This study aimed to investigate the aroma effects of key volatile compounds in a new type of mulberry leaf Fu brick teas (MTs) and traditional Fu brick teas (FTs). Headspace solid–phase microextraction (HS-SPME), gas chromatography–mass spectrometry (GC-MS), sensory evaluation, and chemometrics were used to determine the differences in key flavour qualities between the two. The results showed that a total of 139 volatile components were identified, with aldehydes, ketones, and alcohols dominating. Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) combined with the odour activity value (OAV) showed that seven aroma compounds had an OAV > 10, including 2-(4-methylcyclohex-3-en-1-yl) propan-2-ol with floral and fruity aroma and green attributes, 6-methylhept-5-en-2-one, (E)-6,10-dimethyl-5,9-Undecadien-2-one, (3E,5E)-octa-3,5-dien-2-one, Benzaldehyde, and (E)-3,7,11,15-tetramethylhexadec-2-en-1-ol, which were more abundant in MTs than FTs; Cedrol with sweet aroma attributes was more consistent in MTs than FTs, and we suggest that these odour compounds are important aroma contributors to MTs. Taken together, these findings will provide new insights into the mechanism of formation of the characteristic attributes of aroma in MTs.

The traditional food information model cannot guarantee the traceability of food quality and safety information. In response to this problem, blockchain has garnered significant attention from the food industry, because it can ensure food quality in the food traceability system. However, a trusted traceability system covering the full supply chain, with characteristics of systematic, accountable, and user‐friendly, is important for food quality and safety. Utilizing blockchain and intelligent Internet‐of‐Thing (IoT) technology, the architecture of the trusted traceability system is designed with a physical layer, IoT layer, and blockchain layer. Taking the Fabric alliance chain as the underlying platform, adopting a distributed management mode, and establishing nodes to upload accurate data from each link in the food supply chain, we design traceability information nodes for five organizations (namely, production, processing, distribution, sale, and supervision) and form traceability events at all levels of nodes to form a traceability chain. In addition, the key attributes and functions of the smart contract between institutions are designed, and the transfer parameters of the execution function are constructed so that the organic food node can activate them. Next, the trigger function is constructed to notify the institutional nodes to conduct transactions, thereby realizing the execution process of the three main smart contracts (namely, production–processing organizations, processing–distribution organizations, and distribution–sale organizations). Finally, we implemented a trusted food traceability system for organic grapes. The results show that the system can meet the demand for food traceability.

A traceability system can quickly and accurately query product supply chain circulation information. It is difficult to obtain processing information and achieve sharing due to the big data, long duration, large amount of equipment and scattered and easily lost processing information. In tracing the application of the case-based reasoning (CBR) to product processing, we can solve the problem of establishing an accurate and complete mathematical model between the processing information and product quality defects by finding a target record in a large amount of historical data. The traceability model of ontology and CBR uses the web ontology language (OWL) for case representation to simplify the CBR framework for big data, classifies process data and standardizes information storage. A joint optimization algorithm based on the genetic algorithm (GA) and CBR is proposed to establish an optimization model of process traceability, which is applied to case retrieval and reuse. This algorithm optimizes the genetic operator by combining the optimal preservation strategy and roulette selection method and uses an exponential-scale transformation method to stretch the fitness function. The experiments show that the optimized traceability model can infer information from garbled codes, wrong codes and missing messages to quickly determine the problematic products, thus effectively improving the traceability accuracy of product processing.

Vehicular Ad Hoc Network (VANET) is an important part of the modern intelligent transportation system, which can provide vehicle communication at a certain distance. More importantly, VANET can provide route planning and autonomous driving for drivers by analyzing data. However, VANET’s data privacy and security are a huge challenge when serving drivers. In this paper, we propose a VANET data-sharing model (DSVN) that combines ciphertext-based attribute encryption (CP-ABE), blockchain, and InterPlanetary File System (IPFS). DSVN uses an outsourced and revocable ciphertext policy attribute-based encryption (ORCP-ABE) scheme, which is improved based on CP-ABE. ORCP-ABE uses key encryption key (KEK) trees to manage user attribute groups and revoke user-level attributes. It eliminates redundant attributes in the access policy by attribute-weighted access trees. Moreover, DSVN has no single point of failure. We demonstrate the indistinguishability under the chosen-plaintext attack (IND-CPA) security of DSVN by a game based on the computational Diffie–Hellman (CDH) assumption. Experimental results show that DSVN can store and share data with low overhead. Additionally, it can revoke attributes of users safely.

The number of rice seedlings and their spatial distribution are the main agronomic components for determining rice yield. However, the above agronomic information is manually obtained through visual inspection, which is not only labor-intensive and time-consuming but also low in accuracy. To address these issues, this paper proposes RS-P2PNet, which automatically counts and locates rice seedlings through point supervision. Specifically, RS-P2PNet first adopts Resnet as its backbone and introduces mixed local channel attention (MLCA) in each stage. This allows the model to pay attention to the task-related feature in the spatial and channel dimensions and avoid interference from the background. In addition, a multi-scale feature fusion module (MSFF) is proposed by adding different levels of features from the backbone. It combines the shallow details and high-order semantic information of rice seedlings, which can improve the positioning accuracy of the model. Finally, two rice seedling datasets, UERD15 and UERD25, with different resolutions, are constructed to verify the performance of RS-P2PNet. The experimental results show that the MAE values of RS-P2PNet reach 1.60 and 2.43 in the counting task, and compared to P2PNet, they are reduced by 30.43% and 9.32%, respectively. In the localization task, the Recall rates of RS-P2PNet reach 97.50% and 96.67%, exceeding those of P2PNet by 1.55% and 1.17%, respectively. Therefore, RS-P2PNet has effectively accomplished the counting and localization of rice seedlings. In addition, the MAE and RMSE of RS-P2PNet on the public dataset DRPD reach 1.7 and 2.2, respectively, demonstrating good generalization.

Applying chameleon hash functions to redactable blockchains is still challenging work. Most redactable blockchain solutions using this technique have potential problems, such as too weak decentralization performance and trapdoors with exposure risks. In addition, quantum computing also threatens the security of blockchain systems. The above two issues imply that the development of redactable blockchains is still constrained, and that quantum-resistance will be requirements for blockchain applications. Therefore, we constructed a chameleon hash function over lattices while utilizing a hierarchical identity mechanism to manage trapdoors and assign edit permissions. This variant of the chameleon hash function can support trapdoor updates and quantum-resistant performance, namely a hierarchical identity-based chameleon hash with revocable subkey (HIBCH-RS). We demonstrated the safety performance of HIBCH-RS by defining its safety concepts of collision resistance. Our HIBCH-RS scheme provides a solution for implementing a redactable blockchain with identity encryption and post-quantum cryptography. Finally, this quantum-resistant redactable blockchain was implemented on the Hyperledger Fabric blockchain platform.