ARI KOVANLARININ ÇEVRESEL VE AKUSTİK VERİLERE DAYALI DURUM ANALİZİ: NORMAL VE ÖZEL KOŞULLARIN KARŞILAŞTIRILMASI

Yeliz Durgun; Mahmut Durgun

doi:10.17780/ksujes.1577380

EN TR

ENVIRONMENTAL AND ACOUSTIC DATA-BASED STATUS ANALYSIS OF THE HONEYBEE COLONIES: A COMPARİSON OF NORMAL AND SPECIAL CONDITIONS

Abstract

The continuous and accurate monitoring of bee colony health and activity is crucial for the conservation of bee populations and the support of sustainable agricultural practices. Our study aims to effectively monitor the status of bee colonies by integrating environmental and acoustic sensor data. This includes the analysis of environmental parameters such as CO2 and Total Volatile Organic Compounds (TVOC) concentrations, temperature, and humidity, along with the analysis of acoustic data. The methodology employed involves the time-series analysis of data obtained from various environmental sensors and the extraction of spectral features from audio files. An outlier analysis is applied during the analytical process to distinguish between normal and special conditions. Our results indicate significant temporal changes in environmental parameters. Notably, substantial increases in CO2 and TVOC concentrations were observed under special conditions (CO2: from 1200 ppm to 1450 ppm, TVOC: from 0 ppb to 450 ppb). Additionally, acoustic analysis revealed distinct spectral feature differences between the two conditions. In conclusion, our research confirms that the combination of environmental and acoustic sensor data enables comprehensive and accurate monitoring of bee colony status. The findings suggest that this integrated approach can be a valuable tool for monitoring applications.

Keywords

Kaynakça

Abou-Shaara, H. F., Owayss, A. A., Ibrahim, Y. Y., & Basuny, N. K. (2017). A review of impacts of temperature and relative humidity on various activities of honey bees. Insectes Sociaux, 64(4), 455–463. https://doi.org/10.1007/s00040-017-0573-8
Amsalem, E., & Grozinger, C. M. (2017). Evaluating the molecular, physiological and behavioral impacts of CO2 narcosis in bumble bees (Bombus impatiens). Journal of Insect Physiology, 101, 57–65. https://doi.org/10.1016/j.jinsphys.2017.06.014
Anwar, O., Keating, A., Cardell-Oliver, R., Datta, A., & Putrino, G. (2022). Design and development of low-power, long-range data acquisition system for beehives - BeeDAS. Computers and Electronics in Agriculture, 201, 107281. https://doi.org/10.1016/j.compag.2022.107281
Ayton, S., Tomlinson, S., Phillips, R. D., Dixon, K. W., & Withers, P. C. (2016). Phenophysiological variation of a bee that regulates hive humidity, but not hive temperature. Journal of Experimental Biology, 219(10), 1552–1562. https://doi.org/10.1242/jeb.137588
Bahreini, R., & Currie, R. W. (2015). The Potential of Bee-Generated Carbon Dioxide for Control of Varroa Mite (Mesostigmata: Varroidae) in Indoor Overwintering Honey bee (Hymenoptera: Apidae) Colonies. Journal of Economic Entomology, 108(5), 2153–2167. https://doi.org/10.1093/jee/tov202
Bencsik, M., McVeigh, A., Tsakonas, C., Kumar, T., Chamberlain, L., & Newton, M. (2023). A Monitoring System for Carbon Dioxide in Honeybee Hives: An Indicator of Colony Health. Sensors (Basel, Switzerland), 23. https://doi.org/10.3390/s23073588
Braga, A. R., Gomes, D. G., Rogers, R., Hassler, E. E., Freitas, B. M., & Cazier, J. A. (2020). A method for mining combined data from in-hive sensors, weather and apiary inspections to forecast the health status of honey bee colonies. Computers and Electronics in Agriculture, 169, 105161.
Bretzlaff, T., Kerr, J. T., & Darveau, C. A. (2023). High temperature sensitivity of bumblebee castes and the colony-level costs of thermoregulation in Bombus impatiens. Journal of Thermal Biology, 117, 103710. https://doi.org/10.1016/j.jtherbio.2023.103710

