Age and Sex-Associated Variations in Hematological and Oxidative Stress Profiles of Geese

Age and Sex-Associated Variations in Hematological and Oxidative Stress Profiles of Geese | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Age and Sex-Associated Variations in Hematological and Oxidative Stress Profiles of Geese Elmas Ulutaş, Çağatay SALUM, Ahmet ARAMAN, Erkan ÇALIK, Mehmet Akif BOZ This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9066871/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Hematological parameters and oxidative status indicators are widely used biomarkers for evaluating physiological condition, immune competence, and health status in poultry. However, studies simultaneously examining the effects of age and sex on hematological profiles and oxidative stress parameters in geese remain limited. Therefore, the present study aimed to evaluate selected hematological parameters and oxidative stress indicators in healthy geese raised in Türkiye with respect to age and sex. Most hematological parameters, including erythrocyte count, leukocyte count, hematocrit, hemoglobin, MCV, MCH, MCHC, lymphocyte, heterophil, basophil levels and H/L ratio, did not differ significantly between sexes (p > 0.05). However, eosinophil percentages were significantly higher in males (p < 0.05), whereas monocyte ratios were higher in females (p < 0.01). Regarding oxidative stress indicators, females exhibited higher TOS and OSI values than males (p 0.05). Age significantly influenced several hematological parameters. Young geese showed higher erythrocyte counts and hematocrit values, whereas adults exhibited higher leukocyte counts, heterophil percentages, and H/L ratios (p < 0.001). TAS levels were also higher in adult geese (p 0.05). Overall, the findings indicate that age plays a major role in shaping hematological profiles and immune cell distribution in geese, whereas sex may particularly influence oxidative stress parameters. These results provide valuable reference data for the interpretation of physiological status and the scientific monitoring of flock health in geese. Geese Hematological profile Oxidative stress Total antioxidant status Age and sex Figures Figure 1 Introduction Poultry production is one of the fastest growing industries in global animal protein supply, and there has been a significant increase in poultry meat production in particular over the last fifty years (Zampiga et al., 2021 ). The recognition of poultry production as a more efficient and sustainable source of protein compared to other livestock (Kozák, 2021 ), has also increased interest in alternative poultry varieties (Rothrock et al., 2019 ). Geese have been among the most multifaceted poultry species in terms of production value since their domestication. Goose meat and liver are considered an important source of protein, while their feathers are used primarily as insulation and filling materials (Cüneydioğlu et al., 2022 ). The growing world population and rising consumption of animal protein sources are making goose farming an increasingly important sector in global poultry production (Ainiwaer et al., 2025 ). Geese are notable for their adaptability, suitability for free-range and semi-intensive systems, meat quality, and relatively high disease resistance (Romanov, 1999 ; Wang et al., 2025 ). In Turkey, goose farming continues to be an important production activity, particularly in rural areas, and physiological data specific to local populations is limited. (Demir and Kırmızıbayrak, 2013 ; Cilavdaroğlu et al., 2020 ). For the sustainability of goose farming, it is necessary to monitor not only production performance but also animal health and physiological balance through reliable biomarkers. Hematological and biochemical profiling in both human and veterinary medicine are among the key indicators reflecting the homeostatic state of organisms. (Livingston et al., 2020 ). In avian species, red blood cell (RBC) count, hemoglobin (Hb), hematocrit (Hct), total and differential leukocyte counts, and heterophil/lymphocyte (H/L) ratio provide important information about oxygen-carrying capacity, immune response, and stress levels (Scanes, 2016 ; Wein et al., 2017 ). Furthermore the presence of nucleated erythrocytes in avians further increases the importance of specific assessments for the species (Mitchell and Johns, 2008 ; Carisch et al., 2019 ). It is known that hematological parameters are affected from age, sex, nutrition, environmental conditions, and management practices (Reed et al., 2003 ; Thavasiappan et al., 2023 ). The studies on geese have reported different and sometimes conflicting results regarding the effects of age and sex on blood parameters. Although some studies report higher erythrocyte and hemoglobin values in female geese (Thavasiappan et al., 2023 ), other studies have found no significant difference between the sexs (Hamadani et al., 2014 ; Jahantigh and Zamani-Ahmadmahmudi, 2016 ). In a study carried out on 40 ducklings aged between 6 and 42 days, it was determined that the number of erythrocytes did not show any significant change as age progressed. However, when evaluated according to body weight, a decrease in circulating blood volume has been reported. It is also argued that the blood oxygen carrying capacity of ducklings is lower than that of chickens, and that this may be related to a lower metabolic rate per unit body weight (Kostelecka-Myrcha, 1976 ). In another study, it was reported that carcass weight did not change significantly in geese raised between 13 and 25 weeks of age; however, feather ratio and dry feather weight reached higher values at 25 weeks of age. It has also been noted that male geese have a higher dry feather weight compared to females. (Lin et al., 2023 ). Therefore, since age and sex may affect productivity traits during the rearing process, it is important to evaluate growth-phase physiology and production traits together and, within this scope, to determine reference ranges specific to local populations. In recent years, oxidative stress markers, which are important indicators in the evaluation of avian physiology, have been defined as an imbalance between reactive oxygen species (ROS) production and the antioxidant defense system. Oxidative stress is closely related to environmental and metabolic stress factors encountered in production systems (Surai et al., 2025 ). Biomarkers such as total antioxidant level (TAS), total oxidant level (TOS), and oxidative stress index (OSI) enable a comprehensive assessment of redox homeostasis. Indeed, in the limited number of studies conducted on geese, it has been reported that some oxidative stress parameters may show sex-dependent differences (Yavuz et al., 2023 ). However, studies examining hematological parameters and oxidative status indicators together within the framework of age and sex factors are extremely limited (Lin et al., 2023 ; Thavasiappan et al., 2023 ). Studies evaluating hematological profiles and oxidative stress markers simultaneously while considering age and sex variables in geese are limited. Therefore, this study aimed to investigate selected hematological parameters and oxidative stress biomarkers according to different age groups and sexes in healthy geese raised in Türkiye. This study also provides a comprehensive evaluation of hematological parameters along with oxidative stress markers (TAS, TOS, and OSI) and establishes age- and sex-specific reference values that may contribute to the interpretation of the physiological status of geese and the scientific monitoring of flock health. Materials and Methods Animals, management and diet The animals used in this study consisted of native Turkish geese raised at the Yozgat Bozok University Agricultural Application and Research Center. The study included 40 healthy white geese, which were grouped as follows: 20 young geese (16 weeks old: 10 females and 10 males) and 20 adults (98 weeks old: 10 females and 10 males). The geese were raised under similar environmental conditions and subjected to the same prophylactic veterinary practices. This approach minimizes changes related to nutrition, housing, and health, ensuring that the study results focus on independent variables such as age and sex. The geese were raised in a free-range system, with one goose per square meter in enclosed areas and eight geese per square meter in outdoor areas. They have been provided with continuous access to the free movement area throughout the day. Blood samples were collected from geese freely fed a growth feed containing 15% crude protein, 12.56 MJ ME, 5.4% crude ash, 4.2% crude fiber, 0.290% methionine, 0.670% lysine, 0.750% calcium, and 0.320% phosphorus, outside the egg-laying season. Water was supplied ad libitum. Additional lighting was not used in production; it was done based on natural light depending on seasonal conditions. The approximate live body weights of the geese during the blood collection period were as follows: Young Females (YF) 3680 ± 110 g, Young Males (YM) 4250 ± 142 g, Adult Females (AF) 4575 ± 145 g, Adult Males (AM) 5214 ± 185 g. Blood samples were collected from the wing veins of geese into anticoagulant (EDTA) tubes. Blood samples were transported to the laboratory under appropriate conditions immediately after collection. After the hemogram analyses were completed, the blood samples were centrifuged at 2000 RPM for 5 minutes (Hettich Universal 320R). The blood plasma was then collected using an automatic pipette and stored at -18°C for subsequent analysis. Hematological analysis The hematocrit value was determined using a microhematocrit centrifuge (Hettich Hematocrit 200) (Konuk, 1981 ). The total erythrocyte and total leukocyte were counted using a Neubauer hemocytometer with Natt-Herick solution (Natt and Herrick, 1955 ). Additionally, the mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), and mean corpuscular hemoglobin concentration (MCHC) were calculated according to standard formulations (Konuk, 1981 ). Hemoglobin levels were measured using a spectrophotometric method (BMG Spektrostar Nano) with Drabkin’s solution (Balasubramaniam and Malathi, 1992 ). Three blood smears were prepared for each blood sample and colored using the May-Grünwald-Giemsa staining technique. Leukocyte identification was performed under a light microscope (Carl Zeiss Primostar) to determine leukocyte percentages (Konuk, 1981 ). Sample photos of leukocyte types are presented in Fig. 1 . Total antioxidant status (TAS) and total oxidant status (TOS) measurements The TAS and TOS values of the samples were measured using commercial kits from Relassay (Turkey) and an ELISA device (BMG Spektrostar Nano). Results were calculated in µmol/L (Erel, 2004 ). Since the ratio of TOS to TAS is accepted as the oxidative stress index (OSI), the OSI value was calculated using the following formula (Harma and Erel, 2003 ): OSI (arbitrary unit) = TOS (µmol H 2 O 2 equivalent/L) / TAS (µmol Trolox equivalent/L) Statistical analysis The statistical analysis of the obtained data was performed using the SPSS 23.0 software package (SPSS, Inc., Chicago, IL, USA). Analysis of variance within and between groups was performed, and Duncan’s test was applied to determine differences between groups. Results The mean values of hematological and oxidative stress parameters obtained from healthy geese are presented according to sex (Table 1 ), age (Table 2 ), and the combined effect of age and sex (Table 3 ). Table 1 Blood Parameters Related to Sex Parameters Female Male SEM p Erythrocyte (10 6 /mm 3 ) 2,13 2,19 0,036 0,375 Leukocyte (10 3 /mm 3 ) 7,53 7,37 0,188 