Classification of environmental factors potentially motivating for dairy cows to access shade

Deniz M., de Sousa K. T., Gomes I. C., Vale M. M. d., Dittrich J. R.

JOURNAL OF DAIRY RESEARCH, cilt.88, sa.3, ss.274-277, 2021 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 88 Sayı: 3
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1017/s0022029921000509
  • Dergi Adı: JOURNAL OF DAIRY RESEARCH
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Periodicals Index Online, Agricultural & Environmental Science Database, Analytical Abstracts, BIOSIS, Biotechnology Research Abstracts, CAB Abstracts, Chemical Abstracts Core, EMBASE, Food Science & Technology Abstracts, MEDLINE, Veterinary Science Database
  • Sayfa Sayıları: ss.274-277
  • Anahtar Kelimeler: animal distribution, behavioural pattern, decision tree, pasture, precision livestock farming
  • Gazi Üniversitesi Adresli: Hayır

Özet

The aim of this Research Communication was to apply the data mining technique to classify which environmental factors have the potential to motivate dairy cows to access natural shade. We defined two different areas at the silvopastoral system: shaded and sunny. Environmental factors and the frequency that dairy cows used each area were measured during four days, for 8 h each day. The shaded areas were the most used by dairy cows and presented the lowest mean values of all environmental factors. Solar radiation was the environmental factor with most potential to classify the dairy cow's decision to access shaded areas. Data mining is a machine learning technique with great potential to characterize the influence of the thermal environment in the cows' decision at the pasture.