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Sustaining life on the Earth with its ever-growing population is forcing changes in people’s way of life, industrial and agricultural production, exploitation of energy resources, and approaches to ecology. We face continual growth in the world’s population, and the demand for materials is growing even more rapidly. Every manufacturing and consumer sector is looking for ways to save energy and materials, attempting to minimize their negative impacts on the environment. In the pulp and paper industry, one of the segments in which progress can be made and help protect the planet is to reduce the brightness of paper. Such a reduction would lead to a lowering in the energy and material costs associated with paper production. [ABSTRACT FROM AUTHOR]

Agricultural paper mulch is an indispensable part of modern agriculture. It had the functions of heat preservation, moisture preservation, insect resistance, disease prevention, and weed growth inhibition. In order to extend the service life of the paper mulch, we use the solution immersion method to modify the surface of the paper mulch. A super-hydrophobic paper mulch is mainly prepared by using hydrophobic silica. The static contact angle of the super-hydrophobic paper mulch with water is 160.6°. The super-hydrophobic paper mulch samples were immersed in acid solution (pH = 4.6 H2SO4) and alkaline solution (pH = 8.5 NaOH). The main instruments are contact angle tester, tensile testing machine and high-speed camera. The hydrophobic properties, mechanical properties and rebound properties of the two kinds of paper mulches were compared. The results showed that the tensile strength and droplet bounce height of the superhydrophobic paper mulch decreased after being soaked in acid or alkaline solution for 48 h. The mass loss rate of paper mulch was more significant in acid solution, but its contact angle was still greater than 145°, and it had good bounce performance. After observing the microscopic morphology of its surface, it was found that silica had a micro-rough structure on the surface of the paper mulch. The method was simple and environmentally friendly, and can alleviate the problem of poor acid and alkali corrosion resistance of the paper mulch, and had extraordinary significance for environmental protection. [ABSTRACT FROM AUTHOR]

Purpose - The purpose of this paper is to report the findings from a study that explored the use of art and visual production as a means through which 20 third-graders developed and represented their social studies understandings. The author describes the ways the process of visual production and the finished products illustrate the nature of the students' social studies learning. Design/methodology/approach - The project was grounded in an inductive qualitative approach privileging student voice. This paper reports analysis and interpretation of multiple data sources, including photographs of students' projects, digital recordings of the visual productions and student interviews, as well as field notes and informal teacher conversations. Findings - Results suggest that in the process of visual production and in their final pieces, students moved in fluid ways between making sense of new knowledge, developing important social studies skills, and representing their knowledge. More specifically, students used historical evidence to present humanized versions of history through personalized narratives. These outcomes suggest that the integration of art and visual production can be a valuable and effective way for students to develop and apply social studies skills as well as represent their understanding. Originality/value - This study provides insight into how young children can use art and visual production to develop social studies skills, make sense of new knowledge, and represent their learning, contributing knowledge on an understudied topic and population in social studies education. [ABSTRACT FROM AUTHOR]

Microfluidic analytical devices have gained significant traction by virtue of their unique merits in terms of miniaturization and attractive phenomena at microscale. The utilization of paper as a substrate material has witnessed substantial progress majorly due to its fast fluid transport, capillary action kinetics and improved detection limits bringing forward its techno-economic viability. This article provides light to the state-of-the-art developments in paper-based lab-on-a-chip (pLOC) devices for the detection of agri-food contaminants. Various fabrication processes for paper-based devices are elaborated along with their research progress. An analysis of its potential in detecting pesticides, viruses, food contaminants, foodborne pathogens, mycotoxins, and heavy metals in agricultural and food products has also been highlighted. Finally, the existing challenges and future prospects trending towards digitalization is emphasized to understand its feasibility and commercialization. pLOC devices offer numerous advantages due to its abundant availability of substrate, ease of fabrication, improved surface functionalization processes, as well as the ability to detect multiple analytes simultaneously (i.e., multiplexing) with low-volume requirements. There lies widespread opportunity with paper due to its porous cellulosic matrix and spontaneous channel flow of reagents or analytes enabling the development of standalone analytical devices. The sensitivity, selectivity, and repeatability are the crucial deciding parameters for evaluating the analytical performance of lab-on-a-chip sensors. A frugal engineering approach and protocol is ideally suited for the development of miniaturized sensors for on-site monitoring of contaminants in resource-limited settings. The monitoring of agri-food contaminants may further be combined with nanotechnology for signal enhancement, artificial intelligence and use of algorithms for the smart sensing to make it more user friendly for point-of-care applications. The use of pLOCs for the detection of agri-food contaminants has indeed paved the way to facilitate sustainable precision agriculture. [Display omitted] • pLOCs offer fast fluid transport, capillary action kinetics and high detection limit. • Notable progress is achieved on integrating pLOCs with nanomaterials to improve LOD. • A rapid, straightforward, and high-throughput manufacturing process is needed. • Cost-effective and high sensitive detection/readout mechanisms are required in pLOCs. • Integration of AI & ML can support the design, optimization and fabrication of pLOCs. [ABSTRACT FROM AUTHOR]

