Evaluating mountain goat dairy systems for conversion to the organic model, using a multicriteria method

Organic farming conserves natural resources, promotes biodiversity, guarantees animal welfare and obtains healthy products from raw materials through natural processes. In order to evaluate possibilities of increasing organic animal production, this study proposes a farm-scale multicriteria method for assessing the conversion of dairy goat systems to the organic model. In addition, a case study in the Northern Sierra of Seville, southern Spain, is analysed. A consensus of expert opinions and a field survey are used to validate a list of potential indicators and issues for assessing the conversion, which consider not only the European Community regulations for organic livestock farming, but also agroecological principles. As a result, the method includes 56 variables integrated in nine indicators: Nutritional management, Sustainable pasture management, Soil fertility and contamination, Weed and pest control, Disease prevention, Breeds and reproduction, Animal welfare, Food safety and Marketing and management. The nine indicators are finally integrated in a global index named OLPI (Organic Livestock Proximity Index). Application of the method to a case study with 24 goat farms reveals an OLPI value of 46.5% for dairy goat farms located in mountain areas of southern Spain. The aspects that differ most from the agroecological model include soil management, animal nutrition and product marketing. Results of the case study indicate that the proposed method is easy to implement and is useful for quantifying the approximation of conventional farms to an organic model.     

Review: Towards the agroecological management of ruminants,pigs and poultry through the development of sustainable breeding programmes: I-selection goals and criteria

Agroecology uses natural processes and local resources rather than chemical inputs to ensure production while limiting the environmental footprint of livestock and crop production systems. Selecting to achieve a maximization of target production criteria has long proved detrimental to fitness traits. However, since the 1990s, developments in animal breeding have also focussed on animal robustness by balancing production and functional traits within overall breeding goals. We discuss here how an agroecological perspective should further shift breeding goals towards functional traits rather than production traits. Breeding for robustness aims to promote individual adaptive capacities by considering diverse selection criteria which include reproduction, animal health and welfare, and adaptation to rough feed resources, a warm climate or fluctuating environmental conditions. It requires the consideration of genotype×environment interactions in the prediction of breeding values. Animal performance must be evaluated in low-input systems in order to select those animals that are adapted to limiting conditions, including feed and water availability, climate variations and diseases. Finally, we argue that there is no single agroecological animal type, but animals with a variety of profiles that can meet the expectations of agroecology. The standardization of both animals and breeding conditions indeed appears contradictory to the agroecological paradigm that calls for an adaptation of animals to local opportunities and constraints in weakly artificialized systems tied to their physical environment.     

Towards a biological basis for predicting nutrient partitioning: the dairy cow as an example

Prediction of nutrient partitioning is a long-standing problem of animal nutrition that has still not been solved. Another substantial problem for nutritional science is how to incorporate genetic differences into nutritional models. These two problems are linked as their biological basis lies in the relative priorities of different life functions (growth, reproduction, health, etc.) and how they change both through time and in response to genetic selection. This paper presents recent developments in describing this biological basis and evidence in support of the concepts involved as they relate to nutrient partitioning. There is ample evidence that at different stages of the reproductive cycle various metabolic pathways, such as lipolysis and lipogenesis, are up or down regulated. The net result of such changes is that nutrients are channelled to differing extents to different organs, life functions and end-products. This occurs not as a homeostatic function of changing nutritional environment but rather as a homeorhetic function caused by the changing expression of genes for processes such as milk production through time. In other words, the animal has genetic drives and there is an aspect of nutrient partitioning that is genetically driven. Evidence for genetic drives other than milk production is available and is discussed. Genetic drives for other life functions than just milk imply that nutrient partitioning will change through lactation and according to genotype - i.e. it cannot be predicted from feed properties alone. Progress in describing genetic drives and homeorhetic controls is reviewed. There is currently a lack of good genetic measures of physiological parameters. The unprecedented level of detail and amounts of data generated by the advent of microarray biotechnology and the fields of genomics, proteomics, etc. should in the long-term provide the necessary information to make the link between genetic drives and metabolism. However, gene expression, protein synthesis etc, have all been shown to be environmentally sensitive. Thus, a major challenge in realising the potential afforded by this new technology is to be able to be able to distinguish genetically driven and environmentally driven effects on expression. To do this we need a better understanding of the basis for the interactions between genotypes and environments. The biological limitations of traditional evaluation of genotype × environment interactions and plasticity are discussed and the benefits of considering these in terms of trade-offs between life functions is put forward. Trade-offs place partitioning explicitly at the centre of the resource allocation problem and allow consideration of the effects of management and selection on multiple traits and on nutrient partitioning.     

