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There is rich knowledge in expert systems that can be used to solve practical problems, but its promotion and application must rely on information facilities. The application of both computers and the Internet for Chinese farmers are not common, which leads to restrictions on the promotion and application of expert systems in rural areas of China. On the other hand, the existing call centers lack a professional knowledge base and the method of automatically calling the knowledge base in real-time, which makes it difficult to meet the needs of users wanting to obtain knowledge in a timely manner. To address these problems, a call center embedded in an expert system inference algorithm and knowledge base for farmers to obtain agricultural knowledge through mobile phones or fixed-line telephones was established. By studying the event-condition-action-based (ECA-based) database triggering model, remote method invocation-based (RMI-based) communication and iterative dichotomiser 3 algorithm-based (ID3-based) parameter extraction, the cohesion between the call center and the expert system was realized. The agricultural knowledge audio acquisition model was then coupled with the call center and the expert system was constructed, allowing farmers to acquire agricultural knowledge through mobile phones or fixed phones with fast responses. When used for cotton disease diagnosis, it can achieve a high diagnostic success rate (above 75%) when at least three disease symptoms are input into the expert system via the voice call, which provides an effective channel for Chinese farmers to obtain agricultural knowledge. It presents good application prospects in China, where 5G technology is currently developing rapidly.

In this study, a cotton disease diagnosis method that uses a combined algorithm of case-based reasoning (CBR) and fuzzy logic was designed and implemented. It focuses on the prevention, diagnosis and control of diseases affecting cotton production in China. Conventional methods of disease diagnosis are primarily based on CBR with reference to user-provided symptoms; however, in most cases, user-provided symptoms do not fully meet the requirements of CBR. To address this problem, fuzzy logic is incorporated into CBR to allow for more flexible and accurate models. With the help of CBR and fuzzy reasoning, three diagnostic results can be obtained by the cotton disease diagnosis system (CDDS) constructed in this study: success, success but not exact and failure. To verify the reliability of the CDDS and its ability to diagnose cotton diseases, its diagnostic accuracy and stability were analyzed and compared with the results obtained by the traditional expert scoring method. The analysis results reveal that the CDDS can achieve a high diagnostic success rate (above 90%) and better diagnostic stability than the traditional expert scoring method when at least four disease symptoms are input. The CDDS provides an independent and objective source of information to assist farmers in the diagnosis and prevention of cotton diseases.

Leafy vegetables are consumed in most daily xdiets worldwide. As living standards improve, food quality, safety requirements, and nutrition are becoming increasingly important to consumers when purchasing leafy vegetables. This study proposes an evaluation and traceability method that can be used to track the nutritional quality of leafy vegetables. Employing the principles of the Hazard Analysis and Critical Control Point (HACCP) system combined with fault tree analysis (FTA), a traceability model for the entire production and sale process of leafy vegetables is constructed. Four common leafy vegetables, spinach, rape, lettuce, and celery are examined in this research to establish a nutritional quality index system using fuzzy mathematics subordinate function method to evaluate nutritional quality. A nutritional quality and safety traceability system based on browser/server architecture and quick response (QR) code is then designed and developed for full traceability of leafy vegetable quality. This method can ensure food safety and hygiene through the control of key factors affecting food safety throughout the entire supply chain process.

Against the background of the depletion of fossil fuel energy sources and environmental degradation, solar greenhouses represent an efficient and sustainable agricultural production method in China. The precise measurement and control of the position of the rolling shutter and rolling film is not only one of the core issues in the modification of the greenhouse environment in actual production but also the basis for improving the cleaner production efficiency of solar greenhouses. In this study, a mathematical algorithm for the control of a rolling shutter and rolling film was developed and is based on the simplification of the circular arc of the greenhouse surface. The “Liaoshen-IV” solar greenhouse was used as an example to illustrate the calculation steps of the algorithm. Any position on the light surface can be determined by calculating the angle at the bottom of the back wall of the greenhouse so that the position of the rolling shutter and the rolling film can be measured accurately by the angle sensor. Experiments using a scale model with one or two surface segments were conducted to demonstrate the advantages of the control algorithm with regard to the accuracy and stability compared with the existing control method of a time-delay relay. The relative errors of the control algorithm were stable and less than 1%. The use of the algorithm improved the control accuracy of the rolling shutter and rolling film and the average relative error was reduced by 6.37% in the first stage and by 3.40% in the second stage compared with the time-delay relay. The precise measurement and control of the position of the rolling shutter and rolling film in a solar greenhouse demonstrated in this study has great significance for practical applications. The proposed method may result in a reduction in energy consumption and greenhouse gas (GHG) emissions in greenhouse environments, thereby contributing to the improvement of resource efficiency and a cleaner production. The study also provides application examples and theoretical references for the automation of rolling shutters and rolling film in greenhouses worldwide.