The paper shows how the agri-sector is influenced by the emergence and development of the digitisation process. This is presented using a bibliometric analysis. The importance of studying and understanding the current challenges facing the agricultural sector including the emergence and development of the digitisation process of the sector is the main aim of this paper. All these challenges are felt by both the agricultural sector and the economy as a whole. This paper contributes to the literature. This is due to the bibliometric analysis through which the most important aspects of the challenges facing the entire agricultural sector today are observed. Among the current challenges facing the agricultural sector, climate change is among the most important. The results of the bibliometric analysis show that the keywords searched and their clustering confirm that the emergence and rapid development of digitisation brings both positive and negative effects to the whole agricultural sector. Following the search of Web of Science and Scopus databases, 203 papers were identified in Web of Science and Scopus using the phrase "the impact of digitization on agriculture". The bilbiometric analysis comprises several steps, including the analysis of the years of emergence of studies on the emergence of the digitisation process in agriculture. Thus, within this stage, the analysis of the years, it is signalled the transition from some aspects that concern the technological side to other economic and even human aspects. On the whole, there is a shift in research topics towards studying how the emergence and development of the digitisation process brings both positive and negative influences between the agricultural sector and society. [ABSTRACT FROM AUTHOR]

This paper elaborates on a digital simulation study on supernormal particle flow used to investigate and analyze the process of picking up jujube branches, which was a meaningful attempt to search for accurate and effective advanced numerical analogy methods in the agricultural field. In this paper, the meshless technology based on the element-free Galerkin method was used for the first time to present the effects of particle size, particle number and particle acting force on the movement of irregular particles, and the influence of the gear rotation speed, the feeding amount, and the jujube branch size on the movement behavior as well as the picking rate. It can describe not only the particles' dynamic movement in the process of picking up jujube twigs, such as feeding, collision, throwing and rolling, but also the effect of the quality and shape caused by the particle size, which in turn affects the surface force of particles and interparticle acting force, thereby affecting the weight function in the analytical solution, the total feeding amount and the effect of the acting force resulting from the particles' contact, roll and collision caused by gear rotation. The findings reveal that the digital simulation, based on the meshless Galerkin technology and Rocky software, is effective in dealing with issues related to supernormal particle flow. By eliminating the influence of geometric shapes on calculations, the method boasts an effective solution to the movement problems of irregularly shaped particles, which would be further applied in the agriculture field. [ABSTRACT FROM AUTHOR]

This article reports the first occurrence of Sordaria macrospora causing collar rot of peanut in Shandong province, China. The study describes the symptoms observed on peanut plants, the isolation and identification of the fungus, and the pathogenicity testing conducted. The research was supported by various funding sources, and the sequence data has been deposited in GenBank. This finding expands our knowledge of the distribution and impact of S. macrospora on peanut crops in China. [Extracted from the article]

The Virtuous Incubation System is a solution aimed at transforming poultry farming by integrating Internet of Things (IoT) technology into the incubation process. This paper seeks to improve the efficiency and success rate of poultry egg incubation while minimizing manual intervention, reducing resource consumption, and ensuring optimal conditions for embryo development by providing a smart incubator system. The smart incubator addresses the challenges of traditional manual monitoring and adjustments by leveraging IoT devices, sensors, and data analytics to create an automated and intelligent incubation system. It provides energy efficiency by incorporating energy-efficient components to minimize power consumption, thereby reducing operational costs for farmers, and by providing notifications and alerts where critical deviations in environmental conditions or equipment malfunction, enabling proactive intervention to prevent losses. A cross-section of small- to medium-scale poultry producers, particularly those engaged in hatching chicks, were interviewed to highlight the main challenges regarding the business of hatching chicks. It was learned through the interviews that chick production on a small to medium scale was relatively expensive due to the labor employed to monitor the production and losses due to adverse conditions resulting in a poor success rate in hatching the chicks. Thus, the implementation of the virtuous incubation system comes in to solve the main challenges being faced by the local poultry producers. [ABSTRACT FROM AUTHOR]

