Verification of fresh grass feeding, pasture grazing and organic farming by cows farm milk fatty acid profile

HS-GC-IMS and HS-SPME/GC-MS coupled with E-nose and E-tongue reveal the flavors of raw milk from different regions of China

Milk authentication requires identification of the origin and assessment of the aroma characteristics. In this study, we analyzed 24 raw milk samples from different regions of China by profiling volatile flavors using headspace solid phase microextraction-gas chromatography-mass spectrometry, headspace gas chromatography-ion mobility spectrometry, and intelligent sensory technology (E-tongue and E-nose). The flavor of raw milk in Southern and Northern China had evident differences based on the intelligent sensory technology. However, the differences among the samples from the northeast, northwest, and central regions were not significant. Correlations between milk origin and volatile compounds based on variable importance prediction > 1 and principal component analysis results revealed differential compounds including pyridine, nonanal, dodecane, furfural, 1-decene, octanoic acid, and 1,3,5,7-cyclooctatetraene. Our study findings provided a deeper understanding of the geographical differences in raw milk volatile compounds in China.

Preliminary Feasibility of Near-Infrared Spectroscopy to Authenticate Grazing in Dairy Goats through Milk and Faeces Analysis

Consumers are increasingly prone to request information about the production systems of the food they buy. For this purpose, certification and authentication methodologies are necessary not only to protect the choices of consumers, but also to protect producers and production systems. The objective of this preliminary work was to authenticate the grazing system of dairy goats using Near-Infrared Spectroscopy (NIRS) analyses of milk and faeces of the animals. Spectral information and several mathematical pre-treatments were used for the development of six discriminant models based on different algorithms for milk and faeces samples. Results showed that the NIRS spectra of both types of samples had some differences when the two feeding regimes were compared. Therefore, good discrimination rates were obtained with both strategies (faeces and milk samples), with classification percentages of up to 100% effectiveness. Discrimination of feeding regime and grazing authentication based on NIRS analysis of milk samples and an alternative sample such as faeces is considered as a potential approach for dairy goats and small ruminant production.

Biomarkers for cheese authentication by detailed and fast gas chromatographic profiling of triacylglycerol fatty acids

Unsaturated fatty acid isomers and odd- and branched-chain fatty acids (OBCFAs) in milk triacylglycerols (TAGs) can be quantitated using gas chromatography (GC), providing access to biomarkers of animal species, breeds, diet, geographic origin, and environmental conditions. Such analysis requires expensive cyanopropyl siloxane or ionic liquid columns of at least 50 m in length, which increases the elution time. Aiming to use GC for cheese authentication and characterization while keeping the experiment time short and maintaining a good separation between fatty acid (FA) isomers, we considered using a 30 m polyethylene glycol-2-nitroterephthalate column. The FAs thus quantitated allowed the discovery of specific biomarkers for the origins of cheese varieties highly consumed in several countries. In addition, the simple and multivariate correlations we found between FAs in the cheese TAG matrix were alternative means for characterization and authentication purposes.

Buffalo milk and rumen fluid metabolome are significantly affected by green feed

The use of green feed for livestock breeding is an important strategy to encounter both the increasing demand for animal derived products and the perceptions of the consumers regarding animal welfare and sustainability. The aim of this study was to compare different feeding strategies in lactating water buffaloes by using a metabolomic approach. The study was carried out on 32 milking buffaloes that were randomly divided into two groups for a total period of 90 days (3 sampling times). DD Group (dry diet) received a standard total mixed ratio (TMR) characterized by dry forages and concentrates; ZG Group (zero grazing) fed an isoenergetic and isoproteic diet obtained using 30% of sorghum as green forage. Samples of milk and rumen fluid were analyzed by liquid chromatography-mass spectrometry (LC-MS) techniques. Data analyses revealed the presence of several differentially accumulated metabolites and among these, ten compounds were putatively identified in milk samples (i.e. L-carnitine, acetylcarnitine, propionylcarnitine, butyrylcarnitine, 2-methylbutyroylcarnitine, 2-hexenoylcarnitine, hexanoylcarnitine, glycerophosphocholine, δ-valerobetaine and γ-butyrobetaine) and four in rumen fluid (3-(2-hydroxyphenyl) propanoate, Indole-3-acrylic acid, oleamide (cis-9,10-octadecenoamide) and 20-carboxy-leukotriene B4). The modulation of these molecules in buffalo milk is significantly related to the green/dry based feeding and some the natural compound detected could be considered as health-promoting nutrients.

Comparative evaluation of miniaturized and conventional NIR spectrophotometer for estimation of fatty acids in cheeses

The miniaturization of near-infrared spectrometers has been growing rapidly. Several designs are now available, but there is a lack of understanding of how spectral data from these designs are affected by complex matrices and what are the limitations when compared to established systems. This study compares a popular miniaturized NIR device based on Hadamard-transform spectrometer (named miniaturized NIR) with a system based on dispersive spectrometer (named handheld-NIR) to assess: 1) their predictive performance; 2) the effect of a complex matrix on the performance, and 3) ability to discriminate multiples compounds in that matrix. The devices were challenged with a wide range of cheese types (n = 36) from different species (cow, goat, ewe and buffalo), brands (n = 30), countries of origin (n = 9) and with a broad range of cheese matrices (soft, fresh, semi-hard, hard and aged) to predict fat composition. Spectra were collected non-invasively with no sample preparation. Three wavelength ranges from handheld NIR were compared to miniaturized NIR based on two modelling approaches were used: a linear (Partial Least Square - PLS) and a non-linear (Support Vector Machine - SVM). The important wavelengths for each model were identified and used to assess the ability of the spectral data to differentiate among fatty acids. The highest prediction performance was observed for saturated fatty acids (C4.0, C14.0, C15.0 C16.0, total SCF and total SFA) with the RPD_EXT-VAL for the external validation dataset presenting values higher than 3 and the coefficient of determination for the external validation dataset (R²_EXT-VAL) higher than 0.89, mostly for SVM models. The sum of fatty acids also shows good prediction performance with RPD_EXT-VAL higher than 3 and R²_EXT-VAL higher than 0.89. Models with RPD_EXT-VAL between 2 and 3 includes: C6.0; C17.0; C18.0; C10.1; C16.1; C17.1; iso.C15.0; iso.C.16; iso.C17; C18.1.c11; C18.1.c9; anteiso C17; total MUFA; and total BCFA. The cheese matrix affected the linearity between spectral data and fatty acids concentration requiring a more complex model (SVM), but this effect was not enhanced by the instrument type. It was shown that the spectral information allows discrimination among fatty acids and this ability was not affected by the type of instrument. These findings demonstrated that the miniaturized NIR can be directly applied to a cheese matrix to monitor fatty acid composition with results equivalent to an optical-based design.

