**3.4. Age at first calving (AFC)**

Age at first calving (AFC) is the period between birth and first calving. It represents a period when animals cost the farmer due to yardage expenses. Yardage expenses include costs related to housing, feeding and veterinary care, which represent 15 to 20% of animal expenditures toward the cost of milk production (Mayer et al., 2004). Breeding programs aim to have AFC at 22 to 24 months of age, and reducing the AFC can increase animal life time efficiency (LTE) (Mayer et al., 2004, Vandehaar & St-Pierre, 2006). Reduced AFC should not compromise weight at calving. The data suggest that the optimum weight for Holstein cows right after calving, is 570 kg. The results also showed that milk yield will be reduced about 70 kg for every 10 kg body weight below the optimum (Vandehaar & St-Pierre, 2006). Therefore, AFC can be reduced by a combination of increasing average daily gain and decreasing age at breeding (Mayer et al., 2004). Decreased AFC, and consequently yard cost, is associated with increased feed cost to support a rapid growth rate. Furthermore, if the optimum breeding weight is not achieved, there will be a negative effect on subsequent milk production (Vandehaar & St-Pierre, 2006). Indeed, the economic benefit of a decreased AFC is not well understood and there is a need for further investigation.

#### **3.5. Environmental factors**

Changes in environmental conditions (temperature and humidity) and photoperiod are called seasonal changes. Seasonal changes affect energy efficiency by altering hormone signals and the target cell's responsiveness to hormonal stimulation (Collier et al., 2006). The thermoneutral zone is a range in which animals do not spend energy to maintain their normal body temperature. The upper critical range for dairy cattle is 25 to 26 0C and lower critical range depends on DIM and production level. The lower critical range is 2, -4 and - 10 0C for an animal at maintenance or producing 10 kg or 20 kg of milk, respectively. Dairy cows in cold stress do not need to change their energy requirements due to high heat production but it has an effect on feed digestibility. Research has shown that there is a 2% reduction in digestibility for every 10 degree reduction in ambient temperature; this can possibly be attributed to the increase in passage rate of digesta (NRC, 2001). Therefore, cold stress does not affect energy efficiency significantly in dairy cattle; while, mild to severe heat stress increases the maintenance requirements from 0.7 to 2.4 %, respectively, and decreases DMI. Heat stress affects animal behaviour, metabolism and efficiency (NRC, 2001).

128 Milk Production – An Up-to-Date Overview of Animal Nutrition, Management and Health

2008).

**3.4. Age at first calving (AFC)**

**3.5. Environmental factors**

0.6 (Bewley et al., 2008). Negative and positive correlations have been reported between milk yield and BW changes (-0.41 to 0.45) (Verrkamp, 1998) and BCS changes (Bewley et al., 2008). One BCS unit (5 point scale) is equivalent to ~400 Mcal of ME and its conversion ratio to milk is estimated at 0.82. It is enough to produce an additional 8 kg milk/day in the first 60 days in milk (Vandehaar, 1998; Bewley et al., 2008). Therefore, losing one unit of BCS supports around 2000 kg of increased milk production over 305 days and it is expected to increase GEE from 25 to 26.5% in cows with a production of 8000 kg milk (Vandehaar, 1998). The lost energy reserves are replaced by cows in late lactation, and its replenishment conversion ratio is less (0.7) than that for loss (0.8) (Moe, 1981), but loss of BCS still increases efficiency (Vandehaar, 1998). Besides the increased efficiency, some researchers point out that side effects of losing energy reserves on other traits like reproduction and health should be considered (Vandehaar, 1998; Bewley et al., 2008). For example, cows restart reproduction activity after they pass the NEB period (Goff, 2006). Some of the metabolic diseases such as ketosis/fatty liver complex are highly correlated with NEB (Collier et al., 2006). Researchers proposed that there is a curvilinear relationship between BCS at calving and milk production; furthermore, maximum milk production is associated with 3.25 to 3.5 BCS at calving (Roche et al., 2007; Bewley et al., 2008). Indeed, during early lactation, a controlled loss of body condition of 0.5 to 1.0 units is associated with optimal milk production, health, and reproductive performance. Moreover, excessive BCS losses at calving predispose the animal to metabolic disorders such as ketosis and fatty liver (Spain, 1996; Bewley et al.,

