Aspects of selection for feed efficiency in meat producing poultry

doi:10.1017/S004393391300007X

Aspects of selection for feed efficiency in meat producing poultry O.W. WILLEMS1*, S.P. MILLER1 and B.J. WOOD1, 2 1

Centre for the Genetic Improvement of Livestock, University of Guelph, Ontario, Canada; 2Hybrid Turkeys, 650 Riverbend Drive, Suite C, Kitchener, Ontario, Canada *Corresponding author: [email protected] Over the last five years, the costs of poultry feed ingredients have increased substantially. This has been due to an increased use of corn for ethanol production and a greater overall global feed grain demand. Across the poultry industry this has led to higher production costs and reaffirmed the importance of feed efficiency on profitability. The effect that an increase in feed costs has on profitability is a clear driver for the selection for birds with better feed efficiency. Feed efficiency selection can be achieved using a number of different analytical methods. Selection for feed conversion ratio (FCR) has been used to improve feed efficiency with success but using a ‘ratio’ trait has mathematical limitations because selection pressure tends to be placed on the component traits of FCR in a non-linear manner. Another measure, residual feed intake (RFI) shows moderate to high heritability and does not have the mathematical limitations associated with FCR. RFI has little to no correlation with production traits and this indicates that genetic improvement of RFI within a selection index can be done without the confounding issues inherent with FCR. Improvements in RFI or FCR have a favourable effect on environmental emissions and decreases the environmental impact of poultry production. The current global production of ammonia, CH4, and N2O by the poultry industry is significant, at levels of 2.1, 29.44 and 279 million tonnes CO2eq, respectively. Reductions in emissions can be achieved via improvements in feed efficiency by lowering amounts of manure excreted and decreasing emitted by-products such as ammonia and greenhouse gases (N2O, CO2 and CH4). Consequently, improvements in feed efficiency can not only increase profitability of the poultry industries by lowering production costs but also decrease environmental impact by reducing environmental emissions. Keywords: poultry; genetic parameters; feed efficiency; feed conversion ratio; residual feed intake; greenhouse gases

© World's Poultry Science Association 2013 World's Poultry Science Journal, Vol. 69, March 2013 Received for publication March 30, 2012 Accepted for publication July 17, 2012

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Introduction It is generally accepted that feed costs represent about 70% of the cost of poultry production and this makes a bird's ability to use feed efficiently very important. Birds considered to have better feed efficiency typically have a lower proportion of feed intake to body weight gain. Over the past decades feed efficiency has been improved through changes in a number of aspects of meat poultry production. Firstly, changes in management that have contributed to gains in feed efficiency have included optimising temperatures, lighting and bird densities (Charles, 1986; Davis et al., 1999; Havenstein et al., 2003). Secondly, research in poultry nutrition has played a key role. Understanding the nutritional requirements of poultry has allowed precise diets to be formulated for different growth periods. These dietary formulations have improved feed efficiency by supplying limiting dietary requirements so birds are not eating extra feed to obtain specific nutrients (Havenstein et al., 2003; 2007). Lastly, significant advances have been due to genetic selection for feed efficiency. Originally poultry were selected based on body weight gain, this led to significantly larger birds over time, but as feed costs began to increase it became clear that, to maintain profitability, selection should be widened to include other traits. For the past 40 years feed efficiency has been heavily weighted in breeding objectives for meat producing poultry and as a result, major gains have been made (Emmerson, 1997).