Purpose The selection of marketing channels by vegetable producers directly affects the income of producers and is important for the maintenance of a stable supply of vegetables and food control. The purpose of this paper is threefold: to investigate the cooperative selection of vegetable marketing channels; to identify the factors that influence the selection of marketing channels by professional vegetable cooperatives by comparing emerging and traditional circulation modes; and to solve the problems related to vegetable circulation channels in Beijing. Design/methodology/approach A total of 187 valid questionnaires were collected from seven main vegetable production districts in Beijing urban areas from September to December 2017, with a response rate of 89 percent. Binary logistic regression was used for analysis in this study. Findings Results revealed that the cooperatives mainly selected large wholesalers, wholesale markets, supermarkets and electronic commerce as their marketing channels for their vegetables. Estimation results showed that among the 18 influencing factors in the four categories, the educational level of the person in charge and some other factors significantly influence the selection of these four distribution channels by the cooperatives. Research limitations/implications Due to the lack of time and energy, this paper does not analyze the factors influencing a cooperative’s choice of different e-commerce platforms. If this problem can be solved, it will definitely promote the development of e-commerce in rural areas. Originality/value The results obtained in the present study and their implications could help policy makers establish a science-based and reasonable policy to encourage vegetable producers to participate in the new circulation modes of vegetables in Beijing and ensure their income in the vegetable supply chain. This study suggests methods to improve the vegetable sector in other cities facing similar issues.

The purpose aims to examine the key factors influencing Chinese consumer’s purchasing behaviour of eco‐friendly food in China giving its context as an emerging economy and its rapidly rising importance in the world eco‐friendly food market. This paper adopts and extends the Responsible Environmental Behaviour (REB) theory by empirically testing key psychosocial factors influencing the purchase intention of eco‐friendly food and the moderating effects of consumers’ demographic characteristics on the relationship between the key psychosocial factors and the purchase intention. A number of hypotheses are proposed. A questionnaire was designed and distributed via online survey in Beijing, China. A total of 239 valid responses were received. The empirical data were used to test the research hypotheses using the hierarchical multiple regression analysis. The research finds that the personality factors in the REB model (i.e., pro‐environmental attitudes, the internal locus of control and personal responsibly) have significant positive effects on the consumers’ eco‐friendly food purchase intention. Such effect is stable across consumers with different income levels. On the other hand, the knowledge–skill factors in the REB model do not have significant effect on the purchase intention of consumers. This study contributes to a better understanding of factors affecting eco‐friendly food consumption intention in China and the behavioural characteristics of consumers in developing countries. Moreover, the findings also shed light on the applicability of the REB theory in emerging economies and a specific industrial context.

Automatic visual inspection (AVI) is a popular tool for object detection and analysis in many fields. In fisheries, AVI systems designed for fish egg development analysis are used for fish egg assessments in commercial and experimental fish production systems and in ecological monitoring. The first step in AVI systems is to subdivide an image into meaningful regions. The accuracy of this segmentation directly influences the success of subsequent image analysis operations such as feature selection and classification. At present, a lot of image segmentation techniques are available, but there is no universal segmentation technique suitable for all kinds of images.This paper presents a cascading automatic segmentation method for microscopic digitised images of live common carp (Cyprinuscarpio) eggs in Petri dishes filled with water. The proposed method involves five main steps:1) image pre-processing, 2) image initial segmentation by Otsu’s method, 3) segmentation post-processing based on morphological operations, 4) image edge detection and morphological operations to remove incomplete eggs, and finally 5) a Watershed method was used to resolve the problem of separating adjoining fish eggs. Testing the method in Matlab software verified that fish eggs were recognized, segmented and counted with 100% accuracy compared to manual observation in all 96 test cases.

