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The influence of feeding behaviour on feed intake curve parameters and performance traits of station-tested boars
Livestock Production Science 82 (2003) 105–116 www.elsevier.com / locate / livprodsci
The influence of feeding behaviour on feed intake curve parameters and performance traits of station-tested boars a a a b a, V. Schulze , R. Roehe , J. Lorenzo Bermejo , H. Looft , E. Kalm * a
¨ Tierzucht und Tierhaltung, Christian-Albrechts-Universitat ¨ , Hermann-Rodewald-Straße 6, D-24118 Kiel, Germany Institut f ur b PIC Deutschland, Ratsteich 31, D-24837 Schleswig, Germany Received 12 June 2001; received in revised form 9 January 2003; accepted 3 February 2003
Abstract The use of feed intake behaviour traits, obtained from electronic feeding stations, and feed intake curve parameters to genetically improve performance traits was analysed. Daily feed intake and feed intake behaviour of 5601 group-penned boars of two dam lines were recorded by electronic feeders in weeks 1, 3, 5, 7 and 9 during 10 weeks (100–170 d) on performance test. Additionally, performance test traits and parameters of an individually fitted linear-quadratic regression of feed intake on time on test, were available. A multiple trait animal model considering observed feed intake and feed intake behaviour at each test week as a different trait was used. Estimated heritabilities for feed intake and feed intake behaviour of the entire test period were 0.39, 0.46, 0.34, 0.44, 0.44 and 0.41 for daily feed intake, time per day, visits per day, time per visit, feed intake per visit, and feed intake rate, respectively. Heritabilities for behavioural traits in each test week were below estimates of entire test and showed lower variation, except for daily feed intake and time per day. Residual standard deviation of feed intake using linear-quadratic regression on time on test showed a moderate heritability of 0.22. Genetic correlations of feed intake behaviour traits indicate that number of visits per day was independent from growth performance, while time per day was genetically associated with average daily gain and daily feed intake (0.31 and 0.41). In contrast, visits per day and related traits such as time per visit and feed intake per visit were genetically correlated with residual standard deviation of linear-quadratic regression (20.28, 0.31 and 0.39). Feed intake per visit in the seventh test week resulted in the highest genetic correlation (0.45) with residual standard deviation of the feed intake curve. This residual standard deviation and related traits will be of increasing interest for future breeding programs in order to obtain high performances in a wide range of environments. 2003 Elsevier B.V. All rights reserved. Keywords: Feed intake behaviour; Feed intake curve parameters; Genetic correlations; Growth performance; Heritabilities; Pig-feeding and nutrition
1. Introduction *Corresponding author. Tel.: 149-431-880-2584; fax: 149431-880-2588. E-mail address: [email protected] (E. Kalm).
Electronic feeding stations deliver information about the individual feed intake pattern of grouppenned pigs. These informations were not available
0301-6226 / 03 / $ – see front matter 2003 Elsevier B.V. All rights reserved. doi:10.1016 / S0301-6226(03)00034-4
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V. Schulze et al. / Livestock Production Science 82 (2003) 105–116
before, when either individually penned boars or group-penned progeny were performance tested, to obtain information about feed intake and food conversion. For improving efficient lean growth, Labroue et al. (1997) suggested the replacement of food conversion ratio in a selection index by behavioural traits related to feed intake (feed intake per visit or feed intake rate). Hall et al. (1999b) recommended the incorporation of number of visits per day additionally to feed intake, daily gain and backfat thickness in a selection index, in order to predominantly improve feed efficiency. They also concluded that loss of accuracy of measurements due to reduced length of the recording period of feed intake by electronic feeders can be regained by behavioural traits. Knap (1995) mentioned differences between animals in within-animal variation for feed intake and explained this phenomenon as the individual ability to react to short term environmental influences. As conditions of pig housing are still very heterogeneous, development of animal robustness towards these environmental influences can be of increasing interest for future pig breeding programs. In this study, genetic relationships between feed intake behaviour, performance test traits, and feed intake of test weeks were analysed. Furthermore, genetic associations between behavioural traits and feed intake curve parameters using linear-quadratic regression were investigated for the entire test period and particular test periods. As a predictor for the within-animal variation, the residual standard deviation of the individual feed intake curve during performance test was estimated and analysed with respect to behavioural traits.
2. Material and methods
weeks. On test station, the animals were kept on straw in groups of 12 of the same line. They were given ad libitum a dry pelleted food containing 12.6 MJ metabolizable energy, 10 g lysine and 180 g crude protein per kg. Performance test started after 10 days of adaptation at an average age of 100 days and finished after 10 weeks at an average age of 170 days. For each animal, average daily gain on test (ADG), backfat thickness (BF), daily feed intake (DFI) and food conversion (FC) were available. Backfat thickness was calculated as the mean of two measurements taken 4 and 8 cm lateral off the mid-line between 13th and 14th rib and one measurement taken 4 cm lateral off the mid line on the loin using a one-dimensional ultrasonic Renco device. Feed intake and time information were recorded by ACEMA 48 electronic feeding stations during test weeks 1, 3, 5, 7 and 9, while animals had free access to conventional feed dispensers during remaining test weeks. Successive individual feed intake records differing less than 40 s were condensed to one visit according to results of von Felde (1996). To account for adaptation to the feeder, the first two test days of each test week with feed intake informations were removed from the dataset according to previous results (Schulze et al., 2001). Animals were not considered in the analysis when at least one test week with feed intake was missing or was below the feed intake expected for maintenance within test weeks. Daily feed intake was derived from the total amount of recorded feed intake divided by the number of corresponding days at the feeder. Food conversion was calculated as the ratio of daily feed intake to average daily gain on test. Means (6S.D.) of average daily gain on test, backfat thickness and food conversion ratio were 1015 (6124) g / day, 10.9 (62.1) mm and 2548 (6303) g food per kg gain, respectively.
2.1. Data 2.2. Feed intake and feed intake behaviour The data consist of 5601 young boars from two dam lines (3125 of line three originated from Large White, 2476 of line four originated from Landrace), recorded at the central test station of PIC Germany between June 1992 and April 1998. Piglets were born on five farms, weaned after 3 weeks and reared together in a nursery nearby the test station for 10
Based on feed intake and duration of individual visits, behavioural traits such as feed intake rate (FR), visits per day (VD), time per visit (TV), time per day (TD) and feed intake per visit (FIV) were calculated for the entire test period as well as for single test weeks. Over the entire test period, the
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Table 1 Phenotypic means and standard deviations (6S.D.) for feed intake and feed intake behaviour per test week and of the entire test period Trait a
Unit
Week 1
Week 3
Week 5
Week 7
Week 9
Entire period b
DFIw TDw VDw FRw TVw FIVw
(g / day) (min) (no.) (g / min) (min) (g)
17246452 58.2616.2 8.064.5 30.666.4 9.864.4 2946137
22706475 63.9615.4 7.564.5 36.967.6 11.364.9 4076180
25606512 62.1614.8 6.863.9 42.968.9 11.864.9 4916205
28066551 59.1614.5 6.463.7 49.6610.3 11.764.7 5626220
29836617 56.4614.5 6.263.6 55.4612.1 11.664.7 6196240
24826340 60.1611.1 7.063.4 43.267.8 11.363.8 4766163
a
DFIw5feed intake per day and test week, TDw5Time per day and test week, VDw5Visits per day and test week, FRw5Feed intake rate per test week, TVw5Time per visit and test week, FIVw5Feed intake per visit and test week. b Abbreviations for traits of the entire test period: DFI, TD, VD, FR, TV, FIV.
animals stayed 1 h per day at the feeder and consumed 2482 g of food during seven visits per day (Table 1). This resulted in an average meal size of 476 g, an average time per visit of 11 min and a feed intake rate of 43 g per min. In general, daily feed intake and all feed intake behaviour traits changed during the performance test. Daily feed intake of test weeks increased with decreasing increments during test. Feed intake rate per visit increased almost linearly with time on test while number of visits per day decreased from eight visits in first test week to six visits in test week 9. Time per day at the feeder showed a maximum of 64 min in test week 3 and afterwards decreased. Time per visit was nearly constant at around 11.5 min during the test except for test week 1. Feed intake per visit more than doubled from first to last test week (294–619 g). The highest coefficient of variation was obtained for number of visits per day (56–60%) and related traits such as time per visit and feed intake per visit (39–47%). The coefficient of variation for daily time at the feeder ranged from 24 to 28% while feed intake rate variation was almost constant in all test weeks (21–22%).
2.3. Feed intake curve information A linear-quadratic regression was fitted for individual daily feed intake on time on test to obtain feed intake curve parameters. Based on this function, the average estimated feed intake (AEFI) was derived for five periods of 12 days by integration of this function. The average change in daily feed intake (slope) was calculated for corresponding 12 day periods from the individually fitted linear-quad-
ratic regression. A detailed description of the estimated feed intake curve parameters are given by Schulze et al. (2002). Briefly described, the average estimated feed intake for periods increased from first to last period from 1882 to 2994 g.
2.4. Statistical analysis For estimation of variance components, a multiple-trait animal model was fitted using multivariate REML program MTDFS (Misztal, 1993). The model can be described as following: y i 5 Xb i 1 Zu i 1 e i where y i is the vector of observations for the trait i, b i is the vector of fixed effects of birth farm (5 levels), quarter of year of beginning performance test (21 different seasons), line (two lines) and a linear regression on average weight at start of test (45.9 kg), u i is the vector of random additive genetic effects of animals, and e i is the vector of random residual effects. X and Z are incidence matrices for fixed and random effects, respectively. The variance covariance matrix of the genetic effects u of all traits is A^G, where A is the numerator relationship matrix, G is the matrix of genetic variances and covariances between traits and ^ represents the Kronecker product. The variance covariance matrix of residuals e is I^R, where I is the identity matrix and R is the matrix of residual variances and covariances between traits. Animals were progeny of 581 sires and 2913 dams (297 and 1558 of line 3, 284 and 1355 of line 4). Pedigree information of 9839 ancestors were available for genetic analysis
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using for each animal information up to the fifth generation. Standard errors of genetic correlations were approximated by the method of Robertson (1959).
3. Results
3.1. Heritabilities of feed intake behaviour traits Genetic parameters of feed intake behaviour traits of the entire test period are presented in Table 2.
Traits describing feed intake behaviour can be classified into basic traits characterising feed consumption, duration and frequency of visits (DFI, TD, VD) and traits derived from the former ones (FR, TV, FIV). Time depending traits such as time per day, time per visit, and feed intake rate showed highest heritabilities, while estimates of visits per day, daily feed intake and feed intake per visit were slightly lower. Residual standard deviation of feed intake curve, using linear-quadratic regression, showed a moderate heritability of h 2 5 0.22. Table 3 summarises the estimates of feed intake and feeding
Table 2 2 Genetic ( sˆ a ) and residual ( sˆ e ) standard deviations and heritabilities (h ) for performance traits and feed intake behaviour traits of entire test Trait
Unit
sˆ a
sˆ e
h 2 6S.E.