Age at first calving (AFC) is the period between birth and first calving. It represents a period when animals cost the farmer due to yardage expenses. Yardage expenses include costs related to housing, feeding and veterinary care, which represent 15 to 20% of animal expenditures toward the cost of milk production (Mayer et al., 2004). Breeding programs aim to have AFC at 22 to 24 months of age, and reducing the AFC can increase animal life time efficiency (LTE) (Mayer et al., 2004, Vandehaar & St-Pierre, 2006). Reduced AFC should not compromise weight at calving. The data suggest that the optimum weight for Holstein cows right after calving, is 570 kg. The results also showed that milk yield will be reduced about 70 kg for every 10 kg body weight below the optimum (Vandehaar & St-Pierre, 2006). Therefore, AFC can be reduced by a combination of increasing average daily gain and decreasing age at breeding (Mayer et al., 2004). Decreased AFC, and consequently yard cost, is associated with increased feed cost to support a rapid growth rate. Furthermore, if the optimum breeding weight is not achieved, there will be a negative effect on subsequent milk production (Vandehaar & St-Pierre, 2006). Indeed, the economic benefit of a decreased AFC

Changes in environmental conditions (temperature and humidity) and photoperiod are called seasonal changes. Seasonal changes affect energy efficiency by altering hormone

is not well understood and there is a need for further investigation.

Photoperiod, another environmental factor, affects lactation, reproduction, production, growth and immune function. Most studies are done using short or long day photoperiod concept. Results demonstrated that the physiological basis of attainment of puberty is controlled by photoperiod rather than ambient temperature. Long photoperiod causes early puberty that is associated with rapid growth in calves, and greater mammary parenchyma (Collier et al., 2006). Long day photoperiod can affect energy efficiency by lowering AFC, and increases milk production, but it does not affect feeding behaviour. In addition, other temporary environmental factors such as milking frequency can also affect milk production and energy efficiency. Wall & McFadden (2007) concluded that milking 2 times more frequently than usual (4 vs 2 times/day) for a 3 week interval during early lactation significantly increases milk production.

## **4. Indirect effects of selection for energy efficiency on some related traits**

To this point, factors that practically and directly affect energy efficiency in dairy cattle have been discussed; to maximize gain due to genetic selection for energy efficiency, its genetic base and indirect effects on other traits should also be known. Although reports on direct/indirect selection for efficiency in dairy cattle are scarce (Linn, 2006), many studies have been conducted to study its heritability and the direct/indirect effect that selecting animals based on efficiency traits has on other related traits in different species. The reviewed results showed that the weighted mean of 28 and 9 estimates of heritability in beef for FCR and GEE were reported as 0.32 ± 0.02 and 0.37 ± 0.05, respectively (Koots et al., 1994). The weighted mean of 35 estimates of heritability for RFI in 7 species was reported 0.25 ± 0.02 (Pitchford, 2004). In order to point out the potential effect of selection for efficiency on other related traits, authors discussed this effect on reproduction, activities, organs, body composition, metabolites and health in beef cattle as well as other species in addition to dairy cattle (table 1).


**Table 1.** Summary of indirect response of selection for energy efficiency on related traits in different species

## **4.1. Reproduction**

Reproductive performance and milk production are two main entities in the profitability of dairy cattle industry (LeBlanc, 2010). Although milk production and energy efficiency have increased, the genetic trend of average daughter fertility in Canadian Holsteins has shown a 2% reduction over 14 years. It decreased from 101.9 in 1995 to 99.9 in 2009 (Van Doormaal, 2010). As a result, a selection objective to increase milk production seems to favour cows that genetically produce more milk, but consequently are prone to experience more negative energy balance (NEB). It has been reported that the time of first estrus is closely related to NEB during the first 2 - 3 weeks after calving (Coffey et al., 2006) and "cows appear to resume reproductive activity only after the nadir of NEB has passed" (Veerkamp, 1998).

Some researchers studied the indirect effect of selection for energy efficiency on reproduction traits in beef, and other species. For example, Shaffer et al. (2010) allocated beef heifers into three groups based on their efficiency (low, medium and high RFI) and studied the indirect effects of selection for efficiency on reproduction performance. They reported a negative relationship between RFI and age at puberty. The efficient animals reached puberty later than inefficient animals but it did not affect pregnancy or conception rates. They also quantified this relationship and reported that each unit increase in RFI corresponds to a decrease of 7.5 days in age at puberty. Wang et al. (2012) studied the effect of RFI on bull's reproductive performance and fertility. They had 20 high RFI (inefficient) and 22 low RFI (efficient) beef bulls in a multi-sire breeding system on pasture and examined the association between RFI and semen quality traits (density, progressive motility and morphology), progeny per sire and some other related traits. They concluded that selection for RFI does not have a negative effect on reproductive performance and fertility in bulls bred in multi-sire groups on pasture.