Prediction of Indirect Indicators of a Grass-Based Diet by Milk Fourier Transform Mid-Infrared Spectroscopy to Assess the Feeding Typologies of Dairy Farms

This research aims to develop a predictive model to discriminate milk produced from a cattle diet either based on grass or not using milk mid-infrared spectrometry and the month of testing (an indirect indicator of the feeding ration). The dataset contained 3,377,715 spectra collected between 2011 and 2021 from 2449 farms and 3 grazing traits defined following the month of testing. Records from 30% of the randomly selected farms were kept in the calibration set, and the remaining records were used to validate the models. Around 90% of the records were correctly discriminated. This accuracy is very good, as some records could be erroneously assigned. The probability of belonging to the GRASS modality allowed confirmation of the model's ability to detect the transition period even if the model was not trained on this data. Indeed, the probability increased from the spring to the summer and then decreased. The discrimination was mainly explained by the changes in the milk fat, mineral, and protein compositions. A hierarchical clustering from the averaged probability per farm and year highlighted 12 groups illustrating different management practices. The probability of belonging to the GRASS class could be used in a tool counting the number of grazing days.

Ambient mass spectrometry for rapid authentication of milk from Alpine or lowland forage

Metabolomics approaches, such as direct analysis in real time-high resolution mass spectrometry (DART-HRMS), allow characterising many polar and non-polar compounds useful as authentication biomarkers of dairy chains. By using both a partial least squares discriminant analysis (PLS-DA) and a linear discriminant analysis (LDA), this study aimed to assess the capability of DART-HRMS, coupled with a low-level data fusion, discriminate among milk samples from lowland (silages vs. hay) and Alpine (grazing; APS) systems and identify the most informative biomarkers associated with the main dietary forage. As confirmed also by the LDA performed against the test set, DART-HRMS analysis provided an accurate discrimination of Alpine samples; meanwhile, there was a limited capacity to correctly recognise silage- vs. hay-milks. Supervised multivariate statistics followed by metabolomics hierarchical cluster analysis allowed extrapolating the most significant metabolites. Lowland milk was characterised by a pool of energetic compounds, ketoacid derivates, amines and organic acids. Seven informative DART-HRMS molecular features, mainly monoacylglycerols, could strongly explain the metabolomic variation of Alpine grazing milk and contributed to its classification. The misclassification between the two lowland groups confirmed that the intensive dairy systems would be characterised by a small variation in milk composition.

Characterization of Fat Quality in Cow Milk from Alpine Farms as Influenced by Seasonal Variations of Diets

Simple Summary

Milk produced in Alpine farms under pasture- and-grass-based feeding systems is characterized by beneficial nutritional traits, which are linked to its high fat quality. In this study, milk samples collected in two alpine farms set in the Italian Piedmont region were analyzed together with samples of feedstuffs (pasture, fresh grass, concentrates and total mixed ration) furnished to cows during summer and winter, when the feeding strategy was modified. The results suggested a favorable fat composition of all samples analyzed, with some differences detected between the seasons and the farms. The milk obtained following a pasture- or fresh-grass-based feeding strategy (during summer) showed a higher fat quality, which was characterized by higher amounts of beneficial fatty acids. Particularly, a distinctive fat composition of milk samples coming from cows exclusively fed on pasture during the summer season was evidenced. The outcomes obtained in this study contributed toward evaluating and promoting alpine dairy products from the Alpine region as products associated with an added value, with beneficial effects for both producers and consumers.

Abstract

The production systems linked to mountain animal husbandry have had an environmental, social and cultural role in recent years. Zootechnical systems based on feeding strategies, such as pasture grazing and grass-fed strategies, contribute to a significant increase in the relative amounts of favorable fatty acids (FAs) in animal products, indicating their ability to improve the long-term health of consumers. In this study, we compared different feeding strategies in two small mountain farms in the Piedmont Alpine region, Italy. Particularly, during the summer season, the two farms were distinguished by the exclusive employment of Alpine pasture (farm A), assumed as the best way to improve the quality of the FA profile in milk vs. the supply of daily fresh cut mountain grass plus a reduced implementation with hay and concentrates directly in the barn (farm B). The milk fatty acid profile was analyzed using gas chromatography. The results showed the high quality of alpine milk collected in the two farms. Even with some differences, particularly evidenced when comparing the summer diets, the milk FA profiles in farm A and farm B were favorable from a nutritional point of view in both seasons. Milk samples obtained using the exclusive employment of alpine grazing during summer were represented by an FA profile of higher quality (lower saturated FAs, higher branched FAs and monounsaturated FA, favorable n6/n3 ratio). However, milk obtained using the integrated strategy (fresh grass plus concentrates in the barn farm B) resulted in a more homogenous composition during the summer season, with a higher concentration of polyunsaturated FAs. These outcomes suggested that the integrated strategy, even if related to a lower ability in improving milk FA profile, could represent a valid and cost-effective alternative for mountain farmers to obtain an overall superior quality of milk, which was not strictly linked to the grazing practice. The multivariate analysis showed that information contained in the milk FA profile may provide a valuable tool that can distinguish mountain-grass-based diet.

