New applications of mid InfraRed testing potential implications for dairy farmers and the dairy supply chain.

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1 New applications of mid InfraRed testing potential implications for dairy farmers and the dairy supply chain. B Bartlett, National Milk Laboratories, Fox Talbot House, Greenways Business Park, Chippenham, Wiltshire Benb@nmr.co.uk BACKGROUND It is easy to forget the extent to which dairy cow management has changed over the last 20 years. Gone are the days when it was economically viable for a herdsman to manage a small number of cows, knowing each one as individuals without having to refer to paperwork or computerised systems to verify treatment records or fertility status. Commercial pressures are such that the herdsman now has to be capable of managing a much larger number of cows whilst at the same time ensuring the attention to detail at individual cow level to optimise herd performance. The extent of the change since the early 1990 s is reflected in 1993 guidance notes provided to prospective dairy farmers in the US which indicated that usually one person can take 45 cows or approximately 65 hours per cow annually. 20 years later and Kite research shows showed that for 14 South West dairy herds the average labour input was just 39 hours per cow per year (Kite 2009). Another way of looking at this is litres of milk per labour unit. Analysis conducted in New South Wales, Australia (State of New South Wales Primary Industries, 2007) showed an average of 400,000 litres per labour unit, but some of the larger farms in the state achieving over 800,000 litres per labour unit. This remarkable increase in output per labour unit has been achieved through advances in our understanding of the dairy cow and the application of relevant technology on farm to aid cow management. So what else can we do? This paper explores the potential to further our understanding of the dairy cow through the assessment of mid infra red tests on individual cow milk samples and how the information gained from this analysis has the potential to generate additional gains in terms of cow performance and the nutritional value of outputs from the dairy herd. Milk spectral data may be used to predict individual fatty acids but may also prove useful in adding information to the prediction of energy balance, mastitis, fertility and other performance measures. TACKLING THE LIFETIME YIELD PERFORMANCE GAP In terms of opportunities for improvement in the UK dairy herd, the potential is considerable. This is very clear when looking at the range in performance of milk recorded herds. An analysis of NMR data for the month of November 2011 shows the gulf in performance in lifetime yield between the top and bottom of the industry (Table 1)

2 Table 1: Range in Lifetime Yield Herd Averages (Nov 2011) Average lifetime yield (litres per day) Top 10% of NMR herds Bottom 10% of NMR herds Source: NMR Putting this into context, whilst a 200 cow herd in the top 10% banding will achieve an annual output of 1.08m litres in lifetime yield terms, a 200 cow herd in the bottom 10% banding will achieve an annual output of just 440,920 litres. Clearly one of the challenges facing the industry is narrowing this performance gap in a sustainable fashion. Addressing the challenge will require the use of all available data to identify cow performance issues before they become critical and costly. With the inevitable reduction in cow observation time, tools for providing early warning signals of trends in cow health and performance are going to be key. Good fats and bad fats Data gained from the detailed analysis of milk fat has the potential to provide new insights into cow health and therefore deliver new cow management tools for dairy farmers that will help in tackling this challenge. Milk fat is made from individual fatty acid molecules that are attached to glycerol, a 3-carbon backbone. The fatty acid profile in milk is complex and is determined by a combination of genetics, body fat mobilisation and feed. The function of the rumen is pretty remarkable in that, for example, from 600 grams of 10 different dietary fatty acids the cow will produce approximately 1200 grams of 400 different dairy fatty acids. Of course this process will differ from cow to cow and from herd to herd. Some fats are good fats delivering benefits in terms of human health, whilst others are bad with links to cholesterol problems in humans and subsequent obesity. Generally saturated fatty acids are classed as being bad fats whilst unsaturated fats are classed as good. It is the saturated fat content in cow s milk that has brought the dairy industry to the attention of various health agencies around the world. This is because certain saturated fats cause an elevation in cholesterol levels which in turn is linked to obesity and cardiovascular disease. Obesity in the GB population is a substantial concern currently, particularly given the findings of research such as the Foresight report commissioned by the DTI and conducted by the Department of Health in This report estimated the total annual cost of obesity to be around 6.6bn to 7.4bn.

