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Breeding objectives of livestock and other agricultural species are usually profit maximising. The selection emphasis placed on specific traits to achieve a breeding objective is often informed by the financial value of a trait to a farm system. However, there are alternative, and complementary approaches to defining both the breeding objective and the selection emphasis placed on traits that are included in associated selection tools. These are based on the preferences of stakeholders, which are often heterogeneous and include broader values and motivations than profit. In this regard, stated preference methods are useful when considering traits that have either no discernible market value or whose value is not fully transferred via the market. Such approaches can guide more appropriate breeding decisions that are amenable to changing societal values, for example with reduced negative environmental externalities. However, while stated preference methods offer promising conceptualisations of value in genetic improvement programmes, there is still a substantial knowledge gap in terms of the current state of research and a catalogue of publications to date. This paper reviews publications of stated preference approaches in the field of livestock breeding (and some relevant crop breeding examples), providing a knowledge base of published applications and promoting their continued development and implementation towards the formulation of appropriate breeding objectives and selection indices. A systematic review of 84 peer-reviewed publications and an aggregate ranking of traits for the most commonly studied subject (cattle) reveals uncertainty in preference estimates which may be driven by (i) a diverse set of non-standardised methodologies, (ii) common oversights in the selection, inclusion and description of traits, and (iii) inaccurate representations of the respondent population. We discuss key considerations to help overcome these limitations, including avoiding methodological confinement to a disciplinary silo and reducing complexity so that the values of broader respondent groups may be accounted for.

Breeding objectives of livestock and other agricultural species are usually profit maximising. The selection emphasis placed on specific traits to achieve a breeding objective is often informed by the financial value of a trait to a farm system. However, there are alternative, and complementary approaches to defining both the breeding objective and the selection emphasis placed on traits that are included in associated selection tools. These are based on the preferences of stakeholders, which are often heterogeneous and include broader values and motivations than profit. In this regard, stated preference methods are useful when considering traits that have either no discernible market value or whose value is not fully transferred via the market. Such approaches can guide more appropriate breeding decisions that are amenable to changing societal values, for example with reduced negative environmental externalities. However, while stated preference methods offer promising conceptualisations of value in genetic improvement programmes, there is still a substantial knowledge gap in terms of the current state of research and a catalogue of publications to date. This paper reviews publications of stated preference approaches in the field of livestock breeding (and some relevant crop breeding examples), providing a knowledge base of published applications and promoting their continued development and implementation towards the formulation of appropriate breeding objectives and selection indices. A systematic review of 84 peer-reviewed publications and an aggregate ranking of traits for the most commonly studied subject (cattle) reveals uncertainty in preference estimates which may be driven by (i) a diverse set of non-standardised methodologies, (ii) common oversights in the selection, inclusion and description of traits, and (iii) inaccurate representations of the respondent population. We discuss key considerations to help overcome these limitations, including avoiding methodological confinement to a disciplinary silo and reducing complexity so that the values of broader respondent groups may be accounted for.

The livestock sector is one of the fastest growing subsectors of the agricultural economy and, while it makes a major contribution to global food supply and economic development, it also consumes significant amounts of natural resources and alters the environment. In order to improve our understanding of the global environmental impact of livestock supply chains, the Food and Agriculture Organization of the United Nations has developed the Global Livestock Environmental Assessment Model (GLEAM). The purpose of this paper is to provide a review of GLEAM. Specifically, it explains the model architecture, methods and functionality, that is the types of analysis that the model can perform. The model focuses primarily on the quantification of greenhouse gases emissions arising from the production of the 11 main livestock commodities. The model inputs and outputs are managed and produced as raster data sets, with spatial resolution of 0.05 decimal degrees. The Global Livestock Environmental Assessment Model v1.0 consists of five distinct modules: (a) the Herd Module; (b) the Manure Module; (c) the Feed Module; (d) the System Module; (e) the Allocation Module. In terms of the modelling approach, GLEAM has several advantages. For example spatial information on livestock distributions and crops yields enables rations to be derived that reflect the local availability of feed resources in developing countries. The Global Livestock Environmental Assessment Model also contains a herd model that enables livestock statistics to be disaggregated and variation in livestock performance and management to be captured. Priorities for future development of GLEAM include: improving data quality and the methods used to perform emissions calculations; extending the scope of the model to include selected additional environmental impacts and to enable predictive modelling; and improving the utility of GLEAM output.

The livestock sector is one of the fastest growing subsectors of the agricultural economy and, while it makes a major contribution to global food supply and economic development, it also consumes significant amounts of natural resources and alters the environment. In order to improve our understanding of the global environmental impact of livestock supply chains, the Food and Agriculture Organization of the United Nations has developed the Global Livestock Environmental Assessment Model (GLEAM). The purpose of this paper is to provide a review of GLEAM. Specifically, it explains the model architecture, methods and functionality, that is the types of analysis that the model can perform. The model focuses primarily on the quantification of greenhouse gases emissions arising from the production of the 11 main livestock commodities. The model inputs and outputs are managed and produced as raster data sets, with spatial resolution of 0.05 decimal degrees. The Global Livestock Environmental Assessment Model v1.0 consists of five distinct modules: (a) the Herd Module; (b) the Manure Module; (c) the Feed Module; (d) the System Module; (e) the Allocation Module. In terms of the modelling approach, GLEAM has several advantages. For example spatial information on livestock distributions and crops yields enables rations to be derived that reflect the local availability of feed resources in developing countries. The Global Livestock Environmental Assessment Model also contains a herd model that enables livestock statistics to be disaggregated and variation in livestock performance and management to be captured. Priorities for future development of GLEAM include: improving data quality and the methods used to perform emissions calculations; extending the scope of the model to include selected additional environmental impacts and to enable predictive modelling; and improving the utility of GLEAM output.