The Effect of Verbal and Iconic Messages in the Promotion of High-Quality Mountain Cheese: A Non-Hypothetical BDM Approach

To ensure the sustainable development of mountain livestock farming, the adequate remuneration of high-quality dairy products is fundamental. In this sense, communication strategies aimed at promoting mountain products and ensure better positioning and higher market prices are fundamental. The present research seeks to expand the literature regarding consumers' willingness to pay for mountain foods by using an online real auction experiment aimed at evaluating the premium price that consumers are willing to pay for summer over winter mountain cheese, depending on the information provided concerning the taste anticipation or animal welfare. The results showed an overall small premium price given to the higher quality summer cheese; this could be, partially, due to a generally low degree of consumer knowledge about mountain dairy farming. With reference to communication strategies, the results provide evidence about the effectiveness of the rational messages founded upon sensorial characteristics and the anticipated taste of cheese. In addition, this study explored that adding a logo had no main effect on the price premium participants were willing to pay. This may be due to the fact that logos and claims, having a lower information content, are more indicated to lead the choice of consumers with a higher level of awareness. In the conclusion section, policy and agribusiness implications of the findings are provided.

The Combination of Vibrational Spectroscopy and Chemometrics for Analysis of Milk Products Adulteration

Milk products obtained from cow, goat, buffalo, sheep, and camel as well as fermented forms such as cheese, yogurt, kefir, and butter are in a category of the most nutritious foods due to their high contents of high protein contributing to total daily energy intake. For certain reasons, high price milk products may be adulterated with low-quality ones or with foreign substances such as melamine and formalin which are added into them; therefore, a comprehensive review on analytical methods capable of detecting milk adulteration is needed. The objective of this narrative review is to highlight the use of vibrational spectroscopies (near infrared, mid infrared, and Raman) combined with multivariate analysis for authentication of milk products. Articles, conference reports, and abstracts from several databases including Scopus, PubMed, Web of Science, and Google Scholar were used in this review. By selecting the correct conditions (spectral treatment, normal versus derivative spectra at wavenumbers region, and chemometrics techniques), vibrational spectroscopy is a rapid and powerful analytical technique for detection of milk adulteration. This review can give comprehensive information for selecting vibrational spectroscopic methods combined with chemometrics techniques for screening the adulteration practice of milk products.

Advances in Atypical FT-IR Milk Screening: Combining Untargeted Spectra Screening and Cluster Algorithms

Fourier-transform mid-infrared spectrometry is an attractive technology for screening adulterated liquid milk products. So far, studies on how infrared spectroscopy can be used to screen spectra for atypical milk composition have either used targeted methods to test for specific adulterants, or have used untargeted screening methods that do not reveal in what way the spectra are atypical. In this study, we evaluate the potential of combining untargeted screening methods with cluster algorithms to indicate in what way a spectrum is atypical and, if possible, why. We found that a combination of untargeted screening methods and cluster algorithms can reveal meaningful and generalizable categories of atypical milk spectra. We demonstrate that spectral information (e.g., the compositional milk profile) and meta-data associated with their acquisition (e.g., at what date and which instrument) can be used to understand in what way the milk is atypical and how it can be used to form hypotheses about the underlying causes. Thereby, it was indicated that atypical milk screening can serve as a valuable complementary quality assurance tool in routine FTIR milk analysis.

Invited review: A 2020 perspective on pasture-based dairy systems and products

Grazing pasture is the basis for dairy production systems in regions with temperate climates, such as in Ireland, New Zealand, parts of Australia, the United States, and Europe. Milk and dairy products from cows on pasture-based farms predominantly consuming fresh grazed grass (typically classified as "grass-fed" milk) have been previously shown to possess a different nutrient profile, with potential nutritional benefits, compared with conventional milk derived from total mixed ration. Moreover, pasture-based production systems are considered more environmentally and animal welfare friendly by consumers. As such, there is significant potential for market capitalization on grass-fed dairy products. As competition in this space increases, the regulations of what constitutes as grass-fed vary between different regions of the world. With this in mind, there is a need for clear and independently accredited grass-fed standards, defining the grass-fed criteria for labeling of products as such, subsequently increasing the clarity and confidence for the consumer. This review outlines the numerous effects of pasture production systems on dairy product composition, nutritional profile, and sustainability, and highlights potential future methods for authentication.

Can FT-Mid-Infrared Spectroscopy of Milk Samples Discriminate Different Dietary Regimens of Sheep Grazing With Restricted Access Time?

Milk obtained from sheep grazing natural pastures and some forage crops may be worth a plus value as compared to milk obtained from stall-fed sheep, due to their apparently higher content of beneficial fatty acids (FAs). Fourier transformed mid-infrared (FT-MIR) analysis of FA can help distinguish milk from different areas and diverse feeding systems. The objective was to discriminate milk from sheep and milk from dairy sheep rotationally grazing Italian ryegrass or berseem clover for 2, 4, or 6 h/day. To test this hypothesis, a data-mining study was undertaken using a database of 1,230 individual milk spectra. Data were elaborated by principal component analysis (PCA) and analyzed by linear discriminant analysis (LDA) with or without the use of genetic algorithm (GA) as a variable selection tool with the primary aim to discriminate grazed forages (grass vs. legume), access time (2, 4, or 6 h/day), grazing day (first vs. last grazing day during the 7-day grazing period), and the milking time (morning vs. afternoon milking). The best-fitting discriminant models of FT-MIR spectra were able to correctly predict 100% of the samples differing for the pasture forage, 91.9% of the samples differing for grazing day, and 97.1% of the samples regarding their milking time. The access time (AT) to pasture was correctly predicted by the model in 60.3% of the samples, and the classification ability was improved to 77.0% when considering only the 2 and 6 h/day classes.