3 The current UK target for saturated fat intake is 11% of total energy intake, whilst actual figures are over 13%. With the GB dairy industry contributing over 25% of saturated fat in the diet it is not surprising that our industry has drawn this attention. What is interesting is that there is evidence that cows that produce fat that is good for the human diet are themselves healthier. Of course if this can be proven across a range of UK dairy farming systems and if the profile of milk fat can be economically changed, the scope for the dairy industry to develop a healthier and more productive herd and at the same time enhance the contribution the industry makes to the GB diet would be significant. Some organisations have already taken steps to tap into the potential to adjust fatty acid profiles in milk. In October 2011 Marks and Spencer launched their healthier milk initiative which involves the sale of milk that is naturally lower in saturated fat so much so that M&S estimate that the reduction represents 84 tonnes of saturated fat being taken from its customers diets each year. It is quite likely that others will follow suit in the near future and it is certainly the case that similar initiatives are already being pursued elsewhere in Europe. USE OF FATTY ACID PROFILING DATA It is against this background that NMR has been developing the infrastructure to utilise fatty acid profile information as a new aid to management decisions on farm. Detailed analysis of the milk sample is now possible through advances in testing technology and increased computing power, with the ability to handle significant volumes of data in a manner that could only be dreamed of a few years ago. - Analysis of the fatty acid profile of GB herds Up until recently the primary method for measuring fatty acid profiles in milk was through gas chromatography. Whilst this method is very precise, the method is slow and costly so is not practical as a tool to aid herd management. However, fatty acid profiles can now be established through mid Infra Red (mir) testing at a fraction of the cost of using gas chromatography the same technology that is used for testing milk both for payment purposes and for milk recording. mirinvolves the testing machineinga stream of milk taken from an ordinary preserved milk sample. The light is then reflectedonto a plate and then assessed against milk calibrations This technique then involves assessing the resultant spectrum and calculating the proportion of key constituents such as fat and protein utilising the calibration data. This is the technique that is now being extended to include the calculation of key fatty acids as well as the total fat. Back in 2009 National Milk Laboratories commenced trials utilising this technology. After a year of validation testing, in November 2010 NML was able to commence a programme of testing monitoring bulk milks from across the GB milk pool. This research has thrown up some very interesting findings. The graph below shows the trend in saturated fat percentages across the GB herd over the year. As can be seen there is a marked seasonal variation. This is to be expected given the high level of unsaturated fat found in fresh grass and other similar forages, whilst many components of winter rations are higher in saturated fat.

4 Source: NML In addition NML research has established that there is a wide range across the GB industry. The graph below shows that in November 2011 the overall industry average %SFA was approx 69%, but at the extremes some herds had an SFA % of under 57% whilst others had a % SFA of over 80%.

5 Source: NML Again the reasons for the range in SFA percentages are complex and varied, but the two primary drivers are feeding and breeding. Due to the association between the fatty acid profile in milk and the health of the cow, certain feed companies in GB are already using fatty acid profiling as a tool to assess the nutritional status of dairy herds. This of course then raises the question regarding making management decisions based on herd level data. If all cows within the herd tend to maintain a very similar profile then this broad approach could be adequate. However early analysis of the individual cow profiles within specific herds has shown that the range can be marked. The graph below shows the % SFA results for individual cows plotted against their fat % results based on initial tests conducted on normal NMR recorded samples.

6 Source: NML Some cows can be seen to be producing fat of over 5.5% with SFA results below 60%, whilst others are showing much lower fat results with SFA s that are well over 70%. It should be noted that this testing was conducted using equipment calibrated for bulk milk samples and not individual cow milk samples, so the results are only indicative, but the results are still striking, indicating a need to understand factors affecting the fat:% SFA ratio. In addition there is a need to explore other relationships such as cow health and productivity performance against the fatty acid profile (including specific fatty acids as well as fatty acid groups such as saturated fats). Fatty acid profiles and genetics As well as assessing phenotypic data, there is the opportunity to explore genetic data to establish the extent to which geneticscontrols the fatty acid profile in milk. Considerable work has already been done in this field, including research conducted by a team at the University of Liege in Belgium. This study showed a strong element of heritability in determining fatty acid profiles, with some fatty acids being under stronger genetic control than the controldetermined by the diet and by body fat mobilisation. Estimates for saturated short- and medium-chain individual FA ranged from 0.35 for C4:0 to 0.44 for C8:0, whereas those for monounsaturated long-chain individual FA were lower (around 0.18). Of course theheritability of the fatty acid profile will not only manifest itself in milk, but also in beef from the dairy herd. Given that red meat is the largest contributor of saturated fat in the GB diet, this is clearly another important factor to consider.

