality productivity in enhancing the level of high-quality agricultural development. This enriches empirical research on how new quality productivity fosters the development of high-quality agriculture. [ABSTRACT FROM AUTHOR]

Based on the panel data of provincial units in China from 2000 to 2020, this paper uses the entropy method to calculate agricultural environmental regulation level in China from the perspectives of afforestation projects, water conservancy projects and environmental protection projects. Then, this paper calculates agricultural non-point source pollutant emissions in China by using the unit survey and evaluation method, and calculates agricultural green productivity growth in China by using the SBM directional distance function and Luenberger productivity index. On this basis, the influence of environmental regulation on agricultural green productivity growth in China and its mechanism are empirically analysed. The results show that:(1) During the sample period, agricultural environmental regulation level and agricultural green productivity growth increased significantly, while the emission density of agricultural non-point source pollution decreased significantly; (2) On the whole, environmental regulation significantly promoted agricultural green productivity growth in China, which was mainly reflected in the promotion of agricultural green technology progress change; (3) Environmental regulation can significantly promote agricultural green productivity growth in China through the channel of agricultural innovation investment. The innovation of this paper lies in the measurement of agricultural environmental regulation, and the analysis of the moderating effect of agricultural innovation investment on the impact of environmental regulation on agricultural green productivity growth in China. The research conclusions of this paper verify the 'Porter Hypothesis' theory in the field of agriculture, and have guiding significance for China to promote agricultural green productivity growth by relying on environmental regulation. [ABSTRACT FROM AUTHOR]

The need to develop and provide integrated observation systems to better understand and manage global and regional environmental change is one of the major challenges facing Earth system science today. In 2008, the German Helmholtz Association took up this challenge and launched the German research infrastructure TERrestrial ENvironmental Observatories (TERENO). The aim of TERENO is the establishment and maintenance of a network of observatories as a basis for an interdisciplinary and long‐term research program to investigate the effects of global environmental change on terrestrial ecosystems and their socio‐economic consequences. State‐of‐the‐art methods from the field of environmental monitoring, geophysics, remote sensing, and modeling are used to record and analyze states and fluxes in different environmental disciplines from groundwater through the vadose zone, surface water, and biosphere, up to the lower atmosphere. Over the past 15 years we have collectively gained experience in operating a long‐term observing network, thereby overcoming unexpected operational and institutional challenges, exceeding expectations, and facilitating new research. Today, the TERENO network is a key pillar for environmental modeling and forecasting in Germany, an information hub for practitioners and policy stakeholders in agriculture, forestry, and water management at regional to national levels, a nucleus for international collaboration, academic training and scientific outreach, an important anchor for large‐scale experiments, and a trigger for methodological innovation and technological progress. This article describes TERENO's key services and functions, presents the main lessons learned from this 15‐year effort, and emphasizes the need to continue long‐term integrated environmental monitoring programmes in the future. Plain Language Summary: This paper discusses the importance of creating comprehensive environmental observation systems to better understand and address global and regional environmental changes. In 2008, a German research infrastructure named Terrestrial Environmental Observatories (TERENO) was established to build and maintain a network of observatories. The goal is to conduct interdisciplinary, long‐term research on the impacts of global environmental changes on terrestrial ecosystems and their socio‐economic effects. The TERENO network employs advanced methods from environmental monitoring, geophysics, remote sensing, and modeling to study various environmental aspects. Over the past 15 years, four observatories have been part of this network, contributing to valuable experience in overcoming challenges and exceeding expectations. Today, TERENO is a crucial component for environmental modeling and forecasting in Germany, serving as an information hub for practitioners and policymakers. It also fosters international collaboration, supports large‐scale experiments, and drives methodological and technological advancements. The article highlights key lessons learned from this 15‐year effort and emphasizes the importance of continuing such integrated environmental monitoring programs in the future. Key Points: Integrated observatories ensure a holistic Earth Systems perspective, offering data for current and future ecological challengesThe scientific and societal value of observatories is invaluable, but their design, construction and operation require considerable effortFor assured long‐term data collection, research infrastructure must have flexible design for adapting to changing research needs [ABSTRACT FROM AUTHOR]