Defining feed efficiency traits The concept of feed efficiency is simple. Birds are assessed and ranked based on their ability to convert a certain input to a certain output. In this case the input is quantity of feed, often referred to as feed intake (amount of feed consumed over a given period of time) and the output is body weight or meat gain. There are a number of ways to assess feed efficiency, currently, the most widely used are feed conversion ratio (FCR) and residual feed intake (RFI). FCR can be defined as the amount of feed consumed per unit of weight gain, and is a composite trait of starting and ending body weight and feed intake (Skinner-Noble and Teeter, 2003). Variability in energy required for body weight maintenance that contributes to feed intake, is not accounted for in FCR. The inverse of FCR, weight gain divided by feed intake, referred to as the gain to feed ratio, is occasionally used in the literature and is also measure of efficiency (Dransfield and Sosnicki, 1999). Residual feed intake (RFI) was originally proposed by Byerly (1941) and used by Koch et al. (1963) in beef cattle, and in poultry by Luiting (1990). RFI is defined as the difference between actual and predicted feed intake based on the regression of requirements for production (e.g. egg production, milk, but in this instance weight gain) and body weight maintenance (Van Der Werf, 2004). Residual feed intake can then be calculated as: RFI = FI - [μ + (b1*X) + (b2*Y)], where FI represents feed intake over a defined period, μ represents the average feed intake and b1 and b2 represent the partial regression coefficients. X is a coefficient which is seen in the literature as either metabolic midweight (MMW) or starting body weight (Luiting et al., 1991; Van Bebber and Mercer, 1994; Aggrey et al., 2010; Case et al., 2012). Where MMW is defined as the mid test body weight raised to the power of 0.75. Y can also represent two different traits, average daily gain (ADG) or weight gain over the test period (Van Bebber and Mercer, 1994; Pakdel et al., 2005; Aggrey et al., 2010; Case et al., 2012). A more efficient bird should have a negative value for RFI, indicating that it uses less energy than predicted. Statistically, the mean RFI within a population is zero, and is phenotypically 78

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Poultry feed efficiency selection: O.W. Willems et al. independent from the constituent production traits (Kennedy et al., 1993). Studies across multiple species have found that 60-80% of the inter-animal variation in predicted feed intake is accounted for by differences in body weight and the level of production, leaving RFI to potentially account for the remaining 20-40% of unexplained variation (Bottje and Carstens, 2009). Recently, alternative measures of feed efficiency have been used, including residual maintenance energy (RMEm) (Romero et al., 2009b), residual gain (RG) and residual intake and gain (RIG) (Romero et al., 2009b; Berry and Crowley, 2012). RMEm unlike RFI or FCR aims to measure energetic efficiency without being confounded by feed intake. Non-linear methods are used to estimate the maintenance energy requirement (MEm) of each individual bird. Subsequently a linear regression between MEm and feed intake is performed, the residuals representing RMEm (Romero et al., 2009a). While the correlation between feed intake and production is usually assumed to be constant, and therefore linear, it is likely that true biological efficiency depends on the intake and production level, and this may change over an animal's growth trajectory (Van Der Werf, 2004). This makes a non-linear model for feed intake of interest. In a comparison between RFI and RMEm, where RFI corrects for body weight and RMEm for the effect of dietary thermogenesis, RMEm provided a more consistent estimation of individual energetic efficiency across different feed management schemes (Romero et al., 2009b). Residual gain, a proposed measure of feed efficiency, is defined as the residuals from the linear regression of average daily gain (ADG) on both FI and BW. Residual gain can then be calculated as: RG = ADG - [μ + (b1*FI) + (b2*BW)]. Where, ADG represents the average daily gain over a defined period, μ represents the average ADG, b1 and b2 represent the partial regression coefficients on FI and BW, respectively. Improved RG is, on average, associated with faster growth rates but not with differences in feed intake (Berry and Crowley, 2012). Residual intake and gain combines the beneficial characteristics of both RFI and RG such that RIG is independent of body weight, but when used for selection it can increase weight gain and reduce feed intake simultaneously. Residual intake and gain is calculated as: RIG = [(-1*RFI) + RG], where both RFI and RG are standardised to a variance of one. Multiplying RFI by negative one accounts for the fact that birds with a negative RFI have better feed efficiency, where the opposite is true with RG, a positive number would correspond to having greater feed efficiency (Berry and Crowley, 2012). The impact and use of this relatively new measure has been studied in turkeys and shows some promise in the selection for feed efficiency (Willems, Wood and Miller: unpublished).

