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Objective: The research aims to conduct a meta-analysis evaluating the nutritional benefits of Spirulina supplementation on growth performance, rumen function, antioxidant status, blood biochemistry, fatty acid profile, meat quality, and eating quality in small ruminant, specifically goats and sheep.Methods: A systematic review and meta-analysis were conducted to determine the impact of Spirulina supplementation on various aspects of small ruminant performance and product attributes. Electronic databases (Scopus, PubMed, and Google Scholar) were searched for relevant studies published between 2012 and 2023. From the 350 identified studies, 24 matched the inclusion criteria of original research. A meta-analysis was performed using OpenMEE software. Publication bias was assessed using the precisioneffect test (PET)-precision-effect estimate with standard errors method and Rosenthal's fail-safe N analysis, visualised through PET regression plots in JASP software. Standardised mean differences between Spirulina-supplemented and control groups were calculated to determine the effect magnitude.Results: Meta-analysis show that Spirulina supplementation significantly enhances growth performance, meat quality, and antioxidant status in small ruminants compared to controls. Supplementation increases average daily gain and reduces feed conversion ratio. Additionally, Spirulina supplementation elevates antioxidant enzyme activities, including catalase, glutathione peroxidase, glutathione, and superoxide dismutase. Meat quality parameters, such as fat melting point, intramuscular fat percentage, and pH, are also positively affected. Blood biochemistry markers, including alanine transaminase, aspartate transaminase, cholesterol, haemoglobin, low-density lipoprotein, total protein, urea, and white blood cell counts, remain within normal physiological ranges. Moreover, Spirulina supplementation favorably alters fatty acid composition, increasing the proportion of eicosapentaenoic acid and decreasing the proportion of palmitic acid. Supplementation duration ranged from 14 to 182 days, with doses between 0.014 to 2.14 g/kg body weight/day.Conclusion: Spirulina supplementation has potential effects on small ruminant productivity, especially growth performance, health and meat quality. Spirulina can be a valuable dietary addition for small ruminant. Further research is warranted to optimise supplementation strategies and understand underlying mechanisms.

Objective: This study aimed to develop a method for predicting the body weight of beef cattle using meta-analysis based on digital image processing. Materials and Methods: The meta-analysis process commenced by collecting studies with the keywords “beef cattle,” “correlation,” “digital image,” and “body weight” from Google Scholar and Science Direct. The obtained studies were reviewed papers based on their titles, abstracts, and content, and then categorized by authors, year, country, sample size, and correlation coefficient. A digital image of body measurements used included wither and hip height, chest depth, heart girth, body length, and top view. The statistical analysis was conducted by calculating effect sizes using the correlation coefficient and sample sizes. Results: The results of the meta-analysis, based on 3,017 cattle from 13 selected studies, showed the highest and lowest correlation coefficients for the top view variable and hip height. Based on cattle breed, significant differences (p < 0.05) were observed in the wither height variable with correlation coefficients of 0.94, 0.79, and 0.66 for Hanwoo, Holstein, and Simmental, respectively. Based on sex, significant differences (p < 0.05) were seen in the wither height variable, with correlation coefficients of 0.73 for males and 0.90 for females, while for hip height, the values were 0.70 and 0.87, respectively. Conclusion: In conclusion, to achieve the best accuracy in predicting the body weight of beef cattle based on a digital image, the top view variable can be used. However, for ease of field experimentation, body length or chest depth can also be used while taking breed and sex categories into the model.

Objective: The aim of the study was to use a meta-analysis to identify the correlation between linear body measurements, including body length (BL), wither height (WH), heart girth (HG), and body volume (BV), and body weight in beef cattle by breed, sex, and age as categories. Materials and Methods: These results can be used as a method for predicting beef cattle body weight. This study used systematic review and meta-analysis guidelines to create a checklist. The first stage was searching for papers relevant to the study objectives. The second stage was searching using the keywords beef cattle, body weight, body measurement, and correlation. The third stage was reviewing the title and abstract. The fourth stage was abstracting information from selected papers, and the last stage was tabulating data. Results: The results from this study were obtained, and 32 papers were eligible for the meta-analysis stage. The correlation between linear body measurement and body weight of beef cattle showed that HG (r = 0.88) and BV (r = 0.97) were significantly (p < 0.05) different compared to BL (r = 0.74) and WH (r = 0.72). The correlation between HG and body weight, and the categorization of cattle breeds showed significantly (p < 0.05) different results. The correlation between BV and body weight of cattle according to breed categories showed results that were not significantly (p > 0.05) different, while age was significantly (p < 0.05). Conclusion: In conclusion, to predict beef cattle body weight, it is necessary to use HG or BV, with breed, sex, and age of cattle as categories.

Objective: The research aims to conduct a meta-analysis evaluating the nutritional benefits of Spirulina supplementation on growth performance, rumen function, antioxidant status, blood biochemistry, fatty acid profile, meat quality, and eating quality in small ruminant, specifically goats and sheep. Methods: A systematic review and meta-analysis were conducted to determine the impact of Spirulina supplementation on various aspects of small ruminant performance and product attributes. Electronic databases (Scopus, PubMed, and Google Scholar) were searched for relevant studies published between 2012 and 2023. From the 350 identified studies, 24 matched the inclusion criteria of original research. A meta-analysis was performed using OpenMEE software. Publication bias was assessed using the precision-effect test (PET)-precision-effect estimate with standard errors method and Rosenthal's fail-safe N analysis, visualised through PET regression plots in JASP software. Standardised mean differences between Spirulina-supplemented and control groups were calculated to determine the effect magnitude. Results: Meta-analysis show that Spirulina supplementation significantly enhances growth performance, meat quality, and antioxidant status in small ruminants compared to controls. Supplementation increases average daily gain and reduces feed conversion ratio. Additionally, Spirulina supplementation elevates antioxidant enzyme activities, including catalase, glutathione peroxidase, glutathione, and superoxide dismutase. Meat quality parameters, such as fat melting point, intramuscular fat percentage, and pH, are also positively affected. Blood biochemistry markers, including alanine transaminase, aspartate transaminase, cholesterol, haemoglobin, low-density lipoprotein, total protein, urea, and white blood cell counts, remain within normal physiological ranges. Moreover, Spirulina supplementation favorably alters fatty acid composition, increasing the proportion of eicosapentaenoic acid and decreasing the proportion of palmitic acid. Supplementation duration ranged from 14 to 182 days, with doses between 0.014 to 2.14 g/kg body weight/day. Conclusion: Spirulina supplementation has potential effects on small ruminant productivity, especially growth performance, health and meat quality. Spirulina can be a valuable dietary addition for small ruminant. Further research is warranted to optimise supplementation strategies and understand underlying mechanisms.