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The credit of agricultural product quality and safety reflects the ability of the main actors involved in the supply chain to provide reliable agricultural products to consumers. To fundamentally solve the problem of agricultural product quality and safety, it is worth studying how to make the credit awareness and integrity self-discipline of the supply chain agriculture-related subjects strengthened and the role and value of credit supervision given full play. Starting from the application of blockchain in the agricultural product supply chain, this paper aims to investigate the main factors affecting the credit regulation of agricultural product quality.

Using the DEMATEL-ISM (decision-making trial and evaluation laboratory–interpretative structural modeling) method, we analyze the credit influencing factors of agricultural quality and safety empowered by blockchain technology, find the causal relationship between the crucial influencing factors and deeply explore the hierarchical transmission relationship between the influencing factors. Then, the path analysis in structural equation modeling is utilized to verify and measure the significance and effect value of the transmission relationship among the crucial influencing factors of credit regulation.

The results show that the quality and safety credit regulation of agricultural products is influenced by a combination of direct and deep influencing factors. Long-term stable cooperative relationship, Quality and safety credit evaluation, Supply chain risk control ability, Quality and safety testing, Constraints of the smart contract are the main influence path of blockchain embedded in agricultural product supply chain quality and safety credit supervision.

Credit supervision is an important means to improve the ability and level of social governance and standardize the market order. From the perspective of blockchain embedded in the agricultural supply chain, the regulatory body is transformed from the product body to the supply chain body. Take the credit supervision of supply chain subjects as the basis of agricultural product quality supervision. With the help of blockchain technology to improve the effectiveness of agricultural product quality and safety credit supervision, credit supervision is used to constrain and incentivize the behavior of agricultural subjects.

The purpose of this study is to evaluate food supply chain stakeholders’ intention to use Industry 5.0 (I5.0) drones for cleaner production in food supply chains.

The authors used a quantitative research design and collected data using an online survey administered to a sample of 264 food supply chain stakeholders in Nigeria. The partial least square structural equation model was conducted to assess the research’s hypothesised relationships.

The authors provide empirical evidence to support the contributions of I5.0 drones for cleaner production. The findings showed that food supply chain stakeholders are more concerned with the use of I5.0 drones in specific operations, such as reducing plant diseases, which invariably enhances cleaner production. However, there is less inclination to drone adoption if the aim was pollution reduction, predicting seasonal output and addressing workers’ health and safety challenges. The findings outline the need for awareness to promote the use of drones for addressing workers’ hazard challenges and knowledge transfer on the potentials of I5.0 in emerging economies.

To the best of the authors’ knowledge, this study is the first to address I5.0 drones’ adoption using a sustainability model. The authors contribute to existing literature by extending the sustainability model to identify the contributions of drone use in promoting cleaner production through addressing specific system operations. This study addresses the gap by augmenting a sustainability model, suggesting that technology adoption for sustainability is motivated by curbing challenges categorised as drivers and mediators.

Pesticide residue is a stubborn problem affecting the quality and safety of agricultural products in China, and has not yet been fundamentally resolved. The purpose of this paper is to study farmers' perception of pesticide residues, as well as the main factors affecting their perception from the viewpoint of farmers. Additionally, this research attempts to explore the basic characteristics of pesticide residues arising in the process of producing agricultural products under the prevailing policy background, so as to provide decision‐making references for the Chinese government to deepen the security management system of agricultural products.

The structural equation model (SEM) is an analytical tool for the observation and treatment of latent variables that are difficult to observe directly, and for the consideration of inevitable errors. This paper investigates the main factors affecting farmers' perception of pesticide residues in the investigated regions based on the SEM and samples of 241 farmers in six counties (cities and regions) of three districts in the Jiangsu Province of China.

According to the research, regional difference, farmers' gender, age, years of education, pesticide training and their own demand for safe agricultural products had different influences on their perception of pesticide residues. Additionally, it was difficult to measure the influence of family characteristics on farmers' perception of pesticide residues. Although the present paper only shows a preliminary study, its conclusion provides a reference value for the Chinese government to deepen the reform of the quality and safety regulatory system of agricultural products.

There are many similar studies in overseas countries, but the application of SEM in the study of the main factors affecting farmers' perception of pesticide residues has not been completely reported previously in domestic literatures. The research assumption of this paper has practically verified that corresponding research conclusions of foreign scholars in this field have universality in China.

The quantitative understanding of the safe input management practices of vegetable producers is essential for both food safety and environmental protection. The purpose of this study is to investigate the current status of safe production in vegetable enterprises and examine the key risk factors affecting the safe production of vegetables from the perspective of agricultural inputs.

Based on the theory of risk analysis, a framework of safe vegetable production risk analysis is constructed from the perspective of production input behaviour. Based on 202 valid questionnaires in Beijing, China, this paper identifies direct risks in input management through statistical descriptive analysis; determines weights through an expert elicitation process and calculates weighted safety values accordingly; and finally uses a categorical regression model to explore the indirect risks affecting corporate safety production.