Water scarcity has threatened the food security and been a critical concern in China. Promoting modern agricultural irrigation technologies has been identified as an important measure against water scarcity. The overall goal of this study was to analyze the adoption of water-saving irrigation technology by farmers and to identify the major influencing factors of this decision for metropolis suburbs. Based on a field survey of Beijing of China, the results showed that 53.1% of farmers adopted water-saving irrigation technologies to cope with water scarcity, most of which adopted engineering water-saving technologies. The number of adopted water-saving irrigation technologies followed a strong negative correlation with the share of adopters. Econometric analysis revealed that education, farm size, on-farm demonstration, cooperative, training, groundwater, access to information, water use associations, drought-prone area, neighboring farmers, and policy subsidies significantly improved the adaption to water scarcity. Age, production specialization, and cost posed a negative effect on famers’ adoption of water-saving irrigation technologies. These results and implications provide an understanding of farmers’ sustainable irrigation practices and offer an insight to influencing factors to frame improved strategies and policies that enable to cope with water scarcity of metropolis suburbs.

China is the largest producer and consumer of vegetables, its vegetable industry is playing an important role in the domestic agricultural sector and global vegetable export market. It is important to promote the long-term sustainable development of Chinese vegetable industry for food security and quality of people’s lives. To find out the intrinsic way to promote the development of Chinese vegetable industry, this paper analyzed the influencing factors of Chinese vegetable production by utilizing the LMDI method and demonstrated the spatial-temporal characteristics of vegetable production through application of the ArcGIS spatial autocorrelation analysis method. The results showed that the influencing factors of vegetable production were the cultivated land area, multiple cropping index, vegetable planting proportion and vegetable yield per hectare in China. The major driving factor had changed from vegetable planting proportion to vegetable yield per hectare. The influencing degrees of factors on vegetable production are different in different regions, regionalization is therefore a major feature of Chinese vegetable production. The government should take production technology, regionalization-driven effect, and marketing integration into consideration to promote the development of Chinese vegetable industry. Keywords: Vegetable production, Influencing factors, Contribution ratio, Logarithmic mean Divisia index (LMDI)

Safe food is healthy, nutritious and environmentally friendly by green, sustainable and clean production. The objectives of this study were to examine factors influencing the consumers' purchase intention and willingness to pay a premium price for safe vegetables. To achieve the objectives, this paper developed the model of consumers' purchase safe vegetables. Based on 840 valid questionnaires from Beijing of China, the model was confirmed by the logistic regression method. The results showed that food safety, strict production and processing, and healthy environment were the top three perceived advantages of safe vegetables for consumers. In addition, 93.0% and 87.1% of consumers were familiar with organic vegetables and green vegetables, respectively. Two-thirds of consumers identified safe vegetables via certification labels on vegetable packages. Furthermore, 67.6% of consumers were willing to buy safe vegetables and 65.8% would pay a premium price for safe vegetables. Meanwhile, consumers' purchase intentions for safe vegetables were positively affected by family food expenditure, children, familiarity, differential cognition, safety awareness, nutritional health, packaging, label trust, and online shopping experience but price level, safety status, and freshness had a negative effect. Consumers’ willingness to pay a premium price for safe vegetables was positively affected by family income, familiarity, differential cognition, safety awareness, nutritional health, packaging, label trust, and online shopping experience but family food expenditure, price level, price fluctuations, and safety status had a negative effect. The findings of this study have important implications to improve the consumption and guide cleaner production of safe vegetables. The findings obtained can also provide references for other similar studies in other areas.

Village rules and formal environmental regulations are of great significance for standardizing farmers’ cleaner production behavior, promoting green transformation of agriculture and realizing sustainable development of agriculture. Based on the survey data of 946 farmers in five provinces of China, taking seed coating technology, soil testing and formulated fertilization technology, subsoiling tillage technology, green technology for pest and disease control and straw returning technology as examples, this article empirically analyzes the impact of village rules and formal environmental regulations on farmers’ cleaner production behavior by using the multivariate probit model. When formal environmental regulations are relatively lacking or weak, village rules can be used as a useful supplement to formal environmental regulations to promote farmers’ participation in cleaner production. Based on this, this article argues that the important reason for formal environmental regulations falling into relative system failure is that village rules have not been paid enough attention in promoting farmers’ cleaner production behavior. In the future, we should not only continue to strengthen the role of formal environmental regulations in farmers’ cleaner production, but also cultivate the informal institution represented by the village rules, and build the regulatory system of mutual support between informal institution and formal institution.