This paper mainly aims to identify the key factors that should be included in building of smart cities in a proper efficient way. Due to rapid increase in urban population, it should be responsible to provide a better way in building of a smart city. Smart city is an idea of providing urban development that includes social, financial, ecological parts of a society. A smart and sustainable city has goals to be achieved in an adaptable, reliable, scalable, accessible, and in resilient way which will be discussed in the methodology section. This paper mainly focuses on some important factors in improving sustainability of smart cities such as climate and environmental issues and governance authorities for improving quality of life of citizens. Also, this paper explains 3E's which are environment, economy and equity are plays a crucial role in rapid development of smart cities. This research is focused on discussing various smart technologies recently used in India and the challenges involved in them. Recent literature on smart city development is reviewed, and the challenges that prevailed in recent technologies are analysed. This paper includes how Internet of Things (IoT), Connectivity, Cloud computing and AI etc., should be effectively used for developing a smart city. This paper deals with the requirements to build smart cities in India – regarding various aspects like available resources, lifestyle, transport management system, smart healthcare system, smart waste management, smart Sanitation, smart railways, smart agriculture, home automation, smart energy consumption etc. This paper also discusses 'smart living,"smart infrastructure,"smart governance,"smart economy,' and other various systems which are need for Smart India in particular. When adopted with proper planning, all the above catalysing with smart services and solutions, build a sustainable city. [ABSTRACT FROM AUTHOR]

This study evaluates the treatment efficiency of a horizontal subsurface-flow constructed wetland (HSSF-CW) for the removal of chloro-organic compounds from pulp and paper mill wastewater. The surface area of the HSSF-CW unit was 5.25 m² and was planted with Colocasia esculenta. The wastewater was characterized for different chloro-organic compounds, that is, adsorbable organic halides (AOX), chlorophenolics, and chlorinated resin and fatty acids (cRFAs). Under a hydraulic retention time of 5.9 days, the average AOX, chlorophenolics, and cRFA removal from wastewater was 87, 87, and 93%, respectively. Some of the chlorophenolics were found to accumulate in the plant biomass and soil material. The mass balance studies show that a significant fraction of chlorophenolics and cRFA was degraded in the constructed wetland system. Modeling studies were carried out to estimate the first-order area-based removal rate constants (k) for chemical oxygen demand removal. The HSSF-CW was found to be an effective treatment technology for the remediation of pulp and paper mill wastewater. [ABSTRACT FROM AUTHOR]

Agricultural policies are widening the scope to contribute to environmental objectives, such as the Green Deal, Paris Climate Agreement and sustainable development goals. This leads to new monitoring and data needs. To fulfil these data needs, it is crucial to explore the opportunities and limitations of new technologies. This paper analyses the information flows within the agricultural sector and its potential to contribute to future information needs. Farmers act within a network of commercial and governmental organisations. The information exchange with these organisations could increasingly occur through digital means, but in reality, there is still a lot of data transfer on paper or in PDF format. This implies information loss. Digital information flows provide a wealth of information for policy evaluation and monitoring and have the potential to reduce transaction costs. Combining data from different sources (open data like earth observation data, data from on-farm sensor networks, accountancy data like invoices and data from food chain platforms) concerning a single farm is an even bigger challenge than the transfer from paper to digital. Based on these observations a list of requirements for a future solution for information transfer is defined. Based on these requirements, this paper presents the design of a System for Information Transfer to Reduce Administrative burdens (SITRA) to combine data from different sources and give farmers control who can access these data. SITRA will address farmers' needs to reduce the growing administrative burden placed on them by governments and the food chain sustainability and food safety schemes, especially if data would be stored in a digital farm locker and a farmer could voluntary give his consent through an authorisation mechanism to share specific data with his business partners, paying agency, statistical organisation and Farm Accountancy Data Network (FADN, an EU monitoring system for the Common Agricultural Policy). A platform that provides such data lockers could also provide benchmark facilities and a tool for common (open source) maintenance of coding systems. The paper proposes some follow-up activities to test this design. As a pilot, organic farmers that participate in the Dutch Farm Accountancy Data Network (FADN) will be recruited to co-develop and test the design principles of the system. Given trust issues around data management, the design of the governance and business model of the system are key issues in the follow-up. This group is chosen as organic certification and FADN are the most dataintensive monitoring and evaluation tools in the CAP. The Farm to Fork communication proposes to enlarge the organic sector to 25% of the agricultural area. A new organic control regulation, based on a risk assessment approach is about to be implemented. The Farm to Fork communication also proposes to link the FADN much more with the Farm Advisory System and to extend it to a Farm Sustainability Data Network. [ABSTRACT FROM AUTHOR]

