Is It Possible to Estimate the Composition of a Cow’s Diet Based on the Parameters of Its Milk?
Ana Villar,
Gregorio Salcedo,
Ibán Vázquez-González,
Elena Suárez and
Juan Busqué
Additional contact information
Ana Villar: Centro de Investigación y Formación Agrarias (CIFA), Gobierno de Cantabria, 39600 Muriedas, Spain
Gregorio Salcedo: CIFP “La Granja”, 39792 Heras, Spain
Ibán Vázquez-González: Departamento de Economía Aplicada, Escola Politécnica Superior de Enxeñaría de Lugo, Universidade de Santiago de Compostela (USC), 27002 Lugo, Spain
Elena Suárez: Predictia Intelligent Data Solutions, 39005 Santander, Spain
Juan Busqué: Centro de Investigación y Formación Agrarias (CIFA), Gobierno de Cantabria, 39600 Muriedas, Spain
Sustainability, 2021, vol. 13, issue 8, 1-15
Abstract:
Understanding the composition of a cow’s diet through the analysis of its milk is very useful in the linking of the product consumed with the systems involved in its production. The aim of this study is to show the diet–milk composition relationship using correspondence analysis and multiple linear regression analysis. This study analyzed 174 tank milk samples taken from 89 commercial farms located in “Green Spain”. Sampling was performed in two different periods: autumn 2016 and spring 2017. The correspondence analysis allowed for study into the general relationships between diet components and their relationship with the composition of milk (chemical composition, fatty acid profile (FA), and fat-soluble antioxidants (FSA)). The model used to estimate the percentage of fresh grass (FG) in the diet had a high predictive power (R aj 2 > 0.7), and the explanatory variables included in the model were linolenic acid (C18:3-n3), vaccenic acid ( trans11 -C18:1), and cis12 -C18:1. The regression equation was applied to the 174 tank milk samples individually. To evaluate the equation’s predictive capacity, different thresholds for the dry matter percentage of fresh grass in the ration were marked (15%, 20%, 25%, and 30%), above which milk could be considered “grass-fed milk”, and below which, “not grass-fed milk”. The equation is considered valid when it correctly classifies the sample. The highest percentage of success (89.7%) was obtained by marking a threshold of 25% FG. When analyzing the misclassified milk samples, that is, where the equation did not classify the milk sample well according to its fresh grass composition, it was observed that the majority of cases corresponded to milk samples that came from herds fed with fresh grass above the marked threshold (>25%) but with a high content of concentrate in the ration. The conclusion is that the percentage of concentrate in the diet has a very important influence on the fatty acid profile of milk, particularly with respect to fresh grass. This is in such a way that anywhere above a concentrate content of >30%, the equation’s capacity to estimate the percentage of fresh grass decreases.
Keywords: grass-fed milk; diet authentication; fatty acid profile; carotenoids; multiple linear regression analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:13:y:2021:i:8:p:4474-:d:537765
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