DISCOVERING THE CHEMICAL FACTORS BEHIND REGIONAL ROYAL JELLY DIFFERENCES VIA MACHINE LEARNING

Year 2023, Volume: 23 Issue: 1, 49 - 60, 19.05.2023

Aslı Özkök , Merve Keskin , Aslı Elif Tanuğur , Elif Önder Yorulmaz Gökhan Silahtaroğlu

https://doi.org/10.31467/uluaricilik.1238027

Abstract

This study aims to discover the characteristic chemical factors for determining the region of royal jelly using machine learning. 84 samples from 13 different regions of Turkey were used for the study, and the chemical parameters of moisture, pH, acidity, and 10-hydroxy-2-decanoic acid (10-HDA) were investigated. ANOVA test was conducted to determine whether there are differences between royal jelly from 13 locations concerning the four chemical values. In addition to the statistical tests, a machine learning model was used to find out what makes royal jelly different from each other. The descriptive statistics of the chemical analysis results of royal jelly showed the following values: moisture 63.05%±2.99, pH 3.67±0.08, acidity 45.32±3.55, and 10-HDA 2.40±0.24. Surprisingly, the machine learning model suggests that 10-HDA may be the most prominent parameter for determining the region of royal jelly. This information will help us identify royal jelly’s authenticity more easily.

Keywords

Royal jelly, honeybee, machine learning, 10-HDA

Supporting Institution

Bu çalışma SBS Bilimsel Bio Çözümler Inc. Bee&You Propolis R&D Center tarafından desteklenmiştir.

Project Number

-

Thanks

-

Makine Öğrenimi Yoluyla Bölgesel Arı Sütü Farklarının Arkasındaki Kimyasal Faktörleri Keşfetmek

Abstract

Bu çalışmanın amacı, makine öğrenmesi yoluyla arı sütünün bölgesini belirlemek için ayırt edici kimyasal faktörleri keşfetmektir. Çalışmada, Türkiye'nin 13 farklı bölgesinden 84 numune kullanılmış ve nem, pH, asitlik ve 10-hidroksi-2-dekanoik asit (10-HDA) kimyasal parametreleri incelenmiştir. 13 yerden toplanan arı sütleri arasında dört kimyasal değer açısından farklılık olup olmadığı ANOVA testi ile incelenmiştir. İstatistiksel testlere ek olarak, arı sütlerini birbirinden neyin ayırdığını keşfetmek için bir makine öğrenimi modeli kullanılmıştır. Arı sütü, kimyasal analiz sonuçlarının tanımlayıcı istatistikleri sırasıyla, nem %63,05±2,99, pH 3,67±0,08, asitlik 45,32±3,55 ve 10-HDA 2,40±0,24 olarak bulunmuştur. Şaşırtıcı bir şekilde, makine öğrenimi modeli, 10-HDA'nın arı sütünün bölgesini belirlemek için en belirgin parametre olabileceğini öne sürmektedir. Bu bilgi, arı sütünün doğruluğunun tespitini daha kolay öğrenmemize yardımcı olacaktır.