Review: welfare of dairy cows in continuously housed and pasture-based production systems

There is increasing interest in the use of continuous housing systems for dairy cows, with various reasons put forward to advocate such systems. However, the welfare of dairy cows is typically perceived to be better within pasture-based systems, although such judgements are often not scientifically based. The aim of this review was to interrogate the existing scientific literature to compare the welfare, including health, of dairy cows in continuously housed and pasture-based systems. Although summarising existing work, knowledge gaps and directions for future research are also identified. The scope of the review is broad, examining relevant topics under three main headings; health, behaviour and physiology. Regarding health, cows on pasture-based systems had lower levels of lameness, hoof pathologies, hock lesions, mastitis, uterine disease and mortality compared with cows on continuously housed systems. Pasture access also had benefits for dairy cow behaviour, in terms of grazing, improved lying/resting times and lower levels of aggression. Moreover, when given the choice between pasture and indoor housing, cows showed an overall preference for pasture, particularly at night. However, the review highlighted the need for a deeper understanding of cow preference and behaviour. Potential areas for concern within pasture-based systems included physiological indicators of more severe negative energy balance, and in some situations, the potential for compromised welfare with exposure to unpredictable weather conditions. In summary, the results from this review highlight that there remain considerable animal welfare benefits from incorporating pasture access into dairy production systems.     

Farm characteristics related to on-farm cow mortality in dairy herds: a questionnaire study

Dairy cow mortality is an important animal welfare issue that also causes financial losses. The objective of this study was to identify farm characteristics and herd management practices associated with high on-farm cow mortality in Swedish dairy herds. A postal questionnaire was sent to farmers that had either high or low mortality rates for 3 consecutive years. The questionnaire consisted of five sections: ‘About the farm’, ‘Milking and housing’, ‘Feeding’, ‘Routines’ and ‘Lame and sick cows’. A total of 145 questionnaires were returned (response rate=33%). Ten of the 77 characteristics investigated met the inclusion criteria for multivariable analysis. The final logistic regression model included: herd size, breed, use of natural service bull, bedding improvement frequency and pasture system. Herds with Swedish Holstein as the predominant breed (odds ratio (OR) 22.9, 95% confidence interval (CI) 5.2 to 101.8) or with mixed breeds (OR 5.5, 95% CI 1.7 to 17.5) had a greater risk of being high mortality herds than herds that were predominantly Swedish Red (OR 1). Herds larger than 100 cows (OR 19.6, 95% CI 3.5 to 110.4) and herds with 50 to 99 cows (OR 13.8, 95% CI 3.2 to 60.6) had greater risk of mortality than herds numbering 35 to 50 cows (OR 1). Being a high mortality herd was also associated with having cows on exercise lots during the summer season (OR 3.6, 95% CI 1.3 to 9.9) compared with on pasture. A missing answer on the question of bedding improvement frequency was associated with high mortality herds. Overall, this study suggests that characteristics that are related to intensification of the dairy industry are also associated with high on-farm mortality of dairy cows.     

Implications of feed concentrate reduction in organic grassland-based dairy systems: a long-term on-farm study