Visual simultaneous localization and mapping (VSLAM) is a foundational technology that enables robots to achieve fully autonomous locomotion, exploration, inspection, and more within complex environments. Its applicability also extends significantly to agricultural settings. While numerous impressive VSLAM systems have emerged, a majority of them rely on static world assumptions. This reliance constrains their use in real dynamic scenarios and leads to increased instability when applied to agricultural contexts. To address the problem of detecting and eliminating slow dynamic objects in outdoor forest and tea garden agricultural scenarios, this paper presents a dynamic VSLAM innovation called MOLO-SLAM (mask ORB label optimization SLAM). MOLO-SLAM merges the ORBSLAM2 framework with the Mask-RCNN instance segmentation network, utilizing masks and bounding boxes to enhance the accuracy and cleanliness of 3D point clouds. Additionally, we used the BundleFusion reconstruction algorithm for 3D mesh model reconstruction. By comparing our algorithm with various dynamic VSLAM algorithms on the TUM and KITTI datasets, the results demonstrate significant improvements, with enhancements of up to 97.72%, 98.51%, and 28.07% relative to the original ORBSLAM2 on the three datasets. This showcases the outstanding advantages of our algorithm. [ABSTRACT FROM AUTHOR]

The digital economy is a key driver of greener agriculture and sustainable development. This paper focuses on the impact of the digital economy on green agricultural development and the mediating role of green technology innovation. Using provincial panel data from China from 2011 to 2020, we test hypotheses using fixed effects models. The results indicate that: (a) the digital economy boosts agricultural total factor productivity (AGTFP); (b) green technology innovation positively moderates the relationship between the digital economy and AGTFP; and (c) the positive impact of the digital economy on green agriculture varies across regions, favoring eastern areas. [ABSTRACT FROM AUTHOR]

On-farm experimentation (OFE) renovates agronomic research since it brings researchers out of their experimental field stations to the farms, shaping the direction of research in collaboration with farmers. In the context of increasing interest in OFE, this paper aims to map the current picture of agronomic research articles published on OFE in Italy. We observe that few articles are published on OFE in Italy. Moreover, among these articles, only a few explicitly mentioned farmers' opinions or involvement, while none of them mentioned digital technologies as enablers of OFE. Therefore, we started a SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis to identify the main weaknesses and threats limiting OFE developing in Italy, along with the opportunities and strengths enabling OFE development. Despite the time-consuming research underpinning OFE, the lack of recognition by the academic community, the risk of not robust statistic, and difficulties in publishing, there are a series of opportunities emerging at the national level for which the implementation of OFE could be crucial to properly target the scopes set by the EU concerning agricultural research and innovation. [ABSTRACT FROM AUTHOR]

Copyright of Glasnik Zastite Bilja is the property of Zadruzna Stampa D.D. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Rural industrial integration is the key to promoting the development of rural industrial restructuring and modernization, and plays a vital role in improving agricultural economic resilience. Based on the evaluation index system of agricultural economic resilience and the level of rural industrial integration development, respectively, this paper uses panel data from 30 provincial administrative regions in China from 2000 to 2020 to empirically test the impact of rural industrial integration development on agricultural economic resilience by using an individual fixed-effects model and a mediating-effects model. The results show that rural industrial integration significantly contributes to enhancing agricultural economic resilience, and the conclusion still holds after a series of robustness tests. There is dimensional and regional heterogeneity in the impact of rural industrial integration on agricultural economic resilience, and the strength of the promotion effect by dimension is in the order of adaptive adjustment capacity, transformation and innovation capacity, and resilience to recovery capacity. In the eastern and central regions, the promotion effect of rural industrial integration on agricultural economic resilience is more significant. In the main food-producing areas, the promotion effect of rural industrial integration on resilience to recovery is significantly slighter than that of non-food-producing regions. Mechanism analysis indicates that regional industrial structure optimization is an essential channel for rural industrial integration to enhance the resilience of the agricultural economy. On this basis, in order to strengthen agricultural economic resilience, provinces should actively explore differentiated industrial integration policies to enhance industrial structure optimization and upgrading, stimulate agricultural economic vitality, and foster the development of China's agricultural modernization. [ABSTRACT FROM AUTHOR]