Fourier Transform Infrared Spectroscopy as a Tool to Study Milk Composition Changes in Dairy Cows Attributed to Housing Modifications to Improve Animal Welfare

Animal welfare status is assessed today through visual evaluations requiring an on-farm visit. A convenient alternative would be to detect cow welfare status directly in milk samples, already routinely collected for milk recording. The objective of this study was to propose a novel approach to demonstrate that Fourier transform infrared (FTIR) spectroscopy can detect changes in milk composition related to cows subjected to movement restriction at the tie stall with four tie-rail configurations varying in height and position (TR1, TR2, TR3 and TR4). Milk mid-infrared spectra were collected on weekly basis. Long-term average spectra were calculated for each cow using spectra collected in weeks 8–10 of treatment. Principal component analysis was applied to spectral averages and the scores of principal components (PCs) were tested for treatment effect by mixed modelling. PC7 revealed a significant treatment effect (p = 0.01), particularly for TR3 (configuration with restricted movement) vs. TR1 (recommended configuration) (p = 0.03). The loading spectrum of PC7 revealed high loadings at wavenumbers that could be assigned to biomarkers related to negative energy balance, such as β-hydroxybutyrate, citrate and acetone. This observation suggests that TR3 might have been restrictive for cows to access feed. Milk FTIR spectroscopy showed promising results in detecting welfare status and housing conditions in dairy cows.

A comprehensive review on non-clinical methods to study transfer of medication into breast milk - A contribution from the ConcePTION project

Breastfeeding plays a major role in the health and wellbeing of mother and infant. However, information on the safety of maternal medication during breastfeeding is lacking for most medications. This leads to discontinuation of either breastfeeding or maternal therapy, although many medications are likely to be safe. Since human lactation studies are costly and challenging, validated non-clinical methods would offer an attractive alternative. This review gives an extensive overview of the non-clinical methods (in vitro, in vivo and in silico) to study the transfer of maternal medication into the human breast milk, and subsequent neonatal systemic exposure. Several in vitro models are available, but model characterization, including quantitative medication transport data across the in vitro blood-milk barrier, remains rather limited. Furthermore, animal in vivo models have been used successfully in the past. However, these models don't always mimic human physiology due to species-specific differences. Several efforts have been made to predict medication transfer into the milk based on physicochemical characteristics. However, the role of transporter proteins and several physiological factors (e.g., variable milk lipid content) are not accounted for by these methods. Physiologically-based pharmacokinetic (PBPK) modelling offers a mechanism-oriented strategy with bio-relevance. Recently, lactation PBPK models have been reported for some medications, showing at least the feasibility and value of PBPK modelling to predict transfer of medication into the human milk. However, reliable data as input for PBPK models is often missing. The iterative development of in vitro, animal in vivo and PBPK modelling methods seems to be a promising approach. Human in vitro models will deliver essential data on the transepithelial transport of medication, whereas the combination of animal in vitro and in vivo methods will deliver information to establish accurate in vitro/in vivo extrapolation (IVIVE) algorithms and mechanistic insights. Such a non-clinical platform will be developed and thoroughly evaluated by the Innovative Medicines Initiative ConcePTION.

Physicochemical Composition, Antioxidant Status, Fatty Acid Profile, and Volatile Compounds of Milk and Fresh and Ripened Ewes' Cheese from a Sustainable Part-Time Grazing System

We conducted the first nutritional analysis of dairy products from the traditional Roja Mallorquina sheep breed. Samples of bulk raw milk were taken twice a month from December 2015 to March 2016 from sheep fed using a part-time grazing system, and fresh soft (FC, n = 8) and ripened (RC, n = 8) cheeses were made. The variability in vitamins, total phenolic compounds (TPC), total antioxidant capacity (TAC), and fatty acid (FA) content was influenced by the cheese-making process (differences between the cheese and the original milk) and by the type of cheese-making technology (mainly related to heating, the use of starter culture, and ripening). The most notable physicochemical characteristic of the cheeses was low fat content (24.1 and 29.6 g/100 g for FC and RC). Milk and RC were characterised by major concentrations of retinol (211.4 and 233.6 μg/100 g dry matter (DM), respectively) and TPC (18.7 and 54.6 μg/100 g DM, respectively), while FC was characterised by major concentrations of retinol (376.4 μg) and α-tocopherol (361.7 μg). The fat-soluble components of the FC generally exhibited better nutritional value for human health than those of the milk and RC, with a higher level of retinol and α-tocopherol; lower values for saturated FA, atherogenic, and thrombogenic indices; and higher levels of monounsaturated FA, polyunsaturated FA, n-3, and n-6. Acids, alcohols, and ketones comprised almost 95% of the volatile compounds detected. Acetoin and products of lactose and citrate metabolism played an important role in the development of the aromatic attributes of both kinds of cheese. This preliminary study can contribute to add value to these traditional products according to healthy nutritional criteria and supports the implementation of strategies to promote their commercialisation and obtain product labelling as “pasture-fed” or specific marks.

Analysis of oxylipins to differentiate between organic and conventional UHT milks

Nowadays, there is a strong interest in analytical approaches for assessing organic farming practices. Here, we propose that oxylipins, a group of oxidised metabolites derived from various polyunsaturated fatty acids, could be promising biomarkers for organic milk assessment because their biosynthesis is modulated by both precursor fatty acid availability and physiological or pathological status. Thus, we determined 31 fatty acids, 53 triacylglycerols and 37 oxylipins in one hundred commercial UHT milks by chromatographic methods coupled to mass spectrometry. Of these, 52 milks were conventional (34 whole milk, 11 semi-skimmed milk and 7 skimmed milk) and 48 were organic (31 whole milk, 11 semi-skimmed milk and 6 skimmed milk). Several oxylipins (8-HEPE, 5-HEPE, 11-HEPE, 9-HEPE, 18-HEPE, 9-HOTrE, 13-HOTrE, 12,13-DiHODE and 15,16-DiHODE) could distinguish between organic and conventional milks. Within these oxylipins, arachidonic and linoleic acid derived do not correlate with their fatty acid precursors; therefore these oxylipins could be promising as not only diet-dependent biomarkers for organic milk assessment.