In response to increasing efforts for reducing concentrate inputs to organic dairy production in grassland-rich areas of Europe, a long-term study was conducted, which assessed the impacts of concentrate reductions on cows’ performance, health, fertility and average herd age. In total, 42 Swiss commercial organic dairy cattle farms were monitored over 6 years (‘Y0’, 2008/09 until ‘Y5’, 2013/14). In comparison with overall data of Swiss herdbooks (including conventional and organic farms), the herds involved in the project had lower milk yields, similar milk solids, shorter calving intervals and higher average lactation numbers. During the first 3 project years farmers reduced the concentrate proportion (i.e. cereals, oilseeds and grain legumes) in the dairy cows’ diets to varying degrees. In Y0, farms fed between 0% and 6% (dietary dry matter proportion per year) of concentrates. During the course of the study they changed the quantity of concentrates to voluntarily chosen degrees. Retrospectively, farms were clustered into five farm groups: Group ‘0-conc’ (n=6 farms) already fed zero concentrates in Y0 and stayed at this level. Group ‘Dec-to0’ (n=11) reduced concentrates to 0 during the project period. Groups ‘Dec-strong’ (n=8) and ‘Dec-slight’ (n=12) decreased concentrate amounts by >50% and <50%, respectively. Group ‘Const-conc’ (n=5 farms) remained at the initial level of concentrates during the project. Milk recording data were summarised and analysed per farm and project year. Lactation number and calving intervals were obtained from the databases of the Swiss breeders’ associations. Dietary concentrate amounts and records of veterinary treatments were obtained from the obligatory farm documentations. Data were analysed with GLMs. Daily milk yields differed significantly between farm groups already in Y0, being lowest in groups 0-conc (16.0 kg) and Dec-to0 (16.7 kg), and highest in groups Dec-slight (19.6 kg) and Const-conc (19.2 kg). Milk yield decreases across the years within groups were not significant, but urea contents in milk decreased significantly during the course of the project. Milk protein, somatic cell score, fat–protein ratio, average lactation number, calving interval and frequency of veterinary treatments did not differ by group and year. In conclusion, 5 years of concentrate reduction in low-input Swiss organic dairy farms, affected neither milk composition, nor fertility and veterinary treatments. Milk yields tended to decline, but at a low rate per saved kilogram of concentrate.     

Mixture model for inferring susceptibility to mastitis in dairy cattle: a procedure for likelihood-based inference

A Gaussian mixture model with a finite number of components and correlated random effects is described. The ultimate objective is to model somatic cell count information in dairy cattle and to develop criteria for genetic selection against mastitis, an important udder disease. Parameter estimation is by maximum likelihood or by an extension of restricted maximum likelihood. A Monte Carlo expectation-maximization algorithm is used for this purpose. The expectation step is carried out using Gibbs sampling, whereas the maximization step is deterministic. Ranking rules based on the conditional probability of membership in a putative group of uninfected animals, given the somatic cell information, are discussed. Several extensions of the model are suggested.     

Random regression models for genetic evaluation of clinical mastitis in dairy cattle

A genetic analysis of longitudinal binary clinical mastitis (CM) data recorded on about 90 000 first-lactation Swedish Holstein cows was carried out using linear random regression models (RRM). This method for genetic evaluation of CM has theoretical advantages compared to the method of linear cross-sectional models (CSM), which is currently being used. The aim of this study was to investigate the feasibility and suitability of estimating genetic parameters and predicting breeding values for CM with a linear sire RRM. For validation purposes, the estimates and predictions from the RRM were compared to those from linear sire longitudinal multivariate models (LMVM) and CSM. For each cow, the period from 10 days before to 241 days after calving was divided into four 1-week intervals followed by eight 4-week intervals. Within each interval, presence or absence of CM was scored as '1' or '0'. The linear RRM used to explain the trajectory of CM over time included a set of explanatory variables plus a third-order Legendre polynomial function of time for the sire effect. The time-dependent heritabilities and genetic correlations from the chosen RRM corresponded fairly well with estimates obtained from the linear LMVM for the separate intervals. Some discrepancy between the two methods was observed, with the more unstable results being obtained from the linear LMVM. Both methods indicated clearly that CM was not genetically the same trait throughout lactation. The correlations between predicted sire breeding values from the RRM, summarized over different time periods, and from linear CSM were rather high. They were, however, less than unity (0.74 to 0.96), which indicated some re-ranking of sires. Sire curves based on the time-specific breeding values from the RRM illustrated differences in intercept and slope among the best and the worst sires. To conclude, a linear sire RRM seemed to work well for genetic evaluation purposes, but was sensitive for estimation of genetic parameters.     