Average daily gain on test (ADG) Backfat thickness (BF) Food conversion (FC) Average daily feed intake on test (DFI) Time per day (TD) Visits per day (VD) Feed intake rate (FR) Time per visit (TV) Feed intake per visit (FIV) Residual standard deviation (R.S.D.)a
(g / day) (mm) (g / kg) (g / day) (min) (no.) (g / min) (min) (g) (g)
68.7 1.24 145.3 192.4 7.40 1.93 4.89 2.50 101.2 74.2
91.5 1.24 229.8 239.7 7.97 2.71 5.47 2.85 121.1 140.2
0.3660.04 0.5060.03 0.2860.04 0.3960.03 0.4660.03 0.3460.04 0.4460.03 0.4460.03 0.4160.03 0.2260.05
a
R.S.D. based on linear-quadratic regression of feed intake on time.
Table 3 2 Genetic ( sˆ a ) and residual ( sˆ e ) standard deviations and heritabilities (h ) for daily feed intake and feed intake behaviour traits per test week Traits a
Unit
Estimate
Week 1
Week 3
Week 5
Week 7
Week 9
DFIw
(g / day)
TDw
(min)
VDw
(no.)
FRw
(g / min)
TVw
(min)
FIVw
(g)
sˆ a sˆ e h2 sˆ a sˆ e h2 sˆ a sˆ e h2 sˆ a sˆ e h2 sˆ a sˆ e h2 sˆ a sˆ e h2
150.3 400.9 0.1260.05 7.59 14.11 0.2260.04 2.31 3.86 0.2660.04 3.63 4.86 0.3660.04 2.36 3.62 0.3060.04 69.1 112.0 0.2860.04
210.2 389.1 0.2360.04 8.57 12.64 0.3260.04 2.29 3.81 0.2760.04 4.27 5.77 0.3560.04 2.73 3.94 0.3260.04 98.1 142.3 0.3260.04
257.3 401.1 0.2960.04 8.22 12.04 0.3260.04 1.98 3.35 0.2660.04 5.27 6.66 0.3960.03 2.77 4.00 0.3360.04 115.5 161.9 0.3460.04
331.2 416.2 0.3960.03 8.09 11.75 0.3260.04 1.90 3.07 0.2860.04 6.03 7.83 0.3760.04 2.54 3.90 0.3060.04 123.2 176.8 0.3360.04
340.4 500.0 0.3260.04 8.26 11.48 0.3460.04 1.75 3.11 0.2460.04 6.58 9.50 0.3260.04 2.59 3.91 0.3060.04 124.4 202.6 0.2760.04
a
For abbreviations and units see Table 1.
V. Schulze et al. / Livestock Production Science 82 (2003) 105–116
behaviour traits per test week. In general, all heritabilities were lower compared to those found for the entire test period (Table 2). Heritabilities of test week feed intake increased with time on test and reached a maximum in test week 7. Heritabilities of behavioural traits showed less variation among stages of growth than daily feed intake. Only for time per day recorded at test week 1, heritability was substantially lower compared to estimates of the following weeks.
3.2. Genetic correlations between performance traits and feed intake behaviour Based on the genetic correlations among behavioural traits, time per day and feed intake rate as well as visits per day and its derivatives time per visit and feed intake per visit were closely related (Table 4). Genetic correlations between feed intake behaviour traits and performance traits were always lower than 0.41. Of all behavioural traits highest associations with performance were found for time per day at the feeder, and these were moderate to DFI and ADG (r a 5 0.41 and 0.31), but still low to BF and FC. Also feed intake rate was lowly associated with performance traits, while visits per day and related traits like time per visit and feed intake per visit showed almost no association with performance traits. Moderate associations were found between visits per day, time per visit, feed intake per visit and
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residual standard deviation of the linear-quadratic feed intake curve (r a 5 2 0.28, 0.31, and 0.39). Higher residual standard deviations (R.S.D.) were desirably associated with ADG and food conversion (r a 5 0.37, 20.29) but undesirably with backfat thickness (r a 5 0.29). Especially, estimates for test week 1 were associated with larger standard errors. Genetic correlations between feed intake behaviour and parameters of the linear-quadratic regression and its derived average estimated feed intake and slope for periods are presented in Table 5. Associations of linear-quadratic regression parameters with feed intake behavioural traits were low and very often non-significantly different from zero. Time per day had the highest genetic association with the intercept of linear-quadratic regression (r a 5 0.23), but no association with linear and quadratic terms. Highest associations with these regressors were found for visits per day and feed intake per visit. Estimates of genetic correlations between time per day or feed intake rate and daily feed intake per period were higher when using the estimated feed intake based on a second order polynomial instead of observed weekly feed intake in Table 4. Traits related to visits (visits per day and time per visit) were not correlated with average estimated feed intake. Genetic associations between feed intake behaviour and slope of feed intake curves per period were low and decreasing with time on test. Correlations between slope of the feed intake curve in
Table 4 Genetic correlations between feed intake behaviour traits of the entire test period, performance traits and daily feed intake per test week Trait a
R.S.D.
TD
VD
FR
TV
FIV
TD VD FR TV FIV BF ADG FC DFI DFIw 1 DFIw 3 DFIw 5 DFIw 7 DFIw 9
20.0560.08 20.2860.10 0.1060.09 0.3160.08 0.3960.08 0.2960.07 0.3760.09 20.2960.11 0.1260.09 20.1660.19 0.1760.13 0.1260.12 0.0560.10 0.0760.11
–
– – 20.2260.06 20.8160.02 20.9260.01 0.0560.05 0.0160.08 0.0460.09 0.0260.07 0.1460.15 20.0160.10 20.0660.09 0.0160.07 0.0660.08
– – – 20.2960.04 0.2360.05 0.1660.04 0.1460.06 0.1060.07 0.2060.05 0.0160.11 0.1360.08 0.1960.07 0.2160.05 0.1260.06
– – – –
– – – – –
a
0.2560.06 20.8160.02 0.2560.04 20.1460.05 0.1860.04 0.3160.05 0.1860.07 0.4160.04 0.2560.10 0.2960.07 0.3160.06 0.3160.05 0.3360.05
For abbreviations and units see Tables 1 and 2.
0.8660.01 20.0260.04 0.0460.06 20.0160.07 0.0360.05 20.0960.12 0.0060.08 0.0960.07 0.0360.06 20.0160.07
0.0960.05 0.1560.06 0.0560.08 0.1760.06 20.0660.13 0.1160.09 0.2260.07 0.1760.06 0.0860.07
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Table 5 Genetic correlations between feed intake behaviour traits of the entire test period, feed intake curve parameters of linear-quadratic regression function and average estimated feed intake (AEFI) and its slope Trait a
DFI b
TD b
VD b
FRb
TV b
FIV b
b0 b1 b2 R.S.D. AEFI p1 p2 p3 p4 p5 Slope p1 p2 p3 p4 p5
0.0560.14 0.5260.08 20.2760.10 0.1260.09 0.5660.07 0.8260.02 0.9260.01 0.9860.00 0.8760.01 0.5960.07 0.7260.05 0.6060.04 0.2460.07 0.0660.09
0.2360.11 0.1160.09 20.0360.09 20.0560.08 0.3260.08 0.3360.05 0.3460.05 0.3660.04 0.3360.04 0.1360.09 0.1860.08 0.1960.06 0.1160.07 0.0660.08
0.1860.15 20.2060.12 0.2060.12 20.2860.10 0.1060.12 20.0360.08 20.0560.07 20.0360.06 0.0360.07 20.1860.12 20.1460.11 20.0160.08 0.0960.09 0.1360.10
20.0860.12 0.2260.09 20.1760.09 0.1060.09 0.0660.10 0.1960.06 0.2360.05 0.2260.05 0.1760.05 0.2360.09 0.2360.08 0.1460.06 0.0060.07 20.0660.08
20.1460.12 0.1660.10 20.1560.10 0.3160.08 20.0760.10 0.0460.06 0.0760.06 0.0560.05 0.0160.05 0.1560.10 0.1460.09 0.0460.06 20.0660.08 20.0960.09
20.1560.13 0.2960.10 20.2460.10 0.3960.08 0.0060.10 0.1860.07 0.2260.06 0.2060.05 0.1260.05 0.2960.09 0.2860.08 0.1260.07 20.0560.08 20.1260.09
a Intercept (b 0 ), linear term (b 1 ), quadratic term (b 2 ), residual standard deviation (R.S.D.) based on linear-quadratic regression, AEFI, Slope5average estimated feed intake and rate of increase of feed intake in five periods of 12 days (p1–p5) based on linear-quadratic regression. b For abbreviations and units see Table 2.
periods one to three were moderate to daily feed intake (r a 50.59–0.60), low to time per day, feed intake rate and feed intake per visit for same periods (r a 50.12–0.29), while visits per day and time per visit had no significant association with average increase of feed intake in any of the periods. Visits per day, time per visit and feed intake per visit showed highest correlation to residual standard deviation of feed intake curve using linear-quadratic regression.
3.3. Genetic associations between feed intake behaviour of each test week and performance traits In addition to DFI, all behaviour traits were analysed for each single test week. Genetic correlations between time per day (TDw) and feed intake (DFIw) in Table 6 showed in each corresponding week moderate estimates (r a 50.47–0.57), and these correlations were higher than associations of the same traits over the entire test period (r a 5 0.41) in
Table 6 Genetic correlations between performance traits and time in the feeder per day (TDw) in different test weeks Trait a
TDw 1
TDw 3
TDw 5
TDw 7
TDw 9
DFIw 1 DFIw 3 DFIw 5 DFIw 7 DFIw 9 BF ADG DFI FC TD VD
0.4960.15 0.2460.13 0.2060.11 0.0860.09 0.0860.11 0.0960.07 0.1660.10 0.2360.09 0.1360.12 0.9060.01 0.2960.09
0.2160.15 0.5160.08 0.2660.09 0.1260.07 0.1460.08 0.1160.06 0.2860.07 0.3060.07 0.0760.10 0.9060.01 0.2460.08
0.2260.14 0.2760.10 0.4760.07 0.2860.07 0.2860.08 0.2060.05 0.3160.07 0.4260.06 0.1960.09 0.9460.01 0.2060.08
0.2260.14 0.1860.10 0.2760.08 0.5660.05 0.4860.06 0.2560.05 0.3660.07 0.5160.05 0.2560.09 0.9260.01 0.2360.08
0.0160.14 0.1260.10 0.2060.08 0.3760.06 0.5760.05 0.1660.05 0.2860.07 0.4160.06 0.2260.09 0.8860.01 0.1960.07
a
For abbreviations see Tables 1 and 2.
