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Avocado is one of the most commercialized and profitable fruits in the international market. Its cultivation and production are centered in countries characterized by tropical and subtropical climatic conditions, many of them with emerging economies. Moreover, the use of technology is key to agricultural production improvement strategies. Using avocado crop data to forecast the potential impacts of biotic and abiotic factors, combined with smart farming technologies, growers can apply measures during a single production phase to reduce the risks caused by pests and weather variations. Therefore, this paper aims to distinguish the most relevant variables related to agroclimatic and phytosanitary events in avocado crops, their incidence on production and risk management, as well as the emerging technologies used for the identification and analysis of pests and diseases in avocados. A scientific literature search was performed, and the first search found 608 studies, and once the screening process was applied, 37 papers were included in this review. In the results, three research questions were answered that described the pests and diseases with high impact on avocado production, along with the data sources and the principal enabling technologies used in the identification of agroclimatic and phytosanitary events in avocados. Some challenges and trends in the parameterization of the technology in field conditions for data collection are also highlighted. [ABSTRACT FROM AUTHOR]

Based on the monthly panel data of China's imports of agricultural machinery products from 2016–2022, this paper uses a multi-period double-difference model to assess the impact of China's imposition of counter-tariffs on China's imports of agricultural machinery in the context of U.S.–China trade friction. It is found that China's implementation of counter-tariffs significantly reduces China's imports of agricultural machinery products from the U.S. and significantly increases imports from 16 other countries, but the trade diversion effect is lower than the trade suppression effect. Mechanism analysis finds that China–U.S. trade friction affects the technological innovation capacity of agricultural machinery enterprises and the degree of uncertainty in the Chinese economy, which in turn affects China's agricultural machinery imports. Heterogeneity analysis finds that China–U.S. trade friction has a more significant inhibitory effect on seeding and planting and fertilizing machinery, drainage, irrigation, and water lifting machinery, and other machinery imported from the U.S., and a more significant diversionary effect on agricultural primary processing machinery and harvesting machinery imported from 16 other countries. The imposition of countervailing tariffs mainly affected imports of complete machinery products rather than machinery spare parts. [ABSTRACT FROM AUTHOR]

The current geopolitical and socioeconomic landscape creates a difficult and uncertain operating environment for farming and agri-food businesses. Technological innovation has not been suggested to be a "silver bullet" but is one of the ways organizations can seek to reduce environmental impact, deliver net zero, address the rural skills and labor deficit and produce more output from fewer resources and as a result, make space for nature. But what barriers limit this promissory narrative from delivering in practice? The purpose of the paper is to firstly explore the reported social, technical and systemic barriers to agri-technology adoption in an increasingly uncertain world and then secondly identify potential research gaps that highlight areas for future research and inform key research questions. Socio-technical and infrastructural barriers have been identified within the context of the complex hollowing out and infilling of rural communities across the world. These barriers include seventeen factors that emerge, firstly those external to the farm (economic conditions, external conditions including bureaucracy, market conditions, weather uncertainty and the narratives about farmers), those internal to the farm business (farming conditions, employee relations, general finance, technology and time pressures) and then personal factors (living conditions, personal finances, physical health, role conflict, social isolation and social pressure). Adaptive resilience strategies at personal, organizational and community levels are essential to address these barriers and to navigate agri-technology adoption in an uncertain and dynamic world. [ABSTRACT FROM AUTHOR]

The traditional aviary decontamination process involves farmers applying pesticides to the aviary's ground. These agricultural defenses are easily dispersed in the air, making the farmers susceptible to chronic diseases related to recurrent exposure. Industry 5.0 raises new pillars of research and innovation in transitioning to more sustainable, human-centric, and resilient companies. Based on these concepts, this paper presents a new aviary decontamination process that uses IoT and a robotic platform coupled with ozonizer (O3) and ultraviolet light (UVL). These clean technologies can successfully decontaminate poultry farms against pathogenic microorganisms, insects, and mites. Also, they can degrade toxic compounds used to control living organisms. This new decontamination process uses physicochemical information from the poultry litter through sensors installed in the environment, which allows accurate and safe disinfection. Different experimental tests were conducted to construct the system. First, tests related to measuring soil moisture, temperature, and pH were carried out, establishing the range of use and the confidence interval of the measurements. The robot's navigation uses a back-and-forth motion that parallels the aviary's longest side because it reduces the number of turns, reducing energy consumption. This task becomes more accessible because of the aviaries' standardized geometry. Furthermore, the prototype was tested in a real aviary to confirm the innovation, safety, and effectiveness of the proposal. Tests have shown that the UV + ozone combination is sufficient to disinfect this environment. [ABSTRACT FROM AUTHOR]

Agricultural sensors are essential technologies for smart agriculture, which can transform non-electrical physical quantities such as environmental factors. The ecological elements inside and outside of plants and animals are converted into electrical signals for control system recognition, providing a basis for decision-making in smart agriculture. With the rapid development of smart agriculture in China, agricultural sensors have ushered in opportunities and challenges. Based on a literature review and data statistics, this paper analyzes the market prospects and market scale of agricultural sensors in China from four perspectives: field farming, facility farming, livestock and poultry farming and aquaculture. The study further predicts the demand for agricultural sensors in 2025 and 2035. The results reveal that China's sensor market has a good development prospect. However, the paper garnered the key challenges of China's agricultural sensor industry, including a weak technical foundation, poor enterprise research capacity, high importation of sensors and a lack of financial support. Given this, the agricultural sensor market should be comprehensively distributed in terms of policy, funding, expertise and innovative technology. In addition, this paper highlighted integrating the future development direction of China's agricultural sensor technology with new technologies and China's agricultural development needs. [ABSTRACT FROM AUTHOR]

Global agricultural production is facing unprecedented challenges as the environment becomes increasingly polluted. Governments, scientists, companies and farmers are beginning to focus on appropriate environmental remediation and sustainable agricultural technologies and practices. Innovative environmental adaptation/remediation technologies have been developed and validated, including physical/chemical remediation, green sorbents and bioremediation. The development of environmental remediation technologies has provided additional tools and methods for global agri-environment and food security. The aim of this Special Issue is to bring together 21 cutting-edge research papers covering the latest developments in soil conditions, inorganic pollution, organic pollution, remediation technologies and monitoring methods. The four themes of the Special Issue are "Improvement of agricultural soil properties", "Remediation of potentially toxic element pollution", "Remediation of organic pollution" and "Ecosystem and crop assessment". Based on the results of this Special Issue, we find that combining the latest environmental pollution problems with advanced remediation technologies, continuously promoting technological innovation and policy support, and developing integrated new technologies for environmental protection will be future areas of research for sustainable agro-environmental development. [ABSTRACT FROM AUTHOR]