Freshwater aquaculture is the main form of aquaculture in inland areas, and pollution is a significant challenge. The aim of this work was to propose an effective risk assessment method for aquaculture to predict pollutant bioaccumulation in fish tissue based on water environment variables. This method was designed to assess the risk of pollutant levels in fish tissue that exceed China’s food safety standards. Firstly, field observation and investigation were conducted to analyze the migration mechanisms of the main pollutants between fish tissue and the water environment. Secondly, a classification and regression tree (CART) and generalized additive model (GAM) nexus method was used to analyze the environmental variables related to pollutants in the water environment and establish prediction models. Finally, models of the bio-reaction kinetics were established to predict the pollutant bioaccumulation in fish tissue. The experimental results indicate that the GAM models could explain 73.7%, 84.4%, and 84.5% of the deviations for the three predicted pollutants. For 90% of the sample data, the accuracy of the bioaccumulation prediction was 93.44% for volatile phenol bioaccumulation, and 90.16% for Cu and coliform bioaccumulation. The proposed risk assessment method could be extended for aquaculture applications that require monitoring of additional parameters to safeguard aquaculture quality and facilitate effective safety risk management.

Improving the extraction of cucumber leaf spot disease under complex backgrounds.Redefining the feature distance between pixel xj and clustering center vi.Calculating the two-dimensional neighborhood mean gray value as a sample point.Proposing a new weighting method for gray value and neighborhood gray value. Research reported in this paper aims to improve the extraction of cucumber leaf spot disease under complex backgrounds. An improved fuzzy C-means (FCM) algorithm is proposed in this paper. First, three runs of the marked-watershed algorithm, based on HSI space, are applied to isolate the target leaf. Second, the distance between the pixel xj and the cluster center vi is defined as xj2-vi2. Third, the pixel's neighborhood mean gray value, which constitutes a two-dimensional vector with grayscale information, is calculated as a sample point, rather than FCM grayscale. Finally, the neighborhood mean gray value and pixel gray value are weighted by matrix w. To evaluate the robustness and accuracy of the proposed segmentation method, tests were conducted for 129 cucumber disease images in vegetable disease database. Results show that average segmentation error was only 0.12%. The proposed method provides an effective and robust segmentation means for sorting and grading apples in cucumber disease diagnosis, and it can be easily adapted for other imaging-based agricultural applications.

China is the world's largest energy consumer and is also leading in the solar photovoltaic industry. The solar energy industry, with advantageous clean and highly efficient production, is integral in maintaining the sustainable energy supply in an environmentally sensitive manner. Further development of the Chinese photovoltaic industry requires a status assessment for the current industrial setting. An analysis on the 58 Chinese photovoltaic listed enterprises is conducted in this study to analyze the operating performance, industry agglomeration and spatial characteristics of Chinese photovoltaic industry. Comprehensive analysis and evaluation of the enterprises’ operating performance are based on financial data by utilizing the Data Envelopment Analysis (DEA) method; Systematic analysis examines spatial characteristics through the application of the spatial autocorrelation analysis method. Results confirm the Chinese photovoltaic industry preliminarily appeared industry agglomeration with enterprises mainly distributed in east and north China, and gathered in developed coastal provinces. Superior performing photovoltaic enterprises are specifically located in north China. Most of the enterprises are in the up-stream or mid-stream of the photovoltaic industrial chain. Overall operating performance of the photovoltaic industry in China suffers from weak profits due to low technical efficiency. The key to improve the future development of these enterprises is the improvement of operating performance by strengthening technical efficiencies. Concurrently, governmental guidance should address profitable photovoltaic industry investments and improvement of production rates.

Wireless Sensor Network (WSN) is applied widely in food cold chain logistics. However, traditional monitoring systems require significant real-time sensor data transmission which will result in heavy data traffic and communication systems overloading, and thus reduce the data collection and transmission efficiency. This research aims to develop a temperature Monitoring System for Frozen and Chilled Aquatic Products (MS-FCAP) based on WSN integrated with Compressed Sending (CS) to improve the efficiency of MS-FCAP. Through understanding the temperature and related information requirements of frozen and chilled aquatic products cold chain logistics, this paper illustrates the design of the CS model which consists of sparse sampling and data reconstruction, and shelf-life prediction. The system was implemented and evaluated in cold chain logistics between Hainan and Beijing in China. The evaluation result suggests that MS-FCAP has a high accuracy in reconstructing temperature data under variable temperature condition as well as under constant temperature condition. The result shows that MS-FCAP is capable of recovering the sampled sensor data accurately and efficiently, reflecting the real-time temperature change in the refrigerated truck during cold chain logistics, and providing effective decision support traceability for quality and safety assurance of frozen and chilled aquatic products.