Effects of ear corn silage supplementation on milk production and milk fatty acid profiles in grazing dairy farms

This study investigated the effects of substituting ear corn silage (ECS) for commercial formula feed on milk production and milk fatty acid profiles in grazing dairy farms during the summer season. A field survey was conducted on five grazing dairy farms in every summer month of 2017, 2018, and 2019. Three of the five farms substituted fresh ECS for the commercial formula feed at a ratio of 2:1 from July of each year (ECS farms). Other farms maintained the same feeding management as before (non-ECS farms). An interview survey was conducted on each farm to calculate feed intake and milk yield per cow. Feed and milk samples were collected in each survey. Milk compositions and milk fatty acid profiles were determined. The substitution of ECS for the commercial formula feed did not affect milk yield or milk composition, but ECS farms maintained low levels of milk urea compared with non-ECS farms (p < .01). The ECS substitution also influenced some of the milk fatty acid proportions; C16:0 and C16:1 increased, and trans-11 C18:1, cis-9,trans-11 C18:2, and the sum of polyunsaturated fatty acids decreased, while these fatty acid proportions were maintained in non-ECS farms throughout the summer season (p < .05).

The Mode of Grass Supply to Dairy Cows Impacts on Fatty Acid and Antioxidant Profile of Milk

The optimization of milk production includes a rational use of forages, respect for the environment and offers the best quality to consumers. Milk production based on grass and forages produces healthier milk and it is widely spread throughout the Atlantic arc to maximize milk yield per hectare. However, the mode of offering the grass can have a major influence on milk composition. The aim of this study was to evaluate the effect of grass supply mode (grazing, zero-grazing or ensiling) on dairy cows’ performance, with particular reference to fatty acids and fat-soluble antioxidants concentration. A three by three Latin square experiment was performed with 18 dairy cows. Experimental treatments consisted of exclusive feeding with grass silage and zero-grazing, both offered ad libitum indoors, or grazing for 24 h. The results showed that grazing cows had a higher dry matter intake and greater milk yield than cows feeding on grass silage and zero-grazing, as well as higher concentrations of protein, lactose, nonfat-solids and urea in milk than housed cows. Milk fat from grazing cows had a higher proportion of unsaturated fatty acids than from cows feeding on grass silage and zero-grazing, with significant differences in the proportion of vaccenic and rumenic acids. The 18:1 trans-11 to 18:1 trans-10 ratio is proposed as biomarker to identify the milk produced from the management system of grazing cattle. Milk from grazing cows had a greater proportion of lutein than cows eating grass silage, with the zero-grazing system having intermediate values. In conclusion, the mode of grass supply affects fatty acid and antioxidant profiles of milk.

Raman spectroscopy: A rapid method to assess the effects of pasture feeding on the nutritional quality of butter

The animal diet is a critical variable affecting the composition and functionality of dairy products. As "Grass-Fed" labeling becomes more prominent on the market, rapid and label-free methods for verification of feeding systems are required. This work proposes the use of Raman spectroscopy to study the effects of 3 different experimental cow feeding systems-perennial ryegrass pasture, perennial ryegrass with white clover pasture, and an indoor total mixed ration diet (TMR)-on the nutritional quality of sweet cream butter. The results demonstrate that Raman spectroscopy coupled with multivariate analysis is a promising approach to distinguish butter derived from pasture or conventional TMR feeding systems. A Pearson correlation analysis confirmed high positive correlations between the spectral bin at 1,657 cm^-1, ascribed to the stretching vibrations of C=C bonds, and concentrations of α-linolenic acid and conjugated linolenic acid (CLA) in butter, and in general with the concentration of n-3 and n-3+CLA fatty acids and polyunsaturated fatty acids in the samples. The yellow color indicative of the presence of carotenoids in butter, which has previously been suggested as a biomarker of pasture or "Grass-Fed" feeding, was also positively correlated with the data obtained from the Raman spectra. Raman spectroscopy could also be used to accurately predict indicators of the nutritional quality of butter, such as the thrombogenic index, which showed a strong negative correlation with the spectral bin at 3,023 cm^-1.

Determination of Fatty Acids Profile in Original Brown Cows Dairy Products and Relationship with Alpine Pasture Farming System

This study aimed to evaluate the relationships between fatty acids and the pattern that most contributes to discriminate between two farming systems, in which the main difference was the practice, or not, of alpine summer-grazing. Milk and cheese were sampled every month in two farms of Original Brown cows identical under geographical location and management during no grazing season point of view in the 2018 season. Fatty acids concentrations were determined by gas chromatography. The principal component analysis extracted three components (PCs). Mammary gland de novo synthetized fatty acids (C14:0, C14:1 n9, and C16:0) and saturated and monosaturated C18 fatty acids (C18:0, C18:1 n9c) were inversely associated in the PC1; PC2 included polyunsaturated C18 fatty acids (C18:2 n6c, C18:3 n3) and C15:0 while conjugated linoleic acid (CLA n9c, n11t) and fatty acids containing 20 or more carbon atoms (C21:0, C20:5 n3) were associated in the PC3. The processes of rumen fermentation and de novo synthesis in mammary gland that are, in turn, influenced by diet, could explain the relationships between fatty acids within each PC. The discriminant analyses showed that the PC2 included the fatty acids profile that best discriminated between the two farming systems, followed by PC3 and, lastly, PC1. This model, if validated, could be an important tool to the dairy industry.