Genotype by environment interaction for livability of dairy calves from first parity cows

Death of calves around parturition is a matter of concern for dairy farmers. Relatively high stillbirth rates and unfavourable trends have been reported for Holstein heifers in the Netherlands and several other countries. In our study, we investigated herd differences, genetic parameters and genotype by environment interaction for heifer calf livability. A large dataset with data from calvings between 1993 and 2012 of Dutch dairy farms was used. There were considerable differences between herds in livability of calves from heifers, with averages ranging from 74% to 95%. Both herds with relatively high and low averages showed the same negative trend between 1993 and 2012, with largest declines in herds with the lowest averages. We found that heritability and genetic variation of first parity livability were substantially larger in herd environments where the likelihood of stillbirth was high v. environments where stillbirth was at a low level. The genetic correlations between herd environment levels were all very close to unity, indicating that ranking of sires was similar for all environments. However, for herds with a relatively high stillbirth incidence selecting sires with favourable breeding values is expected to be twice as profitable as in herds with a relatively low stillbirth incidence.     

Selecting an appropriate genetic evaluation model for selection in a developing dairy sector

This study aimed to identify genetic evaluation models (GEM) to accurately select cattle for milk production when only limited data are available. It is based on a data set from the Pakistani Sahiwal progeny testing programme which includes records from five government herds, each consisting of 100 to 350 animals, with lactation records dating back to 1968. Different types of GEM were compared, namely: (1) multivariate v. repeatability model when using the first three lactations, (2) an animal v. a sire model, (3) different fixed effects models to account for effects such as herd, year and season; and (4) fitting a model with genetic parameters fixed v. estimating the genetic parameters as part of the model fitting process. Two methods were used for the comparison of models. The first method used simulated data based on the Pakistani progeny testing system and compared estimated breeding values with true breeding values. The second method used cross-validation to determine the best model in subsets of actual Australian herd-recorded data. Subsets were chosen to reflect the Pakistani data in terms of herd size and number of herds. Based on the simulation and the cross-validation method, the multivariate animal model using fixed genetic parameters was generally the superior GEM, but problems arise in determining suitable values for fixing the parameters. Using mean square error of prediction, the best fixed effects structure could not be conclusively determined. The simulation method indicated the simplest fixed effects structure to be superior whereas in contrast, the cross-validation method on actual data concluded that the most complex one was the best. In conclusion it is difficult to propose a universally best GEM that can be used in any data set of this size. However, some general recommendations are that it is more appropriate to estimate the genetic parameters when evaluating for selection purposes, the animal model was superior to the sire model and that in the Pakistani situation the repeatability model is more suitable than a multivariate.     

Predictive ability of selected subsets of single nucleotide polymorphisms (SNPs) in a moderately sized dairy cattle population

Several studies have shown that computation of genomic estimated breeding values (GEBV) with accuracies significantly greater than parent average (PA) estimated breeding values (EBVs) requires genotyping of at least several thousand progeny-tested bulls. For all published analyses, GEBV computed from the selected samples of markers have lower or equal accuracy than GEBV derived on the basis of all valid single nucleotide polymorphisms (SNPs). In the current study, we report on four new methods for selection of markers. Milk, fat, protein, somatic cell score, fertility, persistency, herd life and the Israeli selection index were analyzed. The 972 Israeli Holstein bulls genotyped with EBV for milk production traits computed from daughter records in 2012 were assigned into a training set of 844 bulls with progeny test EBV in 2008, and a validation set of 128 young bulls. Numbers of bulls in the two sets varied slightly among the nonproduction traits. In EFF₁₂, SNPs were first selected for each trait based on the effects of each marker on the bulls’ 2012 EBV corrected for effective relationships, as determined by the SNP matrix. EFF₀₈ was the same as EFF₁₂, except that the SNPs were selected on the basis of the 2008 EBV. In DIF_max, the SNPs with the greatest differences in allelic frequency between the bulls in the training and validation sets were selected, whereas in DIF_min the SNPs with the smallest differences were selected. For all methods, the numbers of SNPs retained varied over the range of 300 to 6000. For each trait, except fertility, an optimum number of markers between 800 and 5000 was obtained for EFF₁₂, based on the correlation between the GEBV and current EBV of the validation bulls. For all traits, the difference between the correlation of GEBV and current EBV and the correlation of the PA and current EBV was >0.25. EFF₀₈ was inferior to EFF₁₂, and was generally no better than PA EBV. DIF_max always outperformed DIF_min and generally outperformed EFF₀₈ and PA. Furthermore, GEBV based on DIF_max were generally less biased than PA. It is likely that other methods of SNP selection could improve upon these results.     