With continuous rise of table grapes consumption and increased public awareness of food safety, the quality control of grapes in storage after purchase is not sufficiently examined. Home storage constitutes the last and important stage in grape supply chain. Literature review shows that few researches on grape quality focus on the home storage stage compared with numerous researches reported on the quality control during postharvest and transportation process. This paper reports the performance evaluation of grape quality at home storage and consumers’ satisfaction using integrated sensory evaluations. The internal attributes, including Texture, Taste and Odor of the table grapes and the appearance indices, Color and Cleanliness are examined. Key results show that during home storage, all the internal attributes decrease rapidly as time goes on, and cleanliness and color appear to be deteriorating in a lower speed. A comprehensive quality index was created to measure the quality of table grape which has high correlation with the Overall acceptability perceived by consumers.

A new method for extracting key frames of greenhouse videos was proposed.The method took full considerations of characteristics of greenhouse videos.The method combined the visual saliency and online clustering.The IG algorithm was modified by two parameters confirmed by a new measurement. Research reported in this paper aims to improve the identification of greenhouse vegetable diseases based on the greenhouse monitoring video. It presents a method that combines the visual saliency and online clustering to extract the key frame from greenhouse vegetables monitoring video. Firstly X2 histograms are used to measure the similarity of each frame to the first frame, which eliminates the meaningless frames and improve data processing efficiency and costs. Then, all frames will be converted to HSV color space and a saliency map of each frame is generated based on H component value and S component value. According to the saliency map, the salient region can be obtained. During the process of extracting the salient region, there is a possibility that the information of disease spots is lost. Therefore, morphological method would be utilized to restore the lost information. Finally, online clustering is performed to classify the salient regions into different clusters, and mean pixels value is used to select the key frames. The results indicate that this method can obtain information of entire leaf area of vegetables and extract the key frame effectively.

BACKGROUND The main export varieties in China are brand-name, high-quality bred aquatic products. Among them, tilapia has become the most important and fast-growing species since extensive consumer markets in North America and Europe have evolved as a result of commodity prices, year-round availability and quality of fresh and frozen products. As the largest tilapia farming country, China has over one-third of its tilapia production devoted to further processing and meeting foreign market demand. RESULTS Using by tilapia fillet processing, this paper introduces the efforts for developing and evaluating ITS-TF: an intelligent traceability system integrated with statistical process control (SPC) and fault tree analysis (FTA). Observations, literature review and expert questionnaires were used for system requirement and knowledge acquisition; scenario simulation was applied to evaluate and validate ITS-TF performance. CONCLUSION The results show that traceability requirement is evolved from a firefighting model to a proactive model for enhancing process management capacity for food safety; ITS-TF transforms itself as an intelligent system to provide functions on early warnings and process management by integrated SPC and FTA. The valuable suggestion that automatic data acquisition and communication technology should be integrated into ITS-TF was achieved for further system optimization, perfection and performance improvement. © 2014 Society of Chemical Industry

Implementation of food traceability systems in China faces many challenges due to the scale, diversity, and complexity of China's food supply chains. This study aims to identify critical success factors specific to the implementation of traceability systems in China. Twenty-seven critical success factors were identified in the literature. Interviews with managers at four food enterprises in a prestudy helped identify success criteria and five additional critical success factors. These critical success factors were tested through a survey of managers in 83 food companies. This study identifies six dimensions for critical success factors: laws, regulations, and standards; government support; consumer knowledge and support; effective management and communication; top management, company wide, and vendor support; and information and system quality.