In other species, Nielsen et al. (1997) divergently selected mice for energy efficiency, based on heat loss, over 15 generations. They had high efficient, low efficient and control groups, and each group had three replicates. Indirect effects of selection for energy efficiency on reproduction performance (litter size, ovulation rate, number of foetuses at 7 days of gestation and ovulation success) were measured. The results showed that the high efficient line (low heat loss) had 20% smaller litters at first parity in the 15th generation. The efficient line also had a 23% lower ovulation rate when measured at the second parity. However, the high efficiency line had a higher ovulation success rate (86%) than the low efficiency line (84%), but the differences were not significant (Nielsen et al., 1997). A report on pigs demonstrated that pigs with high litter size had a poorer efficiency compared to the control group (Estany et al., 2002). However, Morisson et al (1997) divergently selected hens for RFI over 18 generations and studied the effect of energy efficiency selection on reproduction and sperm characteristics. Contrary to mice and pigs, they found that a high efficient line of hens had only 6% unfertilised eggs compared with 30% in a low efficiency line. The early mortality rate in the inefficient line was twice that of the efficient line. Overall, the efficient line had a better hatchability performance (Morrisson et al., 1997). The better reproductive performance of efficient hens is supported by other researchers who selected hens for low RFI without losses in egg production (Bordas et al., 1992). It could be inferred that some species sacrifice litter size and maintain energy to better take care of the fetus. There is a need to study the associated effects of selection for energy efficiency and reproductive performance in dairy cattle.

#### **4.2. Activity**

130 Milk Production – An Up-to-Date Overview of Animal Nutrition, Management and Health

Data not available. Data not

available.

Did not affect tissues of gastro intestinal organs and internal organs (Richardson et al., 2001).

composition

Less body fat (Richardson et al., 2001) more empty body water (Basarb et al., 2003).

Fatter (Hughes & Pitchford, 2004)

results, increase or decrease fat traits (Liting & Urff, 1991)

Controversial

Data not available. Metabolites Health

Increases the incidence of metabolic diseases (Wassmuth et al., 2000)

Data not available.

Data not available.

Data not available.

Low plasma protein, blood concentration of urea and aspartate amino transfer (Herd & Arthur, 2009) high insulin, glucose and NEFA (Kelly et al., 2010).

Species Reproduction Activities Organs Chemical

Less feeding duration and less head-down time, (Durunna et al., 2010; Nkrumah et al., 2006; Kelly et al., 2010).

Less feeding time, less visits per day, less total time in feeder (Von Felde et al., 1996)

Less activities (Hastings et al., 1997; Rau et al., 2000)

Less activities (Luiting &Urff.,

1991)

Larger livers, caeca, stomachs but smaller hearts (Hughes & Pitchford, 2004)

**Table 1.** Summary of indirect response of selection for energy efficiency on related traits in different

Reproductive performance and milk production are two main entities in the profitability of dairy cattle industry (LeBlanc, 2010). Although milk production and energy efficiency have increased, the genetic trend of average daughter fertility in Canadian Holsteins has shown a 2% reduction over 14 years. It decreased from 101.9 in 1995 to 99.9 in 2009 (Van Doormaal, 2010). As a result, a selection objective to increase milk production seems to favour cows that genetically produce more milk, but consequently are prone to experience more negative

Dairy Decrease daughter fertility

Beef Decreases age at

Pig Decreased litter

2002)

Mice Decreased litter

Chicken Increased fertility, hatchability, decreased mortality (Morrisson et al., 1997). No losses in egg production (Bordas et al.,1992)

**4.1. Reproduction** 

species

size (Estany et al.,

size, ovulation rate (Nielsen et al., 1997)

puberty, does not affect pregnancy rate (Shaffer et al., 2010). Did not affect bull performance (Wang et al., 2012).

> Energy expenditure of feeding depends on feeding behaviour. In addition, results of studies in different species have shown that selection for efficiency had effects on animal's feeding

behaviour. Durunna et al (2010) conducted a 3 year study on 402 and 419 steers on two different diets (grower and finisher). They measured feed intake, feeding duration, headdown time and bunk visits using the Growsafe system. Their results showed that the efficient steers (Low RFI) exhibited less feeding duration, head down time, and bunk visits. In another study, efficient beef cattle (low RFI) had less feeding duration, but a higher feeding frequency (Nkrumah et al., 2006). These results are also supported by other researchers studying finishing heifers (Kelly et al., 2010) that showed efficient heifers had less feeding duration.