Tailored data-driven "Digital Agriculture" solutions bring about many benefits. However, there are also challenges related to complicated data access needs in the farm-to-fork chain. Farm-specific data are mostly locked in by the first-mover companies. This prevents farmers from switching to a better or cheaper alternative. This also hinders agricultural data-driven innovation due to unanswered access seekers. Moreover, already powerful players build exclusive data exchange clusters that further exclude small rivals and other access seekers. Also, upstream input producers have exclusive control over their products' performance data, which generates critical advantages for their downstream data-driven services. These conditions endanger the digital agriculture sector and bring about the risk of reflection of the oligopolistic upstream players in this new sector. This paper explores the adequacy of EU competition law enforcement to address the ag-data access-related concerns – hoping to contribute to the sectoral literature that is currently dominated by regulation-centred discussions. [ABSTRACT FROM AUTHOR]

To assess the effectiveness of the management of land resources for agricultural enterprises suggested factors affecting the market for agricultural products, which integrates a system of environmental, economic and social indicators in this area. The paper highlights main theoretical aspects of the land resource management of the agricultural enterprises. The essence of land resource management is shown based on the definition of the objects of management, which are land resources of agricultural enterprises, subjects of management, which are landowners and employees of such agricultural enterprises, and objective of management, which is providing and maintaining the efficiency of land resources usage as a key factor of agricultural production. The land market and its structure are presented in detail. Described prospects management of land resources of agricultural enterprises. A complete analysis of mortgage lending secured by agricultural lands has been carried out. A decrease in the number of agricultural enterprises, which is mostly connected with imperfections of land governance, formed in the state, has been identified. Relationships between strengths and weaknesses of agricultural enterprises, opportunities, and threats of efficient land use have been identified. Scenarios of economic development have been considered, which should be taken into account while developing a strategy. [ABSTRACT FROM AUTHOR]

Rural operation system reform is vital in promoting rural revitalisation and agricultural and rural modernisation in China. Based on the sample data of 153 counties in Sichuan Province from 2012 to 2020, this paper constructs a PSM-DID evaluation model to analyse the effectiveness of rural operation system reform on agricultural development from the perspective of policy action mechanism, variable differentiation and other aspects. The results show that: (1) rural operation system reform has significantly boosted the economic development of the counties implementing the pilot reform of the rural operation system; (2) rural operation system reform mainly has two components: rural land system reform and agriculture organisation innovation; both have an impact on county economic and social development, but the degrees of impact are different; (3) the effectiveness of the rural operation system reform policy has a specific time lag. The results of this paper enrich the effectiveness evaluation of the reform policy on economic development and have policy implications for further promotion of agricultural and rural reform in China. [ABSTRACT FROM AUTHOR]

The article discusses opinion paper titled "Hydrology and change" by professor of hydrology Demetris Koutsoyiannis. It mentions Hurst-Kolmogorov (HK) statistical effect which is the focus of the paper and suggests invention of tools with HK effect for future day predictions. It also presents discussion on the physical changes along with time such as change in climatic conditions due to human activities including innovation in agriculture, industrial advancement and electronic revolution.

Efficient agricultural advisory and extension service (AES) is poised to lead to improved agricultural productivity as farmers utilize information and knowledge to optimize their use of limited resources. However, the role of AES has progressively evolved due to the changing technological, economic and social context. This paper uses primary and secondary data to study the AES delivery process in Kenya. This process is interrogated from an inclusivity perspective based on the suitability of related AES approaches in reaching out to rural communities in the acquisition of services for innovation purposes. The study finds differences in AES approaches that can effectively stimulate institutional innovation in an equitable way. In addition, approaches for delivery of AES are hampered by several factors that either constrain or perpetuate inclusivity more generally. The paper enhances discussion around the importance of agricultural AES as a key function of the agricultural innovation system, especially in a rural setting. [ABSTRACT FROM AUTHOR]