0,666 Packed Cell Volume (%) 40,42 40,52 0,499 0,918 Hemoglobin (g/dL) 17,54 16,63 0,319 0,157 MCV (µ 3 ) 194,10 188,72 3,723 0,473 MCH (pg) 84,20 77,19 1,895 0,064 MCHC (%) 43,40 41,32 0,680 0,129 Lymphocyte (%) 53,95 53,23 1,217 0,767 Heterophile (%) 40,68 41,45 1,232 0,756 Basophil (%) 2,05 2,09 0,157 0,886 Eosinophil (%) 1,59 a 1,95 b 0,088 0,038* Monocyte (%) 1,73 a 1,27 b 0,078 0,003** H/L Ratio 0,80 0,92 0,048 0,210 TOS (µmol/L) 15,39 a 11,62 b 0,732 0,009** TAS (µmol/L) 1,18 1,22 0,012 0,062 OSİ (%) 1,32 a 0,96 b 0,063 0,004** H/L: Heterophil to lymphocyte ratio, TOS: Total Oxidant Status, TAS: Total Antioxidant Status, OSI: Oxidative Stress Index a, b: The difference between the average values of different letters in the same line is statistically significant. (*): p < 0,05; (**): p < 0,01; (***): p < 0,001 In the evaluation related to sex (Table 1 ), no statistically significant difference was found between female and male geese in terms of erythrocytes, leukocytes, hematocrit, hemoglobin, MCV, MCH, MCHC, lymphocytes, heterophils, basophils, and H/L ratio. (p > 0,05). However, the eosinophil percentage was significantly higher in males than in females (p < 0.05). Conversely, the monocyte ratio was significantly higher in females than in males (p < 0,01). When oxidative stress parameters were examined, TOS and OSI values were found to be higher in females than in males (p 0,05). Table 2 Blood Parameters Related to Age Parameters Young Adult SEM p Erythrocyte (10 6 /mm 3 ) 2,27 a 2,04 b 0,036 0,001*** Leukocyte (10 3 /mm 3 ) 6,74 a 8,16 b 0,188 0,000*** Packed Cell Volume (%) 43,57 a 37,37 b 0,499 0,000*** Hemoglobin (g/dL) 17,68 16,49 0,319 0,062 MCV (µ 3 ) 198,16 184,66 3,723 0,070 MCH (pg) 80,28 81,10 1,895 0,831 MCHC (%) 40,60 a 44,11 b 0,680 0,009** Lymphocyte (%) 61,05 a 46,14 b 1,217 0,000*** Heterophile (%) 33,77 a 48,36 b 1,232 0,000*** Basophil (%) 1,91 2,23 0,157 0,315 Eosinophil (%) 1,41 a 2,14 b 0,088 0,000*** Monocyte (%) 1,86 a 1,14 b 0,078 0,000*** H/L Ratio 0,64 a 1,07 b 0,048 0,000*** TOS (µmol/L) 14,15 12,85 0,732 0,376 TAS (µmol/L) 1,17 a 1,22 b 0,012 0,024* OSİ (%) 1,23 1,04 0,062 0,123 a, b: The difference between the average values of different letters in the same line is statistically significant. (*): p < 0,05; (**): p < 0,01; (***): p < 0,001 In the evaluation of adult geese by age group (Table 2 ), it was determined that the erythrocyte count and hematocrit values were significantly higher in young geese than in adult geese (p < 0,001). In contrast, the total leukocyte count was higher than in young geese (p < 0,001). The lymphocyte ratio was higher in young geese (p < 0,001), The ratios of heterophils, eosinophils, and monocytes were higher in adult geese (p < 0,001). The H/L ratio was also significantly higher in adult geese than in young geese (p < 0,001). Additionally, it was found that MCHC values were higher in adult geese (p 0,05). Regarding oxidative parameters, TAS levels were significantly higher in adult geese than in young geese (p 0,05). Table 3 The Effect of Age and Sex Relationship Parameters Young Female (YF) Adult Female (AF) Young Male (YM) Adult Male (AM) SEM p Erythrocyte (10 6 /mm 3 ) 2,15 ba 2,10 ba 2,40 a 1,99 c 0,036 0,000*** Leukocyte (10 3 /mm 3 ) 6,69 a 8,37 c 6,78 ba 7,96 bc 0,188 0,001*** Packed Cell Volume (%) 42,91 ba 37,93 bc 44,24 a 36,81 c 0,499 0,000*** Hemoglobin (g/dL) 18,15 16,93 17,21 16,06 0,319 0,138 MCV (µ 3 ) 206,16 182,05 190,17 187,27 3,723 0,118 MCH (pg) 87,19 81,20 73,38 80,99 1,895 0,080 MCHC (%) 42,18 ac 44,59 a 39,02 c 43,62 bc 0,680 0,019* Lymphocyte (%) 61,45 a 46,45 cd 60,64 ba 45,82 d 1,217 0,000*** Heterophile (%) 33,64 a 47,73 cd 33,91 ab 49,00 d 1,232 0,000*** Basophil (%) 1,73 2,36 2,09 2,09 0,157 0,566 Eosinophil (%) 1,18 a 2,00 bc 1,64 b 2,27 c 0,088 0,000*** Monocyte (%) 2,00 a 1,45 b 1,73 bc 0,82 c 0,078 0,000*** H/L Ratio 0,56 a 1,04 cd 0,72 ba 1,11 d 0,048 0,000*** TOS (µmol/L) 16,18 14,59 12,13 11,10 1,041 0,303 TAS (µmol/L) 1,13 1,22 1,21 1,23 0,017 0,170 OSİ (%) 1,45 1,18 1,02 0,90 0,089 0,142 a, b, c, d: The difference between the average values of different letters in the same line is statistically significant. (*): p < 0,05; (**): p < 0,01; (***): p < 0,001 When the relationship between age and sex was examined (Table 3 ), significant differences were found in red blood cell count and packed cell volume (p < 0,001). The highest erythrocyte and packed cell volume values were observed in the YM group, while the lowest values were observed in the AM group. The total white blood cell count was highest in the AF group (p < 0,001). Significant differences were observed between the lymphocyte and heterophil percentage groups (p < 0,001). While the lymphocyte percentage was higher in the YF and YM groups, the heterophil percentage was also seen to increase in the AF and AM groups. This tendency was also reflected in the H/L ratio, which was higher in the AF and AM groups (p < 0,001). Statistically significant differences were also found between the groups in terms of eosinophil and monocyte ratios (p < 0.001). The highest eosinophil ratio was observed in the AM group, while the highest monocyte ratio was observed in the YF group. No statistically significant difference was found between age and sex in terms of oxidative stress parameters (TAS, TOS, and OSI) (p > 0,05). Discussion This study examined age- and sex-dependent changes in hematological and oxidative stress parameters in geese. Hematological parameters are among the important biological markers in the assessment of the physiological and pathological state of the organism. Hematological analyses, particularly in poultry species, are widely accepted as a reliable diagnostic method for monitoring health status, early diagnosis of diseases, and identifying physiological changes related to the environment or nutrition (Sandoghdar et al., 2024 ). In our study, young geese in particular had higher red blood cell counts and packed cell volume compared to adult geese. This difference can be considered a physiological adaptation that meets the increased metabolic demands and oxygen transport capacity required during the growth period. Erythropoiesis, or the production of red blood cells, is regulated by erythropoietin (EPO), which is released by the kidneys in response to low oxygen levels (hypoxia). Fast growth and increased tissue development in young geese stimulate erythropoietic activity by increasing oxygen demand (Prokić et al., 2019 ). Some studies have shown that as geese age, there is a decrease in their red blood cell count and packed cell volume (Thavasiappan et al., 2023 ), While consistent with the results of our study, it suggests that differences in the hematological profile of young geese may be related to growth performance. The results that sex has no significant effect on red blood cell count and packed cell volume is consistent with the results of a study by Dolka et al. ( 2014 ), which reported similar red blood cell levels in male and female geese that had not yet reached slaughter maturity (Dolka et al., 2014 ). Additionally, some studies have shown that the effect of sex on erythrocyte parameters is minimal in various poultry species (Jahantigh and Zamani-Ahmadmahmudi, 2016 ). The observation of no significant differences in MCV, MCH, and hemoglobin levels suggests that the morphometric characteristics of erythrocytes remain relatively stable with respect to factors such as age and sex. Similarly, some studies conducted on poultry have reported no statistically significant differences between erythrocyte indices (MCV, MCH, and MCHC) (Gattani et al., 2016 ). When the leukocyte profile was examined, it was found that adult geese had a higher leukocyte count, a higher percentage of heterophils, and a higher H/L ratio. In contrast, a higher percentage of lymphocytes was observed in young geese. Heterophils provide the first line of defense in the natural immunity of poultry, while lymphocytes are essential for the adaptive immune response (Minias, 2019 ). It has been reported that increased glucocorticoid levels cause circulating lymphocytes to migrate to tissues and heterophils released from the bone marrow to flow (Davis et al., 2008 ). This process leads to an increased H/L ratio characterized by an increase in heterophils and a decrease in lymphocytes. The H/L ratio is widely used to assess stress in poultry, particularly as a marker of chronic stress (Davis and Maney, 2018 ). While corticosterone levels rise rapidly in response, changes in the H/L ratio develop more slowly and persist longer (Goessling et al., 2015 ). Our study observed an increase in the percentage of heterophils and the H/L ratio with age, and a decrease in the percentage of lymphocytes. These results may indicate increased chronic stress exposure or age-related differences in immune regulation in adult geese. Thavasiappan et al. ( 2023 ) reported that the percentage of heterophils increased with age, while the percentage of lymphocytes decreased, leading to an increase in the H/L ratio. This result is consistent with the findings of our study. This situation may indicate that physiological stress levels may increase in adult geese, and consequently, physiological resistance may be relatively lower. It can be said that increasing stress can cause oxidative processes and create pressure on antioxidant defense mechanisms. Additionally, it is known that the Bursa of Fabricius, which is necessary for the development of B lymphocytes in avians, undergoes involution with age. This atrophy leads to a decrease in B lymphocyte populations, which in turn affects the percentage of peripheral lymphocytes (Ciriaco et al., 2003 ; Zhang et al., 2016 ). The age-related decrease in lymphocytes and increase in heterophils observed in our study may be related to this physiological involution process. Therefore, changes in the leukocyte profile may indicate not only the stress response but also age-related immunological remodeling. The differences observed in monocyte and eosinophil percentages highlight how sensitive these cell types are to environmental and physiological factors. In particular, studies have shown that the eosinophil percentage may be affected by parasitic infestation and environmental conditions (Benarrós et al., 2020 ). Therefore, rather than attributing these changes to a single biological mechanism, it is more appropriate to evaluate them in the context of population characteristics and breeding conditions. When analyzing oxidative stress parameters, sex had a significant effect, revealing that TOS and OSI values were higher in females. Oxidative stress arises from an imbalance between reactive oxygen species and antioxidant defense mechanisms and is an important marker for the health and production performance of poultry (Surai et al., 2021 ). It is known that the reproductive process can lead to oxidative damage. It has been reported that increased metabolic activity, particularly during vitellogenesis, increases oxidative stress in females and elevates OSI values (Webb et al., 2019 ). In conclusion, the higher TOS and OSI values observed in females in our study may be related to oxidative stress associated with reproductive physiology. However, the absence of significant differences in TOS, TAS, and OSI in analyses based on age and sex combinations suggests that subgrouping may have reduced statistical power. The observation of higher TAS levels in adult geese with age may indicate an adaptive antioxidant response to counteract increased oxidative stress (Surai et al., 2019 ). The fact that this study does not include an assessment of