Unmanned farms employ a variety of sensors, automated systems, and data analysis techniques to enable fully automated and intelligent management. This not only heightens agricultural production efficiency but also reduces the costs associated with human resources. As integral components of unmanned farms' automation systems, agricultural UAVs have been widely adopted across various operational stages due to their precision, high efficiency, environmental sustainability, and simplicity of operation. However, present-day technological advancement levels and relevant policy regulations pose significant restrictions on UAVs in terms of payload and endurance, leading to diminished task efficiency when a single UAV is deployed over large areas. Accordingly, this paper aggregates and analyzes research pertaining to UAV swarms from databases such as Google Scholar, ScienceDirect, Scopus, IEEE Xplorer, and Wiley over the past decade. An initial overview presents the current control methods for UAV swarms, incorporating a summary and analysis of the features, merits, and drawbacks of diverse control techniques. Subsequently, drawing from the four main stages of agricultural production (cultivation, planting, management, and harvesting), we evaluate the application of UAV swarms in each stage and provide an overview of the most advanced UAV swarm technologies utilized therein. Finally, we scrutinize and analyze the challenges and concerns associated with UAV swarm applications on unmanned farms and provide forward-looking insights into the future developmental trajectory of UAV swarm technology in unmanned farming, with the objective of bolstering swarm performance, scalability, and adoption rates in such settings. [ABSTRACT FROM AUTHOR]

The growth of the Indonesian population has led to an increase in the demand for rice, which the country has yet to satisfy. Indonesia needs a comprehensive strategy that integrates meaningful efforts to increase its agricultural production. This study aims to review the examined trends in rice yield in Indonesia for 70 years after Indonesia's independence (1945–2016) followed by the identification of the application technology and factors that contribute to increasing rice yields to forecast sustainable food security scenarios up to 2030. This article reviews the results of research on rice production technology in Indonesia from 1945 to 2016, and the outlook for 2030. This paper examines the main points of the Indonesian transformation of rice technology: improvement of rice varieties, integrated crop management, innovations in agricultural machinery, and the Integrated Cropping Calendar Information System (ICCIS). We found that transformation has helped Indonesia increased its rice yields from 3 t ha−1 prior to 1961 to 4.6 t ha−1 in 1985, stagnated in 1990, and increased again in 2017 to 5.46 t ha−1. The increase in yield was sustained by an increase in the harvested area owing to cropping index (CI) innovation. Food security and sustainable development remain the primary goals of Indonesia's agricultural sector. The application of appropriate technologies and institutional innovations can assist Indonesia in achieving its food security. Therefore, the transformation of technological innovations will continue to be an essential driver of future agricultural growth, including greater use of crop varieties, machinery, and land/institutional reforms. [ABSTRACT FROM AUTHOR]

In Portugal, the olive orchard is the most representative agricultural crop and one of the most impactful on the national economy. Therefore, a production structure accompanying the technological advances in this field would be expected; however, such a structure has not yet been realized, especially within traditional systems. Thus, taking northeastern Portugal as a case study, where a great expression of traditional orchards is visible, the following aspects are addressed within this paper: the region's biophysical framework, the olive orchard's environmental and socio-economic importance and its current management practices and associated pressures. As a result of that assessment, which demonstrates a low level of sustainability for traditional olive orchards, mainly in terms of economic viability, the most effective and simple solution is to act appropriately on factors that interfere with the crop yield, namely, irrigation and fertilization issues. With that purpose, a multiscale precision oliviculture system is also presented that is being developed in order to support decision making in traditional olive orchard management, aiming to obtain economically efficient productions based on eco-friendly cultural practices. Throughout the entire process, it is essential to ensure stakeholder engagement, in particular, olive growers, so that they recognize the effectiveness of potential measures that may avoid the reconversion/abandonment of the traditional olive production system. [ABSTRACT FROM AUTHOR]

Agricultural technological change plays a crucial role in food security and agricultural development. In the case of considering economic risks and technical risk tolerance, farmers will use different technologies to match production factors to achieve the optimal production state. Therefore, under different farmland management modes, farms show different characteristics of technological progress. This paper attempts to compare and analyze agricultural technology development under different farmland management modes: the unified management mode of collective organizations (UMCO) and the decentralized management mode of contracted families (DMCF). The Stochastic Frontier Analysis (SFA) of the translog average production function was applied to the 24 farms of the Hulunbuir Agricultural Reclamation Group, of which 11 farms in the western part of the Greater Khingan Mountains (Western Farms) were managed by the DMCF, and the other 13 farms in the eastern part of the Greater Khingan Mountains (Eastern Farms) were managed by the UMCO. The results are as follows: (1) without considering the resource allocation efficiency, from 2000 to 2019, the generalized technological progress rate (TFPG) of the 13 Eastern Farms (7.65%) was higher than that of the Western Farms (2.25%). (2) The returns to scale (SRC) of the Western Farms was higher than that of the Eastern Farms. (3) The technological efficiency change rate (TEC) and the technical progress (TP) of the Eastern Farms is higher than that of the Western Farms. It is recommended that farms strengthen the construction of their infrastructure and service systems, resist natural disasters, reduce the disaster's impact on technological progress, give full play to the overall planning advantages of the collective organizations, improve the product allocation efficiency factors, and create connotative profit points. [ABSTRACT FROM AUTHOR]