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

• Reviewed "precision agriculture", "smart agriculture" and "digital agriculture" concepts. • Suggested "smart agriculture" and "digital agriculture" be phases of "precision agriculture". • Proposed a few research focuses on smart and digital technologies for agriculture. [ABSTRACT FROM AUTHOR]

3D printing or additive manufacturing process is known as part of the digital manufacturing process, involves gradually adding materials to a geometric representation to manufacture physical objects. A quickly developing technology is 3D printing. The world now uses 3D printing extensively in the many fields such as automotive, locomotive, healthcare, agriculture mass customization, aviation sectors and manufacture of any form of open source designs using 3D printing technology are becoming more common. 3D printing process produce an object directly from a computer-aided design model by depositing material layer by layer. In this world mostly many countries are quickly advancing and heavily investing in 3D printing. The advancement of 3D printing technology in Pakistan will be accelerated by strong government assistance, both in the form of laws that are welcoming to investors and subsidies during the early stages of growth. The use of this technology will bear fruit with a few years. Economy will boost as a result of strong manufacturing base. Pakistan will be able to contribute to the international market with skilled professionals and complex products, thus paving way for a sustainable future. The varieties of 3D printing technologies, the materials utilised in 3D printing, the applications for 3D printing technology, and the difficulties associated with adopting 3D printing technologies in Pakistan are all covered in this article. [ABSTRACT FROM AUTHOR]

This paper introduces an innovative IoT-enabled crop storage monitoring system designed to revolutionize the preservation and quality assurance of stored agricultural produce. Central to this system are IoT sensors strategically deployed within storage facilities. These sensors are tasked with the continuous tracking and monitoring of crucial environmental parameters, specifically temperature, humidity, and gas levels. Leveraging this real-time data, the system is engineered to promptly detect and respond to any deviations from the prescribed optimal storage conditions. The core strength of this system lies in its ability to generate instantaneous alerts upon detecting irregularities. These alerts serve as preemptive measures, effectively averting potential spoilage and curtailing post-harvest losses by enabling timely interventions and corrective actions. By harnessing IoT technology, this paper aims to create a proactive, automated, and responsive framework that ensures the integrity and safety of stored agricultural produce, ultimately contributing to enhanced food security and sustainability. [ABSTRACT FROM AUTHOR]

The smallholder agricultural commercialization and market participation is a key precondition for the transformation of agriculture sector from subsistence to commercial production. However, the contribution of smallholder agricultural commercialization and participation remains low. As a result, this paper aimed to discover the conceptual understanding, the role of smallholder agricultural commercialization and participation, its determinants and to identify the initiative mechanisms to enhance it. In Ethiopia the average landholding size of smallholder farm is 1.18 hectares per farm household which meets the conventional meaning of smallholder farms (less than 2 ha). Ethiopian smallholders agricultural plow over 96% of the full agricultural land, although average smallholder cultivates less than one hectare, and consumes greater than 65% of total. In addition, despite all these efforts, commercialization of smallholder farmers' products is still at a low level. The low-level smallholder agricultural commercialization which in turn low level of value addition as a result -low level of total marketed supply forces the country to import different crops and livestocks. Accordingly, this review identified the major determinants of smallholder agricultural commercialization were technology adoptions, markets and their integration, asset holdings and policy aspects. Therefore, an initiative mechanism to enhance smallholder agricultural commercialization and participation in Ethiopia is an imperative strategy which includes, providing better access to agricultural technologies; encouraging farmers' cooperatives and establishing agro-industry parks. Therefore, this review paper recommends interventions geared towards improving smallholder farmers' organization, producers' association and ensuring appreciable reduction in transaction costs and also farmers' access to productive assets and technologies which is capable of stimulating profitable smallholders' market participation and as a result deemed important to transform subsistence to commercialization agriculture. [ABSTRACT FROM AUTHOR]

Oyster Farming is one of important fisheries and aquaculture industries in Taiwan. Each year, approximately 4000–5000 tons of discarded bamboo scaffolding (BS) used in oyster farming, are generated, so the treatment and utilization of BS should be taken seriously. This study evaluates the suitability of BS for pulp and papermaking by assessing the chemical compositions, microstructural, and fiber morphology. The pulping properties is investigated by soda pulping. The chemical composition of BS shows the potential for application in pulping. The BS microstructure shows that can enhance pulping reactions, while the fiber morphology indicates the possibility of producing high-strength paper. Through the pulping experiment, it demonstrated that BS is suitable for pulping with lower NaOH dosage and longer digestion time. The condition at 170 °C with 14% NaOH dosage for 90 min digestion has the highest yield. After refining the highest pulping yield BS pulp, it can improve the handsheet strength and bulk of the OCC-BS mixed pulp, which can achieve the strength property required for industrial paper. In summary, BS exhibits the potential for pulping application and produces a better paper strength than OCC pulp, exhibiting the feasibility of enhancing the circular utilization value of BS in Taiwan. [ABSTRACT FROM AUTHOR]