Keywords

Arı sütü, bal arısı, makine öğrenimi, 10-HDA

Project Number

-

References

• Aksoy A, Ertürk YE, Erdoğan S, Eyduran E, Tariq MM. Estimation of honey production in beekeeping enterprises from the eastern part of Turkey through some data mining algorithms. Pak. J. Zool. 2018;50(6):2199-2207, http://dx.doi.org/10.17582/journal.pjz/2018.50.6.2199.2207.
• Alpaydin E. Introduction to machine learning (Fourth bas.) MIT. Ss.xix, 2020, 1-3, 13-18.
• Arthur S. Some studies in machine learning using the game of checkers. IBM J. Res. Devep. 1959;3(3):210-229, doi:10.1147/rd.33.0210.
• Bogdanov S, Gallmann P. Authenticity of Honey and Other Bee Products State of the Art, ALP Science Switzerland, 2008, No.520,p.1-12.
• Crane E. The Past and Present Importance of Bee Products to Man, A. Mizrahi, Y. Lensky. (eds.), Bee Products. Springer Science & Business Media New York. 1997,p.1-15.
• Çukur T, Çukur F. Determining Factors Affecting Cooperative Membership of the Beekeepers Using Decision Tree Algorithms. Tarim Bilim. Derg. 2022;28(1):25-32, https://doi.org/10.15832/ankutbd.739230
• Dghim S, Travieso-González CM, Burget R. Analysis of the Nosema cells identification for microscopic images. Sensors, 2021;21(9):3068, https://doi.org/10.3390/s21093068.
• Edwards-Murphy F, Magno M, Whelan PM, O’Halloran J, Popovici EM. b+ WSN: Smart beehive with preliminary decision tree analysis for agriculture and honey bee health monitoring. Comput. Electron. Agric. 2016;124:211-219, https://doi.org/10.1016/j.compag.2016.04.008.
• Fujiwara S, Imai J, Fujiwara M, Yaeshima T, Kawashima T, Kobayashi K. A potent antibacterial protein in royal jelly. Purification and determination of the primary structure of royalisin. J. Biol. Chem. 1990;265(19):11333-11337.
• Garcia-Amoedo LH, Almeida-Muradian LB. Physicochemical composition of pure and adulterated royal jelly. Quím. Nova, 2007;30(2):257-259, https://doi.org/10.1590/S0100-40422007000200002.
• Hidaka S, Okamoto Y, Uchiyama S, Nakatsuma A, Hashimoto K, Ohnishi ST, Yamaguchi M. Royal jelly prevents osteoporosis in rats: beneficial effects in ovariectomy model and in bone tissue culture model. Evid. Based Complementary and Altern. Med. 2006;3(3):339-48, doi: 10.1093/ecam/nel019
• Horwitz W, Latimer G. Official methods of analysis of AOAC International. Gaithersburg MA, USA: Association of Official Analytical Chemist. 2000.
• Kamakura M, Mitani N, Fukuda T, Fukushima M. Antifatigue effect of fresh royal jelly in mice. J. Nutr. Sci. Vitaminol. 2001;47(6):394-401, doi: 10.3177/jnsv.47.394.
• Kanbur M, Eraslan G, Beyaz L, Silici S, Liman BC, Altinordulu S, Atasever A. The effects of royal jelly on liver damage induced by paracetamol in mice. Exp. Toxicol. Pathol. 2009;61(2):123-132, doi: 10.1016/j.etp.2008.06.003.
• Kanelis D, Tananaki C, Liolios V, Dimou M, Goras G, Rodopoulou MA, Karazafiris E, Thrasyvoulou A. A suggestion for royal jelly specifications. Arh. Hig. Rada. Toksikol. 2015;66(4):275-284, doi: 10.1515/aiht-2015-66-2651.
• Karadas K, Kadirhanogullari IH. Predicting honey production using data mining and artificial neural network algorithms in apiculture. Pak. J. Zool. 2017;49(5):1611-1619, DOI:10.17582/journal.pjz/2017.49.5.1611.1619.
• Keskin M, Özkök A, Karahalil F, Kolaylı S. What should be the amount of 10-Hydroxi-2-Decanoic Acid (10-HDA) in royal jelly? Mediterr. Agric. Sci. 2020;33(3):347-350, https://doi.org/10.29136/mediterranean.698926.
• Kim J, Lee J. Quantitative analysis of trans-10-hydroxy decanoic acid in royal jelly products purchased in the USA by high-performance liquid chromatography. J. Agric. Food Chem. 2010; 54:77-86.
• Kohavi R, Provost F. Glossary of terms. Mach. Learn. 1998;20(2-3):271-274.
• Kohno K, Okamoto I, Sano O, Arai N, Iwaki K, Ikeda M, Kurimoto M. Royal jelly inhibits the production of proinflammatory cytokines by activated macrophages. J. Biosci. Biotechnol. Biochem. 2004;68(1):138-145, doi: 10.1271/bbb.68.138.