Animal board invited review: precision livestock farming for dairy cows with a focus on oestrus detection

Dairy cows are high value farm animals requiring careful management to achieve the best results. Since the advent of robotic and high throughput milking, the traditional few minutes available for individual human attention daily has disappeared and new automated technologies have been applied to improve monitoring of dairy cow production, nutrition, fertility, health and welfare. Cows milked by robots must meet legal requirements to detect healthy milk. This review focuses on emerging technical approaches in those areas of high cost to the farmer (fertility, metabolic disorders, mastitis, lameness and calving). The availability of low cost tri-axial accelerometers and wireless telemetry has allowed accurate models of behaviour to be developed and sometimes combined with rumination activity detected by acoustic sensors to detect oestrus; other measures (milk and skin temperature, electronic noses, milk yield) have been abandoned. In-line biosensors have been developed to detect markers for ovulation, pregnancy, lactose, mastitis and metabolic changes. Wireless telemetry has been applied to develop boluses for monitoring the rumen pH and temperature to detect metabolic disorders. Udder health requires a multisensing approach due to the varying inflammatory responses collectively described as mastitis. Lameness can be detected by walk over weigh cells, but also by various types of video image analysis and speed measurement. Prediction and detection of calving time is an area of active research mostly focused on behavioural change.     

Characterization of UMP synthase in dairy cattle heterozygous for a lethal recessive trait

UMP synthase was characterized biochemically in dairy cattle heterozygous for a deficiency of this enzyme. Both activities comprising this bifunctional enzyme are decreased, with OMP decarboxylase more affected than orotate phosphoribosyltransferase. Immunotitration of UMP synthase activity revealed the presence of the protein product of the mutant allele in the heterozygous animals. UMP synthases from normal and deficient cattle were not distinguished from one another by kinetic constants, responses to inhibitors, pH profiles, or thermal lability. It was concluded that the 50% reduction in enzyme activity in heterozygous cattle is the result of the presence of only half the normal level of catalytically active UMP synthase.     

Relative emissions intensity of dairy production systems: employing different functional units in life-cycle assessment

This study aimed to assess the merit and suitability of individual functional units (FU) in expressing greenhouse gas emissions intensity in different dairy production systems. An FU provides a clearly defined and measurable reference to which input and output data are normalised. This enables the results from life-cycle assessment (LCA) of different systems to be treated as functionally equivalent. Although the methodological framework of LCA has been standardised, selection of an appropriate FU remains ultimately at the discretion of the individual study. The aim of the present analysis was to examine the effect of different FU on the emissions intensities of different dairy production systems. Analysis was based on 7 years of data (2004 to 2010) from four Holstein-Friesian dairy systems at Scotland’s Rural College’s long-term genetic and management systems project, the Langhill herd. Implementation of LCA accounted for the environmental impacts of the whole-farm systems and their production of milk from ‘cradle to farm gate’. Emissions intensity was determined as kilograms of carbon dioxide equivalents referenced to six FU: UK livestock units, energy-corrected milk yield, total combined milk solids yield, on-farm land used for production, total combined on- and off-farm land used for production, and the proposed new FU–energy-corrected milk yield per hectare of total land used. Energy-corrected milk was the FU most effective for reflecting differences between the systems. Functional unit that incorporated a land-related aspect did not find difference between systems which were managed under the same forage regime, despite their comprising different genetic lines. Employing on-farm land as the FU favoured grazing systems. The proposed dual FU combining both productivity and land use did not differentiate between emissions intensity of systems as effectively as the productivity-based units. However, this dual unit displayed potential to quantify in a simple way the positive or negative outcome of trade-offs between land and production efficiencies, in which improvement in emissions intensity using one FU may be accompanied by deterioration using another FU. The perceived environmental efficiencies of different dairy production systems in terms of their emissions intensities were susceptible to change based upon the FU employed, and hence the FU used in any study needs to be taken into account in the interpretation of results.     