In beef cattle, feeding behaviour and activity are associated with feed efficiency and methane (CH4) emissions. This study aimed to understand the underlying traits responsible for the contribution of cattle behaviour to individual differences in feed efficiency, performance and CH4 emissions. A total of 84 steers (530±114 kg BW) of two different breeds (crossbreed Charolais and Luing) were used. The experiment was a 2×2×3 factorial design with breed, basal diets (concentrate v. mixed) and dietary treatments (no additive, calcium nitrate or rapeseed cake) as the main factors. The individual dry matter intake (DMI; kg) was recorded daily and the BW was measured weekly over a 56-day period. Ultrasound fat depth was measured on day 56. Based on the previous data, the indexes average daily gain, food conversion and residual feed intake (RFI) were calculated. The frequency of meals, the duration per visit and the time spent feeding per day were taken as feeding behaviour measures. Daily activity was measured using the number of steps, the number of standing bouts and the time standing per day. Agonistic interactions (including the number of contacts, aggressive interactions, and displacements per day) between steers at the feeders were assessed as indicators of dominance. Temperament was assessed using the crush score test (which measures restlessness when restrained) and the flight speed on release from restraint. Statistical analysis was performed using multivariate regression models. Steers that spent more time eating showed better feed efficiency (P=0.039), which can be due to greater secretion of saliva. Feeding time was longer with the mixed diet (P<0.001), Luings (P=0.009) and dominant steers (P=0.032). Higher activity (more steps) in the pen was associated with poorer RFI, possibly because of higher energy expenditure for muscle activity. Frequent meals contributed to a reduction in CH4 emissions per kg DMI. The meal frequency was higher with a mixed diet (P<0.001) and increased in more temperamental (P=0.003) and dominant (P=0.017) steers. In addition, feed intake was lower (P=0.032) in more temperamental steers. This study reveals that efficiency increases with a longer feeding time and CH4 emissions decrease with more frequent meals. As dominant steers eat more frequently and for longer, a reduction in competition at the feeder would improve both feed efficiency and CH4 emissions. Feed efficiency can also be improved through a reduction in activity. Selection for calmer cattle would reduce activity and increase feed intake, which may improve feed efficiency and promote growth, respectively.

In beef cattle, feeding behaviour and activity are associated with feed efficiency and methane (CH4) emissions. This study aimed to understand the underlying traits responsible for the contribution of cattle behaviour to individual differences in feed efficiency, performance and CH4 emissions. A total of 84 steers (530±114 kg BW) of two different breeds (crossbreed Charolais and Luing) were used. The experiment was a 2×2×3 factorial design with breed, basal diets (concentrate v. mixed) and dietary treatments (no additive, calcium nitrate or rapeseed cake) as the main factors. The individual dry matter intake (DMI; kg) was recorded daily and the BW was measured weekly over a 56-day period. Ultrasound fat depth was measured on day 56. Based on the previous data, the indexes average daily gain, food conversion and residual feed intake (RFI) were calculated. The frequency of meals, the duration per visit and the time spent feeding per day were taken as feeding behaviour measures. Daily activity was measured using the number of steps, the number of standing bouts and the time standing per day. Agonistic interactions (including the number of contacts, aggressive interactions, and displacements per day) between steers at the feeders were assessed as indicators of dominance. Temperament was assessed using the crush score test (which measures restlessness when restrained) and the flight speed on release from restraint. Statistical analysis was performed using multivariate regression models. Steers that spent more time eating showed better feed efficiency (P=0.039), which can be due to greater secretion of saliva. Feeding time was longer with the mixed diet (P<0.001), Luings (P=0.009) and dominant steers (P=0.032). Higher activity (more steps) in the pen was associated with poorer RFI, possibly because of higher energy expenditure for muscle activity. Frequent meals contributed to a reduction in CH4 emissions per kg DMI. The meal frequency was higher with a mixed diet (P<0.001) and increased in more temperamental (P=0.003) and dominant (P=0.017) steers. In addition, feed intake was lower (P=0.032) in more temperamental steers. This study reveals that efficiency increases with a longer feeding time and CH4 emissions decrease with more frequent meals. As dominant steers eat more frequently and for longer, a reduction in competition at the feeder would improve both feed efficiency and CH4 emissions. Feed efficiency can also be improved through a reduction in activity. Selection for calmer cattle would reduce activity and increase feed intake, which may improve feed efficiency and promote growth, respectively.