Cold chain is one of the most important ways to guarantee the quality and safety of table grapes. It is necessary to monitoring the temperature in the whole cold chain process to keep the constant temperature and guarantee the quality and safety of table grapes in cold chain. This paper aims to develop a battery-free wireless sensor system with compressed sensing for the table grapes cold chain. The battery-free wireless sensor system was realized by using the ultra high frequency radio frequency identification (UHF RFID) on-chip temperature sensor with no battery. The temperature fluctuation performance of the table grapes in the cold chain, the compressed sensing (CS) performance of the temperature reconstructed error with the original data and the battery-free wireless sensor system with compressed sensing evaluation were comprehensively analyzed and discuss. The developed battery-free wireless sensor system with compressed sensing could effectively monitor the actual temperature with high reconstruction accuracy to save the data storage space, transmission and operation resources, improve the temperature transparency in cold chain, and finally ensure the quality and safety of table grapes. The developed battery-free wireless sensor system with compressed sensing could be extended for other cold chain applications to improve their transparency and transmission efficiency of the wireless monitoring. It is also possible to integrate the relative humidity, gas sensors into the battery-free wireless sensor system to monitor more environment parameters in cold chain.

The paper presents a method that addresses the problem of using catastrophe theory to evaluate the informatization level in four Chinese regions. We developed an index evaluation system that consists of five categories (secondary indices) of Economic strength, Information infrastructure, Information terminal equipment, Human resources and Information utilization, and fourteen tertiary indices as the evaluation index system for the rural informatization level. The effectiveness of this method is tested by evaluating the level of information technology application in four Chinese rural regions (eastern, central, western, and northeastern regions). The results show that the catastrophe progression values (CPV) averaged at 0.806 in mainland China. The CPV for the eastern region is ranked the highest at 0.871, the northeast region second at 0.841, the central region third at 0.553, and the western region the lowest at 0.213. The results are found to be consistent with a priori expectations proving that the catastrophe progression method works well.

This paper theoretically analyzes the quality changes of aquatic products by the temperature environments according to the types of temperature fluctuations. First the temperature fluctuation is divided into three types of temperature environments for discussion during the transportation in the aquatic cold chain, by which the temperature model is put forward for each type. And then quality evaluation models are established respectively for the three temperature fluctuating environments. Finally, experiments are given, which show the effectiveness of the models.

Purpose – Table grape is one of the most important horticultural crops in China. However, quality and safety have become major constraints for the further development of the Chinese table grape industry, which is dominated by small‐scale vinegrowers. Strategic partnership has been regarded as an effective mechanism to manage the supply chain. The purpose of this paper is to examine the impact of a supply chain model based on different strategic partnerships on the effect of safety and quality control and small‐scale vinegrowers' performance.Design/methodology/approach – The field survey was performed in seven representative districts in China, including Inner Mongolia, Gansu, Tianjin, Liaoning, Shandong, Jiangsu and Zhejiang Provinces. A semi‐structured interview was adopted as the data collection method. Both quantitative and qualitative data were generated and analyzed in this research. All quantitative analyses were conducted using EXCEL 2003 version and a comparative analysis was conducted to test the...

Extensive aquaculture has been used in Chinese aquaculture farms for a long time. Inefficient and high consumption are main shortcomings for this aquaculture type. This paper designed and implemented an aquatic parameters real-time monitoring and management system based on water quality sensors, wireless sensor network and information management technologies. The system can monitor water quality parameters in real-time and automatically (or manual) control aquaculture equipment according timing, threshold or mobile short message service. Also, according to different aquaculture objects, the system provides one-stop information services as aquaculture disease warning and diagnosis, bait feeding etc. The applications in eight different regions in China have proved the system can effectively improve the intensive aquaculture informatization level and realized the whole process of aquaculture information management.

The learner’s acceptance of e-learning systems has received extensive attention in prior studies, but how their experience of using e-learning systems impacts on their behavioural intention to reuse those systems has attracted limited research. As the applications of e-learning are still gaining momentum in developing countries, such as China, it is necessary to examine the relationships between e-learners’ experience and perceptions and their behavioural intention to reuse, because it is argued that system reuse is an important indicator of the system’s success. Therefore, a better understanding of the multiple factors affecting the e-learner’s intention to reuse could help e-learning system researchers and providers to develop more effective and acceptable e-learning systems. Underpinned by the information system success model, technology acceptance model and self-efficacy theory, a theoretical framework was developed to investigate the learner’s behavioural intention to reuse e-learning systems. A total of 280 e-learners were surveyed to validate the measurements and proposed research model. The results demonstrated that e-learning service quality, course quality, perceived usefulness, perceived ease of use and self-efficacy had direct effects on users’ behavioural intention to reuse. System functionality and system response have an indirect effect, but system interactivity had no significant effect. Furthermore, self-efficacy affected perceived ease of use that positively influenced perceived usefulness.