Scientifically characterizing the intrinsic mechanism of the biased reduction targets affecting agricultural green innovation is of great practical significance for the systematic promotion of the greening transformation of China's agricultural development mode. This paper first constructed a two-sector endogenous economic growth model, theoretically deducing the intrinsic mechanism by which the bias reduction targets were adjusted through the green transformation of agricultural production input factors, which in turn affected the research and development decision-making of the agricultural innovation sector. To the end, this paper treated the strategy of zero growth in synthetic fertilizer use (ZGS) implemented in 2015 as a policy shock and empirically assessed its green innovation effect using the staggered difference-in-differences model. The results showed that ZGS significantly contributed to the increase of green patents in Chinese agriculture. The above conclusion still held after a series of robustness tests, including using terrain complexity as an instrumental variable, estimating the robust staggered difference-in-differences model, eliminating policy interference, altering the estimated model, and replacing the explanatory variables. However, the obvious regional heterogeneity of this effect was reported: the higher the level of marketization and digitalization, the fuller the release of this innovation effect; and that ZGS was more significant in inducing the green innovation activities of enterprises and individuals than of innovation bodies such as universities and research institutions. Finally, this paper also empirically tested the two paths of the theoretical model about the green innovation effect triggered by the biased reduction targets. The study confirmed that the green innovation effect of ZGS mainly resulted from two channels: the expansion of the market scale for agricultural green technologies and the green-oriented allocation of innovation resources. The above conclusions imply that it is necessary to create a sound innovation ecology by strengthening the innovation of green science and technology institutions and combining active government with an effective market. Particularly, a portfolio of policy instruments, including the fiscal, taxation, financial, investment, price policy, and standard system concerning green technology development, should be created to guarantee green technology development. In addition, ZGS can set up differentiated reduction targets considering regional endowment conditions to ensure its smooth progress. [ABSTRACT FROM AUTHOR]

Shadow, a natural phenomenon resulting from the absence of light, plays a pivotal role in agriculture, particularly in processes such as photosynthesis in plants. Despite the availability of generic shadow datasets, many suffer from annotation errors and lack detailed representations of agricultural shadows with possible human activity inside, excluding those derived from satellite or drone views. In this paper, we present an evaluation of a synthetically generated top-down shadow segmentation dataset characterized by photorealistic rendering and accurate shadow masks. We aim to determine its efficacy compared to real-world datasets and assess how factors such as annotation quality and image domain influence neural network model training. To establish a baseline, we trained numerous baseline architectures and subsequently explored transfer learning using various freely available shadow datasets. We further evaluated the out-of-domain performance compared to the training set of other shadow datasets. Our findings suggest that AgroSegNet demonstrates competitive performance and is effective for transfer learning, particularly in domains similar to agriculture. [ABSTRACT FROM AUTHOR]

Copyright of Economics & Environment / Ekonomia i Środowisko is the property of Fundacja Ekonomistow Srodowiska i Zasobow Naturalnych and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This research conducts an analysis of the sustainability of urban agriculture in Shanghai over the period 2010 to 2020, employing the Triple Bottom Line (TBL) concept as a framework to evaluate sustainability across economic, environmental, and social dimensions through the formulation and application of a comprehensive indicator system. Utilizing the Delphi method alongside the Analytic Hierarchy Process (AHP) for determining indicators and their respective weights, this study adopts a methodologically rigorous approach to analysis. The findings reveal an overall enhancement in agricultural sustainability, albeit accompanied by a decline in economic sustainability. Notably, environmental sustainability emerged as a paramount concern, underscoring the essentiality of incorporating environmental indicators within urban agricultural initiatives. The paper addresses significant challenges such as elevated land prices, demographic shifts, and the imperative for more stringent environmental regulations. It advocates for a multidimensional strategy integrating advanced agricultural technologies and cross-sectoral partnerships to bolster sustainability. Furthermore, the study accentuates the necessity of achieving equilibrium among economic feasibility, environmental stewardship, and social equity to pursue sustainable urban agriculture in Shanghai. Additionally, it highlights the critical role of strategic agricultural policy formulation in fostering sectoral resilience and ensuring enduring sustainability. [ABSTRACT FROM AUTHOR]

Farm Advisory constitutes one of the most important tools to support rural development in the European Union and is also an integral part of Agricultural Knowledge and Innovation System (AKIS). The purpose of this paper is to present the results of the evaluation of the two calls for certification of Farm Advisors in Greece, which were addressed to individuals. The evaluation was based on a questionnaire survey of candidates who participated to the online certification procedure. The analysis is based on descriptive statistics methods and shows that overall most respondents were satisfied with most Modules, although they suggest to provide better links between scientific evidence and practical applications. Although there are serious limitations that do not permit to draw generalized conclusions, the evaluation procedure pointed out specific domains that require improvements and, especially, that a more robust evaluation system is required. [ABSTRACT FROM AUTHOR]