Developing a multi-Kinect-system for monitoring in dairy cows: object recognition and surface analysis using wavelets

Camera-based systems in dairy cattle were intensively studied over the last years. Different from this study, single camera systems with a limited range of applications were presented, mostly using 2D cameras. This study presents current steps in the development of a camera system comprising multiple 3D cameras (six Microsoft Kinect cameras) for monitoring purposes in dairy cows. An early prototype was constructed, and alpha versions of software for recording, synchronizing, sorting and segmenting images and transforming the 3D data in a joint coordinate system have already been implemented. This study introduced the application of two-dimensional wavelet transforms as method for object recognition and surface analyses. The method was explained in detail, and four differently shaped wavelets were tested with respect to their reconstruction error concerning Kinect recorded depth maps from different camera positions. The images’ high frequency parts reconstructed from wavelet decompositions using the haar and the biorthogonal 1.5 wavelet were statistically analyzed with regard to the effects of image fore- or background and of cows’ or persons’ surface. Furthermore, binary classifiers based on the local high frequencies have been implemented to decide whether a pixel belongs to the image foreground and if it was located on a cow or a person. Classifiers distinguishing between image regions showed high (⩾0.8) values of Area Under reciever operation characteristic Curve (AUC). The classifications due to species showed maximal AUC values of 0.69.     

Long-term stability of Avoidance Distance tests for on-farm assessment of dairy cow relationship to humans in alpine traditional husbandry systems

The present study investigates the long-term stability of two behaviour tests used to evaluate the human-animal relationship as well as gather information to refine on-farm welfare assessment protocols in alpine husbandry systems. Two tests, Avoidance Distance (AD) and Avoidance Distance at the Feeding rack (ADF) were performed on 50 lactating cows, bred in a loose housing system, following a protocol validated for dairy cows in the Welfare Quality^® project. AD was performed on each animal at three different times: at the end of the indoor housing period just before the grazing period (AD_bg); during the outdoor summer grazing period in mountain ranges (AD_dg); and at the beginning of the indoor housing period, just after the grazing period (AD_ag). ADF was performed on the same cows only during the housing period, at the bottom of the valley, before (ADF_bg) and after (ADF_ag) the grazing period. Values of AD_ag (113.93 ± 21.21 cm) were significantly higher (P < 0.05) than those observed in AD_bg (71.07 ± 14.63 cm) and in AD_dg (77.68 ± 18.11 cm). No statistical significance was pointed out between AD_bg and AD_dg. A similar trend was recorded also for ADF, which was significantly higher after the grazing period (ADF_bg vs ADF_ag: 25.00 ± 6.80 vs 47.50 ± 8.72 cm; P < 0.05). The summer grazing period seems to affect the reaction of cows towards humans, and AD and ADF are not consistent throughout the year. Certification of on-farm welfare in alpine husbandry systems, therefore requires performing these tests at the end of the indoor period, to gain better insight of the human-animal relationship for the environment in which cows live most of the year.     

Modelling as a tool to redesign livestock farming systems: a literature review

Livestock farming has recently come under close scrutiny, in response especially to environmental issues. Farmers are encouraged to redesign their livestock farming systems in depth to improve their sustainability. Assuming that modelling can be a relevant tool to address such systemic changes, we sought to answer the following question: ‘How can livestock farming systems be modelled to help farmers redesign their whole farming systems?’ To this end, we made a literature review of the models of livestock farming systems published from 2000 to mid-2009 (n = 79). We used an analysis grid based on three considerations: (i) system definition, (ii) the intended use of the model and (iii) the way in which farmers’ decision-making processes were represented and how agricultural experts and farmers were involved in the modelling processes. Consistent rationales in approaches to supporting changes in livestock farming were identified in three different groups of models, covering 83% of the whole set. These could be defined according to (i) the way in which farmers’ decisions were represented and (ii) the model's type of contribution to supporting changes. The first type gathered models that dynamically simulated the system according to different management options; the farmers’ decision-making processes are assumed to consist in choosing certain values for management factors. Such models allow long-term simulations and endorse different disciplinary viewpoints, but the farmers are weakly involved in their design. Models of the second type can indicate the best combination of farm activities under given constraints, provided the farmers’ objectives are profit maximisation. However, when used to support redesigning processes, they address neither how to implement the optimal solution nor its long-term consequences. Models of the third type enable users to dynamically simulate different options for the farming system, the management of which is assumed to be planned according to the farmers’ general objectives. Although more comprehensive, these models do not easily integrate different disciplinary viewpoints and different subsystems, which limits their usefulness as support tools for redesigning processes. Finally, we concluded about what specific requirements should be for modelling approaches if farmers were to be supported in redesigning their whole livestock farming systems using models.     