This paper presents a method to extract color and texture features of an image quickly for content-based image retrieval (CBIR). First, HSV color space is quantified rationally. Color histogram and texture features based on a co-occurrence matrix are extracted to form feature vectors. Then the characteristics of the global color histogram, local color histogram and texture features are compared and analyzed for CBIR. Based on these works, a CBIR system is designed using color and texture fused features by constructing weights of feature vectors. The relevant retrieval experiments show that the fused features retrieval brings better visual feeling than the single feature retrieval, which means better retrieval results.

With the largest population living in rural areas, the lack of clean energy supply is an important problem in China, and the utilization of renewable energy not only meets the demand of energy, but also provides a basis for environmental protection and sustainable development. This paper reviews use of clean energy in a resource-rich region, including the basic principle of the development of recycling agriculture, the potential, the present status and the future of renewable energy in the region rural areas. If the project will be finished, there will be 300,000 families benefiting from it and it can bring at least 2.2 × 108 US dollars revenue increase directly, the indirect revenue increase will be 0.15 billion US dollars, the environment will be improved and the living standard in Jincheng's rural areas is also be greatly improved because of developing biogas project. Based on the developing status and constraint conditions, the solutions to further promote renewable energy projects in this region are also proposed.

Swine-Vet is a kind of a web-based expert system for swine disease diagnosis and has been promoted in north of China past 3years. The few issues relevant with low diagnosis efficiency and error have arisen during the system test and promotion due to the limitation of previous adopted reasoning techniques and immaturity of diagnosis domain knowledge. This paper proposes a hybrid multimodal reasoning mechanism to resolve the swine intercurrent diseases and improve the system diagnosis efficiency. The framework consists of two modules: one is the forward diagnosing module, information fusion method based on evidence theory is used to solve the barriers of syndrome in swine diagnosis field, and the other is the backward confirming module, set pair analysis (SPA) is adopted to resolve evidence conflict and distinguish uncertain and unknown symptom information during the process of diagnosis. Then, in order to demonstrate this model, a case study is given. Finally, the benefits and challenges of the hybrid multimodal reasoning application in expert system are discussed.

Agricultural domestic support is a sensitive issue for all countries producing agricultural commodities. To simulate the dynamic influence of changes in agricultural subsidies on non-agricultural sectors, this paper improved the Indian Storm models by embedding the labor force module based on the new Austrian model. The simulation result showed that a steady increase in the rate of producers' subsidy had little effect on capital flows, non-agricultural sectors and the rate at which agricultural surplus labor force transfers to non-agricultural industries. The non-agricultural industry should benefit from an increase in the rate of producer subsidies, as total consumption expenditure by non-agricultural industry is reduced. Producer subsidies facilitate transfer of labor force from agriculture to the light manufactures sector the most, the fertilizer and service sectors second, and the heavy manufactures sector the least.

This paper, from innovation adoption perspective, investigates people's perceptions and attitudes toward adopting e-learning to explore the key factors affecting the e-learning adoption behavior in China. Based on Rogers' innovation adoption theory, 33 factors of perceived innovative attributes will be quantificationally analysed to test the relationship between the perceived innovative attributes and adoption intention of e-learning by an analytic hierarchy process (AHP). The result shows that some factors of perceived innovative attributes, such as cost, quality, agility, schedule control, certification of degree, personal demands and so on, have more influence on peoples' adoption of e-learning.

Traceability system can effectively trace food quality and reduce safety scares. Recent researches on traceability systems in China focus on technology innovation, traceability system management, and determinants of traceability system implementation. This paper proposes four criteria to analyze strengths and limitations of the operating mechanisms. The result shows the operating mechanism of traceability system in Chinese agribusiness can be classified into three categories and none of operating mechanism of traceability system completely meets the agribusiness traceability service requirement, and each of the three operating mechanisms has its own strengths and limitations. It is suggested that an integrated mechanism is needed to implement traceability system in agribusiness.

