# Relationship between milk intrinsic quality scores and the environmental impact scores of dairy farms

M Lepoivre, C Laurent, Bruno Martin, P.-M Grollemund, Raphaëlle Botreau, F Monsallier, S Hulin, P Gerber, Christophe Chassard, M Coppa

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## To cite this version:

M Lepoivre, C Laurent, Bruno Martin, P.-M Grollemund, Raphaëlle Botreau, et al.. Relationship between milk intrinsic quality scores and the environmental impact scores of dairy farms. 3rd Mountain Livestock Farming Systems Meeting, INRAE; VetAgroSup; Université Clermont Auvergne, Jun 2024, Clermant-Ferrand, France. hal-04934387

HAL Id: hal-04934387

https://hal.science/hal-04934387v1

Submitted on 7 Feb 2025

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# Relationship between milk intrinsic quality scores and the environmental impact scores of dairy farms

M. Lepoivreª, C. Laurentᵇ, B. Martinᵇ, P.-M. Grollemundᶜ, R. Botreauᵇ, F. Monsallierᵈ, S. Hulinᵉ, P. Gerberᵉ, C. Chassardª, M. Coppaᵇ

## 1. Introduction

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Growing societal expectation concerning product quality and the environmental impact of farming system.

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Available assessments of the intrinsic quality of milk and the environmental impacts of dairy farms, but with limitations concerning multidisciplinary, the cost of certain analyses, the time required to collect descriptive data

### AIMS:

* To developed an operational method for multi-criteria assessment of milk quality and environmental impacts from a recently published multi-criteria assessment methodology

* To study the correlations between milk quality and environmental impacts of farms

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ª Université Clermont Auvergne, UMR Fromages, France

ᵇ Université Clermont Auvergne, INRAE, VetAgro Sup, UMR Herbivores, France

ᶜ Université Clermont Auvergne, CNRS, LMBP, France

ᵈ Chambre d'Agriculture du Cantal, France

ᵉ Pôle Fromager AOP Massif Central, France

f University of Turin, Italy

## 2. Materials & methods

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2 adaptations of the environmental impact assessment proposed by Botreau et al. (2018):

* exclusive use of the indicators present in the CAP'2ER® tool

* use of weighted averages to aggregate indicators → criteria → principles → dimensions

3 adaptations of the intrinsic milk quality assessment for cheese production proposed by Rey-Cadilhac et al. (2021):

* selection of indicators that can be only obtained by spectroscopy

* transformation of quantitative data into qualitative data for few indicators (Coppa et al., 2017)

* use of weighted averages to aggregate indicators → criteria → subcriteria → principles → dimensions

## 3. Results & discussion

### A new assessment of:

* milk quality based on 4 dimensions, 16 criteria and 26 indicators

* environmental impact based on 5 dimensions, 6 criteria and 6 indicators

<figure><img src="image_7.png" /><figcaption>Fig. 1: Projection of the 15 farms into the first factorial plane of PCA</figcaption></figure>

Plane from the Principal Component Analyse carried out on the 4 milk quality scores and the 5 environmental quality dimensions scores

Large scattering of the farms on the plane: good sensitiveness of the models

<table><caption>Table 1: Relationship between the scores of the intrinsic dimensions of milk quality and those of the environmental dimensions in the 15 audited dairy farms</caption><thead><tr><th>Pearson's correlations</th><th>Climate change</th><th>Eutrophication</th><th>Acidification</th><th>Resources</th><th>Ecosystem Biodiversity</th></tr></thead><tbody><tr><th>Sensory</th><td>0.10 ns</td><td>-0.33 ns</td><td>-0.19 ns</td><td>0.46 †</td><td>0.01 ns</td></tr><tr><th>Technological</th><td>-0.47 †</td><td>-0.44 †</td><td>-0.50 †</td><td>0.01 ns</td><td>-0.08 ns</td></tr><tr><th>Health</th><td>0.33 ns</td><td><strong>0.56 *</strong></td><td>0.09 ns</td><td>-0.22 ns</td><td>0.43 ns</td></tr><tr><th>Nutritional</th><td>-0.33 ns</td><td>0.42 ns</td><td>0.08 ns</td><td>-0.51 †</td><td>0.44 ns</td></tr></tbody></table>

*= p-value <0,05; † = p-value between 0,05 and 0.10; ns = non significant

<figure><img src="image_8.png" /><figcaption>Fig. 2: Relationship between the global environmental impact score and the annual average milk quality score in the 15 farms in the sample</figcaption></figure>

No correlation between overall milk quality and overall environmental impact scores

Example of significant or trending relationships between dimensions and the main characteristics of farms with the best scores

↑ eutrophication score

↑ health score

large share of permanent pasture surfaces on UAA + long time spent grazing all year round + low stocking rates + late age at first calving + large share of forage area on UAA

## 4. Conclusion

Sensitivity of the multi-criteria evaluation model tested

→ **model to be test on a larger scale and in different contexts**

No correlations between overall quality and overall environmental impact scores

→ **not easy to target top milk quality and low environmental impacts**

Some milk quality dimensions of were correlated with some specific environmental impacts

→ **need to focus the milk quality or environmental targets to choose the agricultural to be implemented**

## REFERENCES

* Botreau R., Beauchet S., Laurent C., Hulin S., Hérisset R., Thiollet-Scholtus M., Kanyarushoki C., Boucault P., Renaud-Gentié C., Jourjon F. 2018. Innov. agron. 63, 23-42

* Coppa M., Revello-Chion A., Giaccone D., Tobacco E. and Borreani G. 2017. J. Dairy Sci. 100:8705-8721

* Rey-Cadhilac L., Botreau R., Ferlay A., Hulin S., Hurtaud C., Lardy R., Martin B., Laurent C. 2021. Animal 15, 100264