V. Schulze et al. / Livestock Production Science 82 (2003) 105–116
Table 4. The magnitude of genetic correlations of time per day to performance traits increased with time on test and reached a maximum in test week 7. While daily gain or daily feed intake were associated with time per day in all test weeks, backfat thickness and food conversion ratio were non-significantly correlated with duration time in test weeks 1 and 3. Because of mainly low associations between the other feed intake behaviour and performance traits, meaningful results are further on only presented in the text. Number of visits for each test week were not significantly associated with performance traits and feed intake per test week (DFIw) except of daily feed intake in test week 9 (r a 5 0.21). Only feed intake in test weeks 5 and 7 showed low but significant association with feed intake per visit in test weeks 5 (r a 5 0.32, 0.19) and seven (r a 5 0.26, 0.20). No associations with performance traits were found for feed intake per visit in test weeks 1 and 3, while correlations for following test weeks 5–9 were low to daily feed intake, average daily gain and backfat thickness (r a 50.14–0.21). Time per visit and feed intake rate for each test week showed no important correlations with performance traits and thus were not presented.
3.4. Feed intake curve parameters and behavioural traits in test weeks Genetic correlations between time per day in each test week and feed intake curve parameters of linearquadratic regression, average estimated feed intake
111
and its slope are shown in Table 7. Association of the intercept (b 0 ) of feed intake curve was highest with time per day in the first test week and decreased with time on test. Correlations of AEFI in periods to time per day in test weeks were similar to those between feed intake per test week and time per day per test week in Table 6, slightly lower on the diagonal for corresponding periods but higher to adjacent test weeks. In general, all estimates with AEFI were accompanied with lower standard errors compared to estimates with observed feed intake (DFI). Low to moderate correlations of time per day in test weeks 5–9 were found with slope of feed intake curve in all periods. Correlations of number of visits per day (results for this trait only present in the text) with residual standard deviation were low and increased slightly with time on test from r a 5 2 0.1760.12 to 20.3860.12. Also, associations between frequency of visits and slope of feed intake in test weeks were low and increased with time on test to r a 5 0.29. Table 8 shows correlations between feed intake per visit for different test weeks and feed intake curve information. Correlation of the residual standard deviation of feed intake curve with feed intake per visit in the first test week was low and increased to a maximum in test week 7 (r a 5 0.45). Average estimated feed intake showed low correlations with meal size of test weeks 5–9. Average daily change of feed intake in periods one and two was associated with feed intake per visit of test weeks 3–9, while the slope of the feed intake curve in the following
Table 7 Genetic correlations between feed intake curve parameters b and time per day (TDw) in different test weeks Trait a
TDw 1
TDw 3
TDw 5
TDw 7
TDw 9
b0 AEFI p1 AEFI p2 AEFI p3 AEFI p4 AEFI p5 Slope p2 Slope p3 Slope p4 Slope p5
0.5060.16 0.4960.12 0.3160.10 0.2160.09 0.1660.08 0.1160.08 20.1160.14 20.1060.10 20.0660.12 20.0360.14
0.3660.15 0.4560.10 0.4160.07 0.3460.07 0.2660.06 0.1560.07 0.0860.12 20.0560.08 20.1460.10 20.1660.11
0.2160.16 0.3360.11 0.4260.07 0.4360.06 0.4260.05 0.3460.05 0.2860.11 0.1860.08 0.0360.10 20.0460.11
0.1860.16 0.2460.12 0.3260.07 0.4060.06 0.5060.05 0.5560.05 0.3160.10 0.4360.07 0.3460.09 0.2660.10
0.0560.16 0.0960.12 0.1760.08 0.2860.07 0.4360.05 0.5460.05 0.2860.10 0.4960.06 0.4560.07 0.3860.09
a b
For abbreviations and units see Tables 1 and 5. Correlations of feed intake curve parameters b 1 , b 2 R.S.D. and Slope of period 1 (p1) were low and not significantly different from zero.
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Table 8 Genetic correlations between feed intake curve parameters b and food intake per visit in test weeks Trait a
FIVw 1
FIVw 3
FIVw 5
FIVw 7
FIVw 9
b1 b2 R.S.D. AEFI p2 AEFI p3 AEFI p4 Slope p1 Slope p2
0.1260.14 20.1460.14 0.1560.12 0.0460.09 0.0360.08 20.0160.07 0.0860.14 0.0360.12
0.2760.12 20.2260.12 0.2960.10 0.1060.08 0.1660.07 0.1560.06 0.2660.12 0.2560.11
0.4360.10 20.4060.10 0.4460.09 0.2860.07 0.3260.06 0.2660.06 0.4160.10 0.3660.09
0.3660.11 20.3160.12 0.4560.09 0.2260.08 0.2760.07 0.2460.06 0.3660.11 0.3360.10
0.2260.14 20.1560.15 0.4060.11 0.1560.09 0.2060.08 0.2160.07 0.2360.14 0.2460.12
a b
For abbreviations and units see Tables 1 and 5. Correlations of feed intake curve parameters b 0 , AEFI p1, AEFI p5 and Slope p3–p5 were low and not significantly different from zero.
periods did not show a significant correlation to meal size in any test week.
4. Discussion
4.1. Performance and behaviour of entire test period
and daily feed intake. One reason for these differences may be the differences in start weight. While performance test started at a weight of 35 kg in the study of Labroue et al. (1997), animals were about 10 kg heavier at the beginning of performance tests analysed by von Felde et al. (1996), Hall et al. (1999a) and in the present study.
4.2. Feed intake behaviour Highest heritability of all performance traits was found for backfat thickness (h 2 5 0.50). This is in agreement with results (h 2 50.38–0.65) from other studies (de Haer, 1992; von Felde et al., 1996; Labroue et al., 1997; Hall et al., 1999a) dealing with feed intake recorded by electronic feeders. Moderate heritabilities for daily gain on test were found by Hall et al. (1999a) and Labroue et al. (1997) for Large White breeds (h 2 50.25 and 0.31), while estimates of studies analysing Landrace (Labroue et al., 1997) or Landrace and Large White breeds together (von Felde et al., 1996) were higher (h 2 5 0.41, 0.43). Estimates of heritability for feed intake of entire test reported by von Felde et al. (1996), de Haer (1992) and Hall et al. (1999a) were substantially lower (h 2 50.16–0.22), compared to those of Labroue et al. (1997) and the present study. The genetic associations of daily gain with feed intake and backfat thickness in the present study were similar to estimates of von Felde et al. (1996) and Hall et al. (1999a). In the study of Labroue et al. (1997), the genetic correlations between daily gain and backfat thickness were lower, but higher between daily gain
High heritabilities for feed intake behavioural traits such as feed intake per visit (FIV), time per day (TD), visits per day (VD), feed intake rate (FR), and visits per day (VD) were reported by von Felde et al. (1996) (h 2 50.43–0.51) as well as by Labroue et al. (1997) (h 2 50.46–0.42) with little differences in estimates of equivalent traits and are in agreement with the results of the present study. Lowest estimates for traits, describing feed intake behaviour, were reported by Hall et al. (1999a) (h 2 50.04– 0.34). They explained these differences as an effect of the type of feeder used, that, in their study as well as in the study of de Haer (1992), allowed competition during feed intake, compared to animals fed at ACEMO feeders, which were protected from penmates during meals. In general, estimates for number of visits per day seemed to be less affected by feeder type, breed or start weight than the other behavioural traits, although definition of visits differed between the studies. Labroue et al. (1997) summarised successive visits with less than 2 min time difference to single meals, while in the present analysis consecutive
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visits differing less than 40 s were combined to one visit. In contrast, Hall et al. (1999a) defined nonfeeding visits as feed intakes with less than 5 g. High genetic correlations were estimated between time per day and feed intake rate in the current study and by Labroue et al. (1997) and Hall et al. (1999a) (r a 5 20.76 to 20.86), while von Felde et al. (1996) estimated a correlation of a lower magnitude between these traits (r a 5 2 0.62). Low associations of time per day were found in the present study as well as by von Felde et al. (1996) to visits per day (r a 5 0.25 and 0.38), feed intake per visit (r a 5 2 0.14 and 20.22), time per visit (r a 5 0.25 and 0.17), while Labroue et al. (1997) and Hall et al. (1999a) found moderate correlations between time per day and visits per day (r a 50.45–0.58), but non-significant associations between feed intake per visit and visits per day. Correlations between feed intake rate and time per visit were almost zero (r a 5 0.01) (von Felde et al., 1996), higher in the current study and that of Labroue et al. (1997) (r a 5 2 0.19 to 20.40) and highest (r a 5 2 0.63) in the study of Hall et al. (1999a). Very different results were obtained in the literature for the correlations between feed intake rate and feed intake per visit or visits per day. Hall et al. (1999a) found no associations between these traits (r a 5 2 0.06 and 0.06), while von Felde et al. (1996) published moderate correlations (r a 5 0.57 and 20.42). Estimates in the present study of feed intake rate to feed intake per visit and visits per day were low and similar to correlations reported by Labroue et al. (1997).
4.3. Associations between growth performance and feed intake behaviour In general, low to moderate genetic correlations between feed intake behavioural traits and performance traits such as average daily gain, backfat thickness, daily feed intake of the entire test, and food conversion ratio were found in this and all other investigations dealing with feed intake information from electronic feeders. Genetic correlations given by von Felde et al. (1996) are similar in sign and magnitude to those found in the current study. Time per visit and visits per day in both studies were not associated with growth performance, while time per
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day showed highest associations of all behavioural traits with performance traits ADG (r a 5 0.31, 0.32), DFI (r a 5 0.44, 0.41), BF (r a 5 0.15, 0.18) and FC (r a 5 0.12, 0.18). Feed intake rate, as a trait constructed from daily feed intake and time per day in the feeder, in both studies showed low associations with average daily gain, daily feed intake and backfat thickness, while feed intake per visit was low associated with daily gain and feed intake (r a 50.15– 0.23). In contrast, highest correlations between feed intake behaviour and performance traits were found in the study of Labroue et al. (1997) for feed intake per visit and feed intake rate with daily gain (r a 5 0.29–0.49), daily feed intake (r a 50.37–0.63), and backfat thickness (r a 50.11–0.31) with differences in magnitude between breeds. Hall et al. (1999a) found a significant association between feed intake rate and backfat thickness (r a 50.45), while correlations of feed intake per visit were moderate with daily gain and backfat thickness (r a 50.49 and 0.35) and low to daily feed intake (r a 50.22). Number of visits to the feeder was correlated with daily gain, backfat thickness and food conversion (r a 5 20.29, 20.15 and 0.31) in the study of Hall et al. (1999a). A high number of visits seemed to decrease feed intake (r a 5 20.31 and 20.35), while associations with other performance traits were low (Labroue et al., 1997). In both studies time per visit showed associations with performance traits similar in magnitude to visits per day but opposite in sign. Labroue et al. (1997) estimated low correlations of time per day with daily gain, feed intake and food conversion ratio (r a 50.02–0.19), while Hall et al. (1999a) found moderate correlations between time per day and daily gain or feed intake (r a 50.46 and 0.31), similar to those of the present study.