hormonal and metabolic parameters limits its capability to draw definitive conclusions about the fundamental mechanisms affecting redox balance. In addition, it suggests that antioxidant defense capacity may become more effective with age, that the organism may have a stronger protective mechanism against oxidative stress factors, and that this may be associated with generally better physiological resistance and health status Conclusion In conclusion, the findings indicate that age significantly affects the hematological profile and immune cell distribution in chickens, while sex may cause differences, particularly in oxidative stress parameters. The decrease in age-related erythrocytes, the increase in heterophils, and the rise in the H/L ratio can be understood as physiological adaptations associated with growth, immune system maturation, and chronic stress levels. Additionally, increased TOS and OSI values in females suggest that reproductive metabolic demands may affect redox balance. These results indicate that evaluating hematological and oxidative stress parameters in geese, as well as age and sex, will contribute to a better interpretation of their physiological resistance and health status. Future studies examining variables such as hormone levels, metabolic indicators, and reproductive status will provide clearer information on the underlying mechanisms of the observed hematological and redox changes. Declarations Ethical Approval Approval was granted by the Erciyes University in Türkiye, Animal Experiments Local Ethics Committee (2021:21/237). Data Availability Statement Manuscript has no associated data. Acknowledgements This study was supported by Scientific and Technological Research Council of Turkey (TÜBİTAK) with Project number of 1919B012102263. The support is gretefully acknowledged. Conflict of Interest Authors approve that to the best of their knowledge, there is not any conflict of interest or common interest with an institution/organization or a person that may affect the review process of the paper. Author’s Contribution Conceptualization: Elmas ULUTAŞ; Methodology: Elmas ULUTAŞ, Çağatay SALUM; Formal analysis and investigation: Elmas ULUTAŞ, Çağatay SALUM, Ahmet ARAMAN, Erkan ÇALIK; Writing - original draft preparation: Elmas ULUTAŞ, Çağatay SALUM, Mehmet Akif BOZ; Writing - review and editing: Elmas ULUTAŞ, Çağatay SALUM, Mehmet Akif BOZ; Funding acquisition: Ahmet ARAMAN, Erkan ÇALIK; Resources: Elmas ULUTAŞ, Mehmet Akif BOZ. References Ainiwaer, T., Babaoğlu, A.S., Unal, K. and Karakaya, M., 2025. A comprehensive study of the fatty acid composition, thermal and some physicochemical properties of abdominal and subcutaneous fats of Linda, Mast and Turkish geese Tropical Animal Health and Production, 57, 1 (Springer) Balasubramaniam, P. and Malathi, A., 1992. Comparative study of hemoglobin estimated by Drabkin′ s and Sahli′ s methods Journal of postgraduate medicine, 38, 8–9 (Medknow) Benarrós, M.S.C., Silva, C.C.B., Silva, G.A. and Silva, K.S.M., 2020. Hematological Parameters of geese used in biomedical research Brazilian Journal of Poultry Science, 22 (SciELO Brasil) Carisch, L., Stirn, M., Hatt, J.M., Federer, K., Hofmann-Lehmann, R. and Riond, B., 2019. White blood cell count in birds: evaluation of a commercially available method BMC veterinary research, 15, 1–7 (BioMed Central) Cilavdaroğlu, E., Yamak, U.S. and Boz, M.A., 2020. Geese meat production Black Sea Journal of Agriculture, 3, 66–70 (Karyay Karadeniz Yayımcılık Ve Organizasyon Ticaret Limited Şirketi) Ciriaco, E., Píñera, P.P., Díaz-Esnal, B. and Laurà, R., 2003. Age-Related Changes in the Avian Primary Lymphoid Organs (Thymus and Bursa of Fabricius) Microscopy Research and Technique, 62, 482–487 Cüneydioğlu, E., Erdem, E. and Yalçın, S., 2022. Effects of the breeder age on the egg yield and egg quality traits of Landes geese (Anser anser) Tropical Animal Health and Production, 54, 387 (Springer) Davis, A.K. and Maney, D.L., 2018. The use of glucocorticoid hormones or leucocyte profiles to measure stress in vertebrates: What’s the difference? Methods in Ecology and Evolution, 9, 1556–1568 (Wiley Online Library) Davis, A.K., Maney, D.L. and Maerz, J.C., 2008. The use of leukocyte profiles to measure stress in vertebrates: a review for ecologists Functional ecology, 22, 760–772 (Wiley Online Library) Demir, P. and Kırmızıbayrak, T., 2013. Kaz yetiştiriciliğinin sosyo-ekonomik önemi (Ankara Üniversitesi) Dolka, B., Włodarczyk, R., Żbikowski, A., Dolka, I., Szeleszczuk, P. and Kluciński, W., 2014. Hematological parameters in relation to age, sex and biochemical values for mute swans (Cygnus olor) Veterinary Research Communications, 38, 93–100 Erel, O., 2004. A novel automated direct measurement method for total antioxidant capacity using a new generation, more stable ABTS radical cation Clinical biochemistry, 37, 277–285 (Elsevier) Gattani, A., Pathak, A., Kumar, A., Mishra, V. and Bhatia, J.S., 2016. Influence of season and sex on hemato-biochemical traits in adult turkeys under arid tropical environment Veterinary world, 9, 530 Goessling, J.M., Kennedy, H., Mendonça, M.T. and Wilson, A.E., 2015. A meta-analysis of plasma corticosterone and heterophil: lymphocyte ratios–is there conservation of physiological stress responses over time? Functional Ecology, 29, 1189–1196 (Wiley Online Library) Hamadani, H., Khan, A.A., Mir, M.S., Pampori, Z.A., Hussain, I. and Banday, M.T., 2014. Physiological and Haemato-Biochemical profiling of domestic geese (Anser anser domesticus) of Kashmir Applied Biological Research, 16, 66–71 (Centre for Advancement of Applied Sciences) Harma, M. and Erel, O., 2003. Increased oxidative stress in patients with hydatidiform mole Swiss medical weekly, 133, 563–566 Jahantigh, M. and Zamani-Ahmadmahmudi, M., 2016. Hematology and serum biochemistry values in greylag geese (Anser anser) in Southeast Iran Comparative Clinical Pathology, 25, 671–675 (Springer) Konuk, T., 1981. Pratik fizyoloji Ankara Üniversitesi Veteriner Fakültesi Yayınları, 314, 66–68 (Ankara Üniversitesi Basımevi Ankara) Kostelecka-Myrcha, A., 1976. Variations in the red blood cell picture during growth of goslings and chickens British Poultry Science, 17, 93–101 (Taylor & Francis) Kozák, J., 2021. Goose production and goose products World’s Poultry Science Journal, 77, 403–414 (Taylor & Francis) Lin, M.J., Chang, S.C., Lin, L.J., Peng, S.Y. and Lee, T.T., 2023. Effect of the age and sex on growth performance and feather quality of 13 to 25-weeks-old White Roman geese Poultry Science, 102, 102941 (Elsevier) Livingston, M.L., Cowieson, A.J., Crespo, R., Hoang, V., Nogal, B., Browning, M. and Livingston, K.A., 2020. Effect of broiler genetics, age, and sex on performance and blood chemistry Heliyon, 6 (Elsevier) Minias, P., 2019. Evolution of heterophil/lymphocyte ratios in response to ecological and life-history traits: A comparative analysis across the avian tree of life Journal of Animal Ecology, 88, 554–565 (Wiley Online Library) Mitchell, E.B. and Johns, J., 2008. Avian hematology and related disorders Veterinary Clinics of North America: Exotic Animal Practice, 11, 501–522 (Elsevier) Natt, M.P. and Herrick, C.A., 1955. The effect of cecal coccidiosis on the blood cells of the domestic fowl: I. A comparison of the changes in the erythrocyte count resulting from hemorrhage in infected and mechanically bled birds. The use of the hematocrit value as an index of the severity Poultry Science, 34, 1100–1106 (Elsevier) Prokić, V.S., Davidov, I., Belić, B., Novakov, N., Aleksić, J. and Lakić, I., 2019. Morphometric parameters of erythrocytes in juvenile mandarin ducks aix galericulata Revista Brasileira de Ciencia Avicola / Brazilian Journal of Poultry Science, 21 Reed, E.T., Gauthier, G., Pradel, R. and Lebreton, J.D., 2003. Age and environmental conditions affect recruitment in Greater Snow Geese Ecology, 84, 219–230 Romanov, M.N., 1999. Goose production efficiency as influenced by genotype, nutrition and production systems World’s Poultry Science Journal, 55, 281–294 (Taylor & Francis) Rothrock, M.J., Gibson, K.E., Micciche, A.C. and Ricke, S.C., 2019. Pastured Poultry Production in the United States: Strategies to Balance System Sustainability and Environmental Impact Frontiers in Sustainable Food Systems, 3 Sandoghdar, T., Irani, M. and Gharahveysi, S., 2024. Taurine amino acid supplementation impacts performance, blood hematology, oxidative stress, and jejunum morphology in broiler chickens Tropical Animal Health and Production, 56, 123 (Springer) Scanes, C.G., 2016. Biology of stress in poultry with emphasis on glucocorticoids and the heterophil to lymphocyte ratio Poultry science, 95, 2208–2215 (Elsevier) Surai, P.F., Kochish, I.I., Fisinin, V.I. and Kidd, M.T., 2019. Antioxidant defence systems and oxidative stress in poultry biology: An update Antioxidants, 8, 235 (MDPI) Surai, P.F., Kochish, I.I. and Kidd, M.T., 2021. Redox homeostasis in poultry: Regulatory roles of nf-κb Antioxidants, 10, 1–50 Surai, P.F., Surai, A. and Earle-Payne, K., 2025. Redox Homeostasis in Poultry/Animal Production (MDPI) Thavasiappan, V., Visha, P. and Anilkumar, R., 2023. Haematological characteristics of nondescript domestic geese (Anser anser) at different ages and sexes Wang, S., Wei, C., Yan, J. and Zhang, Y., 2025. The impact of dietary metabolizable energy levels on the performance of medium-sized geese: A systematic review Poultry Science, 104, 104743 Webb, A.C., Iverson, J.B., Knapp, C.R., DeNardo, D.F. and French, S.S., 2019. Energetic investment associated with vitellogenesis induces an oxidative cost of reproduction Journal of Animal Ecology, 88, 461–472 Wein, Y., Shira, E.B. and Friedman, A., 2017. Avoiding handling-induced stress in poultry: use of uniform parameters to accurately determine physiological stress Poultry Science, 96, 65–73 (Elsevier) Yavuz, E., Irak, K., Çelik, Ö.Y., Bolacali, M., Ergiden, Y., Tufan, T. and Gürgöze, S., 2023. Investigation of the effects of live weight and sex on oxidative stress and antioxidant parameters in healthy geese–preliminary study European Poultry Science, 87, 1–9 (Elsevier) Zampiga, M., Calini, F. and Sirri, F., 2021. Importance of feed efficiency for sustainable intensification of chicken meat production: implications and role for amino acids, feed enzymes and organic trace minerals World’s Poultry Science Journal, 77, 639–659 Zhang, T., Xie, J., Zhang, M., Fu, N. and Zhang, Y., 2016. Effect of a potential probiotics Lactococcus garvieae B301 on the growth performance, immune parameters and caecum microflora of broiler chickens Journal of Animal Physiology and Animal Nutrition, 100, 413–421 Kostelecka-Myrcha, A. (1976). Variations in the red blood cell picture during growth of goslings and chickens. British Poultry Science , 17 (1), 93–101. Lin, M. J., Chang, S. C., Lin, L. J., Peng, S. Y., & Lee, T. T. (2023). Effect of the age and sex on growth performance and feather quality of 13 to 25-weeks-old White Roman geese. Poultry Science, 102(10), 102941. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 08 Apr, 2026 Reviewers invited by journal 08 Apr, 2026 Editor assigned by journal 11 Mar, 2026 First submitted to journal 09 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9066871","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":619426506,"identity":"969906f2-6c23-4ec7-aa22-01a620dd78e9","order_by":0,"name":"Elmas Ulutaş","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABA0lEQVRIiWNgGAWjYDACdgglAyY/NgAJHijGCZghFA8DGwMD40wkLRJEaWHmJUYLPzN34scfDId5DO43P/5su8PGnp/nAOODt20MdeYN2LVINvNuluYBaTnGZiadeyaNWbK3gdlwbhuDhMwB7FoMDvNukGYAa2EwY85tO8xmcJ6BTZoXqAWXy+wP827+CXbYMfbPny3bgIzzDOy/8WkxYObdJgFxGI+BNGPbYQmDsw1szPi0SBzm3WbNY5DOI3ksp0yy90yagWTPwWbJOeckJGfgCrH23s03f1RYy/EdPr75w09wiCUf/PCmzIYfd8SAnYfCY2xgwBeTo2AUjIJRMAoIAwDMa0wn1rjlpQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-5552-3939","institution":"Yozgat Bozok University: Yozgat Bozok Universitesi","correspondingAuthor":true,"prefix":"","firstName":"Elmas","middleName":"","lastName":"Ulutaş","suffix":""},{"id":619426507,"identity":"06582000-c1d4-414c-a103-44c5034431fa","order_by":1,"name":"Çağatay SALUM","email":"","orcid":"","institution":"Kastamonu University: Kastamonu Universitesi","correspondingAuthor":false,"prefix":"","firstName":"Çağatay","middleName":"","lastName":"SALUM","suffix":""},{"id":619426508,"identity":"9ecec576-0352-4db4-9406-edd87ffb7b94","order_by":2,"name":"Ahmet ARAMAN","email":"","orcid":"","institution":"Afyon Kocatepe University: Afyon Kocatepe Universitesi","correspondingAuthor":false,"prefix":"","firstName":"Ahmet","middleName":"","lastName":"ARAMAN","suffix":""},{"id":619426509,"identity":"56883960-b875-44da-99d6-24a937c35463","order_by":3,"name":"Erkan ÇALIK","email":"","orcid":"","institution":"Yozgat Bozok Üniversitesi: Yozgat Bozok Universitesi","correspondingAuthor":false,"prefix":"","firstName":"Erkan","middleName":"","lastName":"ÇALIK","suffix":""},{"id":619426510,"identity":"511d231b-8e7d-4eb6-a303-95dd44681a7c","order_by":4,"name":"Mehmet Akif BOZ","email":"","orcid":"","institution":"Yozgat Bozok University: Yozgat Bozok Universitesi","correspondingAuthor":false,"prefix":"","firstName":"Mehmet","middleName":"Akif","lastName":"BOZ","suffix":""}],"badges":[],"createdAt":"2026-03-08 23:13:45","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9066871/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9066871/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107023330,"identity":"d858afaf-2053-4d8d-8d29-ce7ab79f072f","added_by":"auto","created_at":"2026-04-15 23:36:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":480056,"visible":true,"origin":"","legend":"\u003cp\u003eMicroscopic blood analysis of a) young female, b) young male, c) adult female, d) adult male geese\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9066871/v1/03088f9caa5eb05f0ab6b7cf.png"},{"id":107481010,"identity":"b7a49982-4fe5-4de6-9aad-8e322ab20369","added_by":"auto","created_at":"2026-04-22 02:15:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":936476,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9066871/v1/16697f64-cacb-4069-90ba-a9882e9c67d6.pdf"}],"financialInterests":"","formattedTitle":"Age and Sex-Associated Variations in Hematological and Oxidative Stress Profiles of Geese","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePoultry production is one of the fastest growing industries in global animal protein supply, and there has been a significant increase in poultry meat production in particular over the last fifty years (Zampiga et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The recognition of poultry production as a more efficient and sustainable source of protein compared to other livestock (Koz\u0026aacute;k, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), has also increased interest in alternative poultry varieties (Rothrock et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Geese have been among the most multifaceted poultry species in terms of production value since their domestication. Goose meat and liver are considered an important source of protein, while their feathers are used primarily as insulation and filling materials (C\u0026uuml;neydioğlu et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The growing world population and rising consumption of animal protein sources are making goose farming an increasingly important sector in global poultry production (Ainiwaer et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Geese are notable for their adaptability, suitability for free-range and semi-intensive systems, meat quality, and relatively high disease resistance (Romanov, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In Turkey, goose farming continues to be an important production activity, particularly in rural areas, and physiological data specific to local populations is limited. (Demir and Kırmızıbayrak, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Cilavdaroğlu et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFor the sustainability of goose farming, it is necessary to monitor not only production performance but also animal health and physiological balance through reliable biomarkers. Hematological and biochemical profiling in both human and veterinary medicine are among the key indicators reflecting the homeostatic state of organisms. (Livingston et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In avian species, red blood cell (RBC) count, hemoglobin (Hb), hematocrit (Hct), total and differential leukocyte counts, and heterophil/lymphocyte (H/L) ratio provide important information about oxygen-carrying capacity, immune response, and stress levels (Scanes, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Wein et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Furthermore the presence of nucleated erythrocytes in avians further increases the importance of specific assessments for the species (Mitchell and Johns, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Carisch et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIt is known that hematological parameters are affected from age, sex, nutrition, environmental conditions, and management practices (Reed et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Thavasiappan et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The studies on geese have reported different and sometimes conflicting results regarding the effects of age and sex on blood parameters. Although some studies report higher erythrocyte and hemoglobin values in female geese (Thavasiappan et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), other studies have found no significant difference between the sexs (Hamadani et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Jahantigh and Zamani-Ahmadmahmudi, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). In a study carried out on 40 ducklings aged between 6 and 42 days, it was determined that the number of erythrocytes did not show any significant change as age progressed. However, when evaluated according to body weight, a decrease in circulating blood volume has been reported. It is also argued that the blood oxygen carrying capacity of ducklings is lower than that of chickens, and that this may be related to a lower metabolic rate per unit body weight (Kostelecka-Myrcha, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1976\u003c/span\u003e). In another study, it was reported that carcass weight did not change significantly in geese raised between 13 and 25 weeks of age; however, feather ratio and dry feather weight reached higher values at 25 weeks of age. It has also been noted that male geese have a higher dry feather weight compared to females. (Lin et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Therefore, since age and sex may affect productivity traits during the rearing process, it is important to evaluate growth-phase physiology and production traits together and, within this scope, to determine reference ranges specific to local populations.\u003c/p\u003e \u003cp\u003eIn recent years, oxidative stress markers, which are important indicators in the evaluation of avian physiology, have been defined as an imbalance between reactive oxygen species (ROS) production and the antioxidant defense system. Oxidative stress is closely related to environmental and metabolic stress factors encountered in production systems (Surai et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Biomarkers such as total antioxidant level (TAS), total oxidant level (TOS), and oxidative stress index (OSI) enable a comprehensive assessment of redox homeostasis. Indeed, in the limited number of studies conducted on geese, it has been reported that some oxidative stress parameters may show sex-dependent differences (Yavuz et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, studies examining hematological parameters and oxidative status indicators together within the framework of age and sex factors are extremely limited (Lin et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Thavasiappan et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eStudies evaluating hematological profiles and oxidative stress markers simultaneously while considering age and sex variables in geese are limited. Therefore, this study aimed to investigate selected hematological parameters and oxidative stress biomarkers according to different age groups and sexes in healthy geese raised in T\u0026uuml;rkiye. This study also provides a comprehensive evaluation of hematological parameters along with oxidative stress markers (TAS, TOS, and OSI) and establishes age- and sex-specific reference values that may contribute to the interpretation of the physiological status of geese and the scientific monitoring of flock health.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eAnimals, management and diet\u003c/h2\u003e \u003cp\u003eThe animals used in this study consisted of native Turkish geese raised at the Yozgat Bozok University Agricultural Application and Research Center. The study included 40 healthy white geese, which were grouped as follows: 20 young geese (16 weeks old: 10 females and 10 males) and 20 adults (98 weeks old: 10 females and 10 males). The geese were raised under similar environmental conditions and subjected to the same prophylactic veterinary practices. This approach minimizes changes related to nutrition, housing, and health, ensuring that the study results focus on independent variables such as age and sex.\u003c/p\u003e \u003cp\u003eThe geese were raised in a free-range system, with one goose per square meter in enclosed areas and eight geese per square meter in outdoor areas. They have been provided with continuous access to the free movement area throughout the day. Blood samples were collected from geese freely fed a growth feed containing 15% crude protein, 12.56 MJ ME, 5.4% crude ash, 4.2% crude fiber, 0.290% methionine, 0.670% lysine, 0.750% calcium, and 0.320% phosphorus, outside the egg-laying season. Water was supplied ad libitum. Additional lighting was not used in production; it was done based on natural light depending on seasonal conditions.\u003c/p\u003e \u003cp\u003eThe approximate live body weights of the geese during the blood collection period were as follows: Young Females (YF) 3680\u0026thinsp;\u0026plusmn;\u0026thinsp;110 g, Young Males (YM) 4250\u0026thinsp;\u0026plusmn;\u0026thinsp;142 g, Adult Females (AF) 4575\u0026thinsp;\u0026plusmn;\u0026thinsp;145 g, Adult Males (AM) 5214\u0026thinsp;\u0026plusmn;\u0026thinsp;185 g.\u003c/p\u003e \u003cp\u003eBlood samples were collected from the wing veins of geese into anticoagulant (EDTA) tubes. Blood samples were transported to the laboratory under appropriate conditions immediately after collection. After the hemogram analyses were completed, the blood samples were centrifuged at 2000 RPM for 5 minutes (Hettich Universal 320R). The blood plasma was then collected using an automatic pipette and stored at -18\u0026deg;C for subsequent analysis.