The aim of this paper is to answer the question of whether the Greek AKIS system can contribute to the different requirements of the new trends in agriculture according to its main functions. A SWOT analysis has been applied to examine the internal and external environment. Data were collected from 61 experts/representatives of organizations (policy, education, research, consulting, agricultural cooperatives, credit, private companies, and farmers). The data were analysed using Excel spreadsheets and the Statical Package for Social Sciences (SPSS V.28). Based on this method, dominant strengths and weaknesses as well as opportunities and threats of AKIS were identified as a starting point, as well as useful guidance for decision makers, local authorities, and the other actors in Greece. [ABSTRACT FROM AUTHOR]

This paper investigates the implementation of innovation and the advisory needs of farmers in agricultural holdings in Western Macedonia. The research carried out was divided into two parts. Initially, we investigated how the programs under analysis related to innovation in the agricultural sector, specifically with respect to the improvement plans that were implemented in the region. Specifically, parameters such as age, gender, place of residence, and the types and number of investments were examined. The analysis revealed farmers' characteristics and the types of their investments, in addition to their degrees of adoption of innovation and their attitudes towards innovation. We also tried to clarify the reasons leading farmers toward innovation and the importance of consulting services in their orientation towards innovative ideas. [ABSTRACT FROM AUTHOR]

Digital twins are essential in Agriculture 5.0, providing an accurate digital representation of agricultural objects and processes, enabling data-driven decision-making, the simulation of future scenarios, and innovation for a more efficient and sustainable agriculture. The main objective of this article is to review and compare the main tools for the development of digital twins for Agriculture 5.0 applications using 3D point cloud models created from photogrammetry techniques. For this purpose, the most commonly used tools for the development of these 3D models are presented. As a methodological approach, a qualitative comparison of the main characteristics of these tools was carried out. Then, based on some images taken in an orange grove, a quality analysis of the 3D point cloud models obtained by each of the analyzed tools was carried out. We also obtained a synthetic quality index in order to have a way to categorize the different pieces of software. Finally, as a conclusion, we compared the performance of the different software tools and the point clouds obtained by considering objective metrics (from the 3D quality assessment) and qualitative metrics in the synthetic quality index. With this index, we found that OpenDroneMap was the best software in terms of quality-cost ratio. Also, the paper introduces the concept of Agriculture 6.0, exploring the integration of advancements from Agriculture 5.0 to envision the potential evolution of agricultural practices and technologies, considering their impact on social and economic aspects. [ABSTRACT FROM AUTHOR]

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The year 2022 marks the ten‐year anniversary of the White House's Big Data Research and Development Initiative. While this initiative, and the others it spawned, helped to advance the many facets of data intensive research and discovery, obstacles and challenges still exist. If left unaddressed these obstacles will persist and at a minimum limit the potential of what can be achieved by harnessing the many new ways to collect, analyze, and share data and the insights that can be drawn from them. The opportunities and challenges related to Big Data in agriculture touch on all aspects of the general research data lifecycle; from instruments used to gather data, to advanced digital platforms used to store, analyze, and share data, and the innovative insights from using advanced computational methods. The eight papers included in this special issue were chosen in part because they highlight both the challenges and the opportunities that come from all stages of the data lifecycle common across agricultural research and development. These papers grew out of several workshops made possible by the support of the Midwest Regional Big Data Hub, which is sponsored by the National Science Foundation. Core Ideas: New data generators, data platforms, and analytical methods make the promises of Big Data as relevant as ever.Data intensive agricultural Research & Development is raising ownership and privacy concerns, especially by private stakeholders.Sustained agricultural innovation requires a pipeline of new solutions to address data ownership and privacy issues. [ABSTRACT FROM AUTHOR]