Milk fat: opportunities, challenges and innovation

Milk fat is a high-value milk component that is processed mainly as butter, cheese, cream and whole milk powder. It is projected that approximately 35 million tonnes of milk fat will be produced globally by 2025. This surplus, enhances the need for diversification of milk fat products and the milk pool in general. Infant milk formula producers, for instance, have incorporated enzyme modified ("humanised") milk fat and fat globule phospholipids to better mimic human milk fat structures. Minor components like mono- and di-glycerides from milk fat are increasingly utilized as emulsifiers, replacing palm esters in premium-priced food products. This review examines the chemistry of milk fat and the technologies employed for its modification, fractionation and enrichment. Emerging processing technologies such as ultrasound, high pressure processing, supercritical fluid extraction and fractionation, can be employed to improve the nutritional and functional attributes of milk fat. The potential of recent developments in biological intervention, through dietary manipulation of milk fatty acid profiles in cattle also offers significant promise. Finally, this review provides evidence to help redress the imbalance in reported associations between milk fat consumption and human health, and elucidates the health benefits associated with consumption of milk fat and dairy products.

The use of milk Fourier transform mid-infrared spectra and milk yield to estimate heat production as a measure of efficiency of dairy cows

Background

Transformation of feed energy ingested by ruminants into milk is accompanied by energy losses via fecal and urine excretions, fermentation gases and heat. Heat production may differ among dairy cows despite comparable milk yield and body weight. Therefore, heat production can be considered an indicator of metabolic efficiency and directly measured in respiration chambers. The latter is an accurate but time-consuming technique. In contrast, milk Fourier transform mid-infrared (FTIR) spectroscopy is an inexpensive high-throughput method and used to estimate different physiological traits in cows. Thus, this study aimed to develop a heat production prediction model using heat production measurements in respiration chambers, milk FTIR spectra and milk yield measurements from dairy cows.

Methods

Heat production was computed based on the animal’s consumed oxygen, and produced carbon dioxide and methane in respiration chambers. Heat production data included 168 24-h-observations from 64 German Holstein and 20 dual-purpose Simmental cows. Animals were milked twice daily at 07:00 and 16:30 h in the respiration chambers. Milk yield was determined to predict heat production using a linear regression. Milk samples were collected from each milking and FTIR spectra were obtained with MilkoScan FT 6000. The average or milk yield-weighted average of the absorption spectra from the morning and afternoon milking were calculated to obtain a computed spectrum. A total of 288 wavenumbers per spectrum and the corresponding milk yield were used to develop the heat production model using partial least squares (PLS) regression.

Results

Measured heat production of studied animals ranged between 712 and 1470 kJ/kg BW^0.75. The coefficient of determination for the linear regression between milk yield and heat production was 0.46, whereas it was 0.23 for the FTIR spectra-based PLS model. The PLS prediction model using weighted average spectra and milk yield resulted in a cross-validation variance of 57% and a root mean square error of prediction of 86.5 kJ/kg BW^0.75. The ratio of performance to deviation (RPD) was 1.56.

Conclusion

The PLS model using weighted average FTIR spectra and milk yield has higher potential to predict heat production of dairy cows than models applying FTIR spectra or milk yield only.

Dairy farming system markers: The correlation of forage and milk fatty acid profiles from organic, pasture and conventional systems in the Netherlands

The relationships between the fatty acid (FA) composition in forage and milk (F&M) from different dairy systems were investigated. Eighty milk samples and 91 forage samples were collected from 40 farms (19 organic, 11 pasture and 10 conventional) in the Netherlands, during winter and summer. The FA profiles of F&M samples were measured with gas chromatography. The results showed that the F&M of organic farms were significantly differentiated from the F&M of other farms, both in summer and winter. The differences are likely due to the different grazing strategies in summer and different forage composition in winter. The Pearson's correlation results showed the specific relationship between individual FAs in forages and related milk. A PLS-DA model was applied to classify all milks samples, resulting in 87.5% and 83.3% correct classifications of training set and validation set.

Chemometric authentication of farming systems of origin of food (milk and ripened cheese) using infrared spectra, fatty acid profiles, flavor fingerprints, and sensory descriptions

Milk samples from 1264 cows in 85 farms were authenticated for different farming-systems using a 10-fold cross-validated linear-discriminant-analysis using Fourier-transform infrared spectra (FTIRS) and gas-chromatographic fatty-acid (FA) profiles. FTIRS gave correct classification greater than FAs (97.4% vs. 81.1%) during calibration, but slightly worse in validation (73.5% vs 77.3%) and their combination improved the results. All milk samples were processed into ripened model-cheeses, and analyzed by near-infrared-spectrometry (NIRS), by proton-transfer-reaction time-of-flight mass-spectrometry for their volatile organic compound (VOCs) fingerprint and by panel sensory profiling (SENS). Farming-system authentication on cheese samples was less efficient than on milk, but still possible. The instrumental methods yielded similar validation results, better than SENS, and their combination improved the correct classification rate. The efficiency of the different technics was affected by specific farming systems. In conclusion, dairy products could be discriminated for farming-systems with acceptable accuracy, but the methods tested differ in sampling procedure, rapidity and costs.

The "Grass-Fed" Milk Story: Understanding the Impact of Pasture Feeding on the Composition and Quality of Bovine Milk

Milk is a highly nutritious food that contains an array of macro and micro components, scientifically proven to be beneficial to human health. While the composition of milk is influenced by a variety of factors, such as genetics, health, lactation stage etc., the animal's diet remains a key mechanism by which its nutrition and processing characteristics can be altered. Pasture feeding has been demonstrated to have a positive impact on the nutrient profile of milk, increasing the content of some beneficial nutrients such as Omega-3 polyunsaturated fatty acids, vaccenic acid, and conjugated linoleic acid (CLA), while reducing the levels of Omega-6 fatty acids and palmitic acid. These resultant alterations to the nutritional profile of "Grass-Fed" milk resonate with consumers that desire healthy, "natural", and sustainable dairy products. This review provides a comprehensive comparison of the impact that pasture and non-pasture feeding systems have on bovine milk composition from a nutritional and functional (processability) perspective, highlighting factors that will be of interest to dairy farmers, processors, and consumers.