The results show that direct risk factors include seed treatment risk, pesticide and fertilizer use criteria risk, pesticide and fertilizer operation risk, and pesticide application object risk. The production safety value of Beijing's enterprises is found to be high in the north and south regions, and low in the central region. Finally, some indirect risk factors, namely the cognition of agricultural product safety laws, the cognition of pesticide safety intervals, the cognition of prohibited pesticides and the possession of brands, are found to have positive and significant impacts on the safe production behaviour of enterprises.

These findings provide entry points for interventions aimed at reducing dependence on pesticides and fertilizers and promoting input management for safe vegetable production in enterprises, thus avoiding vegetable safety incidents due to improper practices in the production chain.

An Act to make further provision for securing the health, safety and welfare of persons at work, for protecting others against risks to health or safety in connection with the activities of persons at work, for controlling the keeping and use and preventing the unlawful acquisition, possession and use of dangerous substances, and for controlling certain emissions into the atmosphere; to make further provision with respect to the employment medical advisory service; to amend the law relating to building regulations, and the Building (Scotland) Act 1959; and for connected purposes. [31st July 1974]

Due to consumption changes in the post-pandemic era, the production safety of agricultural products is affecting global consumers. This paper constructs an evaluation index of the agricultural Internet of things (IOT) traceability system and evaluates it using the dynamic hesitant-fuzzy linguistic term sets (HFLTS)-based DEMATEL method to improve agricultural supply-chain links and improve production quality.

The agricultural IOT traceability index system is constructed using the literature and expert interviews; it comprises 6 first-level indices and 20 second-level indices. The agricultural IOT traceability system is evaluated using the dynamic HFLTS-DEMATEL method.

Producers' awareness of agricultural-production safety (A11) has the most significant impact on production and processing links, while warehouse location and storage capacity (A31) have the largest impact on the circulation link. Inspection authenticity and transparency and quarantine information (A41) have the largest impact on the detection-consumption link. The extent to which the traceability-platform construction is complete (A62) has the largest impact on technical support.

The present paper may be limited to the era of post-pandemic, and it is hard to consider all the indices. Further research can broaden the research context and establish a more comprehensive index system.

The index system constructed in this study will surely help relevant regulatory authorities in China to promote the construction of agricultural IOT traceability system and establish a unified standard, so as to provide a basis for future developers to enter the field. Accordingly, it also can help every subject to identify the key indices of each process in the agricultural-product supply chain and guide relevant departments to conduct targeted information tracking and management. The consumers could also understand the standards of traceable agricultural products and effectively protect their own rights and interests.

The existing literature does not provide an objective, unified standard for measuring a decentralized traceability system or identifying key processes. This study therefore proposes a new evaluation index system and uses a dynamic evaluation method to determine the importance of key indices. This study identifies the most important indices in each process, making it possible to discover, improve, and enhance the quality of agricultural products at a practical level.

The purpose of this paper is to analyse the effects of member size and external incentives (food safety certification and target market) on cooperative’s product quality, using data collected from 135 apple producing cooperatives in China.

Given that different indicator variables were used to measure apple quality, the authors employed a principle component analysis method to reduce the measurement dimension. An ordinary least square regression was employed to analyse the effects of member size and selective incentives of agricultural cooperatives on product quality.

The empirical results show that member size and cooperative’s product quality bear an inverse “U-shape” relationship, and food safety certification and target market variables tend to positively and significantly influence cooperative’s product quality. In particular, the cooperatives with more food safety certificates and targeting supermarkets and export enterprises are more likely to supply high-quality products.

This study provides the first attempt to measure apple quality and investigate the factors that influence cooperative’s product quality.

The Equal Pay Act 1970 (which came into operation on 29 December 1975) provides for an “equality clause” to be written into all contracts of employment. S.1(2) (a) of the 1970 Act (which has been amended by the Sex Discrimination Act 1975) provides:

The purpose of this paper is to quantify the benefits of contract farming (CF) on farmers’ income and adoption of food safety measures (FSMs) at the farm level. The paper also investigates the determinants of participation in CF.

The study is based on a survey of 600 tomato farmers from Nepal. Descriptive statistics, regression analysis (using instrumental variable) and propensity score matching have been used to accomplish the objectives of the study.

The study found that the CF ensures higher returns to farmers as well as higher adoption of FSMs at the farm level. The contract farmers earned about 38 per cent higher net returns and had 38 per cent higher adoption of FSM as compared to independent farmers. Caste, occupation, farm size and cropping intensity significantly affected farmers’ participation in CF.

The analysis based on cross-section data has limitations to consider unobserved farmer-level individual heterogeneity.

This study will provide an empirical base to promote CF in Nepal. The study will also contribute to bridge the gap in literature on the drivers of CF and its impact on smallholders’ income and compliance with FSM in Nepal.