Royal jelly, a high-value natural product rich in bioactive compounds, is highly susceptible to quality deterioration during storage and processing. However, current quality standards rely predominantly on basic physicochemical parameters and measuring the content of 10-hydroxy-2-decenoic acid (10-HDA), which fail to capture the comprehensive and dynamic nature of its freshness. This significant knowledge gap hinders the accurate assessment, prediction, and control of royal jelly quality throughout its supply chain. To address this limitation, this review systematically elucidates the molecular mechanisms underlying the deterioration of royal jelly freshness, including key pathways such as protein denaturation, Maillard reactions, enzymatic inactivation, and lipid oxidation, and analyzes the combined effects of intrinsic and extrinsic factors on its quality stability. It highlights the potential applications of novel biochemical markers—including major royal jelly proteins (MRJPs), Maillard reaction products, enzymatic activity indicators, and energy metabolites—while comparing the advantages and limitations of traditional chromatographic techniques with modern rapid sensing and spectroscopic analysis methods. Regarding preservation, a critical yet inadequately summarized area, this review systematically evaluates the applicability and limitations of various approaches, including low-temperature storage, drying treatments, non-thermal sterilization, microencapsulation, and modified atmosphere packaging. Future directions for integrated quality control are outlined, providing a theoretical basis for holistic quality management of royal jelly.

The invasion of Vespa velutina presents a great threat to the agriculture economy, the ecological environment, and human health. An effective strategy for this hornet control is urgently required, but the limited genome information of Vespa velutina restricts the application of molecular-genomic tools for targeted hornet management. Therefore, we conducted large-scale transcriptome profiling of the hornet brain to obtain functional target genes and molecular markers. Using an Illumina HiSeq platform, more than 41 million clean reads were obtained and de novo assembled into 182,087 meaningful unigenes. A total of 56,400 unigenes were annotated against publicly available protein sequence databases and a set of reliable Simple Sequence Repeats (SSRs) and Single Nucleotide Polymorphisms (SNP) markers were developed. The homologous genes encoding crucial behavior regulation factors, odorant binding proteins (OBPs), and vitellogenin, were also identified from highly expressed transcripts. This study provides abundant molecular targets and markers for invasive hornet control and further promotes the genetic and molecular study of Vespa velutina.

Honey variety authentication is critical for ensuring market integrity and protecting consumer rights, especially for high-value unifloral honeys, such as acacia honey, which are frequently adulterated with low-value alternatives such as rape honey due to their similar visual appearance. The aim of this study was to develop a method for precise discrimination between rape honey and acacia honey using their chemical profiles combined with machine learning. A total of 542 honey samples were collected from major beekeeping regions in China. Targeted quantification of 12 sugars and 20 amino acids was performed using UPLC-MS/MS. Multivariate analysis revealed significant differences in sugar and amino acid compositions between the two honey types, though partial samples overlapped due to chemical similarity. Six machine learning algorithms, including the Multilayer Perceptron, were employed for classification. Optimization was performed via 10-fold cross-validation and ADASYN oversampling, yielding optimal performance of 98% and 100% prediction accuracies for rape honey and acacia honey, respectively, on the independent test set. SHAP (Shapley Additive Explanations) analysis identified key differential markers, including fructose, turanose, glucose, and GABA, which contributed most to the classification. Furthermore, a user-friendly web application was developed to facilitate rapid on-site authentication. This study provides an innovative technical framework for honey variety discrimination, with potential applications in quality control and anti-fraud practices.

Royal jelly, a nutrient-rich bee product characterized by high water content and active components, is particularly susceptible to quality deterioration during storage. While temperature effects have been extensively documented, the specific role of light exposure in quality degradation remains largely unexplored. despite its relevance during production, handling, transportation, and display. This study systematically investigated the volatile organic compounds (VOCs) of royal jelly under different storage conditions using gas chromatography-ion mobility spectrometry (GC-IMS) combined with fingerprint analysis. Results from dual-column validation demonstrated that even short-term light exposure at 25 °C induced pronounced alterations in VOC profiles, triggering the accumulation of off-flavor aldehydes (e.g., hexanal, nonanal) and ketones, along with 2-furfural generated via Maillard reaction. Concurrently, characteristic fresh-aroma esters and alcohols were significantly depleted. Multivariate statistical analysis confirmed light exposure as the predominant factor driving quality deterioration, with temperature variation under dark conditions producing comparatively minor effects within the same short timeframe. This work provides the first systematic evidence establishing insights into early volatile changes in royal jelly and identifies key VOC markers that offer valuable insights for optimizing storage strategies and developing rapid quality monitoring protocols.

Drying is an important processing method for extending the shelf life of aquatic products; however, different drying methods may exert distinct effects on protein quality. At present, the effects of sun drying and vacuum freeze-drying on the protein quality of Hippocampus abdominalis remain unclear. This study compared the protein content, amino acid composition, and physicochemical properties of Hippocampus abdominalis subjected to the two drying methods and further characterized changes in the proteomic profile using proteomic analysis. The results showed that the sun-dried group had a higher crude protein content (68.57% vs. 61.86%), whereas the freeze-dried group exhibited greater total amino acid retention (58.79% vs. 48.87%), water-holding capacity (WHC), and oil-holding capacity (OHC). However, no significant differences were observed in protein solubility or surface hydrophobicity between the two groups. Proteomic analysis further revealed that most differentially abundant proteins showed higher relative abundance in the freeze-dried group and were mainly associated with muscle structural stability, amino acid metabolism, and energy metabolism. Overall, the two drying methods affected the protein quality of Hippocampus abdominalis at multiple levels, including nutritional composition and physicochemical properties, while proteomic analysis provided further molecular-level insights into these quality differences.