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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 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]

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]

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]

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]

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]

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]

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]

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]

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]

The purpose of this paper was to examine the differences in using agricultural entrepreneurship support and how it relates to characteristics such as the agrarian structure, socioeconomic development level, and land use across the Polish territory. The analyses were carried out at the district (poviat) level which is an intermediate administrative unit. This study found that the decisions on co-financing the measures dedicated to non-agricultural economic activity heavily depended on the agrarian structure. The highest levels of activity were witnessed in districts where the agrarian structure was particularly fragmented. [ABSTRACT FROM AUTHOR]

The digital economy, closely linked to agricultural progress, plays a key role in reducing agricultural carbon emissions. By utilizing panel data between 2011 and 2021 from 30 Chinese provincial-level regions, the present work empirically assesses the direct impact and nonlinear spatial spillover effects of the digital economy on agricultural carbon emissions, where methodologies including fixed effects, threshold models, and spatial econometrics are employed. The results were as follows: (1) The digital economy led to remarkable inhibition of agricultural carbon emissions, which was consistent across various robustness checks. (2) The carbon reduction efficiency of the digital economy presented obvious spatial variation, which had a greater negative effect in eastern regions and major grain-producing regions. (3) The digital economy had a nonlinear impact on agricultural carbon emissions, and technological innovation played a threshold effect, showing an "inverted U-shaped" characteristic of increasing first and then decreasing overall. (4) This emission abatement effect also showed a significant spatial spillover aspect, meaning that the digital economy development in one area prominently abates agricultural carbon emissions in adjacent provinces. Our findings might provide a theoretical and empirical foundation for comprehending and addressing agricultural carbon emissions abatement in China from the digital economy perspective. [ABSTRACT FROM AUTHOR]

Volumetric-based pricing for irrigation water was introduced as part of a comprehensive reform of agricultural water prices in China. However, operational deficiencies and farmers' lack of willingness to adopt the volumetric pricing policy (VPP) hinder the coordinated implementation of the reform. To address these practical challenges, we employed a binary logistic regression model to analyse farmers' acceptance of the VPP for agricultural irrigation water usage in Suqian City, Jiangsu Province. A variable set was formed by selecting potential variables from four types of influencing factors: the subject (water users), the object (water supply departments), natural condition factors, and social condition factors. Our results revealed seven factors that determine whether farmers accept the VPP: irrigation water measurement at the water inlet of a lateral canal, the irrigation water-saving rewards scale, enforcement efforts of charging by volume, the irrigation water source type, the use of agricultural water-saving for trade, financial investment in water-saving technology, and the level of irrigation water pricing. We determined the degree of influence of the seven determining factors, among which the irrigation water-saving rewards scale and enforcement efforts of charging by volume most influence farmers' decisions on the VPP for irrigation water. The results of this study can be used as a reference for innovation of the agricultural water-saving system in Suqian City, optimisation of an accurate fiscal subsidy scale, quantification of irrigation water rights, optimisation of the measurement facility layout, and effective implementation of agricultural water rights trading. More broadly, this study provides a valuable reference for solving the difficulties faced in the comprehensive reform of agricultural water pricing in China, which includes irrigation water pricing mechanisms, management systems, subsidy mechanisms, and water-saving incentive measures. [ABSTRACT FROM AUTHOR]

The United Nations Environment Programme's (UNEP's) Food Waste Index Report 2021 highlights a global annual food waste of 1 billion tons. The UNEP plays a crucial role in achieving Sustainable Development Goal (SDG) 12.3, which aims to halve per capita global food waste (FW) at the retail and consumer levels and reduce food losses along production and supply chains globally by 2030. On the other hand, the agricultural sector faces the challenge of increasing productivity to feed the world's growing population while reducing the environmental impact on ecosystems and human health. In this context, the conversion of agri-food waste (AFW) into biocides, bio-based fertilizers (BBFs) and biostimulants could represent a successful approach to tackle all these issues. This review shows the latest findings on the different sources of AFW and the application of their bioactive compounds in agriculture. Increasing crop yields and improving plant physiology through the utilization of AFW-derived value products aligns with a circular economy approach, bolstering people's confidence in managing food waste for improved food production. [ABSTRACT FROM AUTHOR]