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eHematological analysis\u003c/h3\u003e\n\u003cp\u003eThe hematocrit value was determined using a microhematocrit centrifuge (Hettich Hematocrit 200) (Konuk, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1981\u003c/span\u003e). The total erythrocyte and total leukocyte were counted using a Neubauer hemocytometer with Natt-Herick solution (Natt and Herrick, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1955\u003c/span\u003e). Additionally, the mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), and mean corpuscular hemoglobin concentration (MCHC) were calculated according to standard formulations (Konuk, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1981\u003c/span\u003e). Hemoglobin levels were measured using a spectrophotometric method (BMG Spektrostar Nano) with Drabkin\u0026rsquo;s solution (Balasubramaniam and Malathi, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1992\u003c/span\u003e). Three blood smears were prepared for each blood sample and colored using the May-Gr\u0026uuml;nwald-Giemsa staining technique. Leukocyte identification was performed under a light microscope (Carl Zeiss Primostar) to determine leukocyte percentages (Konuk, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1981\u003c/span\u003e). Sample photos of leukocyte types are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eTotal antioxidant status (TAS) and total oxidant status (TOS) measurements\u003c/h3\u003e\n\u003cp\u003eThe TAS and TOS values of the samples were measured using commercial kits from Relassay (Turkey) and an ELISA device (BMG Spektrostar Nano). Results were calculated in \u0026micro;mol/L (Erel, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Since the ratio of TOS to TAS is accepted as the oxidative stress index (OSI), the OSI value was calculated using the following formula (Harma and Erel, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2003\u003c/span\u003e):\u003c/p\u003e \u003cp\u003eOSI (arbitrary unit)\u0026thinsp;=\u0026thinsp;TOS (\u0026micro;mol H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e equivalent/L) / TAS (\u0026micro;mol Trolox equivalent/L)\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe statistical analysis of the obtained data was performed using the SPSS 23.0 software package (SPSS, Inc., Chicago, IL, USA). Analysis of variance within and between groups was performed, and Duncan\u0026rsquo;s test was applied to determine differences between groups.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe mean values of hematological and oxidative stress parameters obtained from healthy geese are presented according to sex (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), age (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), and the combined effect of age and sex (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBlood Parameters Related to Sex\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSEM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eErythrocyte (10\u003csup\u003e6\u003c/sup\u003e/mm\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,375\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeukocyte (10\u003csup\u003e3\u003c/sup\u003e/mm\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7,37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,666\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePacked Cell Volume (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40,42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40,52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,499\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,918\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin (g/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17,54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16,63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,157\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCV (\u0026micro;\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e194,10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e188,72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3,723\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,473\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCH (pg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84,20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77,19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,895\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,064\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCHC (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43,40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41,32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,680\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,129\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocyte (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53,95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53,23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,767\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeterophile (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40,68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41,45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,756\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBasophil (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,886\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEosinophil (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,59\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,95\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,038*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonocyte (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,73\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,27\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,003**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH/L Ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,210\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTOS (\u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15,39\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11,62\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,732\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,009**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTAS (\u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,062\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOSİ (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,32\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,96\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,004**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eH/L: Heterophil to lymphocyte ratio, TOS: Total Oxidant Status, TAS: Total Antioxidant Status, OSI: Oxidative Stress Index\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ea, b: The difference between the average values of different letters in the same line is statistically significant.\u003c/p\u003e \u003cp\u003e(*): p\u0026thinsp;\u0026lt;\u0026thinsp;0,05; (**): p\u0026thinsp;\u0026lt;\u0026thinsp;0,01; (***): p\u0026thinsp;\u0026lt;\u0026thinsp;0,001\u003c/p\u003e \u003cp\u003eIn the evaluation related to sex (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), no statistically significant difference was found between female and male geese in terms of erythrocytes, leukocytes, hematocrit, hemoglobin, MCV, MCH, MCHC, lymphocytes, heterophils, basophils, and H/L ratio. (p\u0026thinsp;\u0026gt;\u0026thinsp;0,05). However, the eosinophil percentage was significantly higher in males than in females (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Conversely, the monocyte ratio was significantly higher in females than in males (p\u0026thinsp;\u0026lt;\u0026thinsp;0,01). When oxidative stress parameters were examined, TOS and OSI values were found to be higher in females than in males (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), but no significant difference was observed in TAS levels. (p\u0026thinsp;\u0026gt;\u0026thinsp;0,05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBlood Parameters Related to Age\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYoung\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdult\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSEM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eErythrocyte (10\u003csup\u003e6\u003c/sup\u003e/mm\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,27\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,04\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeukocyte (10\u003csup\u003e3\u003c/sup\u003e/mm\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,74\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8,16\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,000***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePacked Cell Volume (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43,57\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37,37\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,499\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,000***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin (g/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17,68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16,49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,062\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCV (\u0026micro;\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e198,16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e184,66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3,723\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,070\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCH (pg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80,28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81,10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,895\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,831\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCHC (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40,60\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44,11\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,680\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,009**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocyte (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61,05\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46,14\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,000***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeterophile (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33,77\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48,36\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,000***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBasophil (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,315\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEosinophil (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,41\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,14\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,000***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonocyte (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,86\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,14\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,000***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH/L Ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,64\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,07\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,000***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTOS (\u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14,15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12,85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,732\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,376\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTAS (\u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,17\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,22\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,024*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOSİ (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,123\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ea, b: The difference between the average values of different letters in the same line is statistically significant.