An experiment was carried out at the Research Station of the Faculty of Agriculture, University of Baghdad for the 2017 spring season by planting Solanum tuberosum L. (class Burren) on 6 of February 2017 in a mixed soil to determine the effect of adding NPK, organic fertilizer levels as well, iron and zinc paper spraying, and their interactions in the growth and yield of potatoes. Randomized complete Block Design (RCBD) was used in experiment with three-replicates each containing 30 treatments. The experiment included three factors: NPK fertilizer levels (M0) without fertilization, (M1) half of the fertilizer recommendation 50% (160: 40: 120) kg KPN h-1, (M2) complete fertilizer recommendation 100% (240:80:320) kg KPN h-1 and levels of organic manure (poultry) were O0 without fertilization, O1 add 20 Mg h-1 organic fertilizer. The Levels of iron and zinc paper spraying with regular fertilizers and fertilizers manufactured according to nanotechnology were F0 without spraying with iron and zinc, F1 was sprayed with iron and zinc at a concentration of 50 mg Zn-1 + 100 mg Fe-1, F2 was sprayed with 100 mg Zn L-1 + 200 mg Fe-1 using standard compost (EDTA- Zn 14%) and EDDHA-Fe 6%). The levels (F3 and F4) represent the irradiation of iron and zinc produced according to nanotechnology at a concentration of 50 mg Zn-1 + 100 mg Fe-1 and 100 mg Zn-1 + 200 mg Fe-1 respectively, using fertilizer (Chelate Zn 20% and Chelate Fe 10 %). The results showed that the single and double addition of NPK, organic fertilizer, and iron and zinc paper spraying had a significant effect on the dry weight of the vegetative group, the average weight of the tuber, the total yield and the percentage of germination relative to the comparison treatment. The results indicate that the triple interaction, which were the addition of 50% of the M1 fertilizer recommendation, the addition of the level of organic fertilizer O1 and the spraying of iron and zinc produced according to the nanotechnology (F3 and F4), gave the best value for the growth traits and productivity in the quantity and quality. The M1O1F4 treatment exceeded the total dry weight of total vegetative, the average weight of the tuber and the total number which reached (2.62 Mg-1, 106.89 g and 41.15 Mg-1), respectively. The M1O1F3 treatment was superior to 13.24%, with an increase of 70.40% compared to the M0O0F0 comparison. The study showed that half the amount of fertilizer recommendation from mineral fertilizers could be compensated through organic fertilization and paper spray with iron and zinc produced according to nanotechnology and get the best productivity both qualitatively and qualitatively. [ABSTRACT FROM AUTHOR]

Corn crop row recognition during different growth stages is a major difficulty faced by the current development of visual navigation technology for agricultural robots. In order to solve this problem, an algorithm for recognizing corn crop rows during different growth stages is presented based on the ST-YOLOv8s network. Firstly, a dataset of corn crop rows during different growth stages, including the seedling stage and mid-growth stage, is constructed in this paper; secondly, an improved YOLOv8s network, in which the backbone network is replaced by the swin transformer (ST), is proposed in this paper for detecting corn crop row segments; after that, an improved supergreen method is introduced in this paper, and the segmentation of crop rows and background within the detection frame is achieved utilizing the enhanced method; finally, the corn crop row lines are identified using the proposed local–global detection method, which detects the local crop rows first, and then detects the global crop rows. The corn crop row segment detection experiments show that the mean average precision (MAP) of the ST-YOLOv8s network during different growth stages increases by 7.34%, 11.92%, and 4.03% on average compared to the MAP of YOLOv5s, YOLOv7, and YOLOv8s networks, respectively, indicating that the ST-YOLOv8s network has a better crop row segment detection effect compared to the comparison networks. Corn crop row line detection experiments show that the accuracy of the local–global detection method proposed in this paper is improved by 17.38%, 10.47%, and 5.99%, respectively, compared with the accuracy of the comparison method; the average angle error is reduced by 3.78°, 1.61°, and 0.7°, respectively, compared with the average angle error of the comparison method; and the average fitting time is reduced by 5.30 ms, 18 ms, and 33.77 ms, respectively, compared with the average fitting time of the comparison method, indicating that the local–global detection method has a better crop row line detection effect compared to the comparison method. In summary, the corn crop row recognition algorithm proposed in this paper can well accomplish the task of corn crop row recognition during different growth stages and contribute to the development of crop row detection technology. [ABSTRACT FROM AUTHOR]