Climate change poses a serious threat to global agricultural activity and food production. Plant genome editing technologies have been widely used to develop crop varieties with superior qualities or can tolerate adverse environmental conditions. Unlike conventional breeding techniques (e.g., selective breeding and mutation breeding), modern genome editing tools offer more targeted and specific alterations of the plant genome and could significantly speed up the progress of developing crops with desired traits, such as higher yield and/or stronger resilience to the changing environment. In this review, we discuss the current development and future applications of genome editing technologies in mitigating the impacts of biotic and abiotic stresses on agriculture. We focus specifically on the CRISPR/Cas system, which has been the center of attention in the last few years as a revolutionary genome-editing tool in various species. We also conducted a bibliographic analysis on CRISPR-related papers published from 2012 to 2021 (10 years) to identify trends and potential in the CRISPR/Cas-related plant research. In addition, this review article outlines the current shortcomings and challenges of employing genome editing technologies in agriculture with notes on future prospective. We believe combining conventional and more innovative technologies in agriculture would be the key to optimizing crop improvement beyond the limitations of traditional agricultural practices. [ABSTRACT FROM AUTHOR]

Smart farming is a development that has emphasized information and communication technology used in machinery, equipment, and sensors in network-based hi-tech farm supervision cycles. Innovative technologies, the Internet of Things (IoT), and cloud computing are anticipated to inspire growth and initiate the use of robots and artificial intelligence in farming. Such ground-breaking deviations are unsettling current agriculture approaches, while also presenting a range of challenges. This paper investigates the tools and equipment used in applications of wireless sensors in IoT agriculture, and the anticipated challenges faced when merging technology with conventional farming activities. Furthermore, this technical knowledge is helpful to growers during crop periods from sowing to harvest; and applications in both packing and transport are also investigated. [ABSTRACT FROM AUTHOR]

The current international commercial structure places Brazilian Agribusiness in constant conflict to protect its interests before other nations in the global market. Technological innovations are used in all stages from the simplest production tasks, up to the design of negotiation tactics at high-level affairs. This paper has the objective of finding Brazilian contenders in the beef market with cyber capabilities and commercial interest to act in favor of their interests. To construct such a list, a review of the literature on Threat and Cyber Threat Intelligence is presented, followed by a background presentation of how embedded technology is in nowadays agriculture and supply chains in general, and the real necessity for those sectors to be seen as critical infrastructure by governments in general. Also as background information recent cyber attack cases and attacker countries are shown. A Step-by-Step multidisciplinary method is presented that involves the extent of international trade, the interest on specific markets, and the intersection of country cyber capacity index. After applying the method and criteria generated a list of five contender countries. The method may be replicated and/or applied, considering adequate data source assessment and following specifics of each sector. [ABSTRACT FROM AUTHOR]

In farming technologies, it is difficult to properly provide the accurate crop nutrients for respective crops. For this reason, farmers are experiencing enormous problems. Although various types of machine learning (deep learning and convolutional neural networks) have been used to identify crop diseases, as has crop classification-based image processing, they have failed to forecast accurate crop nutrients for various crops, as crop nutrients are numerical instead of visual. Neural networks represent an opportunity for the precision agriculture sector to more accurately forecast crop nutrition. Recent technological advancements in neural networks have begun to provide greater precision, with an array of opportunities in pattern recognition. Neural networks represent an opportunity to effectively solve numerical data problems. The aim of the current study is to estimate the right crop nutrients for the right crops based on the data collected using an artificial neural network. The crop data were collected from the MNIST dataset. To forecast the precise nutrients for the crops, ANN models were developed. The entire system was simulated in a MATLAB environment. The obtained results for forecasting accurate nutrients were 99.997%, 99.996%, and 99.997% for validation, training, and testing, respectively. Therefore, the proposed algorithm is suitable for forecasting accurate crop nutrients for the crops. [ABSTRACT FROM AUTHOR]

Smallholder farmers in East Africa need information and knowledge on appropriate climate-smart agriculture (CSA) practices, technologies, and institutional innovations in order to effectively adapt to changing climatic conditions and cope with climate variability. This paper assesses farmer adoption of climate-smart agricultural practices and innovation after being exposed to Farms of the Future Approach (FotF). First; we explore and assess the various CSA technologies and practices; including institutional innovations farmers are adopting. Second; we identify and document farmer learning and dissemination pathways that can enhance adoption of CSA technologies and practices. Third; we identify existing institutions that enhance adoption of CSA practices. We use household survey data, complemented by qualitative information from focus group discussions and key informant interviews. The results show farmers are adopting a variety of CSA technologies, practices, and institutional innovations to after participating in the FotF approach with use of improved crop varieties, agroforestry, and scientific weather forecast information cited as the main practices. To minimize their risks and reduce vulnerabilities, farmers are diversifying and integrating five to 10 CSA practices in one season. Matengo pits, SACCOs, and efficient energy stoves were adopted by very few farmers due to their high initial investment costs and unsuitability to the area. Ninety-eight percent of farmers reported that they receive agricultural information orally from a variety of sources including government extension workers, seed companies, researchers, traditional experts, neighbors, radio agricultural shows, religious groups, farmer groups, and family members. Lastly, farmers reported that the FotF approach is a useful tool that enabled them to interact with other farmers and learn new CSA practices and innovations. Suggested improvements to make on the FotF included include longer trip duration, increased number of farmer participants, and gender balance and age considerations to include youth. [ABSTRACT FROM AUTHOR]

This article explores the impact of automation on environmental sensing, focusing on advanced technologies that revolutionize data collection analysis and monitoring. The International Union of Pure and Applied Chemistry (IUPAC) defines automation as integrating hardware and software components into modern analytical systems. Advancements in electronics, computer science, and robotics drive the evolution of automated sensing systems, overcoming traditional limitations in manual data collection. Environmental sensor networks (ESNs) address challenges in weather constraints and cost considerations, providing high-quality time-series data, although issues in interoperability, calibration, communication, and longevity persist. Unmanned Aerial Systems (UASs), particularly unmanned aerial vehicles (UAVs), play an important role in environmental monitoring due to their versatility and cost-effectiveness. Despite challenges in regulatory compliance and technical limitations, UAVs offer detailed spatial and temporal information. Pollution monitoring faces challenges related to high costs and maintenance requirements, prompting the exploration of cost-efficient alternatives. Smart agriculture encounters hurdle in data integration, interoperability, device durability in adverse weather conditions, and cybersecurity threats, necessitating privacy-preserving techniques and federated learning approaches. Financial barriers, including hardware costs and ongoing maintenance, impede the widespread adoption of smart technology in agriculture. Integrating robotics, notably underwater vehicles, proves indispensable in various environmental monitoring applications, providing accurate data in challenging conditions. This review details the significant role of transfer learning and edge computing, which are integral components of robotics and wireless monitoring frameworks. These advancements aid in overcoming challenges in environmental sensing, underscoring the ongoing necessity for research and innovation to enhance monitoring solutions. Some state-of-the-art frameworks and datasets are analyzed to provide a comprehensive review on the basic steps involved in the automation of environmental sensing applications. [ABSTRACT FROM AUTHOR]

