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. 2025 Jan 4:103:skaf128.
doi: 10.1093/jas/skaf128.

Assessing the impact of climatic conditions and feeding systems on the quality of raw bovine milk in Spain

Styliani Roufou  1 , Lydia Katsini  2 , Sholeem Griffin  1   3 , Carolina S Silva  4 , Monika Polańska  2 , Ismael Martínez Lede  5 , Jan F M Van Impe  2 , Vasilis P Valdramidis  1   3   6
Affiliations

Assessing the impact of climatic conditions and feeding systems on the quality of raw bovine milk in Spain

Styliani Roufou et al. J Anim Sci. .

Abstract

The dairy industry faces significant challenges from climate change, requiring a deeper understanding of how climatic factors influence raw milk composition and quality. The aim of this study was to evaluate the impact of climatic variables, such as temperature, solar radiation, and carbon dioxide levels, on raw milk parameters, including somatic cell count, protein percentage, fat, and total bacterial count. Selectivity ratio and Spearman rank correlation analyses identified key associations. This study analyzed data from 53 farms in northern Spain (2014 to 2019), using 2 feeding systems: Total Mixed Ration and Hand Feeding. Temperature and solar radiation negatively correlated with fat (r = -0.68, P < 0.05), protein (r = -0.71, P < 0.05), and dry lean percentages (r = -0.65, P < 0.05), while average temperature positively correlated with somatic cell count (r = 0.70, P < 0.05). Total bacterial count showed a negative correlation with carbon dioxide levels (r = -0.66, P < 0.05). Among the climatic variables, solar radiation, and carbon dioxide were highlighted as the most influential factors through selectivity ratio analysis. Additionally, Total Mixed Ration feeding systems appeared to support better metabolic adaptation, underscoring the importance of balanced diets in mitigating climate-induced stress. These findings emphasize the need for improved farm management practices to address climate change impacts on milk quality.

Keywords: climate change; correlation analysis; feed ratio composition; milk composition; multivariate analysis.

Plain language summary

Dairy cows face significant challenges due to climate change, which affects their health and the quality of milk they produce. One of the primary issues is the impact of weather conditions, such as temperature, solar radiation, and carbon dioxide levels, on milk composition. This study investigated how these environmental factors influence milk quality parameters like fat, protein, and somatic cell count (a measure linked to cow health) in 53 farms across northern Spain. Data were collected over 6 yr (2014 to 2019), and an additional analysis comparing 2 feeding systems was held: Total Mixed Ration (TMR), where cows receive a balanced diet tailored to their needs, and Hand Feeding (HAND), where feed proportions are not precisely controlled. Advanced statistical methods highlighted that higher temperatures and sunlight levels negatively affected milk fat, protein, and dry lean percentages while increasing somatic cell counts. Balanced diets provided through TMR helped cows better adapt to these environmental stresses. Understanding the interplay between climate factors and milk quality is essential for developing effective farm management practices. This knowledge can help farmers adopt feeding strategies and environmental interventions to sustain milk production and improve cow well-being under changing climatic conditions.

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Figures

Graphical Abstract
Graphical Abstract
Figure 1.
Figure 1.
Pretreatment analysis of the milk quality parameters originating from pooled farms in the Galicia region of Spain, from 2014 to 2019 and color-coded according to their respective farms. A red line indicates the mean values for each milk variable, while a blue line represents the standard deviation (N = 53). Milk quality parameters (A) Fat (%) (B) Protein (%) (C) Dry Lean (%) (D) SCC (log10Cell/L) and (E) TBC (log10Cell/L)
Figure 2.
Figure 2.
Based on the PLS models, a selection of climatic parameters to predict raw milk quality parameters. Milk quality parameters (A) Fat (%) (B) Protein (%) (C) Dry Lean (%) (D) SCC (log10Cell/L) and (E) TBC (log10Cell/L). “NaN” represents Not a Number. Variables with values below the predefined threshold were considered non-significant and thus treated as NaN. - - Dashes colored lines represent all the farms data, red line represents the mean value, blue line represents the mean ± the standard deviation.
Figure 3.
Figure 3.
Selection of climatic parameters to predict raw milk quality in TMR feeding systems based on the PLS models. The frequency of each climatic variable selected across years from the selectivity ratio is shown in these graphs. (A) Fat (%), (B) Protein (%), (C) Dry Lean (%), (D) SCC (log10Cell/L), (E) TBC (log10Cell/L). “NaN” represents Not a Number and denotes values that were below the predefined threshold and considered non-significant.
Figure 4.
Figure 4.
Selection of climatic parameters to predict raw milk quality in HAND feeding systems based on the PLS models. The frequency of each climatic variable selected across years from the selectivity ratio is shown in these graphs. (A) Fat (%), (B) Protein (%), (C) Dry Lean (%), (D) SCC (log10Cell/L), (E) TBC (log10Cell/L). “NaN” represents Not a Number and denotes values that were below the predefined threshold and considered non-significant.
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