This document is an introduction to a special issue of the journal "Plants" on the topic of "The Application of Spectral Techniques in Agriculture and Forestry." The special issue includes twelve research papers that explore various applications of spectral analysis in agricultural and forestry environments. The papers cover topics such as crop health monitoring, disease detection, forest parameter estimation, soil quality assessment, water stress analysis, and nutrient management. The studies highlight the use of advanced spectral indices, remote sensing techniques, and machine learning algorithms to monitor plant physiological parameters and improve resource management in agricultural ecosystems. The research presented in this special issue demonstrates the broad applicability of spectral technologies in different geographical regions and crops, emphasizing the efforts of scientists from multiple countries to promote precision agriculture and forestry practices. [Extracted from the article]

The agricultural sector is undergoing a transformative paradigm shift with the integration of advanced technologies, particularly artificial intelligence (AI), to enhance data analysis techniques and streamline decision-making processes. This paper delves into the integration of advanced technologies in agriculture, focusing specifically on optimizing data analysis through artificial intelligence (AI) to strengthen decision-making processes in farming. We present a novel AI-powered model that leverages historical agricultural datasets, utilizing a comprehensive array of established machine learning algorithms to enhance the prediction and classification of agricultural data. This work provides tailored algorithm recommendations, bypassing the need to deploy and fine-tune numerous algorithms. We approximate the accuracy of suitable algorithms, highlighting those with the highest precision, thus saving time by leveraging pre-trained AI models on historical agricultural data. Our method involves three phases: collecting diverse agricultural datasets, applying multiple classifiers, and documenting their accuracy. This information is stored in a CSV file, which is then used by AI classifiers to predict the accuracy of new, unseen datasets. By evaluating feature information and various data segmentations, we recommend the configuration that achieves the highest accuracy. This approach eliminates the need for exhaustive algorithm reruns, relying on pre-trained models to estimate outcomes based on dataset characteristics. Our experimentation spans various configurations, including different training–testing splits and feature sets across multiple dataset sizes, meticulously evaluated through key performance metrics such as accuracy, precision, recall, and F-measure. The experimental results underscore the efficiency of our model, with significant improvements in predictive accuracy and resource utilization, demonstrated through comparative performance analysis against traditional methods. This paper highlights the superiority of the proposed model in its ability to systematically determine the most effective algorithm for specific agricultural data types, thus optimizing computational resources and improving the scalability of smart farming solutions. The results reveal that the proposed system can accurately predict a near-optimal machine learning algorithm and data structure for crop data with an accuracy of 89.38%, 87.61%, and 84.27% for decision tree, random forest, and random tree algorithms, respectively. [ABSTRACT FROM AUTHOR]

This paper will examine the social and ethical impacts of using artificial intelligence (AI) in the agricultural sector. It will identify what are some of the most prevalent challenges and impacts identified in the literature, how this correlates with those discussed in the domain of AI ethics, and are being implemented into AI ethics guidelines. This will be achieved by examining published articles and conference proceedings that focus on societal or ethical impacts of AI in the agri-food sector, through a thematic analysis of the literature. The thematic analysis will be divided based on the classifications outlined through 11 overarching principles, from an established lexicon (transparency, justice and fairness, non-maleficence, responsibility, privacy, beneficence, freedom and autonomy, trust, dignity, sustainability, and solidarity). While research on AI agriculture is still relatively new, this paper aims to map the debate and illustrate what the literature says in the context of social and ethical impacts. It aim is to analyse these impacts, based on these 11 principles. This research will contrast which impacts are not being discussed in agricultural AI and which issues are not being discussed in AI ethics guidelines, but which are discussed in relation to agricultural AI. The aim of this is to identify gaps within the agricultural literature, and gaps in AI ethics guidelines, that may need to be addressed. [ABSTRACT FROM AUTHOR]

The article discusses the growing interest in establishing smart cities based on the Internet of Things (IoT) and the challenges they face, particularly in terms of security. The article highlights a special issue of the IETE Journal of Research that focuses on IoT, sensor networks, and blockchain technology for smart cities and societies. The special issue contains 10 full papers that cover various topics such as urban land use change detection, air quality data imputation, steganographic approaches for secured communication, and agricultural applications using blockchain. The article expresses gratitude to the organizers and contributors of the special issue and hopes that it will be a valuable resource for researchers and engineers. [Extracted from the article]