4.4. Feed intake pattern during growth Results on feed intake and feed intake behaviour during growth of group-penned pigs are scarce. Labroue et al. (1994) analysed the eating behaviour of Large White and Landrace animals fed at ACEMA 48 feeding stations. They found between 40 and 90 kg live weight a decrease in number of meals (7.2–5.3) and eating time (63.7–49.6 min / day), an increase in feed intake rate (28.6–58.8), feed intake
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per meal (278–621 g), and daily feed intake (1757– 2810 g), while time per meal was almost constant (11 min). Means reported by von Felde et al. (1996) as well as by Hall et al. (1999a) showed that daily feed intake per period increased with time on test with changing increments between test weeks. Hall et al. (1999a,b) observed the highest increase of feed intake in the beginning, which is in agreement with the present results. von Felde et al. (1996) found a lower number of visits (5.4–4.7) and a 10 min shorter occupation time in the feeder (47–52 min / day), compared to the results of Hall et al. (1999a) for frequency of visits (9.59–11.0), time per day (64.8–58.3 min / day), and own results (8.0–6.2 visits / day and 63.9–56.4 min / day). These differences may be caused by definition of visits and feeder type, but also by a repeated adaptation to the feeder, when animals were fed only every second week with ACEMO feeders (Schulze et al., 2001). Maximum duration in the feeder was recorded in test week 3, as found in the present study as well as by von Felde et al. (1996). In contrast, Hall et al. (1999a) found the longest duration time in the first period, when excluding the first test week from the analysis. This indicates that a pre-test feeding period by electronic feeders of 10 days, as in the present study, may not be enough to avoid influences on feed intake in the first days on test. Estimates of genetic parameters of feed intake behaviour for different test weeks are not available in the literature. The effect of adaptation to the feeder in first test week of recording mentioned above can be observed in genetic and residual standard deviations for time per day (TDw) in Table 3. Residual standard deviation in first test week is higher than in the following test weeks, while genetic standard deviation was almost constant. This resulted in an distinctively lower heritability for time per day in first test week (h 2 5 0.22) than in following test weeks (h 2 50.32– 0.34). The higher environmental influence can also be noticed in residual standard deviation of feed intake of test week 1 that was higher than in the following period. All other traits of feed intake behaviour showed little changes in heritabilities in all test weeks. In general, test week informations were less heritable than feed intake behaviour of the entire test.
Highest associations of feed intake per test week with behavioural traits were found for time per day in corresponding test weeks (r a 50.47–0.57, Table 6) and with feed intake of the fifth and later test weeks. All feed intake behaviour traits of the earlier test weeks 1 and 3 were not associated with performance traits except for low associations of time per day in test week 3 with daily gain and daily feed intake (r a 50.28 and 0.30). In fifth and later test weeks associations with backfat thickness and food conversion ratio were estimated for time per day, while number of visits (VDw) in each test week had no effects on any of the performance traits.
4.5. Associations between feed intake pattern and curve parameters Heritabilities of curve parameters, based on linearquadratic regression, as well as for average estimated feed intake and its slope derived from a second order polynomial were discussed in a previous study (Schulze et al., 2002). Residual standard deviation (R.S.D.) of feed intake curve was used as a parameter to quantify deviations of observed daily feed intake from the predicted feed intake curve for each animal. For this trait, a heritability of 0.22 was estimated, which is half in magnitude of the estimate of Eissen (2000) for R.S.D. (h 2 5 0.46), who fitted a linear regression on daily feed intake information of Duroc boars between 28 and 110 kg live weight. Associations of R.S.D. with performance traits in that study are equal in sign but higher in magnitude to live daily gain, backfat thickness and daily feed intake (r a 50.75, 0.58 and 0.70, respectively) compared to the present study. Differences in estimates may be caused by the function used, breed, start weight as well as by the performance testing scheme (age dependent vs. weight dependent). The intercept of feed intake curve using linearquadratic regression was associated only with time per day at the feeder (r a 5 0.23), while the linear term (b 1 ) showed a moderate correlation to daily feed intake (r a 5 0.52) and, on a low level, to related traits such as feed intake rate and feed intake per visit. The average estimated feed intake per period, based on a linear-quadratic regression, in general led to a higher relationship to feed intake behaviour (Table 5) compared to the observed feed intake per
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test week in Table 4. Moderate associations were found between time per day in the feeder in first and third week with the intercept (r a 50.50 and 0.36) and between R.S.D. and number of visits in fifth and later test weeks (r a 5 20.31 to 20.38). It should be noticed that genetic associations of time per day and visits per day with AEFI in periods are similar to those with daily feed intake in test weeks. This enables the use of behavioural traits combined with average estimated feed intake. The slope of the feed intake curve of the last two periods was lowly associated only with frequency of visits in test weeks 7 and 9. Slope in periods was less affected by duration of corresponding period than by following periods. This was observed also between feed intake per test week and slope (Schulze et al., 2000), and may be explained by the correlations between feed intake and time per day in test weeks in Table 6.
5. Conclusions The benefit of feed intake behaviour for improving feed intake, especially at an early stage of growth is limited, although there were associations of time per day with daily feed intake in earliest periods. Time per day in the feeder showed the highest association with performance traits. This means that a longer occupation in the feeder was genetically associated with higher feed intake and daily gain but also with undesirable higher backfat thickness and food conversion ratio. In contrast, visits per day to the feeder was almost genetically independent of feed consumption and time in the feeder and did not affect growth performances. The association between feed intake behaviour and performance traits may be influenced by the protection of animals during feeding in the ACEMO feeder, as suggested by Hall et al. (1999a). However, heritabilities of behavioural traits are substantially higher based on records of ACEMO feeders (Labroue et al., 1997; von Felde et al., 1996; present results) than on those of IVOG (de Haer, 1992) and FIRE feeders (Hall et al., 1999a). Also, heritabilities of daily feed intake over entire test period and during specific periods were higher based on records of ACEMO feeder than on those of the FIRE system. This may indicate the higher
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accuracy of recording feed intake with ACEMO feeders and may also estimate more accurately the feed intake capacity of pigs. Feed intake behaviour was also lowly associated with feed intake curve parameters, but more closely associated with estimates of feed intake based on these curve parameters. Of great interest is the association of feed intake behaviour traits and residual standard deviation of feed intake after fitting a linear-quadratic regression. With longer time on test, increased associations between feed intake behavioural traits, in particular feed intake per visit, and residual standard deviation were obtained. Feed intake per visit showed a moderate positive correlation with residual standard deviation, indicating that few large meals result in high day-to-day variation in feed intake. A high residual standard deviation was desirable associated with daily gain and food conversion ratio but undesirable with backfat thickness. Eissen (2000) also reported that a large residual standard deviation from a linear regression curve being genetically correlated with fast, however, fat growing pigs, but the magnitude of their correlations were much higher than in the present study. Based on the recommendation of Eissen (2000) of using residual standard deviation to improve selection response, feed intake per visit would be increased and the number of visits would be reduced. Generally, feed intake behaviour traits of the second half of the test period are more related to performance traits than those of the first half, so behavioural information for this test period is of greater interest.
Acknowledgements Financial support for the research project was provided by Deutsche Forschungsgemeinschaft (DFG). We thank I. Misztal for providing the MTDFS program.
References de Haer, L.C.M., 1992. Relevance of eating pattern for selection of growing pigs. PhD thesis, Wageningen, The Netherlands. Eissen, J., 2000. Breeding for feed intake capacity in pigs. PhD thesis, Wageningen, The Netherlands.
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Hall, A.D., Hill, W.G., Bampton, P.R., Webb, A.J., 1999a. Genetic and phenotypic parameter estimates for feeding pattern and performance traits in pigs. Anim. Sci. 68, 43–48. Hall, A.D., Hill, W.G., Bampton, P.R., Webb, A.J., 1999b. Predicted responses to selection from indices incorporating feeding pattern traits of pigs using electronic feeders. Anim. Sci. 68, 407–412. Knap, P.W., 1995. Use of automatic systems for feed consumption control in national programmes for genetic improvement in ´ Nacional de Porcinocultura pigs. XVI Symposium Asociacion ´ Cientıfica (ANAPORC), Barcelona, pp. 1–13. ´ ¨ M.C., 1994. Labroue, F., Gueblez, R., Sellier, P., Meunier-Salaun, Feeding behaviour of group-housed Large White and Landrace pigs in French central test stations. Livest. Prod. Sci. 40, 303–312. ´ Labroue, F., Gueblez, R., Sellier, P., 1997. Genetic parameters of feeding behaviour and performance traits in group-housed Large White and French Landrace growing pigs. Genet. Sel. Evol. 29, 451–468. Misztal, I., 1993. MTDFS, users notes, University of Illinois, USA. Robertson, A., 1959. The sampling variance of the genetic correlation coefficient. Biometrics 15, 469–485.
¨ Schulze, V., Rohe, R., Lorenzo Bermejo, J., Looft, H., Kalm, E., 2000. Genetic analysis of parameters of feed intake curves of performance tested boars. 51. Annual Meeting of the European Association for Animal Production, August 21–24, The Hague, The Netherlands, Session G5.4. ¨ Schulze, V., Rohe, R., Looft, H., Kalm, E., 2001. Effects of continuous and periodic feeding by electronic feeders on accuracy of measuring feed intake information and their genetic association with growth performances. J. Anim. Breed. Genet. 118, 403–416. ¨ Schulze, V., Rohe, R., Lorenzo Bermejo, J., Looft, H., Kalm, E., 2002. Genetic associations between observed feed intake measurements during growth, feed intake curve parameters and growing-finishing performances of central tested boars. Livest. Prod. Sci. 73, 199–211. von Felde, A., 1996. Genetische Analyse der Futteraufnahme¨ Informationen von Jungebern aus Gruppenprufung mit au¨ tomatischen Futterungsanlagen. PhD Thesis, University Kiel, Germany. ¨ von Felde, A., Rohe, R., Looft, H., Kalm, E., 1996. Genetic association between feed intake and feed intake behaviour at different stages of growth of group-housed boars. Livest. Prod. Sci. 47, 11–22.
