2023 Cilt 23 Sayı 1

Permanent URI for this collectionhttps://hdl.handle.net/11452/32903

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Browsing by Subject "Bal arısı"

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    Discovering the chemical factors behind regional royal jelly differences via machine learning
    (Bursa Uludağ Üniversitesi, 2023-03-16) Özkök, Aslı; Keskin, Merve; Samancı, Aslı Elif Tanuğur; Önder, Elif Yorulmaz; Silahtaroğlu, Gökhan
    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.
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    Molecular identification of microbial pathogens in honey bees from Amasya
    (Bursa Uludağ Üniversitesi, 2023-05-04) Utkan, Neşe Gül; Eroğlu, Gözde Büşra
    Honey bees, Apis mellifera are highly beneficial insects that constitute both the livelihood of the producers and the food source of the consumers. However, there are some diseases that affect the yield of bees and cause the collapse of almost the entire colony. Most of these diseases are caused by microbial pathogens originating from viruses, bacteria, and fungi. Beekeeping is an important source of livelihood both in the center of Amasya and in almost all its districts. In this study, microbial pathogens that cause mass bee deaths and epidemics in Amasya province were determined using molecular methods. The results showed that the most common honey bee pathogens in Amasya are the Deformed wing virus, Chronic bee paralysis virus, and Aspergillus flavus fungus. Thus, the profile of bee diseases in Amasya province was determined for the first time with this study. In addition, this study guides other studies planned for the prevention of bee diseases and healthy beekeeping.
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    Phenetic variation in honey bee (apis mellifera) population of the Toratau Geopark, the Republic of Bashkortostan
    (Bursa Uludağ Üniversitesi, 2023-05-11) Sagitov, Salavat T.; Ilyasov, Rustem A.; Sattarov, Vener N.; Abdrakhimova, Yuliya R.; Danilenko, Valery N.; Gazizova, Nailya R.; Sattarova, Amilya V.; Boguslavsky, Dmitry V.
    A phenetic analysis of the honey bee population of the Toratau Geopark (Russia) was performed. Over 1,000 worker and drone bee samples were collected from 250 colonies in 59 apiaries on the territory of the Toratau Geopark (Gafuriysky, Ishimbaysky, Meleuzovsky, and Sterlitamaksky districts of the Republic of Bashkortostan). Six phenes in worker bees and four phenes in drone bees were recognized. The phenes E, 1R, 2R, and 3R in workers and Is, I, and O-gray in drones were predominant in the honey bee population of the Toratau Geopark, which were associated with subspecies of the Clineage. These phenes can be used as indicators of introgressive hybridization in the local dark European honey bee population. The phenes allow for quick evaluation of certain honey bee colonies hybridization states.