Artificial Intelligence-Supported Comparison of Ruminant Animals and Pasture Assets in Villages of Malazgirt District of Muş Province
DOI:
https://doi.org/10.24925/turjaf.v13i12.4041-4052.7903Keywords:
Cattle Livestock Unit (CLU), Diversity index, Python libraries, Z-score normalization, Artificial intelligence processingAbstract
This study aims to conduct a comparative analysis of ruminant livestock populations (cattle, sheep, goats) and available pasture resources in the villages of Malazgirt district, Muş province, to determine the extent to which these resources align with livestock production capacity. Additionally, the efficiency of production potential was evaluated based on factors such as the use of culture breeds and the proportion of female animals. The research material consisted of animal wealth and pasture area data belonging to the villages; basic statistical methods and visualization techniques supported by artificial intelligence (AI) were used in the analyses. The research material consisted of livestock numbers and pasture area data from the villages, analyzed using artificial intelligence-supported techniques. Cattle Livestock Unit (CLU) conversion coefficients were applied for interspecies comparisons, the Shannon-Wiener Diversity Index was used to assess species diversity, Z-score normalization was employed to score development potential, and a median-based classification method was used to categorize the settlements. The findings revealed mismatches between pasture capacity and animal load in some villages, while in others, low ratios of culture breeds and female animals limited production potential. In conclusion, the study highlights that achieving balance between pasture and livestock numbers, promoting culture breed use, and utilizing AI-based analysis can play a critical role in rural development.
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