The influence of feeding behaviour on feed intake curve parameters and performance traits of station-tested boars a a a b a, V. Schulze , R. Roehe , J. Lorenzo Bermejo , H. Looft , E. Kalm * a
¨ Tierzucht und Tierhaltung, Christian-Albrechts-Universitat ¨ , Hermann-Rodewald-Straße 6, D-24118 Kiel, Germany Institut f ur b PIC Deutschland, Ratsteich 31, D-24837 Schleswig, Germany Received 12 June 2001; received in revised form 9 January 2003; accepted 3 February 2003
Abstract The use of feed intake behaviour traits, obtained from electronic feeding stations, and feed intake curve parameters to genetically improve performance traits was analysed. Daily feed intake and feed intake behaviour of 5601 group-penned boars of two dam lines were recorded by electronic feeders in weeks 1, 3, 5, 7 and 9 during 10 weeks (100–170 d) on performance test. Additionally, performance test traits and parameters of an individually fitted linear-quadratic regression of feed intake on time on test, were available. A multiple trait animal model considering observed feed intake and feed intake behaviour at each test week as a different trait was used. Estimated heritabilities for feed intake and feed intake behaviour of the entire test period were 0.39, 0.46, 0.34, 0.44, 0.44 and 0.41 for daily feed intake, time per day, visits per day, time per visit, feed intake per visit, and feed intake rate, respectively. Heritabilities for behavioural traits in each test week were below estimates of entire test and showed lower variation, except for daily feed intake and time per day. Residual standard deviation of feed intake using linear-quadratic regression on time on test showed a moderate heritability of 0.22. Genetic correlations of feed intake behaviour traits indicate that number of visits per day was independent from growth performance, while time per day was genetically associated with average daily gain and daily feed intake (0.31 and 0.41). In contrast, visits per day and related traits such as time per visit and feed intake per visit were genetically correlated with residual standard deviation of linear-quadratic regression (20.28, 0.31 and 0.39). Feed intake per visit in the seventh test week resulted in the highest genetic correlation (0.45) with residual standard deviation of the feed intake curve. This residual standard deviation and related traits will be of increasing interest for future breeding programs in order to obtain high performances in a wide range of environments. 2003 Elsevier B.V. All rights reserved. Keywords: Feed intake behaviour; Feed intake curve parameters; Genetic correlations; Growth performance; Heritabilities; Pig-feeding and nutrition
1. Introduction *Corresponding author. Tel.: 149-431-880-2584; fax: 149431-880-2588. E-mail address: [email protected] (E. Kalm).
Electronic feeding stations deliver information about the individual feed intake pattern of grouppenned pigs. These informations were not available
0301-6226 / 03 / $ – see front matter 2003 Elsevier B.V. All rights reserved. doi:10.1016 / S0301-6226(03)00034-4
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before, when either individually penned boars or group-penned progeny were performance tested, to obtain information about feed intake and food conversion. For improving efficient lean growth, Labroue et al. (1997) suggested the replacement of food conversion ratio in a selection index by behavioural traits related to feed intake (feed intake per visit or feed intake rate). Hall et al. (1999b) recommended the incorporation of number of visits per day additionally to feed intake, daily gain and backfat thickness in a selection index, in order to predominantly improve feed efficiency. They also concluded that loss of accuracy of measurements due to reduced length of the recording period of feed intake by electronic feeders can be regained by behavioural traits. Knap (1995) mentioned differences between animals in within-animal variation for feed intake and explained this phenomenon as the individual ability to react to short term environmental influences. As conditions of pig housing are still very heterogeneous, development of animal robustness towards these environmental influences can be of increasing interest for future pig breeding programs. In this study, genetic relationships between feed intake behaviour, performance test traits, and feed intake of test weeks were analysed. Furthermore, genetic associations between behavioural traits and feed intake curve parameters using linear-quadratic regression were investigated for the entire test period and particular test periods. As a predictor for the within-animal variation, the residual standard deviation of the individual feed intake curve during performance test was estimated and analysed with respect to behavioural traits.
2. Material and methods
weeks. On test station, the animals were kept on straw in groups of 12 of the same line. They were given ad libitum a dry pelleted food containing 12.6 MJ metabolizable energy, 10 g lysine and 180 g crude protein per kg. Performance test started after 10 days of adaptation at an average age of 100 days and finished after 10 weeks at an average age of 170 days. For each animal, average daily gain on test (ADG), backfat thickness (BF), daily feed intake (DFI) and food conversion (FC) were available. Backfat thickness was calculated as the mean of two measurements taken 4 and 8 cm lateral off the mid-line between 13th and 14th rib and one measurement taken 4 cm lateral off the mid line on the loin using a one-dimensional ultrasonic Renco device. Feed intake and time information were recorded by ACEMA 48 electronic feeding stations during test weeks 1, 3, 5, 7 and 9, while animals had free access to conventional feed dispensers during remaining test weeks. Successive individual feed intake records differing less than 40 s were condensed to one visit according to results of von Felde (1996). To account for adaptation to the feeder, the first two test days of each test week with feed intake informations were removed from the dataset according to previous results (Schulze et al., 2001). Animals were not considered in the analysis when at least one test week with feed intake was missing or was below the feed intake expected for maintenance within test weeks. Daily feed intake was derived from the total amount of recorded feed intake divided by the number of corresponding days at the feeder. Food conversion was calculated as the ratio of daily feed intake to average daily gain on test. Means (6S.D.) of average daily gain on test, backfat thickness and food conversion ratio were 1015 (6124) g / day, 10.9 (62.1) mm and 2548 (6303) g food per kg gain, respectively.
2.1. Data 2.2. Feed intake and feed intake behaviour The data consist of 5601 young boars from two dam lines (3125 of line three originated from Large White, 2476 of line four originated from Landrace), recorded at the central test station of PIC Germany between June 1992 and April 1998. Piglets were born on five farms, weaned after 3 weeks and reared together in a nursery nearby the test station for 10
Based on feed intake and duration of individual visits, behavioural traits such as feed intake rate (FR), visits per day (VD), time per visit (TV), time per day (TD) and feed intake per visit (FIV) were calculated for the entire test period as well as for single test weeks. Over the entire test period, the
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Table 1 Phenotypic means and standard deviations (6S.D.) for feed intake and feed intake behaviour per test week and of the entire test period Trait a
Unit
Week 1
Week 3
Week 5
Week 7
Week 9
Entire period b
DFIw TDw VDw FRw TVw FIVw
(g / day) (min) (no.) (g / min) (min) (g)
17246452 58.2616.2 8.064.5 30.666.4 9.864.4 2946137
22706475 63.9615.4 7.564.5 36.967.6 11.364.9 4076180
25606512 62.1614.8 6.863.9 42.968.9 11.864.9 4916205
28066551 59.1614.5 6.463.7 49.6610.3 11.764.7 5626220
29836617 56.4614.5 6.263.6 55.4612.1 11.664.7 6196240
24826340 60.1611.1 7.063.4 43.267.8 11.363.8 4766163
a
DFIw5feed intake per day and test week, TDw5Time per day and test week, VDw5Visits per day and test week, FRw5Feed intake rate per test week, TVw5Time per visit and test week, FIVw5Feed intake per visit and test week. b Abbreviations for traits of the entire test period: DFI, TD, VD, FR, TV, FIV.
animals stayed 1 h per day at the feeder and consumed 2482 g of food during seven visits per day (Table 1). This resulted in an average meal size of 476 g, an average time per visit of 11 min and a feed intake rate of 43 g per min. In general, daily feed intake and all feed intake behaviour traits changed during the performance test. Daily feed intake of test weeks increased with decreasing increments during test. Feed intake rate per visit increased almost linearly with time on test while number of visits per day decreased from eight visits in first test week to six visits in test week 9. Time per day at the feeder showed a maximum of 64 min in test week 3 and afterwards decreased. Time per visit was nearly constant at around 11.5 min during the test except for test week 1. Feed intake per visit more than doubled from first to last test week (294–619 g). The highest coefficient of variation was obtained for number of visits per day (56–60%) and related traits such as time per visit and feed intake per visit (39–47%). The coefficient of variation for daily time at the feeder ranged from 24 to 28% while feed intake rate variation was almost constant in all test weeks (21–22%).
2.3. Feed intake curve information A linear-quadratic regression was fitted for individual daily feed intake on time on test to obtain feed intake curve parameters. Based on this function, the average estimated feed intake (AEFI) was derived for five periods of 12 days by integration of this function. The average change in daily feed intake (slope) was calculated for corresponding 12 day periods from the individually fitted linear-quad-
ratic regression. A detailed description of the estimated feed intake curve parameters are given by Schulze et al. (2002). Briefly described, the average estimated feed intake for periods increased from first to last period from 1882 to 2994 g.
2.4. Statistical analysis For estimation of variance components, a multiple-trait animal model was fitted using multivariate REML program MTDFS (Misztal, 1993). The model can be described as following: y i 5 Xb i 1 Zu i 1 e i where y i is the vector of observations for the trait i, b i is the vector of fixed effects of birth farm (5 levels), quarter of year of beginning performance test (21 different seasons), line (two lines) and a linear regression on average weight at start of test (45.9 kg), u i is the vector of random additive genetic effects of animals, and e i is the vector of random residual effects. X and Z are incidence matrices for fixed and random effects, respectively. The variance covariance matrix of the genetic effects u of all traits is A^G, where A is the numerator relationship matrix, G is the matrix of genetic variances and covariances between traits and ^ represents the Kronecker product. The variance covariance matrix of residuals e is I^R, where I is the identity matrix and R is the matrix of residual variances and covariances between traits. Animals were progeny of 581 sires and 2913 dams (297 and 1558 of line 3, 284 and 1355 of line 4). Pedigree information of 9839 ancestors were available for genetic analysis
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using for each animal information up to the fifth generation. Standard errors of genetic correlations were approximated by the method of Robertson (1959).
3. Results
3.1. Heritabilities of feed intake behaviour traits Genetic parameters of feed intake behaviour traits of the entire test period are presented in Table 2.
Traits describing feed intake behaviour can be classified into basic traits characterising feed consumption, duration and frequency of visits (DFI, TD, VD) and traits derived from the former ones (FR, TV, FIV). Time depending traits such as time per day, time per visit, and feed intake rate showed highest heritabilities, while estimates of visits per day, daily feed intake and feed intake per visit were slightly lower. Residual standard deviation of feed intake curve, using linear-quadratic regression, showed a moderate heritability of h 2 5 0.22. Table 3 summarises the estimates of feed intake and feeding
Table 2 2 Genetic ( sˆ a ) and residual ( sˆ e ) standard deviations and heritabilities (h ) for performance traits and feed intake behaviour traits of entire test Trait
Unit
sˆ a
sˆ e
h 2 6S.E.
