{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T10:59:52Z","timestamp":1781089192993,"version":"3.54.1"},"reference-count":27,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T00:00:00Z","timestamp":1781049600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Insects"],"abstract":"<jats:p>Honeybees are indispensable pollinators for agricultural ecosystems, and a colony\u2019s stability and reproductive capacity depend critically on the presence of a healthy queen. Acoustic monitoring has emerged as a promising non-invasive, lighting-independent approach for long-term colony observation. However, existing studies have largely been confined to single-apiary datasets or merged datasets from multiple similar apiaries for model training. Moreover, model evaluation has relied primarily on overall performance metrics, with insufficient attention to cross-region generalization and the detection of queen loss, a rare but critical condition. This study systematically investigates three complementary strategies: noise-augmented data diversification, lightweight convolutional neural network (CNN) architecture optimization via comprehensive ablation experiments, and transfer learning with fine-tuning to bridge the domain gap between source and target apiaries. Under cross-apiary evaluation, the proposed approach achieves an accuracy of 92.79%, a negative-class F1-score of 0.7900, and a negative-class recall of 0.7834 when only limited target-domain training samples are available. With full target-domain training data, the same strategy further attains an accuracy of 95.05%, a negative-class F1-score of 0.8596, and a negative-class recall of 0.8733. t-distributed Stochastic Neighbor Embedding (t-SNE) visualization demonstrates that noise augmentation effectively expands sample diversity in the feature space, while Gradient-weighted Class Activation Mapping (Grad-CAM) heatmaps confirm the successful transfer of source-domain acoustic features to the target domain. This work provides a practical approach for deploying acoustic-based queen status monitoring across diverse apiaries with minimal local data collection.<\/jats:p>","DOI":"10.3390\/insects17060612","type":"journal-article","created":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T09:25:17Z","timestamp":1781083517000},"page":"612","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Acoustic-Based Queen Bee Status Recognition: A Transfer Learning Approach Refinement"],"prefix":"10.3390","volume":"17","author":[{"given":"Zidong","family":"Dai","sequence":"first","affiliation":[{"name":"School of Mechanical Electronic & Information Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yurong","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, China University of Mining and Technology-Beijing, Beijing 100083, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoping","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Mechanical Electronic & Information Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,6,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2042","DOI":"10.1890\/12-1620.1","article-title":"Bee diversity effects on pollination depend on functional complementarity and niche shifts","volume":"94","author":"Dormann","year":"2013","journal-title":"Ecology"},{"key":"ref_2","first-page":"2556","article-title":"Risk assessment of pesticidal toxicity and threats on pollinators: A review on honey bee","volume":"8","author":"Naharki","year":"2020","journal-title":"Turk. 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