Addressing the urgent sustainability challenges in the wine industry, this study explores the efficacy of sustainability-oriented innovations (SOIs) and smart farming technologies (SFTs) across wine value chains in Cyprus and Italy. Utilising a mixed-methods approach that includes quantitative analysis through Key Performance Indicators (KPIs) and qualitative assessments to understand stakeholders' perspectives, this research delves into the environmental, economic, and social impacts of these technologies. In Cyprus, the integration of digital labelling and smart farming solutions led to a substantial reduction in pesticide usage by up to 75% and enhanced the perceived quality of wine by an average of 8%. A pilot study in Italy witnessed a 33.4% decrease in greenhouse gas emissions, with the additional benefit of a 5.3% improvement in intrinsic product quality. The pilot introduced a carbon credit system, potentially generating an average annual revenue of EUR 4140 per farm. These findings highlight the transformative potential of SOIs and SFTs in promoting sustainable practices within the wine industry, demonstrating significant advancements in reducing environmental impact, improving product quality, and enhancing economic viability. This study underscores the critical role of innovative technologies in achieving sustainability goals and provides a compelling case for their wider adoption within the agricultural sector. [ABSTRACT FROM AUTHOR]

The digitalization of the agricultural industry is manifested through the active use of innovative technologies in all its areas. Agribusiness owners have to constantly improve their security to meet new challenges. In this context, the existing cyber risks of the agrarian industry were assessed and their classification by possible consequences, such as data theft or alteration, cyber terrorism, cyber warfare, software hacking or modification, the blocking of markets and transactions on them, was proposed. Cyber insurance is an effective tool for minimizing the likelihood of cyber incidents and for comprehensive post-incident support, with the involvement of cybersecurity specialists. An algorithm for cooperation between an agricultural company and an insurance company when concluding a cyber risk insurance contract is proposed, which takes into account the needs and wishes of insurers at each stage of the interaction. To assess the need to use cyber insurance in agriculture 4.0, a methodology has been developed to evaluate the regional characteristics of cybersecurity and the digitalization of agribusiness. The results of the study show a heterogeneous need for this tool in different regions of the world. [ABSTRACT FROM AUTHOR]

Over the past few decades, the food industry has undergone revolutionary changes due to the impacts of globalization, technological advancements, and ever-evolving consumer demands. Artificial intelligence (AI) and big data have become pivotal in strengthening food safety, production, and marketing. With the continuous evolution of AI technology and big data analytics, the food industry is poised to embrace further changes and developmental opportunities. An increasing number of food enterprises will leverage AI and big data to enhance product quality, meet consumer needs, and propel the industry toward a more intelligent and sustainable future. This review delves into the applications of AI and big data in the food sector, examining their impacts on production, quality, safety, risk management, and consumer insights. Furthermore, the advent of Industry 4.0 applied to the food industry has brought to the fore technologies such as smart agriculture, robotic farming, drones, 3D printing, and digital twins; the food industry also faces challenges in smart production and sustainable development going forward. This review articulates the current state of AI and big data applications in the food industry, analyses the challenges encountered, and discusses viable solutions. Lastly, it outlines the future development trends in the food industry. [ABSTRACT FROM AUTHOR]

Global food security is a critical issue today, strained by a wide range of factors including global warming, carbon emissions, sociopolitical and economic challenges, traditional workforce decline and population growth. Technical innovations that address food security, like agricultural robotics, are gaining traction in industry settings, moving from controlled labs and experimental test facilities to real-world environments. Such technologies require sufficient network infrastructure to support in-field operations; thus, there is increased urgency to establish reliable, high-speed wireless communication networking solutions that enable deployment of autonomous agri-robots. The work presented here includes two contributions at the intersection of network infrastructure and in-field agricultural robotics. First, the physical performance of a private 5G-SA system in an agri-robotics application is evaluated and in-field experimental results are presented. These results are compared (using the same experimental setup) against public 4G and private WiFi6 (a newly emerging wireless communication standard). Second, a simulated experiment was performed to assess the "real-time" operational delay in critical tasks that may require quick turnaround between in-field robot and off-board processing. The results demonstrate that public 4G cannot be used in the agricultural domain for applications that require high throughput and reliable communication; that private 5G-SA greatly outperforms public 4G in all performance metrics (as expected); and that private WiFi6, though limited in range, is a fast and very reliable alternative in specific settings. While a single wireless solution does not currently exist for the agricultural domain, multiple technologies can be combined in a hybrid solution that meets the communications requirements. [ABSTRACT FROM AUTHOR]

Recent technological advancements have revolutionized agriculture in Asia, leading to significant changes in crop yield stability. This study examines the changing face of crop yield stability in Asia resulting from the increasing adoption of innovative technologies in agriculture. Through a review of current research and case studies, the impact of technology-driven changes on yield levels, variability, and predictability is explored. The study applies a yield stability index (YSI) to evaluate the yield stability of six crops in seven Asian countries during two periods (1961–1994 and 1995–2020), comparing the countries, crops, and stability changes between the two segments. The novelty of the research is the application of YSI, which, contrary to usual stability metrics, can distinguish between rare large extreme yields and frequent minor fluctuations, and based on this feature, evaluates the suitability of the prevailing technologies to local environmental conditions. The YSI is used to evaluate the stability of technologies, indicating whether the technologies can respond well to the annual variations of environmental conditions. Positive YSI values indicate stable technologies that can respond well to the annual variations of environmental conditions, and the concept of a well-technologized crop is used for crops in countries with stable positive YSI values, indicating the suitability of the actual crop to the actual geographical environment. These results can guide production technology developments and the introduction or abandonment of certain crops in certain geographical zones, especially regarding the implications of climate change and global warming. This study highlights the transformative power of technology in improving crop yield stability and food security in Asia, while discussing the potential challenges associated with these changes and the need for continued research to address them. [ABSTRACT FROM AUTHOR]