Average daily gain on test (ADG) Backfat thickness (BF) Food conversion (FC) Average daily feed intake on test (DFI) Time per day (TD) Visits per day (VD) Feed intake rate (FR) Time per visit (TV) Feed intake per visit (FIV) Residual standard deviation (R.S.D.)a
(g / day) (mm) (g / kg) (g / day) (min) (no.) (g / min) (min) (g) (g)
68.7 1.24 145.3 192.4 7.40 1.93 4.89 2.50 101.2 74.2
91.5 1.24 229.8 239.7 7.97 2.71 5.47 2.85 121.1 140.2
0.3660.04 0.5060.03 0.2860.04 0.3960.03 0.4660.03 0.3460.04 0.4460.03 0.4460.03 0.4160.03 0.2260.05
a
R.S.D. based on linear-quadratic regression of feed intake on time.
Table 3 2 Genetic ( sˆ a ) and residual ( sˆ e ) standard deviations and heritabilities (h ) for daily feed intake and feed intake behaviour traits per test week Traits a
Unit
Estimate
Week 1
Week 3
Week 5
Week 7
Week 9
DFIw
(g / day)
TDw
(min)
VDw
(no.)
FRw
(g / min)
TVw
(min)
FIVw
(g)
sˆ a sˆ e h2 sˆ a sˆ e h2 sˆ a sˆ e h2 sˆ a sˆ e h2 sˆ a sˆ e h2 sˆ a sˆ e h2
150.3 400.9 0.1260.05 7.59 14.11 0.2260.04 2.31 3.86 0.2660.04 3.63 4.86 0.3660.04 2.36 3.62 0.3060.04 69.1 112.0 0.2860.04
210.2 389.1 0.2360.04 8.57 12.64 0.3260.04 2.29 3.81 0.2760.04 4.27 5.77 0.3560.04 2.73 3.94 0.3260.04 98.1 142.3 0.3260.04
257.3 401.1 0.2960.04 8.22 12.04 0.3260.04 1.98 3.35 0.2660.04 5.27 6.66 0.3960.03 2.77 4.00 0.3360.04 115.5 161.9 0.3460.04
331.2 416.2 0.3960.03 8.09 11.75 0.3260.04 1.90 3.07 0.2860.04 6.03 7.83 0.3760.04 2.54 3.90 0.3060.04 123.2 176.8 0.3360.04
340.4 500.0 0.3260.04 8.26 11.48 0.3460.04 1.75 3.11 0.2460.04 6.58 9.50 0.3260.04 2.59 3.91 0.3060.04 124.4 202.6 0.2760.04
a
For abbreviations and units see Table 1.
V. Schulze et al. / Livestock Production Science 82 (2003) 105–116
behaviour traits per test week. In general, all heritabilities were lower compared to those found for the entire test period (Table 2). Heritabilities of test week feed intake increased with time on test and reached a maximum in test week 7. Heritabilities of behavioural traits showed less variation among stages of growth than daily feed intake. Only for time per day recorded at test week 1, heritability was substantially lower compared to estimates of the following weeks.
3.2. Genetic correlations between performance traits and feed intake behaviour Based on the genetic correlations among behavioural traits, time per day and feed intake rate as well as visits per day and its derivatives time per visit and feed intake per visit were closely related (Table 4). Genetic correlations between feed intake behaviour traits and performance traits were always lower than 0.41. Of all behavioural traits highest associations with performance were found for time per day at the feeder, and these were moderate to DFI and ADG (r a 5 0.41 and 0.31), but still low to BF and FC. Also feed intake rate was lowly associated with performance traits, while visits per day and related traits like time per visit and feed intake per visit showed almost no association with performance traits. Moderate associations were found between visits per day, time per visit, feed intake per visit and
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residual standard deviation of the linear-quadratic feed intake curve (r a 5 2 0.28, 0.31, and 0.39). Higher residual standard deviations (R.S.D.) were desirably associated with ADG and food conversion (r a 5 0.37, 20.29) but undesirably with backfat thickness (r a 5 0.29). Especially, estimates for test week 1 were associated with larger standard errors. Genetic correlations between feed intake behaviour and parameters of the linear-quadratic regression and its derived average estimated feed intake and slope for periods are presented in Table 5. Associations of linear-quadratic regression parameters with feed intake behavioural traits were low and very often non-significantly different from zero. Time per day had the highest genetic association with the intercept of linear-quadratic regression (r a 5 0.23), but no association with linear and quadratic terms. Highest associations with these regressors were found for visits per day and feed intake per visit. Estimates of genetic correlations between time per day or feed intake rate and daily feed intake per period were higher when using the estimated feed intake based on a second order polynomial instead of observed weekly feed intake in Table 4. Traits related to visits (visits per day and time per visit) were not correlated with average estimated feed intake. Genetic associations between feed intake behaviour and slope of feed intake curves per period were low and decreasing with time on test. Correlations between slope of the feed intake curve in
Table 4 Genetic correlations between feed intake behaviour traits of the entire test period, performance traits and daily feed intake per test week Trait a
R.S.D.
TD
VD
FR
TV
FIV
TD VD FR TV FIV BF ADG FC DFI DFIw 1 DFIw 3 DFIw 5 DFIw 7 DFIw 9
20.0560.08 20.2860.10 0.1060.09 0.3160.08 0.3960.08 0.2960.07 0.3760.09 20.2960.11 0.1260.09 20.1660.19 0.1760.13 0.1260.12 0.0560.10 0.0760.11
–
– – 20.2260.06 20.8160.02 20.9260.01 0.0560.05 0.0160.08 0.0460.09 0.0260.07 0.1460.15 20.0160.10 20.0660.09 0.0160.07 0.0660.08
– – – 20.2960.04 0.2360.05 0.1660.04 0.1460.06 0.1060.07 0.2060.05 0.0160.11 0.1360.08 0.1960.07 0.2160.05 0.1260.06
– – – –
– – – – –
a
0.2560.06 20.8160.02 0.2560.04 20.1460.05 0.1860.04 0.3160.05 0.1860.07 0.4160.04 0.2560.10 0.2960.07 0.3160.06 0.3160.05 0.3360.05
For abbreviations and units see Tables 1 and 2.
0.8660.01 20.0260.04 0.0460.06 20.0160.07 0.0360.05 20.0960.12 0.0060.08 0.0960.07 0.0360.06 20.0160.07
0.0960.05 0.1560.06 0.0560.08 0.1760.06 20.0660.13 0.1160.09 0.2260.07 0.1760.06 0.0860.07
V. Schulze et al. / Livestock Production Science 82 (2003) 105–116
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Table 5 Genetic correlations between feed intake behaviour traits of the entire test period, feed intake curve parameters of linear-quadratic regression function and average estimated feed intake (AEFI) and its slope Trait a
DFI b
TD b
VD b
FRb
TV b
FIV b
b0 b1 b2 R.S.D. AEFI p1 p2 p3 p4 p5 Slope p1 p2 p3 p4 p5
0.0560.14 0.5260.08 20.2760.10 0.1260.09 0.5660.07 0.8260.02 0.9260.01 0.9860.00 0.8760.01 0.5960.07 0.7260.05 0.6060.04 0.2460.07 0.0660.09
0.2360.11 0.1160.09 20.0360.09 20.0560.08 0.3260.08 0.3360.05 0.3460.05 0.3660.04 0.3360.04 0.1360.09 0.1860.08 0.1960.06 0.1160.07 0.0660.08
0.1860.15 20.2060.12 0.2060.12 20.2860.10 0.1060.12 20.0360.08 20.0560.07 20.0360.06 0.0360.07 20.1860.12 20.1460.11 20.0160.08 0.0960.09 0.1360.10
20.0860.12 0.2260.09 20.1760.09 0.1060.09 0.0660.10 0.1960.06 0.2360.05 0.2260.05 0.1760.05 0.2360.09 0.2360.08 0.1460.06 0.0060.07 20.0660.08
20.1460.12 0.1660.10 20.1560.10 0.3160.08 20.0760.10 0.0460.06 0.0760.06 0.0560.05 0.0160.05 0.1560.10 0.1460.09 0.0460.06 20.0660.08 20.0960.09
20.1560.13 0.2960.10 20.2460.10 0.3960.08 0.0060.10 0.1860.07 0.2260.06 0.2060.05 0.1260.05 0.2960.09 0.2860.08 0.1260.07 20.0560.08 20.1260.09
a Intercept (b 0 ), linear term (b 1 ), quadratic term (b 2 ), residual standard deviation (R.S.D.) based on linear-quadratic regression, AEFI, Slope5average estimated feed intake and rate of increase of feed intake in five periods of 12 days (p1–p5) based on linear-quadratic regression. b For abbreviations and units see Table 2.
periods one to three were moderate to daily feed intake (r a 50.59–0.60), low to time per day, feed intake rate and feed intake per visit for same periods (r a 50.12–0.29), while visits per day and time per visit had no significant association with average increase of feed intake in any of the periods. Visits per day, time per visit and feed intake per visit showed highest correlation to residual standard deviation of feed intake curve using linear-quadratic regression.
3.3. Genetic associations between feed intake behaviour of each test week and performance traits In addition to DFI, all behaviour traits were analysed for each single test week. Genetic correlations between time per day (TDw) and feed intake (DFIw) in Table 6 showed in each corresponding week moderate estimates (r a 50.47–0.57), and these correlations were higher than associations of the same traits over the entire test period (r a 5 0.41) in
Table 6 Genetic correlations between performance traits and time in the feeder per day (TDw) in different test weeks Trait a
TDw 1
TDw 3
TDw 5
TDw 7
TDw 9
DFIw 1 DFIw 3 DFIw 5 DFIw 7 DFIw 9 BF ADG DFI FC TD VD
0.4960.15 0.2460.13 0.2060.11 0.0860.09 0.0860.11 0.0960.07 0.1660.10 0.2360.09 0.1360.12 0.9060.01 0.2960.09
0.2160.15 0.5160.08 0.2660.09 0.1260.07 0.1460.08 0.1160.06 0.2860.07 0.3060.07 0.0760.10 0.9060.01 0.2460.08
0.2260.14 0.2760.10 0.4760.07 0.2860.07 0.2860.08 0.2060.05 0.3160.07 0.4260.06 0.1960.09 0.9460.01 0.2060.08
0.2260.14 0.1860.10 0.2760.08 0.5660.05 0.4860.06 0.2560.05 0.3660.07 0.5160.05 0.2560.09 0.9260.01 0.2360.08
0.0160.14 0.1260.10 0.2060.08 0.3760.06 0.5760.05 0.1660.05 0.2860.07 0.4160.06 0.2260.09 0.8860.01 0.1960.07
a
For abbreviations see Tables 1 and 2.