Selection concepts for FCR and RFI Feed conversion ratio is moderately heritable in poultry, consequently, improvement would be possible in feed efficiency using FCR as the selection criterion (Pakdel et al., 2005; Aggrey et al., 2010; Case et al., 2010). In a comparison between a random bred control population and commercially available stock from 1966 and 2003, Havenstein et al. (2007) concluded that selection programs alongside management techniques had improved FCR in the turkey by approximately 20%. In a similar comparison between breeding lines from 1957 and 1991, genetics, nutrition, and other management changes over the 34 year period studied resulted in broilers (in 1991) that showed significantly improved FCR (3.00 vs. 2.04) at both a constant age and weight (Havenstein et al., 1994; Emmerson, 1997). As a ratio of two traits, problems arise when selecting for FCR. Once selection World's Poultry Science Journal, Vol. 69, March 2013

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Poultry feed efficiency selection: O.W. Willems et al. intensity increases, direct selection for FCR causes selection to be focused primarily on the information in the numerator regardless of the distributional properties of the components (Gunsett, 1984). This leads to selection pressure being placed nonlinearly on feed intake and weight gain. While this will still improve FCR, it will do so at a slower rate compared to linear indexes based on the component traits of FCR (Campo and Rodriguez, 1990; Famula, 1990). The advantages of selection based on component traits decrease as the phenotypic correlations between the two increase, high correlations make selecting for one almost as good as selecting for both (Gunsett, 1984). As FCR improvements have been made, growth rate has increased, and age to market has been considerably reduced. While this has improved feed efficiency, it may be due to a shortened growth period as FCR increases with the age of broilers due to higher maintenance energy requirements (Havenstein et al., 2003). RFI is used to quantify feed efficiency by estimating the amount of feed intake not accounted for by body weight gain. The use of RFI has increased for several reasons. Firstly, there is considerable variation present on which to select in commercial meatproducing species as shown in Table 1. Secondly, RFI is moderately heritable in poultry (Table 1) and appears to be independent of production traits. Independence from production traits allows RFI to be incorporated into a multiple-trait selection index without concern of hampering increases in other economically important traits. This has been demonstrated in selection trials for decreased RFI, which led to a reduction in feed intake, improved feed efficiency and resulted in no change in production (Aggrey et al., 2010). While no large experimental selection trial evidence is available in the literature for poultry, given that RFI and production traits are independent, it is conceivable that improvements in RFI and production can occur concurrently. As with most traits, there are drawbacks to consider with RFI. The largest problem being that RFI may penalise higher productivity. Higher production requires higher feed intake, as denoted by high phenotypic and genetic correlations between weight gain and feed intake across several RFI studies in meat-producing poultry (Van Bebber and Mercer, 1994; Aggrey et al., 2010; Case et al., 2012). Higher feed intake in turn produces more heat known as diet-induced thermogenesis (Swennen et al., 2004). Higher feed intake and more energy lost to heat can contribute to an increased RFI measurement on a high producing animal compared to a low producing animal. Alternatively, a slow growing animal eating relatively small amount of feed may have a good RFI value (Berry and Crowley, 2012).

Selection strategies for FCR and RFI The strategies for genetic improvement of FCR and RFI are different, and depend on their specific genetic correlations with important production traits. Both FCR and RFI require the measurement of individual feed intake, which can be difficult to measure in practice. There are a two ways to obtain individual feed intake values. The first requires the use of individually caged birds, which need to have their feed recorded and refilled on a daily basis. The second, an automated electronic feeding system that enables feed intake measurements on specific individuals to be taken in a group-house setting (Howie et al., 2011; Tu et al., 2011). Each method has its advantages and disadvantages. The traditional method of using individually caged birds is widely studied, cheap and simple, but requires a significant amount of barn space and doesn't account for social interactions. The automated electronic feeding system can measure a larger number of birds, and due to the group-housed environment, accounts for social interactions between birds. 80

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Poultry feed efficiency selection: O.W. Willems et al. Selecting for weight gain can make indirect improvements in FCR. By doing this feed intake is increased as a correlated genetic response, but it does so at a slower rate, thereby improving FCR (Varkoohi et al., 2011). In contrast, RFI would not be affected by the indirect selection of weight gain, as it is accounted for in its computation via regression on body weight (Kennedy et al., 1993; Van Der Werf, 2004). Long-term selection trials for FCR are widespread for meat producing birds. Pym and Nicholls (1979) reduced FCR by 0.156 to 0.341 per generation vs. a control line over a five-generation selection experiment, making selections based on FCR. Leenstra and Pit (1987), measured FCR in a broiler sire strain and, after four generations of selection, FCR was 0.17 lower in the line selected for decreased FCR compared to the line selected for increased body weight. Large-scale selections for RFI in poultry over long periods of time do not exist in the literature. Smaller RFI selection experiments have demonstrated decreased maintenance energy requirements and physical activity in poultry with lower RFI (Luiting, 1999; Luiting et al., 1991). Selections based on FCR have made significant improvements in feed efficiency and experimental trials utilising RFI show promising theoretical results. However, it is important to recall the contributions of Kennedy et al. (1993), which note that RFI provides no additional information to a breeding program over and above that provided by its component traits. In the meat producing poultry industry, it may be more useful to follow what effect selection for production and other traits can have on RFI, than the reverse.