This research delves into the intricacies of decision-making processes underpinning the willingness to upgrade technology within the burgeoning domain of intelligent pig farming in China, employing the UTAUT model to scrutinize how various determinants sway upgrade willingness and the ensuing behavioral modification. By applying the UTAUT model to intelligent pig farming, the inquiry evaluates the impact of performance expectations, effort expectations, social influence, and contributory factors on upgrade willingness and behavior, with data amassed from assorted novel agricultural management entities in China. The findings unveil that performance and effort expectations, social influence, and contributory factors have a favorable influence on upgrade willingness, while contributory factors, alongside the augmentation of upgrade willingness, positively affect upgraded behavior. This inquiry underscores the multifaceted interaction of factors guiding technological upgrade verdicts in intelligent pig farming, furnishing invaluable insights for comprehending technology adoption in agriculture. It lays a groundwork for devising strategies to spur technological advancements, harboring potential for wider applications across varied agricultural vistas. [ABSTRACT FROM AUTHOR]

In the context of growing environmental challenges and the push for sustainable agriculture, this study delves into the eco-efficiency of three-season indica rice across 16 key provinces in China from 2004 to 2021. Utilizing the super-efficiency Slacks-Based Measure (SBM) model coupled with the Malmquist index, our approach uniquely incorporates undesirable outputs, focusing on carbon emissions from chemical and plastic inputs. Findings indicate that while the overall efficiency hinged around a modest mean, periods like 2005–2006 and 2017–2018 spotlighted the pivotal role of technological advancements and judicious resource use. The Malmquist Index revealed an intricate interplay between technological change and efficiency, notably when accounting for environmental impact. Diverse provincial efficiencies spotlighted the need for bespoke strategies harmonizing efficiency objectives with ecological sustainability. This study emphasizes the indispensable role of technological innovation in advancing eco-efficiency and fostering sustainable agricultural practices, urging for policy changes that prioritize both technology adoption and ecological awareness. [ABSTRACT FROM AUTHOR]

The application of smart agriculture is increasingly becoming a critical force in transforming the traditional methods of agricultural production in China. This change, based on technological innovation, is essential to promoting a sustainable production system in family farms. This study is based on the resource orchestration theory to investigate how smart agriculture affects the diversity of green production technologies (GPTs) on family farms. Based on a sample of 563 family farms surveyed in 2022, this study utilizes propensity score matching (PSM) methods and instrumental variables to analyze the effect of smart-agriculture adoption on the diversity of GPTs on farms. The findings reveal that smart agriculture has significantly increased the diversity of GPTs on farms by 8.5%. Network consulting services, value-added products, and environmental monitoring services are potential impact mechanisms underlying the positive effects of smart agriculture on the diversity of GPTs on farms. Furthermore, the increased diversity of GPTs is more significant on purely plantation farms, farms without contract farming, and farms with high levels of mechanization. [ABSTRACT FROM AUTHOR]

Based on the perspective of the value chain of agricultural science and technology innovation, in this paper, we divided the process of agricultural science and technology innovation into two stages: the Research and Development (R&D) of agricultural technology and the application of agricultural technology. We took the efficiency of agricultural science and technology innovation of the two stages as a comprehensive index measure for the development of agricultural science and technology innovation in China. On this basis, we used social network analysis to establish a two-stage spatial correlation network for the innovation development of agricultural science and technology in China. The spatial-temporal evolution trends, structural characteristics, and influencing factors of the network were analyzed from the three aspects of the overall, local, and individual network structure. The results show that: a. The development of agricultural science and technology innovation in China demonstrated a clear spatial correlation and spillover effect, and the spatial correlation network was in a connected state. b. The network had the distribution characteristics of 'core-edge' and strong stability, and the hierarchical structure of the members of each province in the network was gradually broken. c. The differences at the market level in agricultural science and technology, the differences in government support for agriculture, the geographically adjacent relationships, and the level of agricultural economic development were important factors affecting the spatial correlation of agricultural science and technology innovation. This study provides a policy reference to use a cross-regional coordinated development mechanism to solve the uneven and asymmetry problem of the distribution of elements in various regions in China. [ABSTRACT FROM AUTHOR]

This study examines the impact of green process innovation (GPI), green entrepreneurial orientation (GPO), and proactive sustainable strategy (PSS) on environmental performance (EP). Data were collected from 294 Indian agriculture technology firms. Structural equation modeling (SEM) was used to analyze the data using Lisrel 8.80. This study aimed to analyze how green entrepreneurial orientation, sustainability strategies, and green process innovation improve the environmental performance of agricultural technology firms. The results show that green process innovation, sustainability strategy, and entrepreneurial orientation play a significant role in enhancing agricultural technology firms' environmental performance. Agricultural technology firms achieve high environmental performance primarily through strategy or sustainability. In every green process, innovation is crucial and essential. This research offers several practical implications that can be utilized by managers of agricultural technology firms to develop systems with cleaner production techniques in agribusiness. The novelty of the study lies in analyzing the direct relationships among green entrepreneurial orientation, strategy, and innovation in promoting the environmental performance of agricultural technology firms by drawing data from an agriculturally oriented developing country such as India. [ABSTRACT FROM AUTHOR]