Bromenshenk, J. J., Henderson, C. B., Seccomb, R. A., Welch, P. M., Debnam, S. E., & Firth, D. R. (2015). Bees as biosensors: Chemosensory ability, honey bee monitoring systems, and emergent sensor technologies derived from the pollinator syndrome. Içinde Biosensors (C. 5, Sayı 4, ss. 678–711). MDPI. https://doi.org/10.3390/bios5040678
Cane, J. H., & Love, B. G. (2021). Hygroscopic larval provisions of bees absorb soil water vapor and release liquefied nutrients. Apidologie, 52(6), 1002–1016. https://doi.org/10.1007/s13592-021-00883-5
Cecchi, S., Spinsante, S., Terenzi, A., & Orcioni, S. (2020). A Smart Sensor-Based Measurement System for Advanced Bee Hive Monitoring. Sensors 2020, Vol. 20, Page 2726, 20(9), 2726. https://doi.org/10.3390/S20092726
Doublet, V., Labarussias, M., de Miranda, J. R., Moritz, R. F. A., & Paxton, R. J. (2015). Bees under stress: Sublethal doses of a neonicotinoid pesticide and pathogens interact to elevate honey bee mortality across the life cycle. Environmental Microbiology, 17(4), 969–983. https://doi.org/10.1111/1462-2920.12426
Durgun, Y. (2021). Nesnelerin İnterneti Teknolojisinin Kümes Ortamına Uygulanması ve Etkileri. European Journal of Science and Technology. https://doi.org/10.31590/ejosat.1005685
Ferrari, S., Silva, M., Guarino, M., & Berckmans, D. (2008). Monitoring of swarming sounds in bee hives for early detection of the swarming period. Computers and Electronics in Agriculture, 64(1), 72–77. https://doi.org/10.1016/j.compag.2008.05.010
Genç, M., & Genç, F. (2019). Stress Factors on Honey Bees (Apis mellifera L.) and The Components of Their Defense System Against Diseases, Parasites, and Pests. Mellifera, 19(1), 7–20.
Gil-Lebrero, S., Quiles-Latorre, F. J., Ortiz-López, M., Sánchez-Ruiz, V., Gámiz-López, V., & Luna-Rodríguez, J. J. (2016). Honey Bee Colonies Remote Monitoring System. Sensors 2017, Vol. 17, Page 55, 17(1), 55. https://doi.org/10.3390/S17010055
Gorgeva, E., Robertson, J., Voss, S., & Hoogewerff, J. (2023). The potential of bioacoustics for surveying carrion insects. Içinde Australian Journal of Forensic Sciences (ss. 1–20). Taylor & Francis. https://doi.org/10.1080/00450618.2023.2295447
Goulson, D., Nicholls, E., Botías, C., & Rotheray, E. L. (2015). Bee declines driven by combined Stress from parasites, pesticides, and lack of flowers. Içinde Science (C. 347, Sayı 6229, s. 1255957). American Association for the Advancement of Science. https://doi.org/10.1126/science.1255957
Kauffeld, N. M. (1967). Seasonal colony activity and individual bee development. Beekeeping in the United States, 335, 5.
Kearns, C. A., & Inouye, D. W. (1997). Pollinators, Flowering Plants, and Conservation Biology. BioScience, 47(5), 297–307. https://doi.org/10.2307/1313191
Lin, Z., Zheng, M., Li, Z., & Ji, T. (2023). Editorial: Biotic and abiotic stresses on honeybee physiology and colony health. Frontiers in Physiology, 14. https://doi.org/10.3389/fphys.2023.1260547
Maxwell, J. T., & Knapp, P. A. (2012). Reconstructed tupelo-honey yield in northwest Florida inferred from Nyssa Ogeche tree-ring data: 1850-2009. Agriculture, Ecosystems and Environment, 149, 100–108. https://doi.org/10.1016/j.agee.2011.11.004
Meikle, W. G., & Holst, N. (2015). Application of continuous monitoring of honeybee colonies. Apidologie, 46(1), 10–22. https://doi.org/10.1007/S13592-014-0298-X/TABLES/1
Meikle, William G, Adamczyk, J. J., Weiss, M., Ross, J., Werle, C., & Beren, E. (2021). Sublethal concentrations of clothianidin affect honey bee colony growth and hive CO2 concentration. Scientific Reports, 11(1), 4364. https://doi.org/10.1038/s41598-021-83958-8
Mirzaei, S. (2024). Smart Beehive System for Measuring Honey Level and Controlling Temperature.
Mitchell, D. (2019). Nectar, humidity, honey bees (Apis mellifera) and varroa in summer: A theoretical thermofluid analysis of the fate of water vapour from honey ripening and its implications on the control of Varroa destructor. Journal of the Royal Society Interface, 16(156), 20190048. https://doi.org/10.1098/rsif.2019.0048
Mobaraki, B., Komarizadehasl, S., Castilla Pascual, F. J., & Lozano-Galant, J. A. (2022). Application of Low-Cost Sensors for Accurate Ambient Temperature Monitoring. Buildings, 12(9), 1411. https://doi.org/10.3390/buildings12091411
Murray, T. E., Kuhlmann, M., & Potts, S. G. (2009). Conservation ecology of bees: Populations, species and communities. Içinde Apidologie (C. 40, Sayı 3, ss. 211–236). EDP Sciences. https://doi.org/10.1051/apido/2009015