Comparisons of feed efficiency among meat producing poultry A summary of phenotypic means, heritability and genetic relationships between FCR and RFI is shown in Table 1. Information on a non-poultry species (beef cattle) is shown for comparison. Mean FCR values in broilers range from 2.00 to 2.45, with outliers as high as 4.35 (Melo et al., 2006). The highest outlier, from Camperos broilers, is a poultry breed used in free-range systems of production, while a value of 3.15 was estimated for a slow-growing line of chickens (Nidri et al., 2006). In turkeys, FCR estimates ranged from 2.95 to 3.10 (Konca et al., 2009; Case et al., 2010). In Japanese quail, FCR has been seen between 2.47 and 2.86 (El-Deen et al., 2009; Khaldari et al., 2010; Varkoohi et al., 2010; 2011). In studies across several species of ducks (Pekin, Muscovy and mule ducks) FCR ranged between 2.12 and 2.90 (Guy et al., 1998; Retailleau, 1999; Pingel, 2011). French guinea fowl demonstrated an FCR of 2.10 to 2.34, and pearl gray guinea fowl 3.86 (Nahashon et al., 2005; Tufarelli et al., 2007). Heritability of FCR varied substantially from 0.11 to 0.41 (Van Bebber and Mercer, 1994; Pakdel et al., 2005; Melo et al., 2006; Nidri et al., 2006; Aggrey et al., 2010). Recent commercial broiler estimates had similar moderate heritably values of 0.29, 0.33 and 0.41 (Pakdel et al., 2005; Nidri et al., 2006; Aggrey et al., 2010). These results are likely to represent current population genetics. Heritability of FCR for species of birds other than chickens is difficult to quantify due to the lower number of estimates in the literature. In turkeys, FCR heritability was 0.23 for 105 to 133 day old toms (Case et al., 2010). In Japanese quail FCR heritability was 0.23 for quail between 7 to 28 days old, and 0.67 in 50 day olds (El-Deen et al., 2009; Varkoohi et al., 2011). FCR heritability was estimated at 0.52 in Pekin ducks (Pingel, 2011). Heritability of RFI in broilers ranged from 0.21 to 0.49. Again, the most recent estimates were highest at 0.42, 0.45 and 0.49 (Pakdel et al., 2005; Nidri et al., 2006; Aggrey et al., 2010). Preliminary RFI estimates for turkeys show a moderate heritability (0.22) similar to the lower end of estimated RFI heritability in broilers (Case et al., 2010). World's Poultry Science Journal, Vol. 69, March 2013

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Poultry feed efficiency selection: O.W. Willems et al. Estimates of the genetic correlations between FCR and RFI are rare in meat producing poultry outside of broilers. In broilers, the estimates range from 0.74 to 0.93. In turkeys there is only one estimate; 0.80 (Case et al., 2010). The high genetic correlation values, from broilers and turkeys, indicate that selection for decreased FCR or RFI would lead to a correlated decrease in the other variable. In Japanese quail estimates are lower (0.26, Varkoohi et al., 2011), this may be due to differences in the age of birds relative to mature age on which estimations were made. The Japanese quail were assessed from 7-28 days of age, where broilers and turkeys ranged from 23-75, and 105-133 days, respectively. Aggrey et al. (2010) noted a much smaller genetic correlation between FCR and RFI amongst younger birds, 0.31 for broilers aged 28-35 days vs. 0.84 for birds aged 35-42 days. Results appear to differ based on the period of the growth curve on which measurements are taken, and this suggests that the nature of the relationship between FCR and RFI may be dependent on age. Genetic correlations between FCR and RFI, along with their heritabilities, are important to note when considering use of one or the other as a selection criterion.

