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The purpose of this paper is to provide a better understanding of the development of intelligent agriculture (IA) in China, which is an important tendency in advancing the agricultural productivity in the coming era.

Considering publications as featured evidence of an emerging phenomenon, the authors review publications of IA. Specifically, the use of term, definition and examples of IA, both English and Chinese literature, and government policies of China are all reviewed. Additionally, the authors use basic statistical and thematic analysis to help synthesizing the literature and drawing conclusions. Findings from various sources of publications supplement with each other.

IA in China has shown three main characteristics: unbalanced geographic distribution, an early stage of the trend and attention mainly focused on a limited range of technologies. Compared with the development of IA in other countries, such as Japan, India and the USA, featured with diversified properties, similarities and differences of IA development in China and in other countries are also discussed.

This general review contributes by uncovering the emergence of IA, identifying its general definition with a comprehensive set of practical examples and pointing out the present characteristics and problems of IA development in China. The general review provides a necessary summary for the policy makers and researchers to have a systematic understanding of IA and better promote its future development. At last, the paper calls for a process-based strategy with different goals at different stages, a sustainable mechanism coordinated by multiple participants, and a localized consideration for relevant policy making.

As the saying goes, “food is heaven of people” the development of agriculture is not only related to the quality of human life but also profoundly affects the efficiency of economic operation. However, under the background of rapid economic and technological development, China’s agricultural modernization process is very slow and incompatible with the development trend of economic modernization. Therefore, it is particularly necessary to innovate the traditional agricultural development model to break through the bottlenecks encountered in the transformation process of agricultural modernization. The proposal of the agricultural logistics ecosphere is to solve the problems of poor industrial linkage, low technical level and backward operation mode in the development process of traditional agriculture, and it is an important starting point for agricultural supply-side structural reform. This study aims to answer three questions in three aspects, namely, what is the agricultural logistics ecosphere, analyzes the general composition of the agricultural logistics ecosphere and how the subjects of the agricultural logistics ecosphere cooperate. It also puts forward suggestions for the coordinated development of the agricultural logistics ecosphere under the leadership of Taoxin. Also, it inspires the transformation of the agricultural development model in other regions and countries.

This study adopts a case study and a qualitative analysis method to collate the first-hand and secondary data obtained from the interview and form a tertiary coding. It explores the mechanism of coordinated development of the agricultural logistics ecosphere from four levels: goal synergy, resource synergy, ability synergy and benefit synergy.

First, the formation of the agricultural logistics ecosphere will not be achieved overnight, as operational management matures and ecosphere experiences the germination-development-mature evolution process. Second, target synergy is the foundation and premise for the formation of agricultural logistics ecosphere: to attract external resources with Taoxin characteristic core resources, to attract external resources to achieve synergy, to provide a guarantee for the realization of the maximum value of the agricultural logistics ecosphere and then to realize the interest synergy of internal and external subjects. Third, driving agricultural products upward in the “10 + 1” model: it is the core resource of the agricultural logistics ecosphere led by Taoxin and attracts external subjects to gather with core resources to further improve the value of the ecosphere. The improvement of the value of the ecosphere can broaden the ecosphere network. This is both an important construction of the ecosphere, and it is also the path choice of the coordinated development of the agricultural logistics ecosphere.

This study has a very important practical value and theoretical significance. In practical terms, the integration of “primary, secondary and tertiary industries” is helpful to foster new momentum for the development of agriculture and rural areas and promote the general framework of the agricultural logistics economy, the analysis of the general mechanism and extension of the transition of the new economy.

Focusing on the problem that the visual detection algorithm of navigation path line in intelligent harvester robot is susceptible to interference and low accuracy, a navigation path detection algorithm based on improved random sampling consensus is proposed.

First, inverse perspective mapping was applied to the original images of rice or wheat to restore the three-dimensional spatial geometric relationship between rice or wheat rows. Second, set the target region and enhance the image to highlight the difference between harvested and unharvested rice or wheat regions. Median filter is used to remove the intercrop gap interference and improve the anti-interference ability of rice or wheat image segmentation. The third step is to apply the method of maximum variance to thresholding the rice or wheat images in the operation area. The image is further segmented with the single-point region growth, and the harvesting boundary corner is detected to improve the accuracy of the harvesting boundary recognition. Finally, fitting the harvesting boundary corner point as the navigation path line improves the real-time performance of crop image processing.