\u003c/p\u003e \u003cp\u003e(*): p\u0026thinsp;\u0026lt;\u0026thinsp;0,05; (**): p\u0026thinsp;\u0026lt;\u0026thinsp;0,01; (***): p\u0026thinsp;\u0026lt;\u0026thinsp;0,001\u003c/p\u003e \u003cp\u003eIn the evaluation of adult geese by age group (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), it was determined that the erythrocyte count and hematocrit values were significantly higher in young geese than in adult geese (p\u0026thinsp;\u0026lt;\u0026thinsp;0,001). In contrast, the total leukocyte count was higher than in young geese (p\u0026thinsp;\u0026lt;\u0026thinsp;0,001). The lymphocyte ratio was higher in young geese (p\u0026thinsp;\u0026lt;\u0026thinsp;0,001), The ratios of heterophils, eosinophils, and monocytes were higher in adult geese (p\u0026thinsp;\u0026lt;\u0026thinsp;0,001). The H/L ratio was also significantly higher in adult geese than in young geese (p\u0026thinsp;\u0026lt;\u0026thinsp;0,001). Additionally, it was found that MCHC values were higher in adult geese (p\u0026thinsp;\u0026lt;\u0026thinsp;0,01), however, no significant difference was observed in hemoglobin, MCV, and MCH values between age groups (p\u0026thinsp;\u0026gt;\u0026thinsp;0,05). Regarding oxidative parameters, TAS levels were significantly higher in adult geese than in young geese (p\u0026thinsp;\u0026lt;\u0026thinsp;0,05), however, no significant difference was observed between age groups in TOS and OSI values (p\u0026thinsp;\u0026gt;\u0026thinsp;0,05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe Effect of Age and Sex Relationship\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYoung Female (YF)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdult Female (AF)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYoung Male (YM)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdult Male (AM)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSEM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eErythrocyte (10\u003csup\u003e6\u003c/sup\u003e/mm\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,15\u003csup\u003eba\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,10\u003csup\u003eba\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,40\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,99\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,000***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeukocyte (10\u003csup\u003e3\u003c/sup\u003e/mm\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,69\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8,37\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6,78\u003csup\u003eba\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7,96\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePacked Cell Volume (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42,91\u003csup\u003eba\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37,93\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44,24\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e36,81\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,499\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,000***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin (g/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18,15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16,93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17,21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16,06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,138\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCV (\u0026micro;\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e206,16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e182,05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e190,17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e187,27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3,723\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,118\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCH (pg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87,19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81,20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73,38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e80,99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,895\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,080\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCHC (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42,18\u003csup\u003eac\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44,59\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39,02\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43,62\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,680\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,019*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocyte (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61,45\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46,45\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60,64\u003csup\u003eba\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45,82\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,000***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeterophile (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33,64\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47,73\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33,91\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49,00\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,000***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBasophil (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,566\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEosinophil (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,18\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,00\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,64\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,27\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,000***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonocyte (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,45\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,73\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,82\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,000***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH/L Ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,56\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,04\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,72\u003csup\u003eba\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,11\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,000***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTOS (\u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16,18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14,59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12,13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11,10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,303\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTAS (\u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,170\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOSİ (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,142\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003ea, b, c, d: The difference between the average values of different letters in the same line is statistically significant. (*): p\u0026thinsp;\u0026lt;\u0026thinsp;0,05; (**): p\u0026thinsp;\u0026lt;\u0026thinsp;0,01; (***): p\u0026thinsp;\u0026lt;\u0026thinsp;0,001\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWhen the relationship between age and sex was examined (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), significant differences were found in red blood cell count and packed cell volume (p\u0026thinsp;\u0026lt;\u0026thinsp;0,001). The highest erythrocyte and packed cell volume values were observed in the YM group, while the lowest values were observed in the AM group. The total white blood cell count was highest in the AF group (p\u0026thinsp;\u0026lt;\u0026thinsp;0,001).\u003c/p\u003e \u003cp\u003eSignificant differences were observed between the lymphocyte and heterophil percentage groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0,001). While the lymphocyte percentage was higher in the YF and YM groups, the heterophil percentage was also seen to increase in the AF and AM groups. This tendency was also reflected in the H/L ratio, which was higher in the AF and AM groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0,001). Statistically significant differences were also found between the groups in terms of eosinophil and monocyte ratios (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The highest eosinophil ratio was observed in the AM group, while the highest monocyte ratio was observed in the YF group. No statistically significant difference was found between age and sex in terms of oxidative stress parameters (TAS, TOS, and OSI) (p\u0026thinsp;\u0026gt;\u0026thinsp;0,05).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study examined age- and sex-dependent changes in hematological and oxidative stress parameters in geese. Hematological parameters are among the important biological markers in the assessment of the physiological and pathological state of the organism. Hematological analyses, particularly in poultry species, are widely accepted as a reliable diagnostic method for monitoring health status, early diagnosis of diseases, and identifying physiological changes related to the environment or nutrition (Sandoghdar et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In our study, young geese in particular had higher red blood cell counts and packed cell volume compared to adult geese. This difference can be considered a physiological adaptation that meets the increased metabolic demands and oxygen transport capacity required during the growth period. Erythropoiesis, or the production of red blood cells, is regulated by erythropoietin (EPO), which is released by the kidneys in response to low oxygen levels (hypoxia). Fast growth and increased tissue development in young geese stimulate erythropoietic activity by increasing oxygen demand (Prokić et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Some studies have shown that as geese age, there is a decrease in their red blood cell count and packed cell volume (Thavasiappan et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), While consistent with the results of our study, it suggests that differences in the hematological profile of young geese may be related to growth performance.