Aflatoxin is one of the high-risk contaminants in the processing of peanut oil. Its contamination has pervaded the entire industrial chain, including the peanut cultivation, procurement, storage, transportation, and processing at present. There is a grave threat to the health of consumers in the sustainable industry. It is of great significance to systematically control aflatoxin in industrial development for food safety. Therefore, a three-dimensional prevention and control framework of the “source-process-removal at the processing end” has been established for the control of the aflatoxin in peanut oil. This article aims to systematically review the application technologies for the control of aflatoxin in the entire industrial chain of peanut oil processing. The key aspects were also covered, including the aflatoxin prevention and control at the source of peanuts, the control of aflatoxin during procurement, storage, and transportation of the peanuts, and the removal of the aflatoxin in the processing of peanut oil. At the source of peanut growth, the Aspergillus flavus and Rhizobia Coupling (ARC) microbial agents were achieved in the green prevention and control of aflatoxin at the source. The prevention and control of the aflatoxin at the source was also carried out in the breeding of the ARC microbial agents and the peanut varieties resistant to aflatoxin. Meanwhile, the efficient nodulation and nitrogen fixation of peanuts were induced to significantly promote the yield. That is, the coupling role was observed to prevent and control the contamination of Aspergillus flavus and its toxins. In peanut cultivation, the self-built bases or the order-based planting model were used to realize the quality control of the peanut raw materials. Professional and standardized planting and fertilization were also adopted using advanced equipment and facilities. The origin examination, sample testing, and inspection were carried out during the procurement, storage, and transportation of the peanuts. According to the temperature variation in the storage and transportation of the peanuts, the storage parameters were optimized to reduce the risk of aflatoxin contamination. Furthermore, the vibratory screening and color sorting were carried out on the peanut oil. A vibratory sieve with physical screening and a color sorter was applied to remove the contaminated peanuts in the pre-treatment stage during processing. The deep removal of the aflatoxin was also realized, according to the combination of multiple technologies, such as ultraviolet degradation, physical adsorption, and alkali refining. Among them, the ultraviolet irradiation and physical adsorption were suitable for the control of the aflatoxin in the pressed peanut oil. While the alkali refining was suitable for the control of aflatoxin in the refined peanut oil. Some challenges still remain in the control of aflatoxin in peanut oil at present, such as the insufficient stability of the source prevention and control, as well as the online lagging detection. As such, it is necessary to promote source biocontrol technologies in the future; Artificial intelligence detection can be expected to intensify the real-time and accurate online monitoring equipment for the aflatoxin content. The data resources of each link can be integrated into the entire industrial chain. A multi-dimensional coordinated prevention and control system can also be constructed for the quality and safety of edible oil products.

Aflatoxins are the secondary metabolites that are predominantly produced by fungi, such as Aspergillus flavus and Aspergillus parasiticus under natural conditions. As the most toxic and carcinogenic mycotoxins up to now, the aflatoxins can contaminate over 110 types of agricultural foods and foods, such as peanuts, corn, rice, and nuts. The aflatoxins have posed significant threats to global grain security, food safety, and human health. This review aims to outline the research status and prospect of aflatoxins detection, prevention, and control in agricultural products and food. Firstly, a concise overview was performed on the classification and toxicity of aflatoxins. Then a systematic summary was presented of the recent advances in the detection and control technologies of aflatoxin contamination. Finally, the potential applications of aflatoxin contamination were proposed for the smart monitoring and prevention or mitigation strategies from the source. Conventional technologies with large instruments and equipment were widely used in aflatoxins detection, including high-performance liquid chromatography (HPLC), and liquid chromatography-mass spectrometry (LC-MS), due to their high accuracy and reliability in the laboratory. Meanwhile, the emerging techniques of aflatoxin detection offered high sensitivity, simplicity, and portability, such as immunochromatographic test strips, immuno-fluorescence techniques, and nanomaterial-enhanced biosensors. The main tools were then served for many kinds of fields, such as harvest, transport, and process. Particularly, they were also valuable for the large-scale screening and real-time monitoring in the on-site test, due to the cost and time saving. In the aflatoxin contamination prevention and control, integrated approaches were often required for the planting, harvest, storage, and transportation. At the pre-harvest stage, the breeding strategy was applied for the disease resistance in the crop varieties for the functional microbial inoculants. The agronomic practices were then optimized to inhibit Aspergillus flavus colonization and aflatoxins production. Post-harvest interventions were also proposed to prevent and control aflatoxin contamination, such as the physical (e.g., proper drying and storage, γ-ray irradiation, high pressure, and adsorption removal), the chemical (e.g., ozone treatment, strong oxidant, alkali treatment), and the biologicals (e.g., microbial adsorption, microbial detoxification and enzymic degradation). Among them, the biological approaches gained much more attention, especially for the functional microbial inoculants control from source, due to the high efficiency, environmental compatibility, and sustainability to decrease the toxic fungi from source, such as Aspergillus flavus and Aspergillus parasiticus. Research development direction and trend were also fully considered over the various techniques. The future research interests were also focused on integrating intelligent detection and early warning technologies with source prevention and control strategies. Smart monitoring and early warning technologies (e.g., highly sensitive sensors with the internet of things, artificial intelligence-driven early warning of aflatoxins contamination) and source control technology (e.g., the bio-coupling technology between aflatoxins prevention and inducing peanut and soybean nitrogen fixation for quality improvement and yield increase) can be expected to achieve a more precise, efficient, and sustainable aflatoxins control, prevention, and management. Interdisciplinary collaboration in microbiology, soil environment science, chemistry, and food can be essential to drive innovation in aflatoxins detection and prevention. These advancements can also provide key technical support for agricultural products and food safety in sustainable agricultural industries.