V. Schulze et al. / Livestock Production Science 82 (2003) 105–116
Table 4. The magnitude of genetic correlations of time per day to performance traits increased with time on test and reached a maximum in test week 7. While daily gain or daily feed intake were associated with time per day in all test weeks, backfat thickness and food conversion ratio were non-significantly correlated with duration time in test weeks 1 and 3. Because of mainly low associations between the other feed intake behaviour and performance traits, meaningful results are further on only presented in the text. Number of visits for each test week were not significantly associated with performance traits and feed intake per test week (DFIw) except of daily feed intake in test week 9 (r a 5 0.21). Only feed intake in test weeks 5 and 7 showed low but significant association with feed intake per visit in test weeks 5 (r a 5 0.32, 0.19) and seven (r a 5 0.26, 0.20). No associations with performance traits were found for feed intake per visit in test weeks 1 and 3, while correlations for following test weeks 5–9 were low to daily feed intake, average daily gain and backfat thickness (r a 50.14–0.21). Time per visit and feed intake rate for each test week showed no important correlations with performance traits and thus were not presented.
3.4. Feed intake curve parameters and behavioural traits in test weeks Genetic correlations between time per day in each test week and feed intake curve parameters of linearquadratic regression, average estimated feed intake
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and its slope are shown in Table 7. Association of the intercept (b 0 ) of feed intake curve was highest with time per day in the first test week and decreased with time on test. Correlations of AEFI in periods to time per day in test weeks were similar to those between feed intake per test week and time per day per test week in Table 6, slightly lower on the diagonal for corresponding periods but higher to adjacent test weeks. In general, all estimates with AEFI were accompanied with lower standard errors compared to estimates with observed feed intake (DFI). Low to moderate correlations of time per day in test weeks 5–9 were found with slope of feed intake curve in all periods. Correlations of number of visits per day (results for this trait only present in the text) with residual standard deviation were low and increased slightly with time on test from r a 5 2 0.1760.12 to 20.3860.12. Also, associations between frequency of visits and slope of feed intake in test weeks were low and increased with time on test to r a 5 0.29. Table 8 shows correlations between feed intake per visit for different test weeks and feed intake curve information. Correlation of the residual standard deviation of feed intake curve with feed intake per visit in the first test week was low and increased to a maximum in test week 7 (r a 5 0.45). Average estimated feed intake showed low correlations with meal size of test weeks 5–9. Average daily change of feed intake in periods one and two was associated with feed intake per visit of test weeks 3–9, while the slope of the feed intake curve in the following
Table 7 Genetic correlations between feed intake curve parameters b and time per day (TDw) in different test weeks Trait a
TDw 1
TDw 3
TDw 5
TDw 7
TDw 9
b0 AEFI p1 AEFI p2 AEFI p3 AEFI p4 AEFI p5 Slope p2 Slope p3 Slope p4 Slope p5
0.5060.16 0.4960.12 0.3160.10 0.2160.09 0.1660.08 0.1160.08 20.1160.14 20.1060.10 20.0660.12 20.0360.14
0.3660.15 0.4560.10 0.4160.07 0.3460.07 0.2660.06 0.1560.07 0.0860.12 20.0560.08 20.1460.10 20.1660.11
0.2160.16 0.3360.11 0.4260.07 0.4360.06 0.4260.05 0.3460.05 0.2860.11 0.1860.08 0.0360.10 20.0460.11
0.1860.16 0.2460.12 0.3260.07 0.4060.06 0.5060.05 0.5560.05 0.3160.10 0.4360.07 0.3460.09 0.2660.10
0.0560.16 0.0960.12 0.1760.08 0.2860.07 0.4360.05 0.5460.05 0.2860.10 0.4960.06 0.4560.07 0.3860.09
a b
For abbreviations and units see Tables 1 and 5. Correlations of feed intake curve parameters b 1 , b 2 R.S.D. and Slope of period 1 (p1) were low and not significantly different from zero.
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Table 8 Genetic correlations between feed intake curve parameters b and food intake per visit in test weeks Trait a
FIVw 1
FIVw 3
FIVw 5
FIVw 7
FIVw 9
b1 b2 R.S.D. AEFI p2 AEFI p3 AEFI p4 Slope p1 Slope p2
0.1260.14 20.1460.14 0.1560.12 0.0460.09 0.0360.08 20.0160.07 0.0860.14 0.0360.12
0.2760.12 20.2260.12 0.2960.10 0.1060.08 0.1660.07 0.1560.06 0.2660.12 0.2560.11
0.4360.10 20.4060.10 0.4460.09 0.2860.07 0.3260.06 0.2660.06 0.4160.10 0.3660.09
0.3660.11 20.3160.12 0.4560.09 0.2260.08 0.2760.07 0.2460.06 0.3660.11 0.3360.10
0.2260.14 20.1560.15 0.4060.11 0.1560.09 0.2060.08 0.2160.07 0.2360.14 0.2460.12
a b
For abbreviations and units see Tables 1 and 5. Correlations of feed intake curve parameters b 0 , AEFI p1, AEFI p5 and Slope p3–p5 were low and not significantly different from zero.
periods did not show a significant correlation to meal size in any test week.
4. Discussion
4.1. Performance and behaviour of entire test period
and daily feed intake. One reason for these differences may be the differences in start weight. While performance test started at a weight of 35 kg in the study of Labroue et al. (1997), animals were about 10 kg heavier at the beginning of performance tests analysed by von Felde et al. (1996), Hall et al. (1999a) and in the present study.
4.2. Feed intake behaviour Highest heritability of all performance traits was found for backfat thickness (h 2 5 0.50). This is in agreement with results (h 2 50.38–0.65) from other studies (de Haer, 1992; von Felde et al., 1996; Labroue et al., 1997; Hall et al., 1999a) dealing with feed intake recorded by electronic feeders. Moderate heritabilities for daily gain on test were found by Hall et al. (1999a) and Labroue et al. (1997) for Large White breeds (h 2 50.25 and 0.31), while estimates of studies analysing Landrace (Labroue et al., 1997) or Landrace and Large White breeds together (von Felde et al., 1996) were higher (h 2 5 0.41, 0.43). Estimates of heritability for feed intake of entire test reported by von Felde et al. (1996), de Haer (1992) and Hall et al. (1999a) were substantially lower (h 2 50.16–0.22), compared to those of Labroue et al. (1997) and the present study. The genetic associations of daily gain with feed intake and backfat thickness in the present study were similar to estimates of von Felde et al. (1996) and Hall et al. (1999a). In the study of Labroue et al. (1997), the genetic correlations between daily gain and backfat thickness were lower, but higher between daily gain
High heritabilities for feed intake behavioural traits such as feed intake per visit (FIV), time per day (TD), visits per day (VD), feed intake rate (FR), and visits per day (VD) were reported by von Felde et al. (1996) (h 2 50.43–0.51) as well as by Labroue et al. (1997) (h 2 50.46–0.42) with little differences in estimates of equivalent traits and are in agreement with the results of the present study. Lowest estimates for traits, describing feed intake behaviour, were reported by Hall et al. (1999a) (h 2 50.04– 0.34). They explained these differences as an effect of the type of feeder used, that, in their study as well as in the study of de Haer (1992), allowed competition during feed intake, compared to animals fed at ACEMO feeders, which were protected from penmates during meals. In general, estimates for number of visits per day seemed to be less affected by feeder type, breed or start weight than the other behavioural traits, although definition of visits differed between the studies. Labroue et al. (1997) summarised successive visits with less than 2 min time difference to single meals, while in the present analysis consecutive
V. Schulze et al. / Livestock Production Science 82 (2003) 105–116
visits differing less than 40 s were combined to one visit. In contrast, Hall et al. (1999a) defined nonfeeding visits as feed intakes with less than 5 g. High genetic correlations were estimated between time per day and feed intake rate in the current study and by Labroue et al. (1997) and Hall et al. (1999a) (r a 5 20.76 to 20.86), while von Felde et al. (1996) estimated a correlation of a lower magnitude between these traits (r a 5 2 0.62). Low associations of time per day were found in the present study as well as by von Felde et al. (1996) to visits per day (r a 5 0.25 and 0.38), feed intake per visit (r a 5 2 0.14 and 20.22), time per visit (r a 5 0.25 and 0.17), while Labroue et al. (1997) and Hall et al. (1999a) found moderate correlations between time per day and visits per day (r a 50.45–0.58), but non-significant associations between feed intake per visit and visits per day. Correlations between feed intake rate and time per visit were almost zero (r a 5 0.01) (von Felde et al., 1996), higher in the current study and that of Labroue et al. (1997) (r a 5 2 0.19 to 20.40) and highest (r a 5 2 0.63) in the study of Hall et al. (1999a). Very different results were obtained in the literature for the correlations between feed intake rate and feed intake per visit or visits per day. Hall et al. (1999a) found no associations between these traits (r a 5 2 0.06 and 0.06), while von Felde et al. (1996) published moderate correlations (r a 5 0.57 and 20.42). Estimates in the present study of feed intake rate to feed intake per visit and visits per day were low and similar to correlations reported by Labroue et al. (1997).
4.3. Associations between growth performance and feed intake behaviour In general, low to moderate genetic correlations between feed intake behavioural traits and performance traits such as average daily gain, backfat thickness, daily feed intake of the entire test, and food conversion ratio were found in this and all other investigations dealing with feed intake information from electronic feeders. Genetic correlations given by von Felde et al. (1996) are similar in sign and magnitude to those found in the current study. Time per visit and visits per day in both studies were not associated with growth performance, while time per
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day showed highest associations of all behavioural traits with performance traits ADG (r a 5 0.31, 0.32), DFI (r a 5 0.44, 0.41), BF (r a 5 0.15, 0.18) and FC (r a 5 0.12, 0.18). Feed intake rate, as a trait constructed from daily feed intake and time per day in the feeder, in both studies showed low associations with average daily gain, daily feed intake and backfat thickness, while feed intake per visit was low associated with daily gain and feed intake (r a 50.15– 0.23). In contrast, highest correlations between feed intake behaviour and performance traits were found in the study of Labroue et al. (1997) for feed intake per visit and feed intake rate with daily gain (r a 5 0.29–0.49), daily feed intake (r a 50.37–0.63), and backfat thickness (r a 50.11–0.31) with differences in magnitude between breeds. Hall et al. (1999a) found a significant association between feed intake rate and backfat thickness (r a 50.45), while correlations of feed intake per visit were moderate with daily gain and backfat thickness (r a 50.49 and 0.35) and low to daily feed intake (r a 50.22). Number of visits to the feeder was correlated with daily gain, backfat thickness and food conversion (r a 5 20.29, 20.15 and 0.31) in the study of Hall et al. (1999a). A high number of visits seemed to decrease feed intake (r a 5 20.31 and 20.35), while associations with other performance traits were low (Labroue et al., 1997). In both studies time per visit showed associations with performance traits similar in magnitude to visits per day but opposite in sign. Labroue et al. (1997) estimated low correlations of time per day with daily gain, feed intake and food conversion ratio (r a 50.02–0.19), while Hall et al. (1999a) found moderate correlations between time per day and daily gain or feed intake (r a 50.46 and 0.31), similar to those of the present study.
