Relationship between climatic variables and the variation in bulk tank milk composition using canonical correlation...

Area of Science:

• Agricultural Science
• Environmental Science
• Dairy Science

Background:

• Previous studies on climate and milk composition used limited univariate methods.
• Understanding climate's influence on dairy production is crucial for farm management.

Purpose of the Study:

• To investigate the impact of climatic variables on milk composition, price, and monthly production using a multivariate approach.
• To compare univariate and multivariate statistical methods in analyzing climate-dairy farm relationships.

Main Methods:

• Utilized bulk tank milk data (composition, price, production) from 2014-2016.
• Employed canonical correlation analysis, a multivariate technique.
• Compared results with univariate correlation analysis.

Main Results:

• Univariate analysis showed minimal correlation between climate and milk composition.
• Canonical correlation revealed a strong, significant relationship (r_c=0.95, p=0.0029).
• Ambient temperature (mean, min, max) and temperature-humidity index (THI) were key variables; 10.2% of output variation linked to climate.

Conclusions:

• Multivariate analysis effectively captures complex climate-dairy production interactions.
• Ambient temperature and THI are critical factors influencing milk composition, price, and production.
• Findings highlight the need for climate-adaptive dairy farming strategies.