Ozger, Z. B., Cihan, P., & Gokce, E. (2024). A Systematic Review of IoT Technology and Applications in Animals. Kafkas Universitesi Veteriner Fakultesi Dergisi, 411. https://doi.org/10.9775/kvfd.2024.31866
Papa, G., Maier, R., Durazzo, A., Lucarini, M., Karabagias, I. K., Plutino, M., Bianchetto, E., Aromolo, R., Pignatti, G., Ambrogio, A., Pellecchia, M., & Negri, I. (2022). file:///C:/Users/togu/Downloads/scholar (26).ris. Biology, 11(2), 233. https://doi.org/10.3390/biology11020233
Qandour, A., Ahmad, I., Habibi, D., & Leppard, M. (2014). Remote beehive monitoring using acoustic signals. Acoustics Australia, 42(3), 204–209.
Rafael Braga, A., G. Gomes, D., Rogers, R., E. Hassler, E., M. Freitas, B., & A. Cazier, J. (2020). A method for mining combined data from in-hive sensors, weather and apiary inspections to forecast the health status of honey bee colonies. Computers and Electronics in Agriculture, 169(7), 105161. https://doi.org/https://doi.org/10.1016/j.compag.2019.105161
Ratnadass, A., Fernandes, P., Avelino, J., & Habib, R. (2012). Plant species diversity for sustainable management of crop pests and diseases in agroecosystems: A review. Içinde Agronomy for Sustainable Development (C. 32, Sayı 1, ss. 273–303). Springer. https://doi.org/10.1007/s13593-011-0022-4
Rigakis, I., Potamitis, I., Tatlas, N. A., Psirofonia, G., Tzagaraki, E., & Alissandrakis, E. (2023). A Low-Cost, Low-Power, Multisensory Device and Multivariable Time Series Prediction for Beehive Health Monitoring. Sensors, 23(3), 1407. https://doi.org/10.3390/s23031407
Ruvinga, S., Hunter, G. J. A., Duran, O., & Nebel, J. C. (2021). Use of LSTM Networks to Identify “Queenlessness” in Honeybee Hives from Audio Signals. 2021 17th International Conference on Intelligent Environments, IE 2021 - Proceedings, 1–4. https://doi.org/10.1109/IE51775.2021.9486575
Schöning, C., Gisder, S., Geiselhardt, S., Kretschmann, I., Bienefeld, K., Hilker, M., & Genersch, E. (2012). Evidence for damage-dependent hygienic behaviour towards Varroa destructor-parasitised brood in the western honey bee, Apis mellifera. Journal of Experimental Biology, 215(2), 264–271. https://doi.org/10.1242/jeb.062562
Sharif, M. Z., Di, N., & Yu, B. (2023). Honeybee (Apis spp.) (Hymenoptera: Apidae) Colony Monitoring Using Acoustic Signals from the Beehive: An Assessment by Global Experts and Our Feedback. Agriculture (Switzerland), 13(4), 769. https://doi.org/10.3390/agriculture13040769
Szczurek, A., Maciejewska, M., & Batog, P. (2023). Monitoring System Enhancing the Potential of Urban Beekeeping. Applied Sciences (Switzerland), 13(1), 597. https://doi.org/10.3390/app13010597
Tang, J., Ji, C., Shi, W., Su, S., Xue, Y., Xu, J., Chen, X., Zhao, Y., & Chen, C. (2023). Survey Results of Honey Bee Colony Losses in Winter in China (2009–2021). Insects, 14(6), 554. https://doi.org/10.3390/insects14060554
Terenzi, A., Cecchi, S., & Spinsante, S. (2020). On the importance of the sound emitted by honey bee hives. Veterinary Sciences, 7(4), 1–14. https://doi.org/10.3390/vetsci7040168
Thapa, R. (2006). Honeybees and other Insect Pollinators of Cultivated Plants: A Review. Journal of the Institute of Agriculture and Animal Science, 27, 1–23. https://doi.org/10.3126/jiaas.v27i0.691
Tien, J. M. (2017). Internet of Things, Real-Time Decision Making, and Artificial Intelligence. Annals of Data Science, 4(2), 149–178. https://doi.org/10.1007/s40745-017-0112-5
vanEngelsdorp, D., Evans, J. D., Saegerman, C., Mullin, C., Haubruge, E., Nguyen, B. K., Frazier, M., Frazier, J., Cox-Foster, D., Chen, Y., Underwood, R., Tarpy, D. R., & Pettis, J. S. (2009). Colony collapse disorder: A descriptive study. PLoS ONE, 4(8), e6481. https://doi.org/10.1371/journal.pone.0006481
VanEngelsdorp, D., Traynor, K. S., Andree, M., Lichtenberg, E. M., Chen, Y., Saegerman, C., & Cox-Foster, D. L. (2017). Colony Collapse Disorder (CCD) and bee age impact honey bee pathophysiology. PLoS ONE, 12(7), e0179535. https://doi.org/10.1371/journal.pone.0179535
Wardhany, V. A., Hidayat, A., Subono, & Jhoswanda, M. (2020). Temperature and Humidity Control of Smart Cage Bee Honey Based on Internet of Things. 2020 3rd International Conference on Computer and Informatics Engineering, IC2IE 2020, 467–472. https://doi.org/10.1109/IC2IE50715.2020.9274620
Zaman, A., & Dorin, A. (2023). A framework for better sensor-based beehive health monitoring. Içinde Computers and Electronics in Agriculture (C. 210, s. 107906). Elsevier. https://doi.org/10.1016/j.compag.2023.107906

