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ABSTRACT: Increasing consumer concerns underscore the importance of verifying the practices and origins of food, especially certified premium products. The aim of this study was to evaluate the ability of Fourier-transform mid-infrared (FT-MIR) spectroscopy to authenticate animal welfare parameters, farming practices, and dairy systems. Data on farm characteristics were obtained from the Parmigiano Reggiano Consortium in northern Italy. Animal welfare data were collected by trained veterinarians using the assessment protocol developed by the Italian National Reference Center for Animal Welfare (CReNBA), and bulk milk test-day data were obtained from the laboratory of the Breeders Association of the Emilia Romagna Region. A merged final dataset of 12,083 bulk FT-MIR spectra records from 949 farms was created. Using a nonhierarchical clustering approach, the farms were classified into 5 dairy systems: 2 traditional systems comprising farms located in either the Apennines or the Po Plain; 2 modern systems, one that used TMR and one did not; and one traditional dairy system comprising farms rearing local breeds. To evaluate the ability of bulk milk to capture differences in farming systems, we conducted an ANOVA on milk composition. The linear models included the following effects: season, dairy system, farm, and the interaction between dairy system and season. The effect of the dairy system was significant for all milk composition traits. A 10-iteration linear discriminant analysis was used to evaluate the discriminative ability of the spectra in classifying farming practices and dairy systems. The average results of the area under the receiver operating characteristic curve revealed good authentication performance for genetic type (0.98), housing system (0.91), and feeding system (0.89), and medium-low authentication performance for geographical area (0.70); poor results were obtained for the percentage of concentrate in the diet and animal welfare parameters (0.57–0.64). With regard to dairy systems, the best result was obtained when dairy systems were grouped into 2 simplified categories, traditional versus modern (0.89), instead of the 5 categories (0.87). The results of this study show that FT-MIR is a useful tool for authenticating farming practices and dairy systems, but not animal welfare as defined by CReNBA evaluation criteria. Our results show that infrared spectroscopy has the potential to authenticate dairy products and quality label certifications.

ABSTRACT: The study of the complex relationships between milk metagenomics and milk composition and cheese-making efficiency as affected by indoor farming and summer highland grazing was the aim of the present work. The experimental design considered monthly sampling (over 5 mo) of the milk produced by 12 Brown Swiss cows divided into 2 groups: the first remained on a lowland indoor farm from June to October, and the second was moved to highland pastures in July and then returned to the lowland farm in September. The resulting 60 milk samples (2 kg each) were used to analyze milk composition, milk coagulation, curd firming, and syneresis processes, and to make individual model cheeses to measure cheese yields and nutrient recoveries in the cheese. After DNA extraction and Illumina Miseq sequencing, milk microbiota amplicons were also processed by means of an open-source pipeline called Quantitative Insights Into Microbial Ecology (Qiime2, version 2018.2; https://qiime2.org). Out of a total of 44 taxa analyzed, 13 bacterial taxa were considered important for the dairy industry (lactic acid bacteria, LAB, 5 taxa; and spoilage bacteria, 4) and for human (other probiotics, 2) and animal health (pathogenic bacteria, 2). The results revealed the transhumant group of cows transferred to summer highland pastures showed an increase in almost all the LAB taxa, bifidobacteria, and propionibacteria, and a reduction in spoilage taxa. All the metagenomic changes disappeared when the transhumant cows were moved back to the permanent indoor farm. The relationships between 17 microbial traits and 30 compositional and technological milk traits were investigated through analysis of correlation and latent explanatory factor analysis. Eight latent factors were identified, explaining 75.3% of the total variance, 2 of which were mainly based on microbial traits: pro-dairy bacteria (14% of total variance, improving during summer pasturing) and pathogenic bacteria (6.0% of total variance). Some bacterial traits contributed to other compositional-technological latent factors (gelation, udder health, and caseins).

A dramatic increase of the demand for products of animal origin is expected to occur due to: i) the exponential growth of world’s population, which should reach 9 billion people in 2050, according to FAO predictions, ii) the process of urbanization which will likely lead to a concentration of 60% of the population in urban areas by the same year, and iii) the increase of income of a large part of the population in emergent countries such as China and India. So far, the increased demand for food has been supplied by agriculture due to improvement of techniques, increase of cultivated land areas and increase of consumption of water and energy. Despite that, unequal food distribution throughout the world has lead to almost 1 billion undernourished or starving people at the first decade of the twenty-one century. In the future, it will be necessary to achieve a sustainable supply of food, especially of animal origin, because land and other production factors are not unlimited resources. This work deals with related problems and possible sustainable solutions for the increasing demand for products of animal origin, by a detailed analysis of the Animal footprint, i.e. the Ecological footprint of animal production.