Simple Summary: As the importance of farming continues to grow, innovative technology and sensors play an increasingly important role. Automation and robots in agriculture have the potential to play a significant role in helping society fulfill its future demands for food supply. Wearable sensors connected to or within cows can monitor eating, rumination, pH, body temperature, laying behavior, animal activity, animal position or placement, and more. Research concentrates on biosensing technologies that have the potential to improve livestock early disease detection, management, and operations. The goals of this study were to investigate the currently available knowledge regarding agricultural innovations and their application tactics, and we intended to give a critical perspective and advance the understanding of what is known and unknown about innovations and dairy cattle. Precision livestock farming has a crucial function as farming grows in significance. It will help farmers make better decisions, alter their roles and perspectives as farmers and managers, and allow for the tracking and monitoring of product quality and animal welfare as mandated by the government and industry. Farmers can improve productivity, sustainability, and animal care by gaining a deeper understanding of their farm systems as a result of the increased use of data generated by smart farming equipment. Automation and robots in agriculture have the potential to play a significant role in helping society fulfill its future demands for food supply. These technologies have already enabled significant cost reductions in production, as well as reductions in the amount of intensive manual labor, improvements in product quality, and enhancements in environmental management. Wearable sensors can monitor eating, rumination, rumen pH, rumen temperature, body temperature, laying behavior, animal activity, and animal position or placement. Detachable or imprinted biosensors that are adaptable and enable remote data transfer might be highly important in this quickly growing industry. There are already multiple gadgets to evaluate illnesses such as ketosis or mastitis in cattle. The objective evaluation of sensor methods and systems employed on the farm is one of the difficulties presented by the implementation of modern technologies on dairy farms. The availability of sensors and high-precision technology for real-time monitoring of cattle raises the question of how to objectively evaluate the contribution of these technologies to the long-term viability of farms (productivity, health monitoring, welfare evaluation, and environmental effects). This review focuses on biosensing technologies that have the potential to change early illness diagnosis, management, and operations for livestock. [ABSTRACT FROM AUTHOR]

Throughout the course of human history, owing to innovations that shape the future of mankind, many technologies have been innovated and used towards making people's lives easier. Such technologies have made us who we are today and are involved with every domain that is vital for human survival such as agriculture, healthcare, and transportation. The Internet of Things (IoT) is one such technology that revolutionizes almost every aspect of our lives, found early in the 21st century with the advancement of Internet and Information Communication (ICT) Technologies. As of now, the IoT is served in almost every domain, as we mentioned above, allowing the connectivity of digital objects around us to the Internet, thus allowing the remote monitoring, control, and execution of actions based on underlying conditions, making such objects smarter. Over time, the IoT has progressively evolved and paved the way towards the Internet of Nano-Things (IoNT) which is the use of nano-size miniature IoT devices. The IoNT is a relatively new technology that has lately begun to establish a name for itself, and many are not aware of it, even in academia or research. The use of the IoT always comes at a cost, owing to the connectivity to the Internet and the inherently vulnerable nature of IoT, wherein it paves the way for hackers to compromise security and privacy. This is also applicable to the IoNT, which is the advanced and miniature version of IoT, and brings disastrous consequences if such security and privacy violations were to occur as no one can notice such issues pertaining to the IoNT, due to their miniaturized nature and novelty in the field. The lack of research in the IoNT domain has motivated us to synthesize this research, highlighting architectural elements in the IoNT ecosystem and security and privacy challenges pertaining to the IoNT. In this regard, in the study, we provide a comprehensive overview of the IoNT ecosystem and security and privacy pertaining to the IoNT as a reference to future research. [ABSTRACT FROM AUTHOR]

Smart farming is essential to increasing crop production, and there is a need to consider the technological advancements of this era; modern technology has helped us to gain more accuracy in fertilizing, watering, and adding pesticides to the crops, as well as monitoring the conditions of the environment. Nowadays, more and more sophisticated sensors are being developed, but on a larger scale, agricultural networks and the efficient management of them is very crucial in order to obtain proper benefits from technology. Our idea is to achieve sustainability in large-scale farms by improving communication between wireless sensor nodes and base stations. We want to increase communication efficiency by introducing machine learning algorithms. Reinforcement learning is the area of machine learning which is concerned with how involved agents are supposed to take action in specified environments to maximize reward and achieve a common goal. In our network, a large number of sensors are being deployed on large-scale fields; reinforcement learning is used to find the optimal set of paths towards the base station. After a number of successful paths have been developed, they are then used to transmit the sensed data from the fields. The simulation results have shown that in larger scales, our proposed model had less transmission delay than the shortest path transmission model and broadcasting techniques that were tested against the data transmission paths developed by reinforcement learning. [ABSTRACT FROM AUTHOR]

Smallholder livestock farmers (SLF) are important in research and policy development agenda because of the everlasting issue of food insecurity and the livelihoods in sub-Sahara Africa. Lack of access to technologies and information, poor infrastructure and lack of access to markets and environmental factors play a key role in deterring sustainable smallholder livestock farming. In recent years, studies have provided evidence that livestock species can play a role towards solving household food insecurity and enhancing Africa's resilient livelihoods, particularly in rural settings. However, no studies have been conducted on the effectiveness of emerging technologies (available information technologies) as risk mitigation tools for smallholder livestock farmers. The study used survey data from 278 interviewer-administered questionnaires and 13 in-depth interviews village herds from Dumba, Mapayi, Old Nuli and Shabwe to explore whether rural SLF would use the emerging technologies to enhance their operations, and mitigate supply chain risk, exposures to stock theft and loss. Empirical results show the overwhelming need for the use of emerging technologies by the SLF, and that emerging technologies have significant and positive effects on the risk management activities. SLF indicated that, using digital technologies, they could enhance their risk mitigation and value chains. The results of the study have several policy implications. For instance, the agricultural comparative advantage should be improved through various emerging agricultural technologies. Moreover, the immediate rural development service networks for SLF could be strengthened through the Department of Rural Development and Land Reform to reduce livestock risk exposures, disasters and market reactions. Although rural livestock farming in Beitbridge has survived over the years at a subsistence level, the paper provides some interesting and pertinent findings, and projects some possible future research pathways. [ABSTRACT FROM AUTHOR]

China's National Agricultural Science and Technology Parks (NASTPs) play a key role in improving the nation's agro-industrial structure and regional economic development; notably, NASTPs can demonstrate innovations in modern agricultural science and technology and, relatedly, incubate emerging modern agri-industries. However, after more than 20 years of development, scholars have not yet to confirm whether NASTPs contribute to local economies. This study sought to explore the impact of NASTPs on county economic development, to identify the mechanisms behind this impact, and to verify these effects using a multi-period double difference method based on panel data from 1743 counties in China collected between 2000 and 2019. The study found that the NASTPs significantly improved county economic development. The policy effects were mainly evident in western regions and counties with higher levels of financial resources. No spatial spillover effects were observed. The NASTPs drove county economic growth through three main channels: agglomeration, institutional environment, and innovation effects. These findings provide insights useful for designing policies related to the high-quality construction of agricultural sci-tech parks, the high-quality growth of county economies, and a reduction in regional economic development gaps. [ABSTRACT FROM AUTHOR]