Influence of Supplemental Feed Choice for Pasture-Based Cows on the Fatty Acid and Volatile Profile of Milk

The purpose of this study was to examine the impact of a variety of supplemental feeds on the composition and quality of milk in a pasture-based dairy system. Four pasture-supplemented feeding systems were compared: Group 1 supplementation with 16% crude protein parlour concentrate (CONC); Group 2 supplementation with palm kernel expeller plus parlour concentrate (PKE); Group 3 supplemented with soya hulls plus parlour concentrate (SOYA); Group 4 was supplemented with molassed beet pulp plus parlour concentrate (BEET). Supplemental feeding system was demonstrated to have a significant effect on the size of native casein micelles and the gelation properties of milks. While CONC feeding produced significantly higher casein micelle size, gel strength (Young’s Modulus) was significantly negatively correlated with casein micelle size. Supplemental feeding system had a significant effect on a number of fatty acids (FA) and indices derived therefrom, including total saturated and unsaturated fatty acids, de novo produced FA, omega 3, and omega 6 FA. The volatile profile of milks was also affected by supplemental feed choice, whereby multivariate analysis demonstrated that the CONC diet was distinctly different to that of the PALM, SOYA, and BEET milks. Multivariate analysis demonstrated that it is possible to distinguish milks from different pasture-supplemented feeding systems by their FA profile.

Factors Influencing the Flavour of Bovine Milk and Cheese from Grass Based versus Non-Grass Based Milk Production Systems

There has been a surge in interest in relation to differentiating dairy products derived from pasture versus confined systems. The impact of different forage types on the sensory properties of milk and cheese is complex due to the wide range of on farm and production factors that are potentially involved. The main effect of pasture diet on the sensory properties of bovine milk and cheese is increased yellow intensity correlated to β-carotene content, which is a possible biomarker for pasture derived dairy products. Pasture grazing also influences fat and fatty acid content which has been implicated with texture perception changes in milk and cheese and increased omega-3 fatty acids. Changes in polyunsaturated fatty acids in milk and cheese due to pasture diets has been suggested may increase susceptibility to lipid oxidation but does not seem to be an issue to due increased antioxidants and the reducing environment of cheese. It appears that pasture derived milk and cheese are easier to discern by trained panellists and consumers than milk derived from conserved or concentrate diets. However, milk pasteurization, inclusion of concentrate in pasture diets, cheese ripening time, have all been linked to reducing pasture dietary effects on sensory perception. Sensory evaluation studies of milk and cheese have, in general, found that untrained assessors who best represent consumers appear less able to discriminate sensory differences than trained assessors and that differences in visual and textural attributes are more likely to be realized than flavour attributes. This suggests that sensory differences due to diet are often subtle. Evidence supports the direct transfer of some volatiles via inhalation or ingestion but more so with indirect transfer post rumen metabolism dietary components. The impact of dietary volatiles on sensory perception of milk and dairy products obviously depends upon their concentration and odour activity, however very little quantitative studies have been carried out to date. Some studies have highlighted potential correlation of pasture with enhanced “barny” or “cowy” sensory attributes and subsequently linked these to accumulation of p-cresol from the metabolism of β-carotene and aromatic amino acids or possibly isoflavones in the rumen. p-Cresol has also been suggested as a potential biomarker for pasture derived dairy products. Other studies have linked terpenes to specific sensory properties in milk and cheese but this only appears to be relevant in milk and cheese derived from unseeded wild pasture where high concentrations accumulate, as their odour threshold is quite high. Toluene also a product of β-carotene metabolism has been identified as a potential biomarker for pasture derived dairy products but it has little impact on sensory perception due to its high odour threshold. Dimethyl sulfone has been linked to pasture diets and could influence sensory perception as its odour threshold is low. Other studies have linked the presence of maize and legumes (clover) in silage with adverse sensory impacts in milk and cheese. Considerably more research is required to define key dietary related impacts on the flavour of milk and cheese.

Capacity of milk composition to identify the feeding system used to feed dairy cows

This Research Paper addresses the hypothesis that is possible to identify the type of feed used for dairy cows by means of the analysis of milk composition and the fatty acid profile of milk fat. Sixteen dairy farms were monitored during 1 year with quarterly visits between summer 2014 and spring 2015. Rations varied throughout the year due to annual dynamic change of forage production, forage rotation, variation of nutrient requirements according to physiological state of the animal, etc. The ingredients of the rations were analysed by cluster identifying five feeding systems based on the main ingredient of the diet: grazing, maize silage, grass silage, dry forage and concentrate. Milk composition could explain up to 91·3% of the total variability among feeding systems, while fatty acid profile could explain only up to 61·2% of total variability. However, when the sum of types of fatty acids and their ratios are taken, up to 93·5% of total variability could be explained. The maize silage system had the greatest milk yield, protein, solid non-fat and urea proportions, as well as the highest proportion of saturated fatty acid and lowest concentration of trans11 18 : 1, cis9 18 : 1 and 18 : 3 n3. Principal component analysis distinguishes the maize silage system from other feeding systems, both from milk composition and milk fatty acid profile. Concentrate system overlapped partially with the grazing, grass silage and dry forage systems. The latter systems had the highest concentrations of cis9 18 : 1, trans11 18 : 1 and 18 : 3, but there was no clear differentiation among them.

Partial least squares-discriminant analysis (PLS-DA) for classification of high-dimensional (HD) data: a review of contemporary practice strategies and knowledge gaps

This review highlights and discusses critically various knowledge gaps in classification modelling using PLS-DA for high dimensional data.