This paper surveys some of the key themes in European agricultural policy research in recent decades. It identifies three main drivers of this research: a gradual broadening of the scope of the discipline in response to changing political priorities and values; an enlarged toolbox of policy instruments that has raised new questions and required the development of new modes of analysis; and the availability of new data sources, increased computing power, as well as the introduction of new methodological advances from economics, statistics and psychology that have opened the way to new and more powerful analytical tools. Particular attention is paid to direct payments and agri-environment-climate measures as examples of new policy instruments that have driven the research agenda. The paper concludes by identifying requirements to ensure that agricultural policy research remains vibrant and relevant in the future. [ABSTRACT FROM AUTHOR]

Finding out how to scale innovations successfully is high on the agendas of researchers, practitioners and policy makers involved in agricultural development. New approaches and methodologies seek to better address related complexities, but none of them include a systematic perspective on the role of capacity in (partnerships for) scaling innovations. We posit that this has left an important topic insufficiently addressed in relation to partnerships for scaling innovations. The need to address this gap became apparent in the context of the CGIAR Roots, Tubers, and Bananas (RTB) Scaling Fund initiative. This paper presents how we explored ways forward in relation to this by combining three methodological approaches: The Five-Capabilities, Scaling Readiness, and the Multi-Level Perspective on socio-technical innovation. This combined approach—dubbed Capacity for Scaling Innovations (C4SI)—was applied in three projects related to scaling innovations for sweet potato, cassava and banana, involving five countries in Africa. It then discusses implications for a partners-in-scaling perspective, the contribution of scaling innovations to sustainable development, the importance of research organisations considering their own capabilities in partnerships for scaling, and the extent to which C4SI was helpful in the three cases—for example, in decision making. The paper concludes that a capacity perspective on the scaling of innovations should be an essential part of a 'science of scaling'. Finally, it provides recommendations for using the approach or parts of it in research and intervention practice for scaling, pointing in particular to the need for context-specific adaptation. [ABSTRACT FROM AUTHOR]

The agricultural sector has a critical role in creating social and environmental value of natural resources in addition to its traditional role of creating economic value by supplying food to the ever-increasing world population. In fulfilling this dual role, the agricultural sector often faces competing pressures: to operate financially profitable businesses and to create, maintain, and benefit from ecosystem services (ES) in their operations. This paper analyses these pressures in an examination of drivers and barriers to the initiation of the business model innovation process for sustainability (BMIpfS) as perceived by ten agricultural business managers who operate farms in southern Sweden. The paper explores the interplay between managerial cognition and business decisions as revealed in semi-structured interviews. The new ES in focus connect to radical land-use change, paludiculture, as used in the rewetting of farmland intended to reduce the greenhouse gas emissions that drained peat soil causes. The paper contributes to the literature by identifying drivers and barriers that moderates the initiation of the BMIpfS. Although the managers acknowledge the importance of long-term, sustainable social, and environmental value creation, they have grave doubts about the profitability of activities associated with the preservation of peat soils and connected ES. These managers would benefit from taking a more proactive, long-term approach to business model changes for sustainability and from acquiring more knowledge about market demand for sustainability-oriented ES. Successful facilitation and implementation of knowledge transfer and government subsidies that support ES could improve the turning of profits based on sustainable value creation. [ABSTRACT FROM AUTHOR]

The need to increase the volume of domestic agricultural production and overcome the import dependence of hightech intermediate products actualizes the task of creating mechanisms to support and stimulate demand for innovative products of the agro-industrial complex. The purpose of the article is to develop theoretical and methodological foundations for the formation of scientific and technological policy to stimulate demand for innovative products in the agro-industrial complex. The theoretical foundations of the institutional interaction between the state, universities, academic institutions, agribusiness based on marketing and co-creation of values have been developed. taking into account the needs for innovation in the context of industries and regions. The study analyzes the innovative activity of some European countries, reveals disproportions between the costs of innovation and the volume of shipped products in various countries. The calculation of the index of marketing potential on the basis of a database for 83 regions was carried out and a comparison was made of the index of the country as a whole and a typical region in order to develop targeted strategies for state support. The practical significance of the research results lies in the possibility of their use in the development of mechanisms for state support of demand for innovations and digital technologies in the agro-industrial complex. [ABSTRACT FROM AUTHOR]