\u003c/p\u003e \u003cp\u003eThe results that sex has no significant effect on red blood cell count and packed cell volume is consistent with the results of a study by Dolka et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), which reported similar red blood cell levels in male and female geese that had not yet reached slaughter maturity (Dolka et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Additionally, some studies have shown that the effect of sex on erythrocyte parameters is minimal in various poultry species (Jahantigh and Zamani-Ahmadmahmudi, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The observation of no significant differences in MCV, MCH, and hemoglobin levels suggests that the morphometric characteristics of erythrocytes remain relatively stable with respect to factors such as age and sex. Similarly, some studies conducted on poultry have reported no statistically significant differences between erythrocyte indices (MCV, MCH, and MCHC) (Gattani et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhen the leukocyte profile was examined, it was found that adult geese had a higher leukocyte count, a higher percentage of heterophils, and a higher H/L ratio. In contrast, a higher percentage of lymphocytes was observed in young geese. Heterophils provide the first line of defense in the natural immunity of poultry, while lymphocytes are essential for the adaptive immune response (Minias, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). It has been reported that increased glucocorticoid levels cause circulating lymphocytes to migrate to tissues and heterophils released from the bone marrow to flow (Davis et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). This process leads to an increased H/L ratio characterized by an increase in heterophils and a decrease in lymphocytes.\u003c/p\u003e \u003cp\u003eThe H/L ratio is widely used to assess stress in poultry, particularly as a marker of chronic stress (Davis and Maney, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). While corticosterone levels rise rapidly in response, changes in the H/L ratio develop more slowly and persist longer (Goessling et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Our study observed an increase in the percentage of heterophils and the H/L ratio with age, and a decrease in the percentage of lymphocytes. These results may indicate increased chronic stress exposure or age-related differences in immune regulation in adult geese. Thavasiappan et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) reported that the percentage of heterophils increased with age, while the percentage of lymphocytes decreased, leading to an increase in the H/L ratio. This result is consistent with the findings of our study. This situation may indicate that physiological stress levels may increase in adult geese, and consequently, physiological resistance may be relatively lower. It can be said that increasing stress can cause oxidative processes and create pressure on antioxidant defense mechanisms.\u003c/p\u003e \u003cp\u003eAdditionally, it is known that the Bursa of Fabricius, which is necessary for the development of B lymphocytes in avians, undergoes involution with age. This atrophy leads to a decrease in B lymphocyte populations, which in turn affects the percentage of peripheral lymphocytes (Ciriaco et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The age-related decrease in lymphocytes and increase in heterophils observed in our study may be related to this physiological involution process. Therefore, changes in the leukocyte profile may indicate not only the stress response but also age-related immunological remodeling.\u003c/p\u003e \u003cp\u003eThe differences observed in monocyte and eosinophil percentages highlight how sensitive these cell types are to environmental and physiological factors. In particular, studies have shown that the eosinophil percentage may be affected by parasitic infestation and environmental conditions (Benarr\u0026oacute;s et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Therefore, rather than attributing these changes to a single biological mechanism, it is more appropriate to evaluate them in the context of population characteristics and breeding conditions.\u003c/p\u003e \u003cp\u003eWhen analyzing oxidative stress parameters, sex had a significant effect, revealing that TOS and OSI values were higher in females. Oxidative stress arises from an imbalance between reactive oxygen species and antioxidant defense mechanisms and is an important marker for the health and production performance of poultry (Surai et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). It is known that the reproductive process can lead to oxidative damage. It has been reported that increased metabolic activity, particularly during vitellogenesis, increases oxidative stress in females and elevates OSI values (Webb et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In conclusion, the higher TOS and OSI values observed in females in our study may be related to oxidative stress associated with reproductive physiology.\u003c/p\u003e \u003cp\u003eHowever, the absence of significant differences in TOS, TAS, and OSI in analyses based on age and sex combinations suggests that subgrouping may have reduced statistical power. The observation of higher TAS levels in adult geese with age may indicate an adaptive antioxidant response to counteract increased oxidative stress (Surai et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The fact that this study does not include an assessment of hormonal and metabolic parameters limits its capability to draw definitive conclusions about the fundamental mechanisms affecting redox balance. In addition, it suggests that antioxidant defense capacity may become more effective with age, that the organism may have a stronger protective mechanism against oxidative stress factors, and that this may be associated with generally better physiological resistance and health status\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, the findings indicate that age significantly affects the hematological profile and immune cell distribution in chickens, while sex may cause differences, particularly in oxidative stress parameters. The decrease in age-related erythrocytes, the increase in heterophils, and the rise in the H/L ratio can be understood as physiological adaptations associated with growth, immune system maturation, and chronic stress levels. Additionally, increased TOS and OSI values in females suggest that reproductive metabolic demands may affect redox balance. These results indicate that evaluating hematological and oxidative stress parameters in geese, as well as age and sex, will contribute to a better interpretation of their physiological resistance and health status. Future studies examining variables such as hormone levels, metabolic indicators, and reproductive status will provide clearer information on the underlying mechanisms of the observed hematological and redox changes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eApproval was granted by the Erciyes University in T\u0026uuml;rkiye, Animal Experiments Local Ethics Committee (2021:21/237).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eManuscript has no associated data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by Scientific and Technological Research Council of Turkey (T\u0026Uuml;BİTAK) with Project number of 1919B012102263. The support is gretefully acknowledged.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors approve that to the best of their knowledge, there is not any conflict of interest or common interest with an institution/organization or a person that may affect the review process of the paper.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s Contribution\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: Elmas ULUTAŞ; Methodology: Elmas ULUTAŞ, \u0026Ccedil;ağatay SALUM; Formal analysis and investigation: Elmas ULUTAŞ, \u0026Ccedil;ağatay SALUM, Ahmet ARAMAN, Erkan \u0026Ccedil;ALIK; Writing - original draft preparation: Elmas ULUTAŞ, \u0026Ccedil;ağatay SALUM, Mehmet Akif BOZ; Writing - review and editing: Elmas ULUTAŞ, \u0026Ccedil;ağatay SALUM, Mehmet Akif BOZ; Funding acquisition: Ahmet ARAMAN, Erkan \u0026Ccedil;ALIK; Resources: Elmas ULUTAŞ, Mehmet Akif BOZ.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAiniwaer, T., Babaoğlu, A.S., Unal, K. and Karakaya, M., 2025. A comprehensive study of the fatty acid composition, thermal and some physicochemical properties of abdominal and subcutaneous fats of Linda, Mast and Turkish geese Tropical Animal Health and Production, 57, 1 (Springer)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBalasubramaniam, P. and Malathi, A., 1992. Comparative study of hemoglobin estimated by Drabkin\u0026prime; s and Sahli\u0026prime; s methods Journal of postgraduate medicine, 38, 8\u0026ndash;9 (Medknow)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBenarr\u0026oacute;s, M.S.C., Silva, C.C.B., Silva, G.A. and Silva, K.S.M., 2020. Hematological Parameters of geese used in biomedical research Brazilian Journal of Poultry Science, 22 (SciELO Brasil)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCarisch, L., Stirn, M., Hatt, J.M., Federer, K., Hofmann-Lehmann, R. and Riond, B., 2019. White blood cell count in birds: evaluation of a commercially available method BMC veterinary research, 15, 1\u0026ndash;7 (BioMed Central)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCilavdaroğlu, E., Yamak, U.S. and Boz, M.A., 2020. Geese meat production Black Sea Journal of Agriculture, 3, 66\u0026ndash;70 (Karyay Karadeniz Yayımcılık Ve Organizasyon Ticaret Limited Şirketi)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCiriaco, E., P\u0026iacute;\u0026ntilde;era, P.P., D\u0026iacute;az-Esnal, B. and Laur\u0026agrave;, R., 2003. Age-Related Changes in the Avian Primary Lymphoid Organs (Thymus and Bursa of Fabricius) Microscopy Research and Technique, 62, 482\u0026ndash;487\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eC\u0026uuml;neydioğlu, E., Erdem, E. and Yal\u0026ccedil;ın, S., 2022. Effects of the breeder age on the egg yield and egg quality traits of Landes geese (Anser anser) Tropical Animal Health and Production, 54, 387 (Springer)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDavis, A.K. and Maney, D.L., 2018. The use of glucocorticoid hormones or leucocyte profiles to measure stress in vertebrates: What\u0026rsquo;s the difference? Methods in Ecology and Evolution, 9, 1556\u0026ndash;1568 (Wiley Online Library)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDavis, A.K., Maney, D.L. and Maerz, J.C., 2008. The use of leukocyte profiles to measure stress in vertebrates: a review for ecologists Functional ecology, 22, 760\u0026ndash;772 (Wiley Online Library)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDemir, P. and Kırmızıbayrak, T., 2013. Kaz yetiştiriciliğinin sosyo-ekonomik \u0026ouml;nemi (Ankara \u0026Uuml;niversitesi)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDolka, B., Włodarczyk, R., Żbikowski, A., Dolka, I., Szeleszczuk, P. and Kluciński, W., 2014. Hematological parameters in relation to age, sex and biochemical values for mute swans (Cygnus olor) Veterinary Research Communications, 38, 93\u0026ndash;100\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eErel, O., 2004. A novel automated direct measurement method for total antioxidant capacity using a new generation, more stable ABTS radical cation Clinical biochemistry, 37, 277\u0026ndash;285 (Elsevier)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGattani, A., Pathak, A., Kumar, A., Mishra, V. and Bhatia, J.S., 2016. Influence of season and sex on hemato-biochemical traits in adult turkeys under arid tropical environment Veterinary world, 9, 530\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoessling, J.M., Kennedy, H., Mendon\u0026ccedil;a, M.T. and Wilson, A.E., 2015. A meta-analysis of plasma corticosterone and heterophil: lymphocyte ratios\u0026ndash;is there conservation of physiological stress responses over time? Functional Ecology, 29, 1189\u0026ndash;1196 (Wiley Online Library)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHamadani, H., Khan, A.A., Mir, M.S., Pampori, Z.A., Hussain, I. and Banday, M.T., 2014. Physiological and Haemato-Biochemical profiling of