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Introduction. Precision Livestock Farming (PLF) is spreading rapidly in intensive cattle farms. It is based on the monitoring of individuals using different kinds of sensors. Applied to grazing animals, PLF is mainly based on the recording of three parameters: the location, the posture and the movements of the animal. Until now, several techniques have been used to discriminate grazing and ruminating behaviors with accuracies over 90% on average, when compared to observations, providing valuable tools to improve the management of pasture and grazing animals. However, bites and jaw movements are still overlooked, even though they are of utmost importance to assess the animal grazing strategies for various pasture types and develop future techniques allowing better estimation of their intake. Literature. The goal of this review is to explore the possibility of monitoring the individual jaw movements and the differentiation of bites in grazing animals. For this purpose, (1) the mechanisms of forage intake in cattle are explained briefly in order to understand the movements performed by the cow, especially during grazing, (2) the various sensors that have been proposed to monitor jaw movements of ruminants such as mechanical sensors (pressure sensors), acoustic sensors (microphone) and electromyography sensors are compared and (3) finally the relationship between jaw movements, biting behavior and forage intake is discussed. Conclusions. The review clearly demonstrated the abilities of mechanical, acoustic and electromyography sensors to classify the difference types of jaw movements. However, it also indicated a wide range of accuracies and different observation windows required to reach these accuracies when compared to the observed movement. This classification purpose could lead to a better detection of more specific behavior, e.g. bite detection, and their exact location on pasture.

The dairy industry represents 13% of the turnover of the European food industry and north-west Europe produces 60% of the European milk. However, in 2014 the milk market has experienced a substantial fall in milk prices of some 50%. At these lower prices for milk the business of many milk producers is not sustainable. Due to recent advances, the mid-infrared (MIR) analysis of milk performed within milk recording (MR) promises more information than used traditionally. Beside the established MR parameters (protein, fat, lactose, and urea), the spectra could provide additional information on cows' status for a range of characteristics (e.g. fertility, health, energy balance, feeding and methane emission). Thus, the spectra routinely obtained from the MIR analysis of milk offer a possibility to develop novel, cost-effective tools which enable milk producers to improve the management of their dairy herds and in turn reduce the costs for milk production. The OptiMIR project aims to improve the sustainability of the dairy sector by developing and providing innovative, economical and standardized MIR-based tools for the management of dairy herds. Additionally, the project aims to create and promote a framework for the cross-border exchange of information and practices to enhance the service of milk recording organizations (MROs) in north-west Europe and to strengthen their competitiveness. In order to achieve these objectives, in 2011 the European OptiMIR project was officially launched for a 5-year-period. The INTERREG IV B funded OptiMIR project is a cooperation between three research centers, three universities, 11 MROs, and one laboratory from six north-western European countries. To accomplish the goals, the different processes from the identification of the priority areas to the development, validation, and implementation of the novel tools were outlined in three working packages comprising 10 actions. A common transnational database combines the phenotypic data of the cows and the MIR spectra from the European MR, which enables the detection of relevant phenotypic traits and their reflection in the MIR spectra. Additionally, a standardization has been installed among all instruments of the milk analyzing laboratories involved in the OptiMIR project to ensure a stable prediction over time and a correction of deviations. Due to the monthly standardization process the developed prediction equations can be used in routine on all instruments taking part in the standardization. Different models for the prediction of the pregnancy status, energy balance, the methane emission as well as the detection of ketosis and acidosis have been developed within OptiMIR. It is worth mentioning, that those models predict the status of the animal with different accuracies and that progress on development and implementation differs between the models. Some of the tools developed within OptiMIR are already used in the field and provide dairy farmers with useful information e.g. about the health status or methane emission of a certain cow. The OptiMIR project also resulted in a collaborative planning on an economic interest group formation of the participating MROs. The final OptiMIR scientific and expert meeting disseminates the results obtained through OptiMIR more detailed and also provides an overview of recent advances in the development of management tools for the dairy sector. Initial application of the MIR-based tools has shown their potential for providing dairy farmers with information to improve their herd management in a cost-effective way. However, further research and development is required to finish a greater extend of MIR-based tools so that north-western European stakeholders can acquire competitive advantage in the dairy sector.

Improvements after precision dietary management of nitrogen rejection in two commercial dairy farms in Wallonia. Two dairy farms located in Pays de Herve and in Ardennes were followed at regular intervals in order to assess levels of nitrogen rejection. In Farm 1, the cows were divided into two groups: group HP contained high production cows and group BP contained cows with a lower production yield. Each group was offered a specific basal diet. In Farm 2, only one group of cows was assessed. The feed rations on both farms were characterized by a imbalance between the yields allowed by the energy or the nitrogen supplies and by an extremely high OEB balance of 794, 582 and 726 g, respectively, in groups HP and BP and in the Farm 2 group. Dietary changes were proposed in order to balance milk yields and to reduce the hypothesized nitrogen balance. The yield and urea content data from each milk record, along with data regarding nitrogen rejection, were statistically analyzed using a mixed model, which included an autoregressive covariance. The data from records 2, 3, 4 and 5 were then compared to the data from record 1. The advised changes implemented in the feeding management plan maintained milk yields at values similar to the yields observed in record 1 – 36.2, 24.3 and 23.0 l of 4% fat-corrected milk expressed for fixed days in milk produced by groups HP and BP and the Farm 2 group. The changes induced a significant reduction in the milk urea content (220 vs 300 mg·l-1) and a significant reduction in nitrogen rejection, whether expressed in terms of g per day per cow, g·l-1 or kg per year per cow. The cows in the Farm 2 group rejected less nitrogen in absolute terms (217.9 vs 260.1 g per day). However, it is interesting to note that the management approach in Farm 1 was more efficient in terms of nitrogen rejection since the level was on average 9 g·l-1 in comparison with 10 g·l-1 in Farm 2. In conclusion, it appears that, for either farm, whether an intensive or extensive management regime was being employed, the provision of well balanced feed rations led to a reduction in nitrogen rejection. It should, however, be noted that management advice needs to be provided on a farm by farm basis.

The main objective of this paper is the use of milk composition data as a management tool. Milk composition, and in particular, milk fat content and fatty acid profiles may be significantly altered due to a variety of factors. These factors are reviewed in the literature; they include diet, animal (genetic) selection, management aspects and animal health. Changes in milk composition can be used as an indicator of the animal's metabolic status or the efficiency of the feed management system. The advantages of using this kind of data as a management tool would be to allow the early detection of metabolic or management problems. The present review suggests that milk and, especially milk fat composition may be used as a sustainability management tool and as a monitoring and prevention tool for several pathologies or health disorders in dairy cattle. Further, due to the use of mid-infrared spectrometry (MIR) technology, these tools may be easily implemented in practice and are relatively cheap. In the field, milk labs or milk recording agencies would be able to alert farmers whenever threshold values for disease were reached, allowing them to improve their dairy production from an economic, ecological and animal (welfare) point of view.

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