When Everything Becomes Bigger: Big Data for Big Poultry Production

The efficacy of licorice root extract on meat amino acid, fatty acid, vitamin, and mineral composition and productivity of quail

Background and Aim

Poultry meat is an excellent animal protein source accessible to many low-income families in developing countries. It is also part of a balanced diet and contains valuable nutrients necessary for maintaining human health. The poultry sector implements improved processes to increase the quality and nutritional value of poultry meat. This study aimed to determine the influence of licorice root extract on the amino acid, fatty acid, vitamin, mineral composition, nutritional value, and productivity of quail meat.

Materials and Methods

Two groups were formed from Japanese quails: A control group and one experimental group, each consisting of 50 individuals. Quails from both the experimental and control groups received the same complete diet. Quails in the experimental group had licorice root extract added to their water at a dosage of 10 g/L, starting from the age of 3 days to 42 days of growth. At 42 days of age, 30 birds from each group were slaughtered to examine their meat productivity and chemical composition. The quail carcasses were analyzed for the following parameters: Live weight, carcass weight, nutritional value, mineral substances, vitamin content, fatty acid composition, amino acid composition, and amino acid score.

Results

This study demonstrated that quails in the experimental group receiving water with licorice extract exhibited higher indicators than those in the control group. Calcium (21.05%), magnesium (20.83%), and phosphorus (23.53%) were the most elevated mineral substances in the meat of the experimental birds. Vitamins E (22.22%) and C (20.0%) showed the greatest increase in vitamin content. The fatty acid composition parameters 17:0 margaric acid (8.16%), 18:3 linolenic acid (6.25%), and 20:4 arachidonic acid (4.49%) showed the highest increase. There was a clear increase in the amino acids valine (4.61%), lysine (4.32%), threonine (5.99%), tryptophan (4.87%), phenylalanine (5.87%), and cysteine (14.17%). The application of licorice root extract also positively impacted the amino acid score of quail meat, except for leucine, which remained within the range compared with the control group. Quails in the experimental group weighed 7.96% more live weight before slaughter than the controls. Moreover, the carcass weight was in favor of the experimental group (8.59%).

Conclusion

The use of licorice root extract positively influences the quality and biological value of quail meat. Data on amino acids, fatty acids, vitamins, trace elements, and other important components of quail meat will significantly expand our understanding of the biological value of licorice root extract. These findings can be used in the formulation of balanced diets for children and adults and highlight the importance of this issue.

Digital Phenotyping: A Game Changer for the Broiler Industry

In response to escalating global demand for poultry, the industry grapples with an array of intricate challenges, from enhancing productivity to improving animal welfare and attenuating environmental impacts. This comprehensive review explores the transformative potential of digital phenotyping, an emergent technological innovation at the cusp of dramatically reshaping broiler production. The central aim of this study is to critically examine digital phenotyping as a pivotal solution to these multidimensional industry conundrums. Our investigation spotlights the profound implications of 'digital twins' in the burgeoning field of broiler genomics, where the production of exact digital counterparts of physical entities accelerates genomics research and its practical applications. Further, this review probes into the ongoing advancements in the research and development of a context-sensitive, multimodal digital phenotyping platform, custom-built to monitor broiler health. This paper critically evaluates this platform's potential in revolutionizing health monitoring, fortifying the resilience of broiler production, and fostering a harmonious balance between productivity and sustainability. Subsequently, the paper provides a rigorous assessment of the unique challenges that may surface during the integration of digital phenotyping within the industry. These span from technical and economic impediments to ethical deliberations, thus offering a comprehensive perspective. The paper concludes by highlighting the game-changing potential of digital phenotyping in the broiler industry and identifying potential future directions for the field, underlining the significance of continued research and development in unlocking digital phenotyping's full potential. In doing so, it charts a course towards a more robust, sustainable, and productive broiler industry. The insights garnered from this study hold substantial value for a broad spectrum of stakeholders in the broiler industry, setting the stage for an imminent technological evolution in poultry production.

Application of Mamdani Fuzzy Inference System in Poultry Weight Estimation

Traditional manual weighing systems for birds on poultry farms are time-consuming and may compromise animal welfare. Although automatic weighing systems have been introduced as an alternative, they face limitations in accurately estimating the weight of heavy birds. Therefore, exploring alternative methods that offer improved efficiency and precision is necessary. One promising solution lies in the application of AI, which has the potential to revolutionize various aspects of poultry production and management, making it an indispensable tool for the modern poultry industry. This study aimed to develop an AI approach based on the FL model as a viable solution for estimating poultry weight. By incorporating expert knowledge and considering key input variables such as indoor temperature, indoor humidity, and feed consumption, FL-based models were developed with different configurations using Mamdani inferences and evaluated across eight different rearing periods in Samsun, Türkiye. This study's results demonstrated the effectiveness of FL-based models in estimating poultry weight. The models achieved varying average absolute error values across different age groups of broilers, ranging from 0.02% to 5.81%. These findings suggest that FL-based methods hold promise for accurate and efficient poultry weight estimation. This study opens up avenues for further research in the field, encouraging the exploration of FL-based approaches for improved poultry weight estimation in poultry farming operations.