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Determination of Factors Affecting Net Profit in Buffalo Milk Production by Different Data Mining Algorithms: A Case Study of Iğdır Province

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Titel: Determination of Factors Affecting Net Profit in Buffalo Milk Production by Different Data Mining Algorithms: A Case Study of Iğdır Province
Autoren: Köksal Karadaş, Osman Doğan Bulut, Hakan Duman
Quelle: Türk Tarım ve Doğa Bilimleri Dergisi. 12:640-652
Verlagsinformationen: Turk Tarim ve Doga Bilimleri Dergisi, 2025.
Publikationsjahr: 2025
Beschreibung: Buffalo milk is an important animal product because it has more protein and fat content compared to other types of milk. This study aimed to identify the key factors influencing profitability in buffalo milk production using advanced data mining algorithms. Data were collected from 92 buffalo farms in Iğdır Province, Türkiye, in 2016 by using the Simple Random Sampling Method. Among the 4 models developed in the R program, the Multivariate Adaptive Regression Splines (MARS) model demonstrated superior predictive performance based on cross-validation and goodness-of-fit criteria. The results revealed that lactation year (LY) and lactation period (LP) were the most significant variables affecting net profit. Profitability was highest in the seventh lactation year, while extending the lactation period beyond 175 days contributed to linear profit increases. The findings suggest that buffalo producers should adopt management strategies focused on culling buffaloes after the seventh lactation and extending lactation periods to improve economic outcomes. This research highlights the effectiveness of data mining techniques in determining profitability factors and provides recommendations to optimize production efficiency in livestock systems. In future research, more comprehensive models can be developed using larger datasets and additional variables.
Publikationsart: Article
Sprache: English
ISSN: 2148-3647
DOI: 10.30910/turkjans.1671584
Dokumentencode: edsair.doi...........080c4edef939d7069c4d0394fc80c49b
Datenbank: OpenAIRE
Beschreibung
Abstract:Buffalo milk is an important animal product because it has more protein and fat content compared to other types of milk. This study aimed to identify the key factors influencing profitability in buffalo milk production using advanced data mining algorithms. Data were collected from 92 buffalo farms in Iğdır Province, Türkiye, in 2016 by using the Simple Random Sampling Method. Among the 4 models developed in the R program, the Multivariate Adaptive Regression Splines (MARS) model demonstrated superior predictive performance based on cross-validation and goodness-of-fit criteria. The results revealed that lactation year (LY) and lactation period (LP) were the most significant variables affecting net profit. Profitability was highest in the seventh lactation year, while extending the lactation period beyond 175 days contributed to linear profit increases. The findings suggest that buffalo producers should adopt management strategies focused on culling buffaloes after the seventh lactation and extending lactation periods to improve economic outcomes. This research highlights the effectiveness of data mining techniques in determining profitability factors and provides recommendations to optimize production efficiency in livestock systems. In future research, more comprehensive models can be developed using larger datasets and additional variables.
ISSN:21483647
DOI:10.30910/turkjans.1671584