Impact of feed efficiency on environmental emissions The environmental impact of poultry production is a continuing challenge. It is predicted that global consumption of poultry meat will increase between 2000 and 2030 at an average annual rate of 2.51% (Fiala, 2008). Although managerial and nutritional strategies have achieved some success in reducing the amount of waste products (manure) and greenhouse gases (GHG), such strategies may not provide sufficient relief nor be able to address ever-increasing levels of poultry production. The most significant emissions from poultry production include ammonia (NH3) and the GHG that are considered to be a component of global warming, nitrous oxide (N2O), carbon dioxide (CO2), and methane (CH4). Even though CH4 and N2O are emitted in lower quantities than CO2, they have global warming potentials of 25 and 298 times of that of CO2, respectively, making them equally important to examine. Recent estimates of environmental impact of animal production show poultry has the lowest NH3 and GHG emissions. In the European Union (EU-27), total GHG production from livestock farming is 493 teragrams CO2eq per year, with the beef, swine and poultry industries representing approximately 35%, 16% and 6%, respectively. On a per kg product basis, beef had by far the highest GHG emission with 22.6 kg CO2eq, pork 3.5 kg CO2eq and poultry 1.6 kg CO2eq (Lesschen et al., 2011). The largest direct contributor to N2O and CH4 emissions in meat producing poultry operations are from built up litter (Gates et al., 2008; Verge et al., 2009), which emit approximately 279 and 29.44 million tonnes (CO2eq), respectively, globally per year (Johnson and Ward, 1996; Oenema et al., 2005). As feed efficiency improves, the amount of waste products decreases and this lowers emissions in two ways. Firstly, the amount of enteric fermentation decreases as feed conversion improves, lowering N2O and CH4 (Wang and Huang, 2005). Secondly, decreasing amounts of waste entering the manure storage systems will result in decreased emissions of GHG as by-products (Miles et al., 2006; Hill and Azain, 2009). These concepts have recently been demonstrated in selection experiments. Over a four-generation selection experiment, after correcting for feed intake levels, a line of broilers selected for decreased FCR excreted 67.4% less than a random control line (De Verdal et al., 2010). In a separate eight-generation divergent selection experiment, a more efficient line of broilers (FCR of 1.72 vs. 2.72) had a 41.3% decrease in fresh excreta weight. High genetic correlations are also reported between 82

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Poultry feed efficiency selection: O.W. Willems et al. both FCR, RFI, and fresh excreta weight (corrected for body weight), 0.99 and 0.91, respectively (De Verdal et al., 2011). These preliminary results show that selection for lower RFI and/or FCR can improve feed efficiency, reduce feed intake, decrease waste products, and lower GHG emissions.

Economic importance of feed efficiency Poultry feed costs continue to climb, with corn and soy prices being the primary driver (Schmit et al., 2009). Clearly increased feed prices have led to an increase in live production costs for both broilers and turkeys, demonstrating the impact on profitability that feed intake and feed efficiency can have (Donohue and Cunningham, 2009). The economic aspects of both the broiler and turkey industries have been examined (Jiang et al., 1998; Wood, 2009). Economic values for broiler breeding were calculated within an integrated and non-integrated broiler enterprise using a deterministic model (Groen et al., 1998). For the integrated system, increases in the representative feed price by 30% changed the economic value of feed intake from -0.0033 to -0.0043 USD per marketable bird (Jiang et al., 1998). A 30% increase in feed price ($0.18/kg to $0.235/kg) would increase the cost to produce a 2.5 kg broiler (with an FCR of 2.00) by $0.275. On a per farm basis, with 100,000 broilers per cycle, and six cycles/year, this represents an increased annual cost of approximately $165,000. Annual improvements in FCR from genetic and nutritional gains continue to be realised for broilers and turkeys. Economic values for turkeys using an integrated deterministic model were estimated by Wood (2009). Feed intake in the example system was given an economic value of -0.0050 USD per kg. Using the total North American production of turkey meat 2,734,953 tonnes, FAOSTAT (2009), a feed cost of $250 a ton, and an FCR improvement from 2.60 to 2.59, the total cost savings from feed alone could reach up to 6.8 million dollars. Market requirements differ from country to country for commercial broiler and turkey production. Consequently, different selection and improvement strategies should be applied. Regardless of these differences, the huge impact that feed efficiency has on the profitability of the meat producing poultry industry is clear and should be an important factor when considering the usage of such traits.