4.4. Feed intake pattern during growth Results on feed intake and feed intake behaviour during growth of group-penned pigs are scarce. Labroue et al. (1994) analysed the eating behaviour of Large White and Landrace animals fed at ACEMA 48 feeding stations. They found between 40 and 90 kg live weight a decrease in number of meals (7.2–5.3) and eating time (63.7–49.6 min / day), an increase in feed intake rate (28.6–58.8), feed intake
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per meal (278–621 g), and daily feed intake (1757– 2810 g), while time per meal was almost constant (11 min). Means reported by von Felde et al. (1996) as well as by Hall et al. (1999a) showed that daily feed intake per period increased with time on test with changing increments between test weeks. Hall et al. (1999a,b) observed the highest increase of feed intake in the beginning, which is in agreement with the present results. von Felde et al. (1996) found a lower number of visits (5.4–4.7) and a 10 min shorter occupation time in the feeder (47–52 min / day), compared to the results of Hall et al. (1999a) for frequency of visits (9.59–11.0), time per day (64.8–58.3 min / day), and own results (8.0–6.2 visits / day and 63.9–56.4 min / day). These differences may be caused by definition of visits and feeder type, but also by a repeated adaptation to the feeder, when animals were fed only every second week with ACEMO feeders (Schulze et al., 2001). Maximum duration in the feeder was recorded in test week 3, as found in the present study as well as by von Felde et al. (1996). In contrast, Hall et al. (1999a) found the longest duration time in the first period, when excluding the first test week from the analysis. This indicates that a pre-test feeding period by electronic feeders of 10 days, as in the present study, may not be enough to avoid influences on feed intake in the first days on test. Estimates of genetic parameters of feed intake behaviour for different test weeks are not available in the literature. The effect of adaptation to the feeder in first test week of recording mentioned above can be observed in genetic and residual standard deviations for time per day (TDw) in Table 3. Residual standard deviation in first test week is higher than in the following test weeks, while genetic standard deviation was almost constant. This resulted in an distinctively lower heritability for time per day in first test week (h 2 5 0.22) than in following test weeks (h 2 50.32– 0.34). The higher environmental influence can also be noticed in residual standard deviation of feed intake of test week 1 that was higher than in the following period. All other traits of feed intake behaviour showed little changes in heritabilities in all test weeks. In general, test week informations were less heritable than feed intake behaviour of the entire test.
Highest associations of feed intake per test week with behavioural traits were found for time per day in corresponding test weeks (r a 50.47–0.57, Table 6) and with feed intake of the fifth and later test weeks. All feed intake behaviour traits of the earlier test weeks 1 and 3 were not associated with performance traits except for low associations of time per day in test week 3 with daily gain and daily feed intake (r a 50.28 and 0.30). In fifth and later test weeks associations with backfat thickness and food conversion ratio were estimated for time per day, while number of visits (VDw) in each test week had no effects on any of the performance traits.
4.5. Associations between feed intake pattern and curve parameters Heritabilities of curve parameters, based on linearquadratic regression, as well as for average estimated feed intake and its slope derived from a second order polynomial were discussed in a previous study (Schulze et al., 2002). Residual standard deviation (R.S.D.) of feed intake curve was used as a parameter to quantify deviations of observed daily feed intake from the predicted feed intake curve for each animal. For this trait, a heritability of 0.22 was estimated, which is half in magnitude of the estimate of Eissen (2000) for R.S.D. (h 2 5 0.46), who fitted a linear regression on daily feed intake information of Duroc boars between 28 and 110 kg live weight. Associations of R.S.D. with performance traits in that study are equal in sign but higher in magnitude to live daily gain, backfat thickness and daily feed intake (r a 50.75, 0.58 and 0.70, respectively) compared to the present study. Differences in estimates may be caused by the function used, breed, start weight as well as by the performance testing scheme (age dependent vs. weight dependent). The intercept of feed intake curve using linearquadratic regression was associated only with time per day at the feeder (r a 5 0.23), while the linear term (b 1 ) showed a moderate correlation to daily feed intake (r a 5 0.52) and, on a low level, to related traits such as feed intake rate and feed intake per visit. The average estimated feed intake per period, based on a linear-quadratic regression, in general led to a higher relationship to feed intake behaviour (Table 5) compared to the observed feed intake per
V. Schulze et al. / Livestock Production Science 82 (2003) 105–116
test week in Table 4. Moderate associations were found between time per day in the feeder in first and third week with the intercept (r a 50.50 and 0.36) and between R.S.D. and number of visits in fifth and later test weeks (r a 5 20.31 to 20.38). It should be noticed that genetic associations of time per day and visits per day with AEFI in periods are similar to those with daily feed intake in test weeks. This enables the use of behavioural traits combined with average estimated feed intake. The slope of the feed intake curve of the last two periods was lowly associated only with frequency of visits in test weeks 7 and 9. Slope in periods was less affected by duration of corresponding period than by following periods. This was observed also between feed intake per test week and slope (Schulze et al., 2000), and may be explained by the correlations between feed intake and time per day in test weeks in Table 6.
5. Conclusions The benefit of feed intake behaviour for improving feed intake, especially at an early stage of growth is limited, although there were associations of time per day with daily feed intake in earliest periods. Time per day in the feeder showed the highest association with performance traits. This means that a longer occupation in the feeder was genetically associated with higher feed intake and daily gain but also with undesirable higher backfat thickness and food conversion ratio. In contrast, visits per day to the feeder was almost genetically independent of feed consumption and time in the feeder and did not affect growth performances. The association between feed intake behaviour and performance traits may be influenced by the protection of animals during feeding in the ACEMO feeder, as suggested by Hall et al. (1999a). However, heritabilities of behavioural traits are substantially higher based on records of ACEMO feeders (Labroue et al., 1997; von Felde et al., 1996; present results) than on those of IVOG (de Haer, 1992) and FIRE feeders (Hall et al., 1999a). Also, heritabilities of daily feed intake over entire test period and during specific periods were higher based on records of ACEMO feeder than on those of the FIRE system. This may indicate the higher
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accuracy of recording feed intake with ACEMO feeders and may also estimate more accurately the feed intake capacity of pigs. Feed intake behaviour was also lowly associated with feed intake curve parameters, but more closely associated with estimates of feed intake based on these curve parameters. Of great interest is the association of feed intake behaviour traits and residual standard deviation of feed intake after fitting a linear-quadratic regression. With longer time on test, increased associations between feed intake behavioural traits, in particular feed intake per visit, and residual standard deviation were obtained. Feed intake per visit showed a moderate positive correlation with residual standard deviation, indicating that few large meals result in high day-to-day variation in feed intake. A high residual standard deviation was desirable associated with daily gain and food conversion ratio but undesirable with backfat thickness. Eissen (2000) also reported that a large residual standard deviation from a linear regression curve being genetically correlated with fast, however, fat growing pigs, but the magnitude of their correlations were much higher than in the present study. Based on the recommendation of Eissen (2000) of using residual standard deviation to improve selection response, feed intake per visit would be increased and the number of visits would be reduced. Generally, feed intake behaviour traits of the second half of the test period are more related to performance traits than those of the first half, so behavioural information for this test period is of greater interest.
Acknowledgements Financial support for the research project was provided by Deutsche Forschungsgemeinschaft (DFG). We thank I. Misztal for providing the MTDFS program.
References de Haer, L.C.M., 1992. Relevance of eating pattern for selection of growing pigs. PhD thesis, Wageningen, The Netherlands. Eissen, J., 2000. Breeding for feed intake capacity in pigs. PhD thesis, Wageningen, The Netherlands.
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Hall, A.D., Hill, W.G., Bampton, P.R., Webb, A.J., 1999a. Genetic and phenotypic parameter estimates for feeding pattern and performance traits in pigs. Anim. Sci. 68, 43–48. Hall, A.D., Hill, W.G., Bampton, P.R., Webb, A.J., 1999b. Predicted responses to selection from indices incorporating feeding pattern traits of pigs using electronic feeders. Anim. Sci. 68, 407–412. Knap, P.W., 1995. Use of automatic systems for feed consumption control in national programmes for genetic improvement in ´ Nacional de Porcinocultura pigs. XVI Symposium Asociacion ´ Cientıfica (ANAPORC), Barcelona, pp. 1–13. ´ ¨ M.C., 1994. Labroue, F., Gueblez, R., Sellier, P., Meunier-Salaun, Feeding behaviour of group-housed Large White and Landrace pigs in French central test stations. Livest. Prod. Sci. 40, 303–312. ´ Labroue, F., Gueblez, R., Sellier, P., 1997. Genetic parameters of feeding behaviour and performance traits in group-housed Large White and French Landrace growing pigs. Genet. Sel. Evol. 29, 451–468. Misztal, I., 1993. MTDFS, users notes, University of Illinois, USA. Robertson, A., 1959. The sampling variance of the genetic correlation coefficient. Biometrics 15, 469–485.
¨ Schulze, V., Rohe, R., Lorenzo Bermejo, J., Looft, H., Kalm, E., 2000. Genetic analysis of parameters of feed intake curves of performance tested boars. 51. Annual Meeting of the European Association for Animal Production, August 21–24, The Hague, The Netherlands, Session G5.4. ¨ Schulze, V., Rohe, R., Looft, H., Kalm, E., 2001. Effects of continuous and periodic feeding by electronic feeders on accuracy of measuring feed intake information and their genetic association with growth performances. J. Anim. Breed. Genet. 118, 403–416. ¨ Schulze, V., Rohe, R., Lorenzo Bermejo, J., Looft, H., Kalm, E., 2002. Genetic associations between observed feed intake measurements during growth, feed intake curve parameters and growing-finishing performances of central tested boars. Livest. Prod. Sci. 73, 199–211. von Felde, A., 1996. Genetische Analyse der Futteraufnahme¨ Informationen von Jungebern aus Gruppenprufung mit au¨ tomatischen Futterungsanlagen. PhD Thesis, University Kiel, Germany. ¨ von Felde, A., Rohe, R., Looft, H., Kalm, E., 1996. Genetic association between feed intake and feed intake behaviour at different stages of growth of group-housed boars. Livest. Prod. Sci. 47, 11–22.