domestic geese (Anser anser domesticus) of Kashmir Applied Biological Research, 16, 66\u0026ndash;71 (Centre for Advancement of Applied Sciences)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHarma, M. and Erel, O., 2003. Increased oxidative stress in patients with hydatidiform mole Swiss medical weekly, 133, 563\u0026ndash;566\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJahantigh, M. and Zamani-Ahmadmahmudi, M., 2016. Hematology and serum biochemistry values in greylag geese (Anser anser) in Southeast Iran Comparative Clinical Pathology, 25, 671\u0026ndash;675 (Springer)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKonuk, T., 1981. Pratik fizyoloji Ankara \u0026Uuml;niversitesi Veteriner Fak\u0026uuml;ltesi Yayınları, 314, 66\u0026ndash;68 (Ankara \u0026Uuml;niversitesi Basımevi Ankara)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKostelecka-Myrcha, A., 1976. Variations in the red blood cell picture during growth of goslings and chickens British Poultry Science, 17, 93\u0026ndash;101 (Taylor \u0026amp; Francis)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKoz\u0026aacute;k, J., 2021. Goose production and goose products World\u0026rsquo;s Poultry Science Journal, 77, 403\u0026ndash;414 (Taylor \u0026amp; Francis)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLin, M.J., Chang, S.C., Lin, L.J., Peng, S.Y. and Lee, T.T., 2023. Effect of the age and sex on growth performance and feather quality of 13 to 25-weeks-old White Roman geese Poultry Science, 102, 102941 (Elsevier)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLivingston, M.L., Cowieson, A.J., Crespo, R., Hoang, V., Nogal, B., Browning, M. and Livingston, K.A., 2020. Effect of broiler genetics, age, and sex on performance and blood chemistry Heliyon, 6 (Elsevier)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMinias, P., 2019. Evolution of heterophil/lymphocyte ratios in response to ecological and life-history traits: A comparative analysis across the avian tree of life Journal of Animal Ecology, 88, 554\u0026ndash;565 (Wiley Online Library)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMitchell, E.B. and Johns, J., 2008. Avian hematology and related disorders Veterinary Clinics of North America: Exotic Animal Practice, 11, 501\u0026ndash;522 (Elsevier)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNatt, M.P. and Herrick, C.A., 1955. The effect of cecal coccidiosis on the blood cells of the domestic fowl: I. A comparison of the changes in the erythrocyte count resulting from hemorrhage in infected and mechanically bled birds. The use of the hematocrit value as an index of the severity Poultry Science, 34, 1100\u0026ndash;1106 (Elsevier)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eProkić, V.S., Davidov, I., Belić, B., Novakov, N., Aleksić, J. and Lakić, I., 2019. Morphometric parameters of erythrocytes in juvenile mandarin ducks aix galericulata Revista Brasileira de Ciencia Avicola / Brazilian Journal of Poultry Science, 21\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eReed, E.T., Gauthier, G., Pradel, R. and Lebreton, J.D., 2003. Age and environmental conditions affect recruitment in Greater Snow Geese Ecology, 84, 219\u0026ndash;230\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRomanov, M.N., 1999. Goose production efficiency as influenced by genotype, nutrition and production systems World\u0026rsquo;s Poultry Science Journal, 55, 281\u0026ndash;294 (Taylor \u0026amp; Francis)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRothrock, M.J., Gibson, K.E., Micciche, A.C. and Ricke, S.C., 2019. Pastured Poultry Production in the United States: Strategies to Balance System Sustainability and Environmental Impact Frontiers in Sustainable Food Systems, 3\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSandoghdar, T., Irani, M. and Gharahveysi, S., 2024. Taurine amino acid supplementation impacts performance, blood hematology, oxidative stress, and jejunum morphology in broiler chickens Tropical Animal Health and Production, 56, 123 (Springer)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eScanes, C.G., 2016. Biology of stress in poultry with emphasis on glucocorticoids and the heterophil to lymphocyte ratio Poultry science, 95, 2208\u0026ndash;2215 (Elsevier)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSurai, P.F., Kochish, I.I., Fisinin, V.I. and Kidd, M.T., 2019. Antioxidant defence systems and oxidative stress in poultry biology: An update Antioxidants, 8, 235 (MDPI)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSurai, P.F., Kochish, I.I. and Kidd, M.T., 2021. Redox homeostasis in poultry: Regulatory roles of nf-κb Antioxidants, 10, 1\u0026ndash;50\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSurai, P.F., Surai, A. and Earle-Payne, K., 2025. Redox Homeostasis in Poultry/Animal Production (MDPI)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThavasiappan, V., Visha, P. and Anilkumar, R., 2023. Haematological characteristics of nondescript domestic geese (Anser anser) at different ages and sexes\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang, S., Wei, C., Yan, J. and Zhang, Y., 2025. The impact of dietary metabolizable energy levels on the performance of medium-sized geese: A systematic review Poultry Science, 104, 104743\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWebb, A.C., Iverson, J.B., Knapp, C.R., DeNardo, D.F. and French, S.S., 2019. Energetic investment associated with vitellogenesis induces an oxidative cost of reproduction Journal of Animal Ecology, 88, 461\u0026ndash;472\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWein, Y., Shira, E.B. and Friedman, A., 2017. Avoiding handling-induced stress in poultry: use of uniform parameters to accurately determine physiological stress Poultry Science, 96, 65\u0026ndash;73 (Elsevier)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYavuz, E., Irak, K., \u0026Ccedil;elik, \u0026Ouml;.Y., Bolacali, M., Ergiden, Y., Tufan, T. and G\u0026uuml;rg\u0026ouml;ze, S., 2023. Investigation of the effects of live weight and sex on oxidative stress and antioxidant parameters in healthy geese\u0026ndash;preliminary study European Poultry Science, 87, 1\u0026ndash;9 (Elsevier)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZampiga, M., Calini, F. and Sirri, F., 2021. Importance of feed efficiency for sustainable intensification of chicken meat production: implications and role for amino acids, feed enzymes and organic trace minerals World\u0026rsquo;s Poultry Science Journal, 77, 639\u0026ndash;659\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang, T., Xie, J., Zhang, M., Fu, N. and Zhang, Y., 2016. Effect of a potential probiotics Lactococcus garvieae B301 on the growth performance, immune parameters and caecum microflora of broiler chickens Journal of Animal Physiology and Animal Nutrition, 100, 413\u0026ndash;421\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKostelecka-Myrcha, A. (1976). Variations in the red blood cell picture during growth of goslings and chickens. \u003cem\u003eBritish Poultry Science\u003c/em\u003e, \u003cem\u003e17\u003c/em\u003e(1), 93\u0026ndash;101.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLin, M. J., Chang, S. C., Lin, L. J., Peng, S. Y., \u0026amp; Lee, T. T. (2023). Effect of the age and sex on growth performance and feather quality of 13 to 25-weeks-old White Roman geese. Poultry Science, 102(10), 102941.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"tropical-animal-health-and-production","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"trop","sideBox":"Learn more about [Tropical Animal Health and Production](https://www.springer.com/journal/11250)","snPcode":"11250","submissionUrl":"https://submission.nature.com/new-submission/11250/3","title":"Tropical Animal Health and Production","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Geese, Hematological profile, Oxidative stress, Total antioxidant status, Age and sex","lastPublishedDoi":"10.21203/rs.3.rs-9066871/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9066871/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHematological parameters and oxidative status indicators are widely used biomarkers for evaluating physiological condition, immune competence, and health status in poultry. However, studies simultaneously examining the effects of age and sex on hematological profiles and oxidative stress parameters in geese remain limited. Therefore, the present study aimed to evaluate selected hematological parameters and oxidative stress indicators in healthy geese raised in T\u0026uuml;rkiye with respect to age and sex.\u003c/p\u003e \u003cp\u003eMost hematological parameters, including erythrocyte count, leukocyte count, hematocrit, hemoglobin, MCV, MCH, MCHC, lymphocyte, heterophil, basophil levels and H/L ratio, did not differ significantly between sexes (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). However, eosinophil percentages were significantly higher in males (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), whereas monocyte ratios were higher in females (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Regarding oxidative stress indicators, females exhibited higher TOS and OSI values than males (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), while TAS levels were not affected by sex (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Age significantly influenced several hematological parameters. Young geese showed higher erythrocyte counts and hematocrit values, whereas adults exhibited higher leukocyte counts, heterophil percentages, and H/L ratios (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). TAS levels were also higher in adult geese (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), whereas TOS and OSI values did not differ significantly between age groups (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eOverall, the findings indicate that age plays a major role in shaping hematological profiles and immune cell distribution in geese, whereas sex may particularly influence oxidative stress parameters. These results provide valuable reference data for the interpretation of physiological status and the scientific monitoring of flock health in geese.\u003c/p\u003e","manuscriptTitle":"Age and Sex-Associated Variations in Hematological and Oxidative Stress Profiles of Geese","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-15 23:36:39","doi":"10.21203/rs.3.rs-9066871/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2026-04-08T07:22:09+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-08T07:18:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-11T04:06:27+00:00","index":"","fulltext":""},{"type":"submitted","content":"Tropical Animal Health and Production","date":"2026-03-09T10:32:48+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"tropical-animal-health-and-production","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"trop","sideBox":"Learn more about [Tropical Animal Health and Production](https://www.springer.com/journal/11250)","snPcode":"11250","submissionUrl":"https://submission.nature.com/new-submission/11250/3","title":"Tropical Animal Health and Production","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"fc3e63be-f1fc-426d-9c23-b4624a0f4471","owner":[],"postedDate":"April 15th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-15T23:36:39+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-15 23:36:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9066871","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9066871","identity":"rs-9066871","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}