Conclusions Selection for feed efficiency is driven by multiple dynamic factors. Selection schemes incorporating feed efficiency traits in the poultry industry are a must. Gains in feed efficiency may concurrently reduce the ammonia and GHG emissions from poultry. Increases in feed efficiency have a correlated decrease in manure production, which is responsible in turn for a reduction in GHG and ammonia emissions. As research continues and genetic parameters between efficiency and emissions traits are estimated, the best way to incorporate traits into breeding schemes to select for a decrease in environmental impact will become clear. Genetic improvements in feed efficiency are additionally of great economic importance as the global cost of feed increases over time. Continual economic assessments of poultry production systems are necessary to maintain the optimum inclusion of efficiency traits within multipletrait selection indexes to keep the industry viable. Aspects of selection for feed efficiency must be especially considered at all industry levels, from the primary breeder to the commercial grower in order to return the greatest results. World's Poultry Science Journal, Vol. 69, March 2013

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Poultry feed efficiency selection: O.W. Willems et al. Table 1 Comparison of meat producing poultry feed efficiency traits (Mean FCR, FCR and RFI heritability (h2), genetic correlation between FCR and RFI (rg), using literature values‡). Mean FCR

h2 FCR h2 RFI* rg †

Aggrey et al. (2010)

2.00

Melo et al. (2006)

4.35

Pakdel et al. (2005)

2.04

0.41 0.02 0.11 0.07 0.29 0.06 0.12 0.02 0.33 0.03

Source

Population used for estimation

Broilers

van Bebber and Mercer 2.45 (1994) Nidri et al. (2006) 3.15

± ± ± ± ±

0.42 0.01 0.23 0.10 0.49 0.07 0.21 0.03 0.45 0.06

± ± ± ±

0.84 0.01 0.84 0.15 0.93 0.03 0.74 0.06

±

Broilers from 35-42 days

± ±

529 Campero-INTA broilers from 54-75 days 2,166 broilers from 23-48 days

±

8,443 broilers from 49-63 days

±

1061 birds from a commercial slowgrowing meat producing line

Turkey Case et al. (2010)

2.95

Konca et al. (2009)

3.10

0.24 ± 0.02

0.22 ± 0.02

0.80 ± 0.02

16,412 Tom Turkeys from 15-19 weeks 120 turkey toms reared in summer conditions from 4-18 weeks

Japanese Quail Varkoohi et al. (2010, 2011) Khaldari et al. (2010)

2.47

0.67

2.44

El-Deen et al. (2009)

2.86

0.23 ± 0.11

2.85 2.50 2.90 2.12

0.52

0.26 ± 0.08

505 family groups of Japanese quail between 7-28 days Japanese quail selected for 4 week body weight Japanese quail with a medium age of sexual maturity (50 days)

Ducks Pingel (2011) Retailleau (1999) Retailleau (1999) Guy et al. (1998)

Pekin ducks between 28-49 days Pekin males between 0-49 days Muscovy males between 0-84 days Female mule ducks between 0-42 days

Guinea Fowl Nahashon et al. (2005) 2.10 -2.34 Tufarelli et al. (2007) 3.86

French guinea broilers fed diets differing in amounts of ME and CP Pearl gray guinea fowl from 28-91 days

Beef Nkrumah et al. (2007)

7.29

Schenkel et al. (2004)

6.11

Arthur et al. (2001)

6.70

0.41 ± 0.15 0.37 ± 0.06 0.46 ± 0.04

0.42 ± 0.15 0.38 ± 0.07 0.39 ± 0.04

0.78 ± 0.10 0.69 0.85 ± 0.05

464 crossbred beef cattle over 3 year test period Six types of purebred beef bulls over 112 or 140 test day period 5,493 Charolais bulls from 396-494 days

*By definition the average RFI across a measured population is zero and therefore not reported in this table †Genetic correlation (rg) between FCR and RFI ‡Note: Due to differing growth periods which are represented the comparisons are not direct, but an overview of what exists in the literature

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