In this study, we aim to explore the possible relationships between innovation, social capital, and farm viability towards sustainability, using indicators from the literature and developing complex indexes for all examined concepts in the framework of an agriculture cooperative located on the Greek island of Samos. Data from the United Winemaking Agricultural Cooperative of Samos (UWC SAMOS) were collected through semi-structured questionnaires and further personal in-depth interviews. The findings revealed a highly complex relationship between these indexes that could not just be analyzed quantitatively. Instead, qualitative data explain the weak innovation and low level of social trust by identifying the "institutionalization of the members of the cooperative", emphasizing the importance of mixed methods approaches. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) is revolutionizing approaches in plant disease management and phytopathological research. This review analyzes current applications and future directions of AI in addressing evolving agricultural challenges. Plant diseases annually cause 10–16% yield losses in major crops, prompting urgent innovations. Artificial intelligence (AI) shows an aptitude for automated disease detection and diagnosis utilizing image recognition techniques, with reported accuracies exceeding 95% and surpassing human visual assessment. Forecasting models integrating weather, soil, and crop data enable preemptive interventions by predicting spatial-temporal outbreak risks weeks in advance at 81–95% precision, minimizing pesticide usage. Precision agriculture powered by AI optimizes data-driven, tailored crop protection strategies boosting resilience. Real-time monitoring leveraging AI discerns pre-symptomatic anomalies from plant and environmental data for early alerts. These applications highlight AI's proficiency in illuminating opaque disease patterns within increasingly complex agricultural data. Machine learning techniques overcome human cognitive constraints by discovering multivariate correlations unnoticed before. AI is poised to transform in-field decision-making around disease prevention and precision management. Overall, AI constitutes a strategic innovation pathway to strengthen ecological plant health management amidst climate change, globalization, and agricultural intensification pressures. With prudent and ethical implementation, AI-enabled tools promise to enable next-generation phytopathology, enhancing crop resilience worldwide. [ABSTRACT FROM AUTHOR]

Feeding nine billion people by 2050 will be a challenge due to climate change. There is a significant portion of abandoned and unused marginal lands across the nation and in the Puglia region, in Southern Italy. Innovative techniques and practices in the frame of climate-smart agriculture can help rehabilitate marginal lands into productive and profitable areas. The objective of this study was to systematically review the literature on marginal areas in Puglia, responding to the lack of information in this context and evaluate their revitalization potential. We systematically reviewed the literature on unused/marginal areas and identified related studies dealing with different types of marginal areas and their potential for sustainable rural development. Marginal areas in Puglia represent a range of historical rural landscapes that support biodiversity, the economy, and ecological services. However, the analysis of the current situation in Puglia's marginal areas indicates a lack of infrastructure and scarce resources, which led to land abandonment and the migration of local residents, resulting in the deterioration of the ecological system. Therefore, establishing a sustainable policy is crucial for preserving the local heritage and economy of the region. However, policymakers should carefully study the challenges and opportunities arising from local contexts before embarking on ambitious place-based innovation strategies. The analysis indicates that both biophysical and socio-economic factors are strategic elements for improving the revitalization potential of marginal areas for sustainable development. This review provides useful information regarding the revitalization potential of marginal areas for food, feed, and non-food production, which is crucial in the implementation of a sustainable development strategy for rural communities in Puglia but can also be applied to similar areas in other countries. However, the success of the sustainable development strategy in Puglia's marginal areas should consider the vital function of farmers' self-organization and social capital as key factors in the adoption of agricultural innovations for the revitalization of these areas. [ABSTRACT FROM AUTHOR]

The digitalization of agriculture generates a new environment for the actors involved in agrifood production. In such a context, Agricultural Knowledge and Innovation Systems (AKISs) face the challenge of reconsidering their operational paradigms, redefining priorities, and designing strategies to achieve new aims. To do so, the actors participating in AKISs should develop and exploit a set of competencies known as dynamic capabilities, including the aptitude to sense the change in the external environment, the capacity to seize the opportunities that this change creates, and an ability to transform and adapt themselves to the new conditions that digitalization generates. In this study, using as examples the AKISs operating in Greece and Italy, we aimed to uncover if and how actors participating in these systems attempt and manage to deploy such capabilities. Based on a qualitative approach and drawing on data from two workshops, we discovered that seizing the opportunities sensed is a challenging task for AKIS actors. Our results also indicate that knowledge is a pivotal resource for AKISs, allowing actors to enhance their transformative capacity. However, to create a "collective" knowledge base, AKISs should ensure a functional connection between stakeholders and strengthen the roles of actors not actively engaged with the system, like public advisory organizations, universities, and technology providers. [ABSTRACT FROM AUTHOR]

Agricultural chambers together with agricultural advisory centers and other entities are part of the European Union Agricultural Knowledge and Innovation System (AKIS). The system consists of a network of entities whose activities are focused on the introduction of new products, technologies, and organizational forms for use in agriculture. The AKIS is also defined as a network of research institutes, advisory centers, agricultural chambers, agricultural schools, and other non-governmental organizations that help farmers to upgrade the innovativeness and competitiveness of their farms and solve agriculture-related problems. In Poland, the activities of self-government in the agricultural sector are specified by the Act on Agricultural Chambers of 14 December 1995. An important research problem is the assessment of the activities of agricultural chambers in terms of the transfer of knowledge and innovations in agriculture in Poland and the determination of their place in the AKIS. This study of the impact of agricultural self-government on the transfer of knowledge and innovations in agriculture was carried out through the analysis of selected agricultural chambers in various regions of Poland taking into account the differences in the average surface area of agricultural land belonging to one farm. The research shows that agricultural chambers' activities had a substantial impact on the rate of absorption of EU funds under the Rural Development Program in the analyzed regions. The comparison of the effectiveness of the agricultural chambers in Poland with the activities of chambers in the other EU Member States indicates a weak influence of the former on developmental processes in agriculture. Agricultural chambers should actively participate in the formulation of the national agricultural policy, take greater measures to ensure the stability of agricultural income and the flow of information, and be an important partner for farmers in representing their interests. [ABSTRACT FROM AUTHOR]