Ayrıntılar

Birincil Dil

Türkçe

Konular

Nöral Ağlar

Bölüm

Araştırma Makalesi

Yazarlar

Yeliz Durgun ^*
0000-0003-3834-5533
Türkiye

Mahmut Durgun
0000-0002-5010-687X
Türkiye

Yayımlanma Tarihi

3 Mart 2025

Gönderilme Tarihi

1 Kasım 2024

Kabul Tarihi

26 Aralık 2024

Yayımlandığı Sayı

Yıl 1970 Cilt: 28 Sayı: 1

DOI

https://doi.org/10.17780/ksujes.1577380

IZ

https://izlik.org/JA67HM55KS

Kaynak Göster

RIS / Bibtex

APA

Durgun, Y., & Durgun, M. (2025). ARI KOVANLARININ ÇEVRESEL VE AKUSTİK VERİLERE DAYALI DURUM ANALİZİ: NORMAL VE ÖZEL KOŞULLARIN KARŞILAŞTIRILMASI. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi, 28(1), 414-429. https://doi.org/10.17780/ksujes.1577380

Cited By

KENAR BİLİŞİM TABANLI OTOMATİK KALİTE ANALİZİ: KAYNAK SÜREÇLERİNDE SES VERİSİNİN KULLANIMI

Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi

https://doi.org/10.17780/ksujes.1673438

ARI KOVANLARININ ÇEVRESEL VE AKUSTİK VERİLERE DAYALI DURUM ANALİZİ: NORMAL VE ÖZEL KOŞULLARIN KARŞILAŞTIRILMASI

ENVIRONMENTAL AND ACOUSTIC DATA-BASED STATUS ANALYSIS OF THE HONEYBEE COLONIES: A COMPARİSON OF NORMAL AND SPECIAL CONDITIONS

Abstract

Keywords