There is a clear research gap in understanding how future pathways and disruptions to the New Zealand (NZ) agricultural system will have an impact on the environment and productivity. Agriculture is in a period of significant change due to market disruptions, climate change, increasingly stringent environmental regulations, and emerging technologies. In NZ, agriculture is a key sector of the economy, therefore government and industry need to develop policies and strategies to respond to the risks and opportunities associated with these disruptors. To address this gap, there is a need to develop an assessment tool to explore pathways and interventions for increasing agricultural profitability, resilience, and sustainability over the next 5–30 years. A decision support tool was developed through Stella Architect, bringing together production, market values, land use, water use, energy, fertiliser consumption, and emissions from agricultural sectors (dairy, beef, sheep, cereals, horticulture, and forests). The parameters are customisable by the user for scenario building. Two future trend scenarios (Business as usual, Optimisation and technology) and two breakaway scenarios (Carbon farming, Reduction in dairy demand) were simulated and all met carbon emissions goals, but profitability differed. Future environmental regulations can be met by adjusting levers associated with technology, carbon offsets, and land use. The model supports the development and assessment of pathways to achieve NZ's national agriculture goals and has the potential to be scaled globally. [ABSTRACT FROM AUTHOR]

The creation and deployment of digital technologies throughout the agro-food system contribute to achieving Sustainable Development Goal nine. However, various digitalization studies offer limited insight into the policy issues and solutions around emerging technologies and big data systems in agriculture. There is a need for an additional understanding of how agricultural policymaking should respond to the usage of digital technologies in the agri-food sector. Furthermore, evidence is limited on how existing agricultural government programs such as land reform can be linked with digitalization policy. This systematic review of literature sought to determine the transformation that is needed in the political and economic environment for the digital revolution to take place within South African land reform agriculture. A thematic analysis of data sampled from ProQuest Central, Scopus, Dimensions, and Google Scholar reveals five areas of intervention from agricultural policymaking. The digital revolution in agriculture can be brought about by transforming digital infrastructure, data interoperability and governance, digital markets, the compatibility of government incentives with the private sector, and the digital cultural landscape. This essay contributes to agricultural policy and decision-making dialogues that pay attention to digital technologies and land reform programs in South Africa. [ABSTRACT FROM AUTHOR]

Food innovations can create novel nutritious food, improve agricultural sustainability, and increase the agri-food industry's market profits. Our study proposes a consensus definition of food innovations and forecasts food innovations that will be available to consumers in the next five years by using a Delphi study. Thirteen experts aged 35 to 85 from the US and the UK researching or working in agriculture and nutrition, public health, the agri-food industry, or food policy participated in three rounds of this Delphi study. The experts were chosen using the snowball sampling method. This study followed the implementation and data analysis guidelines popularized by the Rand Corporation. The consensus definition for food innovations (with 76.9% agreement) was that 'food innovations aid in the development, production, or transportation of new food products, processes, or technology to promote human health, food security, or environmental sustainability'. The specific food innovations, which had over 69% agreement, are ranked as (1) plant-based meat alternatives, (2) personalized nutrition, (3) natural foods, (4) new genetically modified organisms, (5) regenerative agriculture, (6) urban agriculture, (7) packing innovations, (8) alternative flours, (9) improving shelf life, (10) supply chain technologies, (11) improved soil health, and (12) technology for traceability. The food innovation definition and identified specific food innovations could further connect the agricultural value chain to develop novel nutritious foods and improve agricultural sustainability. Agri-food industry specialists, practitioners, researchers, and policymakers can advance food innovation development and research pinpointing the specific food innovations along the agricultural value chain. [ABSTRACT FROM AUTHOR]

After the Second World War, technological advancements helped to develop agriculture and meet urgent food needs. The green revolution was based on the cultivation of new high-yielding varieties, the adoption of plant protection measures, and synthetic fertilizer use. Today, agriculture is called upon to recover its productivity in environmentally friendly terms and to face challenges such as climate change and international political–military events that threaten global sufficiency in agricultural products. The objective of the study is to evaluate the function that crop-protection technologies play in ensuring the continuity of agricultural output. The research was conducted by the use of a questionnaire in a sample of 250 farmers in Northern Greece. Specifically, through descriptive and regression analysis, the roles of biological crop protection, chemical crop-protection techniques, and mechanical crop-protection techniques were explored, and it was found that they either have a positive effect or a significant relationship with sustainable agricultural productivity. In order to meet the current environmental, economic, and political challenges, the agriculture sector at the global and local level should improve and further adopt existing technologies, consolidate the use of integrated pest-management strategies, and fully introduce innovations, combined with digital transformation, into agricultural management and production. [ABSTRACT FROM AUTHOR]

Plants maintain the ecological equilibrium of the earth and stabilize the ecosystem. Today, traditional commodities and new value-added markets can be served simultaneously. There is significant biosource and bioprocess innovation for biobased industrial products. Furthermore, plant-based innovation is associated with the transition to sustainability. This study performed a bibliometric and in-depth content analysis to review plant-based innovations in the research field between 1995 and 2022. A set of 313 articles was identified from the Scopus and Web of Science databases. Different analytical scientometric tools (topic mapping and overlay visualization networks) were used to analyze 124 articles; the most influential countries, institutions, authors, journals and articles were identified. Through in-depth studies, based on the grounded theory approach, five leading research areas related to plant-based innovation were determined: (1) agricultural/environmental innovation, (2) plant-based food or feed innovation, (3) innovation within the medical/pharmaceutical research area, (4) technology-related innovation and (5) economic/business aspects of plant-based innovations. Future research directions include exploring less examined and new topics, such as the sustainability implications of incorporating various plant-based foods and Industry 4.0 in plant-based innovation, and linking and developing findings from different research areas. [ABSTRACT FROM AUTHOR]