Some studies have been done on mice to determine the effect of selection for RFI on activity. Hastings et al (1997) found that high efficiency (low RFI) mice were 67% less active than the low efficiency mice. Furthermore, Rauw et al (2000) selected mice for high litter size at birth (S line) and showed that the S line had higher RFI (low efficiency). They reported that low efficiency mice, when compared with control group, had more locomotion activity, and they ran faster in two types of runaway tests. In hens, Luiting &Urff (1991) reported that high efficient layer hens were less active than the control group. However, efficient boars had a lower feeding rate, less feed intake per visit, fewer visits per day, and less total time in the feeder per day (Von Felde et al., 1996). Herd & Arthur (2009) concluded that the positive and high genetic correlation of feeding time per day and eating sessions per day with RFI indicates that there are some common genes controlling feeding behaviour and RFI.

## **4.3. Organs and body composition**

Liver, the largest visceral organ, accounts for 17 to 31% of total body energy expenditures (Eisemann & Nienaber, 1990; Ortigues and Visseiche 1995). All of the visceral organs account for up to 40 to 50% of body energy expenditures in sheep and cattle (Perry et al., 1997). It was concluded that selection for efficiency may result in lower proportions of liver and visceral tissues (Pitchford, 2004). In female mice, the results contradicted this conclusion and the efficient mice (low RFI) had larger livers, caeca, intestines, and stomachs but smaller hearts (Hughes & Pitchford, 2004). In cattle divergently selected for RFI, the weight of highly activate tissues of gastrointestinal organs and internal organs were not significantly different. It was concluded that variation in ME intake and energy efficiency was due to metabolic processes rather than changes in body composition (Richardson et al., 2001).

Results of divergently selecting steers for RFI showed that there is a correlation between chemical composition and variation in RFI. Animals with low RFI had more whole-body chemical protein and less whole-body chemical fat (Richardson at al., 2001). Basarab et al (2003) also found that efficient steers had more empty body water but less empty body fat than low efficient steers. The divergently selected steers had almost the same amount of empty body protein. In another study, Shaffer et al (2010) grouped beef heifers of British breeds into low, medium and high RFI groups and found that efficient heifers (low RFI) had less lean meat area (cm2) per 100 kg of BW than inefficient (high RFI) heifers. In mice, the results have shown that the high efficiency lines had slightly lower post-weaning weight (0- 12%), little differences in mature weight (0-30%) and were fatter (5-60% depending on the age at measurement) than low efficiency lines. Luiting & Urff (1991) summarized reports of phenotypic and genetic correlations between RFI and body fat traits in chickens and found that they ranged from -0.4 to 0.45. Herd & Arthur (2009) concluded that the amount and direction of association between body composition and variation in energy efficiency in cattle depends on age and stage of maturity.

## **4.4. Metabolites and health**

132 Milk Production – An Up-to-Date Overview of Animal Nutrition, Management and Health

less feeding duration.

**4.3. Organs and body composition** 

behaviour. Durunna et al (2010) conducted a 3 year study on 402 and 419 steers on two different diets (grower and finisher). They measured feed intake, feeding duration, headdown time and bunk visits using the Growsafe system. Their results showed that the efficient steers (Low RFI) exhibited less feeding duration, head down time, and bunk visits. In another study, efficient beef cattle (low RFI) had less feeding duration, but a higher feeding frequency (Nkrumah et al., 2006). These results are also supported by other researchers studying finishing heifers (Kelly et al., 2010) that showed efficient heifers had

Some studies have been done on mice to determine the effect of selection for RFI on activity. Hastings et al (1997) found that high efficiency (low RFI) mice were 67% less active than the low efficiency mice. Furthermore, Rauw et al (2000) selected mice for high litter size at birth (S line) and showed that the S line had higher RFI (low efficiency). They reported that low efficiency mice, when compared with control group, had more locomotion activity, and they ran faster in two types of runaway tests. In hens, Luiting &Urff (1991) reported that high efficient layer hens were less active than the control group. However, efficient boars had a lower feeding rate, less feed intake per visit, fewer visits per day, and less total time in the feeder per day (Von Felde et al., 1996). Herd & Arthur (2009) concluded that the positive and high genetic correlation of feeding time per day and eating sessions per day with RFI

indicates that there are some common genes controlling feeding behaviour and RFI.