Productive,economic and risk assessment of grazing dairy systems with supplemented cows milked once a day

Milking cows once a day (OAD) is a herd management practice that may help to reduce working effort and labour demand in dairy farms. However, a decrease in milk yield per cow occurs in OAD systems compared with twice a day (TAD) systems and this may affect profitability of dairy systems. The objective of this study was to assess productive and economic impact and risk of reducing milking frequency from TAD to OAD for grazing dairy systems, using a whole-farm model. Five scenarios were evaluated by deterministic and stochastic simulations: one scenario under TAD milking (TADAR) and four scenarios under OAD milking. The OAD scenarios assumed that milk yield per cow decreased by 30% (OAD30), 24% (OAD24), 19% (OAD19) and 10% (OAD10), compared with TADAR scenario, based on experimental and commercial farms data. Stocking rate (SR) was increased in all OAD scenarios compared to TADAR and two levels of reduction in labour cost were tested, namely 15% and 30%. Milk and concentrate feeds prices, and pasture and crop yields, were allowed to behave stochastically to account for market and climate variations, respectively, to perform risk analyses. Scenario OAD10 showed similar milk yield per ha compared with TADAR, as the increased SR compensated for the reduction in milk yield per cow. For scenarios OAD30, OAD24 and OAD19 the greater number of cows per ha partially compensated for the reduction of milk yield per cow and milk yield per ha decreased 21%, 15% and 10%, respectively, compared with TADAR. Farm operating profit per ha per year also decreased in all OAD scenarios compared with TADAR, and were US$684, US$161, US$ 303, US$424 and US$598 for TADAR, OAD30, OAD24, OAD19, OAD10, respectively, when labour cost was reduced 15% in OAD scenarios. When labour cost was reduced 30% in OAD scenarios, only OAD10 showed higher profit (US$706) than TADAR. Stochastic simulations showed that exposure to risk would be higher in OAD scenarios compared with TADAR. Results showed that OAD milking systems might be an attractive alternative for farmers who can either afford a reduction in profit to gain better and more flexible working conditions or can minimise milk yield loss and greatly reduce labour cost.     

Towards a theory of meaning in biology: a proposal for an operative definition.

Information is a concept developed inside the context of computational and computer sciences. Entropy is a concept developed inside physics context. The best concept in biology is that of "meaning" which is quite impossible to be measured as stated by some examples which are reported. A suggestion to develop a discussion in order to obtain an integration of these concepts inside the general problems of evolutionary biology is here reported to the attention of researchers.     

Evaluation of the impact of a Herd Health and Production Management programme in organic dairy cattle farms: a process evaluation approach

Animal health planning activities are not always providing a satisfactory positive impact on herd health and welfare. Moreover, evaluating the impact of advisory programmes is complex due to multiple interacting elements that influence its outcome. Therefore, measuring solely health outcomes is not sufficient: the whole process of the implementation and use of such programmes should be evaluated. In order to evaluate the impact of an intervention with a Herd Health and Production Management (HHPM) programme a process evaluation framework was designed and used. The intervention involved 20 organic dairy cattle farmers and their advisors, in both France and Sweden. In both countries 20 organic dairy farms were selected as control herds. The evaluation of the HHPM programme was based on: (a) the compliance to the programme; (b) the programme’s functions influencing herd health management practices and stimulating dialogue between farmers and advisors; (c) its effectiveness in terms of improving herd health compared with control farms. Complete compliance to the programme was fulfilled by 21 out of 40 farmers–advisors. Results from a questionnaire showed that the programme functioned as intended (e.g. by allowing early identification of herd health problems), stimulated change in farmers’ herd health management practices and farmer–advisor dialogue. Even though the majority of the users perceived that the programme contributed to herd health improvements, no significant differences in health outcomes were found when compared with control farms 12 months after the start of the intervention. The programme allowed creating an environment promoting the exchange of information between farmers and advisors, necessary to define pertinent advice in a farm-specific situation. Future research should aim at improving methods for the evaluation of the effect of advisory programmes, by identifying early indicators for effective advice and developing methods to evaluate the quality of advisory situations without interfering with them.