This paper is an historical analysis of how global pressures and aspirations have affected US farm bill debates over time, from the first farm bill in 1933 to the current debates over a 2018 farm bill. It focuses in particular on how nationalist and patriotic arguments have been used to support the USA's desired place in global agricultural markets over time. For example, debates over the 2008 farm bill reflected strong international concerns around both trade and energy, with early discussion focusing on keeping the USA 'competitive' as an agricultural exporter alongside emerging agricultural powerhouses, and later debates focusing on increasing domestic bioenergy production to 'protect' the USA from what were seen as risky energy imports. In other words, debates over trade and energy in 2008 provide insight into how stakeholders positioned the USA with respect to the rest of the world and how that positioning changed over the course of debates. But such questions about the USA's global aspirations—whether to maximize US production for export or protect US agriculture from global rivals—have been part of the farm bill since its earliest days. This analysis will examine how concerns over such national agricultural prominence in a globalizing context have played into and influenced the contours of domestic farm policy over time, with implications for the 2018 farm bill debates. [ABSTRACT FROM AUTHOR]

[Display omitted] • A real-time grading method of roasted tobacco quality based on near infrared spectroscopy. • A key indicators selection method based on information gain and Fisher criterion was proposed. • A chemical indicator grading table was designed for reference. • Chemical indicator grading based on near infrared spectroscopy is a convenient, rapid and promising grading method. Traditional tobacco quality grading methods have limitations such as high human resource consumption and poor consistency, resulting in the grading accuracy being affected. Near infrared spectroscopy (NIRS) technology, as a rapid and non-destructive analytical method, has been widely used for online inspection. This study aims to accomplish rapid, accurate and reliable real-time grading of tobacco quality by employing online near-infrared spectroscopy to detect key chemical indicators. A key indicators selection method based on information gain and Fisher criterion (IFRI) was proposed in this paper by associating tobacco chemical indicators with traditional quality grades. The key chemical indicators were selected from many indicators by two classical feature selection functions, and a chemical indicator grading table was designed based on a large number of statistical data on tobacco chemical indicators, and the table was applied to grade the tobacco quality of real data from different years. The results show that the IFRI algorithm is an effective method for selecting key indicators, and the selected reducing sugars-to-total nitrogen ratio and nicotine are the key indicators for tobacco quality grading. Moreover, we demonstrated that the designed grading table is reasonable and feasible. Compared with traditional grading, chemical indicator grading based on near infrared spectroscopy can not only be realized quickly by using an online near infrared instrument, but also the tobacco of the same grade is less discrete, better consistency and more representative after grading, and it is applicable to tobacco samples of different years, which is a convenient, rapid and promising grading method that can provide a reference for tobacco quality grading. Furthermore, the formulation design by utilizing different grades after grading can greatly improve the utilization rate of tobacco leaves. Notably, the method can also be applied to other fields, such as quality control of agricultural products, monitoring of food processing processes, etc. [ABSTRACT FROM AUTHOR]

This special issue features 14 new research papers investigating the role of farmers' organizations (e.g., collective action, self‐help groups, producer companies/organizations, and cooperatives) in supporting sustainable development. The key findings include: (1) farmer groups and cooperatives promote farmers' adoption of good farm management practices, new agricultural technologies and sustainable farming practices, although not substantially improving farm yield; (2) outsourcing services provided by agricultural cooperatives help to increase the technical efficiency of crop production; (3) cooperative membership enhances members' bargaining power and enables them to sell their products at higher prices; (4) cooperatives motivate rural laborers to work in off‐farm sectors, while self‐help groups empower rural women in decision‐making; (5) internet use improves agricultural cooperatives' economic, social, and innovative performances; (6) direct administrative intervention supporting cooperative development may lead to the emergence of shell cooperatives; (7) participation in forest farmer organizations enables wood value chain upgrading; (8) increasing the cooperative size in terms of income, equity, and assets increases the profitability of savings and credit cooperatives; and (9) creating cross‐border cooperation between cooperatives generates benefits for all parties involved. These findings can inspire the design of policies aimed to support farmers' organizations in achieving sustainable development goals. [ABSTRACT FROM AUTHOR]

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]