Liver, the largest visceral organ, accounts for 17 to 31% of total body energy expenditures (Eisemann & Nienaber, 1990; Ortigues and Visseiche 1995). All of the visceral organs account for up to 40 to 50% of body energy expenditures in sheep and cattle (Perry et al., 1997). It was concluded that selection for efficiency may result in lower proportions of liver and visceral tissues (Pitchford, 2004). In female mice, the results contradicted this conclusion and the efficient mice (low RFI) had larger livers, caeca, intestines, and stomachs but smaller hearts (Hughes & Pitchford, 2004). In cattle divergently selected for RFI, the weight of highly activate tissues of gastrointestinal organs and internal organs were not significantly different. It was concluded that variation in ME intake and energy efficiency was due to metabolic processes rather than changes in body composition (Richardson et al., 2001).

Results of divergently selecting steers for RFI showed that there is a correlation between chemical composition and variation in RFI. Animals with low RFI had more whole-body chemical protein and less whole-body chemical fat (Richardson at al., 2001). Basarab et al (2003) also found that efficient steers had more empty body water but less empty body fat than low efficient steers. The divergently selected steers had almost the same amount of empty body protein. In another study, Shaffer et al (2010) grouped beef heifers of British breeds into low, medium and high RFI groups and found that efficient heifers (low RFI) had less lean meat area (cm2) per 100 kg of BW than inefficient (high RFI) heifers. In mice, the results have shown that the high efficiency lines had slightly lower post-weaning weight (0- 12%), little differences in mature weight (0-30%) and were fatter (5-60% depending on the There are some reports on associations between efficiency and some metabolites, which are indicators of production, and health. For example, high concentrations of total plasma protein, blood concentrations of urea and aspartate amino transfer were reported in high RFI cattle (inefficient) compared to low RFI (efficient). These metabolites are an index of protein turnover and inefficient cattle had higher protein turnover rates compared to low efficient cattle (Herd & Arthur, 2009). In other research, Kelly et al (2010) divergently selected heifers based on RFI and found that inefficient animals had higher plasma urea, Bhydroxybutyrate, and leptin concentration and lower NEFA, plasma glucose and insulin than efficient animals. Higher levels of cortisol and red and white blood cells were reported in high RFI steers, which indicates that these animals (inefficient) may be more susceptible to stress (Richardson et al., 2004). In another report, a positive correlation between IGF-I, a growth metabolite, and RFI was reported in beef cattle (Moore et al., 2005). However, separation of RFI into post weaning and feedlot periods determined that there is a positive correlation of IGF-I with RFI during post weaning time while there is a negative correlation during the feedlot period (Herd & Arthur., 2009). Kelly et al (2010) concluded that some plasma analytes such as B-hydroxybutyrate may be potential indicators of net efficiency in beef cattle.

Overall, animals are efficient and profitable, if they are healthy. Rauw et al (1998) reviewed undesirable effects of selection for high efficiency in farm animals and concluded that selection had a negative correlation with health traits. Wassmuth et al (2000) used feed intake data of 7752 young dairy bulls (2203 Danish Red, 4527 Danish Friesian and 1022 Danish Jersey), and combined the feed intake data with recorded incidence of mastitis, retained placenta, metritis, sole of ulcer and ketosis data of 473,613 dairy cows in their early lactation to investigate the relationship between efficiency and diseases in dairy cattle. They defined efficiency as "the feed energy intake per kilogram live weight gain" in bulls. The size and direction of relationship depended on breed, but the overall energy efficiency was positively correlated with incidence of diseases. Currently, selection indices in dairy cattle favour animals with high milk production and consequently negative energy balance (NEB). NEB is generally related to poorer health status and fertility and it can have an indirect economic effect (Goff, 2006; Veerkamp, 1998).

Overall, the physiological basis of energy efficiency (RFI) has been reviewed by Herd & Arthur (2009). The results of Angus steers divergently selected for net feed efficiency (RFI) revealed that feeding pattern, metabolism including turn over and stress, body composition, digestibility, heat increment of fermentation, and activity accounted for 2, 37, 5, 10, 9 and 10 % of the variation in RFI, respectively, and the remaining variation was attributed to other unknown processes (Herd & Arthur, 2009).