Aspergillus species are ubiquitous fungi that produce mycotoxins (secondary metabolites) known as sterigmatocystin and aflatoxins in many different kinds of foods, which leads to serious contamination in agricultural products, thereby endangering human health. Extensive studies on Aspergillus fungi have been conducted on growth and development, aflatoxin biosynthesis, and their interactions with environment. Here, we summarized a series of functional genes of the main Aspergillus fungi relative to toxins occurrence in foods, which revealed the signal transduction mechanisms of their involvement in growth and development, toxin production, and response to light, anticipating providing theoretical guidance on developing control and prevention technologies for mycotoxin contamination in agricultural products to ensure food safety.

Meeting the evolving demands of the public for the nutrition and quality of agricultural products is the eternal driving force and direction for high-quality agricultural development. Science of agricultural product quality has emerged in response to this need, which plays a crucial role in guiding the development of the agricultural industry and supporting rural revitalization. Based on a review of domestic and international research on agricultural product quality, this paper outlined the development history of science of agricultural product quality and introduced the concept of modern science of agricultural product quality. This concept focused on agricultural products such as grains, vegetables, aquatic products, dairy, fruits, meat, poultry, tuber and root, and medicinal food plants. By employing modern detection methods and analytical techniques, the core of this discipline was the nutritional quality and intelligent characterization of agricultural products. It aimed to establish a quality evaluation system for agricultural products based on different uses, elucidate the material basis and influencing factors of product quality, uncover the mechanisms of quality composition (structure-function) and quality formation (deterioration), and establish comprehensive control measures, thus producing high-quality agricultural products to meet consumer demand, guide processing, and improve agricultural industrial efficiency. From the perspective of industrial high-quality development and public health, the paper also analyzed the necessity of modern science of agricultural product quality research. Additionally, it identified key challenges in current agricultural product quality research, including: (1) Unclear spatiotemporal variation patterns and undefined characteristic quality, lack of evaluation technologies, and low precision and portability of detection technologies; (2) The complexity of agricultural product components, unclear relationships between spatial structure and quality characteristics, excessive processing, resource waste, and difficulty in premium prices for high quality; (3) Unclear quality influence patterns, unidentified molecular targets for formation and deterioration, and difficulty in controlling and maintaining quality. Based on these challenges, the paper proposed three major research areas in modern science of agricultural product quality, including agricultural products characteristic quality exploration and evaluation detection technologies, mechanisms of quality composition (structure-function) and high-value utilization technologies, and mechanisms of quality formation (deterioration) and control technologies. Finally, the paper outlined key future research tasks, including: (1) Constructing a database of agricultural product quality based on IoT, big data, and artifical intelligence technologies to achieve precise individual nutritional needs; (2) Building sensor networks and data collection systems driven by AI-powered supply chain technologies to achieve intelligent characterization of agricultural product quality throughout the entire industry chain; (3) Developing a green circular model system based on quality gradients and comprehensive utilization technologies to realize high-value resource transformation in the entire agricultural production process; (4) Creating an agricultural product AI intelligent system based on multi-source knowledge integration technologies for full-process quality control of agricultural products. This review aimed to provide the guidance and support for agricultural research, production, and management practices, addressing current bottlenecks in improving agricultural product quality, and contributing to the high-quality development of the agricultural industry.