Background: The adoption of new agricultural technologies is one of the key factors for achieving sustainable agricultural development. With the rapid development of China's economy and the widening gap between urban and rural areas, it has become the norm for farmers to seek employment outside their home villages. This phenomenon not only changes the lifestyle of farmers but may also affect their attitudes toward and adoption behavior of new agricultural technologies. However, existing research in this field is not yet sufficient. This paper aims to assess the overall impact, heterogeneous effects, and mechanisms of action of migrant work experience on farmers' willingness to adopt new agricultural technologies. Methods: Based on the 8,391 sample data from 243 counties in the 2018 China Labor Force Dynamic Survey (CLDS2018), this paper uses the Linear Probability Model (LPM), Two Stage Least Square (2SLS), Conditional Mixed Process (CMP) methods, and omitted variable test to estimate the impact of migrant work experience on farmers' willingness to adopt new agricultural technologies. Simultaneously, it explored the heterogeneity in the relationship between migrant work experience and the willingness to adopt new agricultural technologies from the perspectives of gender, age, and educational level. Lastly, the Karlson-Holm-Breen (KHB) model was utilized to analyze the mechanisms through which migrant work experience affects farmers' willingness to adopt new agricultural technologies. Results: Migrant work experience significantly enhances farmers' willingness to adopt new agricultural technologies, with the probability of willingness among farmers with migrant work experience being 26.65% higher than that of farmers without such experience. At the same time, compared to female farmers, those born before 1980, and those with primary education or less, this enhancing effect is more pronounced among male farmers, those born after 1980, and those with more than a primary education. Furthermore, it was found that migrant work experience not only directly enhances farmers' willingness to adopt new agricultural technologies but also indirectly promotes it by increasing capital accumulation, enhancing risk awareness, expanding social networks, and strengthening agricultural cognition, with risk awareness and agricultural cognition playing a larger indirect role. Conclusion: Based on the empirical results, this paper suggests actively guiding farmers with migrant work experience to adopt new agricultural technologies, and encouraging return migrant labor with the intention of resettling in rural areas to engage in agriculture again, to further promote the adoption of new agricultural technologies. [ABSTRACT FROM AUTHOR]

Modern and precision agriculture is constantly evolving, and the use of technology has become a critical factor in improving crop yields and protecting plants from harmful insects and pests. The use of neural networks is emerging as a new trend in modern agriculture that enables machines to learn and recognize patterns in data. In recent years, researchers and industry experts have been exploring the use of neural networks for detecting harmful insects and pests in crops, allowing farmers to act and mitigate damage. This paper provides an overview of new trends in modern agriculture for harmful insect and pest detection using neural networks. Using a systematic review, the benefits and challenges of this technology are highlighted, as well as various techniques being taken by researchers to improve its effectiveness. Specifically, the review focuses on the use of an ensemble of neural networks, pest databases, modern software, and innovative modified architectures for pest detection. The review is based on the analysis of multiple research papers published between 2015 and 2022, with the analysis of the new trends conducted between 2020 and 2022. The study concludes by emphasizing the significance of ongoing research and development of neural network-based pest detection systems to maintain sustainable and efficient agricultural production. [ABSTRACT FROM AUTHOR]

This is the full article based on a conference paper. Pipe robots are used in agricultural engineering for transportation of materials. Also, they are used for cleaning the internal surfaces of the pipes. In the process of numerical investigation of dynamics of a pipe robot, a specific model for viscous friction is used. This influences the results of numerical calculations of dynamics of a pipe robot. A numerical procedure for more precise calculation of viscous friction is proposed in the paper. Results of investigations for two values of time steps are obtained and presented: without the proposed procedure and with it. Advantages of the improved calculation of viscous friction are indicated. [ABSTRACT FROM AUTHOR]

The growth of Walailak Journal of Science and Technology is chronicled through a scientometric analysis from 2010 to 2015. The number of submissions has vastly increased since the online submission system was introduced in 2011 and surpassed 400 manuscripts per year in 2014 - 2015. It follows that the acceptance ratio has been reduced to the minimum of 25 % in 2015. The 339 published papers, mostly full-length research articles, are categorized into Science (46.61 %), Agricultural technology (23.30 %), Engineering (17.70 %), Health sciences (6.78 %) and Information technology (4.72 %). The journal is benefited from demographic diversity of authors. Papers submitted from 27 different countries were published during this 6-year period. Furthermore, domestic reviewers and editorial board members have become the minority since 2012. The citation recorded in SCOPUS database has continued to improve with the reduction in self-citation ratio. The lastest Scimago Journal Rank (SJR) obtained in 2014 is 0.207 with 33 citations and average 0.33 citations per paper. [ABSTRACT FROM AUTHOR]

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