• Kolaylı S, Sahin H, Can Z, Yildiz O, Malkoc M, Asadov A. Member of complementary medicinal food: Anatolian royal jellies, their chemical compositions, and antioxidant properties. Evid. Based Complementary and Altern. Med. 2015;21(4):43-48, doi: 10.1177/2156587215618832.
• Krell, R. Value-Added Products from Beekeeping, Fao Agricultural Services Bulletin No. 124, Food and Agriculture Organization of the United Nations Rome. 1996.
• Liu JR, Yang YC, Shi L, Peng C. Antioxidant properties of royal jelly associated with larval age and time of harvest. J. Agric. Food Chem. 2008;56(23):11447-11452, doi: 10.1021/jf802494e.
• Melliou E, Chinou I. Chemistry and bioactivities of royal jelly. Stud. Nat. Prod. Chem., 2014;43: 261-290, https://doi.org/10.1016/B978-0-444-63430-6.00008-4.
• Melliou E, Chinou I. Chemistry and bioactivity of royal jelly from Greece. J. Agric. Food Chem. 2005;53(23):8987-8992, doi: 10.1021/jf051550p.
• Rafael Braga A, Gomes DG, Freitas BM, Cazier JA. A cluster-classification method for accurate mining of seasonal honey bee patterns. Ecol. Inform. 2020;59:101107, DOI:10.1016/j.ecoinf.2020.101107
• Ramadan MF, Al-Ghamdi A. Bioactive compounds and health-promoting properties of royal jelly: A Review. J. Funct. Foods. 2012;4(1):39-52, https://doi.org/10.1016/j.jff.2011.12.007
• Robles-Guerrero A, Saucedo-Anaya T, González-Ramérez E, Galván-Tejada CE. Frequency Analysis of Honey Bee Buzz for Automatic Recognition of Health Status: A Preliminary Study. Res. Comput. Sci. 2017;142:89-98, DOI:10.13053/RCS-412-1-9.
• Salazar-Olivo LA, Paz-Gonzalez V.Screening of biological activities present in honeybee (Apis mellifera) royal jelly. Toxicol. In Vitro, 2005;19(5):645-651, doi: 10.1016/j.tiv.2005.03.001.
• Schmidt JO. Bee Products: Chemical Composition and Application, A. Mizrahi&Y. Lensky. (eds.), Bee Products. Springer Science&Business Media New York; 1997, p.15-25.
• Schug J, Schuller WP, Kappen C, Salbaum JM, Bucan M, Stoeckert CJ. Promoter features related to tissue specificity as measured by Shannon entropy. Genome Biol. 2005;6(4):1-24.
• Shafer J, Agrawal R, Mehta M. SPRINT: A scalable parallel classifier for data mining. VLDB, 1996;96: 544-555.
• Silahtaroğlu G. An attribute-center-based decision tree classification algorithm. World Academy of Science, J. Eng. Technol. 2009;56:302-306, https://doi.org/10.5281/zenodo.1084171
• Silahtaroğlu G. Veri madenciliği: Kavram ve algoritmaları. Papatya Bilim, 2013, s.300.
• Tamura S, Amano S, Kono T, Kondoh J, Yamaguchi K, Kobayashi S. Molecular characteristics and physiological functions of major royal jelly protein 1 oligomer. Proteomics, 2009;9:5534-5543.
• Tamura T, Fujii A, Kuboyama N. Antitumor effects of royal jelly (RJ). Nihon Yakurigaku Zasshi, 1987; 89(2):73-80.
• Terada Y, Narukawa M, Watanabe T. Specific hydroxy fatty acids in royal jelly activate TRPA1. J. Agric. Food Chem. 2011;59(6):2627-2635, DOI: 10.1021/jf1041646
• Tokunaga KH, Yoshida C, Suzuki KM, Maruyama H, Futamura Y, Araki Y, Mishima S. Antihypertensive effect of peptides from royal jelly in spontaneously hypertensive rats. Biol. Pharm. Bull. 2004;27(2):189-192, DOI: 10.1248/bpb.27.189
• Vucevic D, Melliou E, Vasilijic S, Gasic S, Ivanovski P, Chinou I, Colic M. Fatty acids isolated from royal jelly modulate the dendritic cell-mediated immune response in vitro. Int. Immunopharmacol. 2007;7(9):1211-1220, DOI: 10.1016/j.intimp.2007.05.005
• Wytrychowski M, Chenavas S, Daniele G, Casabianca H, Batteau M, Guibert S, Brion B. Physicochemical characterization of French royal jelly: Comparison with commercial royal jellies and royal jellies produced through artificial bee-feeding. J. Food Compos. Anal. 2013;29(2):126-133, DOI: 10.1016/j.jfca.2012.12.002
• Yavuz İ, Gürel F. Chemical properties of the royal jellies in Turkish markets. Mediterr. Agric. Sci. 2017.30(3): 281-285.
• Yukunc GO. Royal jelly: Proteins and peptides. J. Apit. Nat. 2019;2(2):59-70.
• Zheng HQ, Hu FL, Dietemann, V. Changes in the composition of royal jelly harvested at different times: Consequences for quality standards. Apidologie, 2010;2(1):39-47.