Determination of the effect of climate change on small cattle milk yield in Iğdır province via machine learning

Year 2024, , 374 - 384, 28.09.2024

Ayça Nur Şahin Demirel , Taner Erik

https://doi.org/10.29050/harranziraat.1464601

Abstract

This study examines the potential impact of climate change on small cattle livestock and milk productivity in Iğdır province. The study takes into account various factors, including the effects of climate change on animal stress levels, nutrient quality in grazing areas, and the spread of parasites or diseases, which may indirectly affect milk productivity. To evaluate this impact, the study utilizes eXtreme Gradient Boosting (XGBoost) machine learning models with five different climate variables, analyzing the small cattle data from Iğdır province between 2004 and 2023. Two machine learning models were created to investigate the effect of climate variables on milk yield in small cattle in Iğdır province, using a dataset of 10820 rows and 16 columns. The machine learning models revealed that five different climate variables had no significant effect on milk yield. This finding is important for the economic welfare of the region, as cattle farming plays a crucial role in the economy of Iğdır province. The neutral effect of climate change is therefore evaluated positively for Iğdır province. The study suggests that there has been no significant change in milk productivity over the last 20 years due to the constant percentage of sheep that produce milk. It is recommended that farmers in Iğdır province consider increasing the number of lactating sheep to enhance overall cattle milk production.

Keywords

Diary Milk, Machine learning, Milk Yield, Sheep, Goat

Iğdır ilinde iklim değişikliğinin küçükbaş süt verimi üzerine etkisinin makine öğrenmesi ile belirlenmesi

Abstract

Bu çalışma, iklim değişikliğinin Iğdır ilindeki küçükbaş hayvancılık ve süt verimliliği üzerindeki potansiyel etkisini incelemektedir. Çalışmada, iklim değişikliğinin hayvanların stres seviyeleri üzerindeki etkileri, otlatma alanlarındaki besin kalitesi ve süt verimliliğini dolaylı olarak etkileyebilecek parazitlerin veya hastalıkların yayılması gibi çeşitli faktörler dikkate alınmaktadır. Bu etkiyi değerlendirmek için çalışmada beş farklı iklim değişkeni ile eXtreme Gradient Boosting (XGBoost) makine öğrenimi modelleri kullanılmış ve Iğdır ilinin 2004-2023 yılları arasındaki küçükbaş hayvan verileri analiz edilmiştir. Iğdır ilindeki küçükbaş hayvanlarda iklim değişkenlerinin süt verimi üzerindeki etkisini araştırmak için 10820 satır ve 16 sütundan oluşan bir veri seti kullanılarak iki makine öğrenmesi modeli oluşturulmuştur. Makine öğrenimi modelleri, beş farklı iklim değişkeninin süt verimi üzerinde önemli bir etkisi olmadığını ortaya koymuştur. Büyükbaş hayvancılık Iğdır ilinin ekonomisinde önemli bir rol oynadığından, bu bulgu bölgenin ekonomik refahı açısından önemlidir. Dolayısıyla iklim değişikliğinin nötr etkisi Iğdır ili için olumlu olarak değerlendirilmektedir. Çalışma, süt üreten koyun oranının sabit kalması nedeniyle son 20 yılda süt verimliliğinde önemli bir değişiklik olmadığını göstermektedir. Iğdır ilindeki çiftçilere, toplam sığır sütü üretimini artırmak için süt veren koyun sayısını artırmayı düşünmeleri önerilmektedir.

Keywords

Süt Verimi, Koyun, Keçi, Makine öğrenimi, Günlük Süt

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