We estimated the risk posed by hydroxybenzene in farm-raised Crucian carps (Carassius carassius) from a pond on a fish farm in Beijing, China, by analyzing a time-series of observed hydroxybenzene concentrations in fish within a culturing season in year 2006. We used the basic linear regression to model the data and forecast the probability of hydroxybenzene concentration in pond fish exceeding selected health effect criteria (the risk) using Monte Carlo simulation. The risk is highly correlated with the time a fish stays in the pond. The results indicate that the risk–days in pond relationship resembles a sigmoid function with an inflection point around 150 days. The resulting model can be used to demonstrate the benefit of improving water quality in terms of increased fish production.

Consumers around the world increased consumption of fish and fish products in recent years due to recognition of their nutritional value. Frequent occurrences of food safety scares heightened public awareness causing significant reduction in the consumption of the affected products. Many countries, including China, implemented a traceability system to increase vertical coordination and guarantee safety in fish products. This paper aims to provide information on consumers’ awareness to quality and safety of fish products, purchasing behavior, and willingness to pay (WTP) for safe fish products in Beijing, China, based on a survey of consumers. The results show a shortage of safety knowledge among customers concerning fish products, including processing, storage, and the traceability system. The age of consumers, educational level, the perception safety and the average price, are the main determinants of Beijing consumer’s WTP for the traceable products. On average, consumers are willing to pay a 6% premium for safe, traceable fish products over the price of non-traced products of uncertain safety.

Expert systems (ESs) were introduced more than two decades ago, but their effectiveness and success are still in debate. This paper attempts to make a contribution to the better understanding of ES applications from a knowledge transfer perspective. This paper argues that an ES application is knowledge transfer that uses Information and Communication Technologies (ICT). Underpinned by knowledge transfer theories and through a series of empirical investigations of ES projects in agriculture, this study recognises the importance of human interactions in the ESs implementation process. Based on the evidence collected, a number of key players are examined. They are knowledge provider/sender, knowledge engineer, knowledge extensionist and knowledge recipient. This paper represents a first attempt to acknowledge the role of a knowledge extensionist in the ICT-based knowledge transfer process. The name ‘extensionist’ is borrowed from earlier literature and describes an actor whose role is an intermediary in supporting transferring knowledge towards the knowledge user. Findings demonstrate the significant contributions made by extensionists towards the success of ESs applications. It is argued that the rigidity and limitations of ESs in ICT-based knowledge transfer can be significantly reduced with the involvement of close human interactions with the knowledge recipient.

Fish disease is becoming the major factor damaging the sustainable development of aquaculture and the quality security of aquatic product in China. Many researchers provide assistances and advice in fish disease diagnosis and appropriate treatment measures. However, the risk of misdiagnosis, incorrectly treatment or over-treatment also exists due to carrying out after disease outbreaks. So it is necessary to develop an early warning system. Taking into account that fish disease outbreak is mainly caused by suboptimal water quality in north of China, the best way is to develop decision aids tool that can assess and early warning the risk of fish disease based on water quality management. This paper introduces a knowledge-based early warning system for fish disease via water quality management. The architecture, the process for knowledge engineering, main components and their functions, especially a series of water quality management mathematic models are described. At present, the system is in pilot in the city of Tianjin in China. The stage achievements in developing the intellectual system of fish disease early warning are summarized.

This paper reports research findings from a project funded by the European Commission. The research used case studies and surveys to identify gaps between Europe and China in the level of Internet adoption in fresh-produce supply chains. The project reveals barriers to Internet adoption in China in this industry, and employs a transnational knowledge transfer approach to reduce these barriers. In a wider context, the paper analyses the features involved in this knowledge transfer from a knowledge management perspective. Specifically, it outlines the main activities, key actors and the transfer stages involved. The insights gained help further our understanding of knowledge transfer in transnational contexts. The implications of these findings for academia, managers and policy makers are summarized.

This study examines perceptions and attitudes towards adoption of mobile commerce from an innovation adoption perspective. Six variables of a theoretical framework developed based on the TAM model are tested using a cross‐sectional survey in China's rural areas. The findings indicate that the six variables, perceived usefulness, perceived ease of use, personal innovativeness, compatibility, perceived reliability, cost, all significantly affect user attitude to adoption of m‐commerce. The study helps providers to gain valuable insights into the key factors influencing uptake and to offer more effective, relevant and successful m‐commerce products.