Based on the microdata of 11,547 farmers from the China Labor Dynamics Survey (CLDS) database in 2017, an ordered multi-classification logistic model was constructed to empirically test the impact of social capital (i.e., social networks, social participation, and social trust) on farmers' willingness to adopt agricultural technology. The moderating effect of demographic changes (i.e., the number of instances of hukou migration) on social capital and farmers' willingness to adopt new agricultural technology was further investigated. The results show that the following: (1) Social trust has a significant positive impact on farmers' willingness to adopt new agricultural technologies, while social participation has no significant impact on farmers' willingness to adopt new technologies. (2) Social networks influence farmers' technology adoption behavior differently, e.g., the scope of relatives' wedding gifts has a significant and positive influence on farmers' technology adoption behavior, while the scope of non-relatives' wedding gifts has no significant influence on farmers' technology adoption behavior. (3) Demographic change plays a moderating role in the impact of social capital on farmers' willingness to adopt new agricultural technologies. In other words, the greater the number of instances of hukou migration, the less the promoting effect of social capital on farmers' willingness to adopt agricultural technology. (4) In the eastern and central regions of China, social capital has a significant positive impact on farmers' adoption of new agricultural technologies. In the western region of China, social capital has a significant negative impact on farmers' adoption of new agricultural technology. In the northeast region of China, social capital has no significant impact on farmers' adoption of new agricultural technologies. Social capital and population changes are important factors that affect farmers' willingness to adopt new agricultural technologies. Therefore, attention should be paid to cultivating and promoting farmers' social capital to improve farmers' willingness to adopt new agricultural technologies. [ABSTRACT FROM AUTHOR]

As a collection of technologies that match the carrying capacity of resources and the environment, harmonize ecology and life, and balance the quantity and quality of agricultural products in agricultural production, green production technologies are regarded as an important means to help promote sustainable agricultural production. It includes scientific fertilization technology, water-saving irrigation technology, biological control technology, and conservation tillage technology. However, the smallholders' low level of awareness and application of green production technology has become a key factor limiting the sustainable development of Chinese agriculture. Several technological innovations have been implemented to address these problems while many studies have been conducted on the smallholders' willingness to adopt the technology. However, the correlation and the hierarchical structure among different factors are not clear. Therefore, to clarify these issues, we used the logit model and interpretative structural modeling (ISM) to analyze the factors influencing the adoption of green production technologies by smallholders and the hierarchical linkage between them based on a sample of 709 from 16 provinces in China. Our results revealed that scientific fertilization and biological control technology were most preferred by smallholders. Compared with wheat (38.8%, 43.2%) and maize (29.3%, 39.4%), rice smallholders (66.7%, 82.5%) were more willing to adopt the two technologies. In addition, the technology awareness and technology benefits were expected to significantly affect the smallholders' willingness to adopt the technology directly. Household characteristics and land characteristics are the root factors affecting the smallholders' willingness to adopt green production technology. Family characteristics and land characteristics also changed the willingness of smallholders to adopt green production technologies by changing their awareness of production technology and the technological benefits expected. Therefore, accelerating the promotion of green production technologies through the implementation of policies such as increasing the promotion of high-value-added agricultural products and cultivation techniques, increasing out-of-school knowledge education, and enhancing the construction of agricultural production infrastructure can be potentially viable ways to promote green transformation in agriculture. This study provides case support for increasing the smallholders' adoption of green production technology. [ABSTRACT FROM AUTHOR]

Aquaponics is an innovative, smart, and sustainable agricultural technology that integrates aquaculture (farming of fish) with hydroponics in growing vegetable crops symbiotically. The correct implementation of aquaponics helps in providing healthy organic foods with low consumption of water and chemical fertilizers. Numerous research attempts have been directed toward real implementations of this technology feasibly and reliably at large commercial scales and adopting it as a new precision technology. For better management of such technology, there is an urgent need to use the Internet of things (IoT) and smart sensing systems for monitoring and controlling all operations involved in the aquaponic systems. Thence, the objective of this article is to comprehensively highlight research endeavors devoted to the utilization of automated, fully operated aquaponic systems, by discussing all related aquaponic parameters aligned with smart automation scenarios and IoT supported by some examples and research results. Furthermore, an attempt to find potential gaps in the literature and future contributions related to automated aquaponics was highlighted. In the scope of the reviewed research works in this article, it is expected that the aquaponics system supported with smart control units will become more profitable, intelligent, accurate, and effective. [ABSTRACT FROM AUTHOR]

Precision farming innovations are designed to improve the efficiency of agricultural activities via minimal initial input of material and human resources and avoiding harmful effects on the environment on one hand and automatizing the production on another hand, thus providing environmental, social and economic benefits. In the article, the tendencies in the adoption of precision agriculture technologies (PAT) in Ukraine were observed, with a specific focus on cooperatives as a valuable tool of social and solidarity economy helping to achieve progress in local rural development. On the example of cooperatives, applying a technology acceptance model (TAM) has identified how the adoption of new smart farming tools influence their behavior in implementing technological innovations. The results of the study will be of particular interest to representatives of other cooperatives and to agribusiness players engaged in agriculture or software development. In addition, the outputs will be useful for researchers in the field of the socio-economic development of territories and the impact of new technologies on it, as well as for local governments and higher-level government officials, which can contribute to the implementation of better rural development strategies. [ABSTRACT FROM AUTHOR]

We examine technological progress in the US and Canada to answer the question: has the efficiency (e.g., the edible energy efficiency, or EEE) for producing agricultural products in the US and Canada increased in recent decades? Specifically, we determined the energy efficiency of agriculture at the farm gate in recent decades by dividing the outputs (the total annual crop and animal output in energy units minus the feed used for animal production and the grain used for ethanol production) by the energy inputs: all the energy used by the nation to produce food (the energy used to generate and apply the fertilizer, pesticides, seed and to operate machinery) minus the energy inputs to produce grain for ethanol. Our data comes primarily from national and international agricultural censuses. Our study found that the energy efficiency of US agriculture has more than doubled from 0.8:1 in 1970 to 2.2:1 by 2000, then increased more slowly to 2.3:1 by 2009. The energy efficiency of the agricultural sector in Canada has not changed appreciably since 1980, and has varied about a mean of 2:1 from 1981 to 2009. Our study found that EEE improvements in the US could be attributable in part to advancements in crop production per hectare, and lower direct fuel consumption, but also a greater proportion of less energy-intensive corn and changes to the diet of livestock (e.g., increased use of meals and other by-products which have increased the availability of grain). Thus increases due to technological progress alone for the last several decades appear small, less than one percent a year. [ABSTRACT FROM AUTHOR]