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Genomic selection is rapidly becoming the state-of-the-art genetic selection methodology in dairy cattle breeding schemes around the world. The objective of this paper was to explore possibilities to apply genomic selection for traits related to dairy cow robustness. Deterministic simulations indicate that replacing progeny testing with genomic selection may favour genetic response for production traits at the expense of robustness traits, owing to a disproportional change in accuracies obtained across trait groups. Nevertheless, several options are available to improve the accuracy of genomic selection for robustness traits. Moreover, genomic selection opens up the opportunity to begin selection for new traits using specialised reference populations of limited size where phenotyping of large populations of animals is currently prohibitive. Reference populations for such traits may be nucleus-type herds, research herds or pooled data from (international) research experiments or research herds. The RobustMilk project has set an example for the latter approach, by collating international data for progesterone-based traits, feed intake and energy balance-related traits. Reference population design, both in terms of relatedness of the animals and variability in phenotypic performance, is important to optimise the accuracy of genomic selection. Use of indicator traits, combined with multi-trait genomic prediction models, can further contribute to improved accuracy of genomic prediction for robustness traits. Experience to date indicates that for newly recorded robustness traits that are negatively correlated with the main breeding goal, cow reference populations of ⩾10 000 are required when genotyping is based on medium- or high-density single-nucleotide polymorphism arrays. Further genotyping advances (e.g. sequencing) combined with post-genomics technologies will enhance the opportunities for (genomic) selection to improve cow robustness.
A phenotype describes the outcome of the interacting development between the genotype of an individual and its specific environment throughout life. Animal breeding currently exploits large data sets of phenotypic and pedigree information to estimate the genetic merit of animals. Here we describe rapid, low-cost phenomic tools for dairy cattle. We give particular emphasis to infrared spectroscopy of milk because the necessary spectral data are already routinely available on milk samples from individual cows and herds, and therefore the operational cost of implementing such a phenotyping strategy is minimal. The accuracy of predicting milk quality traits from mid-infrared spectroscopy (MIR) analysis of milk, although dependent on the trait under investigation, is particularly promising for differentiating between good and poor-quality dairy products. Many fatty acid concentrations in milk, and in particular saturated fatty acid content, can be very accurately predicted from milk MIR. These results have been confirmed in many international populations. Albeit from only two studied populations investigated in the RobustMilk project, milk MIR analysis also appears to be a reasonable predictor of cow energy balance, a measure of animal robustness; high accuracy of prediction was not expected as the gold standard method of measuring energy balance in those populations was likely to contain error. Because phenotypes predicted from milk MIR are available routinely from milk testing, longitudinal data analyses could be useful to identify animals of superior genetic merit for milk quality and robustness, as well as for monitoring changes in milk quality and robustness because of management, while simultaneously accounting for the genetic merit of the animals. These sources of information can be very valuable input parameters in decision-support tools for both milk producers and processors.
This paper presents a method for automating weed detection in colour images despite heavy leaf occlusion. A fully convolutional neural network is used to detect the weeds. The network is trained and validated on a total of more than 17,000 annotations of weeds in images from winter wheat fields, which have been collected using a camera mounted on an all-terrain vehicle. Hereby, the network is able to automatically detect single weed instances in cereal fields despite heavy leaf occlusion.
The livestock sector has a key and growing role in the agricultural economy. It is a major provider of livelihood support for a large part of the world's poor. It is also an important determinant of human health and diet. Over the last three decades, the global livestock sector has rapidly evolved in response to human population growth, income growth and urbanization. And until recently, much of the focus of the sector has been geared towards satiating this demand. However, the rapid growth in demand for animal protein, has resulted in complex interactions among bio-physical resources, economic and social objectives with implications for the natural resource-base and the environment. Livestock production has a large impact on the world's natural resources and contributes significantly to environmental problems such as ecosystem pollution and degradation, global warming and climate change by emission of greenhouse gases and biodiversity loss. This paper provides an overview of the growth within the livestock sector, explores the inter-linkages between the rapidly increasing demand for animal protein and environmental consequences, as well as advances possible technical and policy interventions that are appropriate for the enhancement of the sector's role in food security, poverty reduction, economic development while contributing to environmental sustainability.
In France, the horse population has been expanding since 1995 to reach 950 000 heads in 2010, representing about 15% of the total European horse population today. This growth is the result of the development of pony-riding for children and the increasing interest of French people in recreational riding and horse-betting. These changes offer major advantages to the different horse sectors, especially in the context of declining State support, increasing international competition on the horse market, societal changes regarding animal welfare, decreasing horse-meat consumption and harmonization of regulations at European level.
Scientific literature in social sciences that deals with nitrate embraces two centuries, whereas very little socio-economic work has addressed other forms of reactive nitrogen. Nitrogen has always had an ambivalent role as both a raw material indispensable for the development of agricultural and a source of negative impacts. This ambivalence has accompanied the social history of livestock production and can explain the conflicting nature of the subject and the moderate environmental efficiency of environmental policies. The legal system is particularly complex. The main cause of territorial pollutions is linked to the industrialisation and spatial concentration of livestock production in France, as in numerous countries in Europe and North America. This conglomeration movement is translated by a concentration of animal manure, which drives to nitrogen balance surplus and associated serious environmental consequences.
Phosphorus (P) is an essential mineral that needs to be supplied in sufficient quantities for maintenance and growth and milk production in dairy cattle. However, over 60% of the P consumed can be excreted in faeces with a potential to cause environmental pollution. Concern over higher levels of P in intensively managed livestock systems has led to legislation such as the Water Framework Directive in the European Union. In this manuscript, several methods of reducing P pollution are discussed. A major source of environmental P pollution has been overfeeding P mainly due to addition of ‘safety margin’ over the animal's requirement and concerns related to fertility. Matching the animal's requirement and feeding in groups so that animals at the same physiological status are fed according to their requirement has a potential to reduce P excretion significantly. P can also be reduced by matching available P with the metabolizable energy content of the diet because more P can be incorporated into milk when P is utilized by rumen microbes, which are limited by energy. Plants contain phytate bound P that need to be broken up before they can be absorbed by the animal. Although ruminants can digest phytate, use of phytase enzyme could help either directly by acting on phytate P or improvement of feed digestibility. Pasture management can lead to improved nutrient cycling, particularly if the soil is deficient in P. However, overfertilizing pasture could result is higher runoff of dissolved reactive P. Management practices that leave adequate forage residue on the surface such as rotational grazing will improve infiltration and decrease runoff, reducing nutrient losses.
On the basis of a review of the industry, the dynamics of past trends and current questions about its future, the foresight panel identified around 40 drivers of change likely to impact the future of the horse industry. These were categorised, prioritised and organised into five components that formed the basis of the scenario-building exercise:
the economic and societal context;
public expectations of horses and of equestrian and horseracing activities;
public policy and regulation;
equestrianism and horseracing;
the organisation and strategies of horse producers.
This chapter presents the main trends and future outlooks for the factors encompassed within these five major thematic areas synthesised in microscenarios.