The experimental results demonstrate that the improved random sampling consensus with an average success rate of 94.6% has higher reliability than the least square method, probabilistic Hough and traditional random sampling consensus detection. It can extract the navigation line of the intelligent combine robot in real time at an average speed of 57.1 ms/frame.

In the precision agriculture technology, the accurate identification of the navigation path of the intelligent combine robot is the key to realize accurate positioning. In the vision navigation system of harvester, the extraction of navigation line is its core and key, which determines the speed and precision of navigation.

The Internet of Things (IoT) is becoming increasingly popular in agribusiness to help increase food production capacity for the ever-expanding global population. This chapter provides a holistic overview of the latest trends around the applications of IoT in agriculture. We begin by giving an overview of IoT and its capabilities, followed by a deep dive into the practical and realistic aspects of leveraging IoT into the agroecosystem. IoT is already being used for many intelligent agriculture applications, such as open-field agriculture, controlled environment agriculture (greenhouse), livestock breeding, agricultural machinery, and more. This chapter examines those applications and ventures beyond the farm into several other aspects of the ecosystem, including storage, warehouse ambiance control, agri-data analytics and decision control, logistics, environmental safety, etc. The contents of the chapter would be based on extensive studies and empirical analysis of the latest research papers on this subject from around the globe, accurately interpreted and transformed by the authors in light of their academic background and professional experience in the digital transformation arena.

The purpose of this paper is to provide a comprehensive review on the academic journey of artificial intelligence (AI) in agriculture and to highlight the challenges and opportunities in adopting AI-based advancement in agricultural systems and processes.

The authors conducted a bibliometric analysis of the extant literature on AI in agriculture to understand the status of development in this domain. Further, the authors proposed a framework based on two popular theories, namely, diffusion of innovation (DOI) and the unified theory of acceptance and use of technology (UTAUT), to identify the factors influencing the adoption of AI in agriculture.

Four factors were identified, i.e. institutional factors, market factors, technology factors and stakeholder perception, which influence adopting AI in agriculture. Further, the authors indicated challenges under environmental, operational, technological, economical and social categories with opportunities in this area of research and business.

The proposed conceptual model needs empirical validation across countries or states to understand the effectiveness and relevance.

Practitioners and researchers can use these inputs to develop technology and business solutions with specific design elements to gain benefit of this technology at larger scale for increasing agriculture production.

This paper brings new developed methods and practices in agriculture for betterment of society.

This paper provides a comprehensive review of extant literature and presents a theoretical framework for researchers to further examine the interaction of independent variables responsible for adoption of AI in agriculture.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2020-0448

Supply of food from the early stages of societies was one of the most important needs of humans. Sustainable supply of food is a demand in modern societies. The agri-food market grows as the population rises every year. The increase in the demand side of the market is more than the growth of the supply side. The rate of using technology in the supply side is increasing rapidly. By using technology in some parts, the efficiency of production improved and caused more production while resources are the same. Availability of resources in different areas causes different ways of production and nurturing innovative technologies to maintain food security. Water, soil, climate change, and growth of population are drivers of using technology in food security. To depict the role of different technologies in the food industry, the authors have reviewed the role of the most important technologies in this field. Knowing the trends of changes in the industry will help to focus on the most important questions and solutions. Having a share in the global food market requires the major use of technology in production processes. In this chapter, the authors will review the most important trends of technology absorption in the food industry.

The purpose of this paper is to present the current state research of cyber-physical system (CPS) and its application in libraries. CPS is a kind of large-scale and networked system that consists of physical and cyber elements and is currently of interest in academia, industry and government. In this survey, the definitions, theoretical foundation and basic applications of CPS are systematically reviewed. In addition, the development of library and current research of CPS application in library management are presented. The vision and challenge of smart library are also discussed.

By retrieving the main scholarly databases, the literature of CPS and its application in libraries were examined.

This study shows that a lot of CPS technology applications are still in initial stage, and explores CPS potential impacts on libraries.

The application of CPS in library management has not been paid much attention, this study provides a prospective for the application of CPS in libraries.