This study systematically explores, analyses, reports on and synthesises research on the topic of sectoral innovation systems related to agriculture and agri-food in OECD countries. It is based on systematic mapping of the literature (academic papers published in scientific journals) in the period 1997-2017. The aim is to show the state of current knowledge on sectoral innovation systems in agri-food, in order to identify knowledge gaps and future areas for research and provide methodological and theoretical perspectives. Abstracts for a total of 320 papers were analysed, using a qualitative approach. Key elements of agricultural innovation systems identified were organised into 8 main themes/topics: agents, basic technologies, knowledge and learning processes, mechanisms of interaction, institutions, end-users, system transition and contextual variables. Areas identified as requiring research included making the sector more consumer- and market-oriented, increasing interactions outside conventional system boundaries, including the consumer perspective and societal changes, and determining the role of gender in innovation in agri-food systems. [ABSTRACT FROM AUTHOR]

Agricultural innovation implies sharing information between researchers and farmers. Acknowledging the value of the other partner's knowledge is a preliminary step to facilitate agricultural interactive models. Traditionally, researchers' knowledges have been dominant, and farmers' knowledges have been underestimated. A large number of innovation papers pay attention to farmers' attitudes, interests, perceptions, barriers or drivers to change their practices. However, there is not so much information about researchers' point of view. The present paper analyses researchers' perceptions about farmers' knowledges and information sources. It is based on a survey of 156 agricultural researchers mostly from public institutions in Spain. Descriptive statistics and principal component analysis (PCA) focused on researchers' perceptions of farmers' knowledges and information sources. This paper finds that there are two distinct profiles of researchers according to their perceptions on the relevance of knowledges and information sources for farmers. However, both profiles shared the view of 'own experience' as a highly relevant source for farmers' knowledges. It advises how to promote knowledge sharing according to different researchers' perceptions of farmers' knowledges and information sources. This paper classifies agricultural researchers according to their perceptions of farmers' knowledges and information sources. This classification enriches the discussion about agricultural interactive knowledge models. This paper pays attention to researchers' perceptions of farmers' knowledges and information sources. It particularly focuses on multi-actor approaches and the integration of farmers' and researchers' knowledges. [ABSTRACT FROM AUTHOR]

We studied innovation processes in agriculture and nutrition to discuss a scaling approach that encompasses the technical, institutional, and behavioral dimensions of change. To understand dynamics across these dimensions, we analyzed farmers' innovation processes through two analytical lenses: farmer-centered and structural. Focus group discussions in Kapchorwa, Uganda, and Teso South, Kenya, looked at farmers' choices of innovations. Individual interviews and stakeholder workshops at both study sites increased understanding of the local innovation system. To address local challenges, strive for livelihood aspirations, and fulfill personal taste preferences, farmers selected and adapted practices promoted by a research project. A wide range of additional support providers encouraged farmers to develop innovations in agriculture, marketing, and nutrition. By promoting innovation as a process rather than an outcome, it is possible to address context-specific needs and enhance farmers' adaptive capacities. Scaling these processes necessitates the involvement of innovation support service providers in order to create an enabling environment for experimentation. Analytical dualism highlights the different roles of human agency and structures in innovation processes needed to design successful scaling strategies. This paper sets out a novel approach to understanding the increasingly discussed dimensions of scaling by linking them with concepts from innovation studies. [ABSTRACT FROM AUTHOR]

Sustainability in our food and fiber agriculture systems is inherently knowledge intensive. It is more likely to be achieved by using all the knowledge, technology, and resources available, including data-driven agricultural technology and precision agriculture methods, than by relying entirely on human powers of observation, analysis, and memory following practical experience. Data collected by sensors and digested by artificial intelligence (AI) can help farmers learn about synergies between the domains of natural systems that are key to simultaneously achieve sustainability and food security. In the quest for agricultural sustainability, some high-payoff research areas are suggested to resolve critical legal and technical barriers as well as economic and social constraints. These include: the development of holistic decision-making systems, automated animal intake measurement, low-cost environmental sensors, robot obstacle avoidance, integrating remote sensing with crop and pasture models, extension methods for data-driven agriculture, methods for exploiting naturally occurring Genotype x Environment x Management experiments, innovation in business models for data sharing and data regulation reinforcing trust. Public funding for research is needed in several critical areas identified in this paper to enable sustainable agriculture and innovation. [ABSTRACT FROM AUTHOR]