7 With the advent of genomics there is a real prospect that significant advances can be made in the genetic makeup of the UK dairy cow such that she will respond well to feeding strategies designed to change the fatty acid profile in the milk that she produces. Thus a strategy for the UK could be to use routinely generated milk spectral data to predict a range of new phenotypes such as fatty acids, and then use those data to produce genetic (and genomic) evaluations for fatty acids profile. This will provide farmers with options in addition to feeding when looking to modify milk constituents. TURNING RESEARCH FINDINGS INTO GAINS FOR THE DAIRY FARMER Considerable research has already been undertaken into the links between fatty acid profiles and technical cow performance. Indeed at last year s Cattle Breeders Conference Roel Veerkamp gave an update on progress with the RobustMilk project (a project involving six EU research organisations which focussed on this specific area). However there is still much work to be done to strengthen the analyses undertaken to date and to unravel the complex dynamics that exist in different farm scenarios. In these difficult economic times, some might question whether the industry can afford the time and resource to undertake this work. However the potential prize at the end of this journey is a very big one for the GB dairy industry with the prospect of feeding and breeding programmes that will improve cow health (with all the consequential benefits in terms of improved productivity and reduced replacement costs) and also strengthen the nutritional value of milk within the human diet (with benefits in terms of new market opportunities for the industry). As a result the importance of this research is arguably stronger than ever and perhaps the question is whether the UK industry can afford not to develop this technology. The industry is still some way off from achieving these ideals, but good progress is being made with help from various research partners. NMR and SAC areparticipants in the Optimir project ( a four year project involving 17 organisations across 5 EU member states which is co-funded by the European Regional Development Fund. This project is pulling together expertise from various different EU research centres and is pooling information captured from the mid infra red analysis of milk samples alongside phenotypic data with the objective of delivering new decision support tools relating to fertility, health, feeding and the environment. Clearly initial outputs from such research will need to be handled with care but as the use of these tools becomes more widespread, it is anticipated that they will become part of the normal toolkit for the modern dairy farmer.

8 CONCLUSIONS With the use of the latest technology, the UK dairy industry has the opportunity to unlock tools to boost cow performance through detailed analysis of the simple milk sample. Such analysis has the potential to deliver additional benefits in terms of cow health and productivity and also strengthen the credentials of dairy products within the human diet. The subject area is complex, so these new tools will need to be handled with care and further research is needed to minimise the risk of unintended consequences occurring when adjusting fatty acid profiles, but given the scale of the potential benefits, the industry needs to fully embrace the research. Once the research organisations have fulfilled their roles, the challenge will turn to service providers to convert research findings into practical, effective and cost efficient commercial offerings. This is where organisations such as NML will have a role to play. In addition the input of consultants, feed reps and breeding advisors will be key. Getting the combination of information and advice right has the potential to help farmers tackle the lifetime yield performance gap through driving gains in cow productivity and health and help the industry tackle the challenge currently at its door regarding the healthiness of dairy in the diet. References Kite Consulting (2009) Stevens, B and Ricketts R (1993). Before you go into Dairying (University of Missouri) McKormick B Economic costs of obesity and the case for government intervention Obesity Reviews (2007) 8 (Department of Health, London, UK) C. Bastin, N Gengler, H Soyeurt: Phenotypic and genetic variability of production traits and milk fatty acid contents across days in milk for Walloon Holstein first-parity cows (University of Liège, Gembloux Agro-Bio Tech, Animal Science Unit, B-5030 Gembloux, Belgium) Journal of Dairy Science, Volume 94