Characterization of Retail Conventional, Organic, and Grass Full-Fat Butters by Their Fat Contents, Free Fatty Acid Contents, and Triglyceride and Fatty Acid Profiling

In the Netherlands, butter is produced from milk originating from three different production systems: conventional, organic, and grass-fed cows. The aim of the current study was to characterize these types of butters, and pinpoint distinct compositional differences. Retail conventional (n = 28), organic (n = 14), and grass (n = 12) full-fat butters were collected during the winter and summer seasons. Samples were analyzed for their fat content, free fatty acid (FFA) content, and triglyceride (TG) and fatty acid (FA) profiles. The fat content was significantly lower in conventional butters than in organic butters and the FFA content was significantly lower in conventional butters compared with grass butters. Also, organic butters differed significantly from their conventional counterparts with regard to their TG and FA profiles. The TG profiles of the organic and grass butters did not differ significantly. The FA profiles of grass butters were less distinct, since only a few FAs differed significantly from conventional (six FAs) and organic (eight FAs) butters.

Quality characteristics, chemical composition, and sensory properties of butter from cows on pasture versus indoor feeding systems

This study evaluated the effects of 3 widely practiced cow feeding systems in the United States, Europe, and Southern Hemisphere regions on the characteristics, quality, and consumer perception of sweet cream butter. Fifty-four multiparous and primiparous Friesian cows were divided into 3 groups (n=18) for an entire lactation. Group 1 was housed indoors and fed a total mixed ration diet (TMR) of grass silage, maize silage, and concentrates; group 2 was maintained outdoors on perennial ryegrass-only pasture (GRS); and group 3 was maintained outdoors on a perennial ryegrass/white clover pasture (CLV). Mid-lactation butter was manufactured in triplicate with milk from each group in June 2015 (137±7d in milk) and was analyzed over a 6-mo storage period at 5°C for textural and thermal properties, fatty acid composition, sensory properties, and volatile compounds. The nutritional value of butters was improved by pasture feeding, and butter from pasture-fed cows had significantly lower thrombogenicity index scores compared with butters from TMR-fed cows. In line with these results, pasture-derived milks (GRS and CLV) produced butter with significantly higher concentrations of conjugated linoleic acid (cis-9,trans-11) and trans-β-carotene than TMR butter. Alterations in the fatty acid composition of butter contributed to significant differences in textural and thermal properties of the butters. Total mixed ration-derived butters had significantly higher hardness scores at room temperature than those of GRS and CLV. Onset of crystallization for TMR butters also occurred at significantly higher temperatures compared with pasture butters. Volatile analysis of butter by gas chromatography-mass spectrometry identified 25 compounds present in each of the butters, 5 of which differed significantly based on feeding system, including acetone, 2-butanone, 1-pentenol, toluene, and β-pinene. Toluene was very significantly correlated with pasture-derived butter. Sensory analysis revealed significantly higher scores for GRS-derived butter in several attributes including "liking" of appearance, flavor, and color over those of TMR butter. Partial least square regression plots of fatty acid profiles showed clear separation of butter derived from grazed pasture-based perennial ryegrass or perennial rye/white clover diets from that of a TMR system, offering further insight into the ability of fatty acid profiling to verify such pasture-derived dairy products.

Effect of pasture versus indoor feeding systems on raw milk composition and quality over an entire lactation

The aim of this study was to investigate the effects of different feeding systems on milk quality and composition. Fifty-four multiparous and primiparous Friesian lactating cows were divided into 3 groups (n=18) to study the effects of 3 feeding systems over a full lactation. Group 1 was housed indoors and offered a total mixed ration diet (TMR), group 2 was maintained outdoors on a perennial ryegrass pasture (referred to as grass), and group 3 was also grazed outdoors on a perennial ryegrass/white clover pasture (referred to as clover). Bulk milk samples were collected from each group at morning and afternoon milkings once weekly from March 11 to October 28 in 2015. Milk from pasture-fed cows (grass and clover) had significantly higher concentrations of fat, protein, true protein, and casein. The pasture feeding systems induced significantly higher concentrations of saturated fatty acids C11:0, C13:0, C15:0, C17:0, C23:0, and unsaturated fatty acids C18:2n-6 trans, C18:3n-3, C20:1, and C20:4n-6 and a greater than 2-fold increase in the conjugated linoleic acid C18:2 cis-9,trans-11 content of milk compared with that of the TMR feeding system. The TMR feeding system resulted in milks with increased concentrations of C16:0, C18:2n-6 cis, C18:3n-6 cis, C22:0 C22:1n-9, and C18:2 cis-10,trans-12. Principal component analysis of average fatty acid profiles showed clear separation of milks from the grazed pasture-based diets to that of a TMR system throughout lactation, offering further insight into the ability to verify pasture-derived milk by fatty acid profiling.

Discrimination of "grazing milk" using milk fatty acid profile in the grassland dairy area in Hokkaido

Milk produced by the grazing system, referred to as "grazing milk" contains many components required for human health. The milk fatty acid (FA) profile is strongly associated with the diet on the farms. In the present study, based on the FA profile of farmer's bulk milk, we determined how to discriminate between milk produced on grazing and on a confinement system. A field survey was conducted four times (grazing and confinement season) in the Konsen (29 farms) and Okhotsk (25 farms) area in Hokkaido. Farmer's bulk milk samples and details of feeding management were collected and the FA profile of milk was measured. Milk produced during the grazing season contained less C16:0 and cis-9 C16:0, and more C18:0, cis-9 C18:1, trans-11 C18:1, cis-9,12 C18:2, cis-9,trans-11 C18:2 and cis-9,12,15 C18:3 than milk produced during the confinement season. Discrimination analysis using 16 FA revealed that almost all milk samples were discriminated correctly (confinement season: 90% correct and 10% borderline, grazing season: 88% correct, 9% borderline and 3% incorrect). For farmers that were categorized incorrectly and were considered borderline in the grazing season, the dependency on pasture was low compared with that for farmers correctly discriminated. Therefore, to claim "grazing milk", a high dependency on pasture is required for grazing dairy farmers.