scholarly journals Estimation of Genetic Parameters for Feeding Pattern Traits and Its Relationship to Feed Efficiency and Production Traits in Duroc Pigs

Agriculture ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 850
Author(s):  
Kier G. Santiago ◽  
Sung-Hoon Kim ◽  
Bryan Irvine Lopez ◽  
Dong-Hui Lee ◽  
Young-Gyu Cho ◽  
...  
Keyword(s):  
Genetic Correlation ◽  
Feed Intake ◽  
Feed Efficiency ◽  
Genetic Parameters ◽  
Feeding Rate ◽  
Occupation Time ◽  
Feeding Pattern ◽  
Phenotypic Correlation ◽  
Production Traits ◽  
Average Occupation

This study was conducted to estimate the genetic parameters of different feeding pattern traits, including average daily feed intake (ADFI), average occupation time per day (AOTD), average occupation time per visit (AOTV), average daily feeding rate (ADFR), average feeding rate per feeding visit (AFRV), average feed intake per feeding visit (AFIV), and average number of visits per day (ANVD), and their genetic relationship to production traits, such as on-test average daily gain (ADG), backfat thickness (BFT), loin muscle area (LMA), lean percentage (LP), and feed efficiency traits, such as feed conversion ratio (FCR) and five measures of residual feed intake (RFI1 to RFI5), in Duroc pigs (DD). The non-heritable common spatial pen effect was also estimated in all studied traits. The feeding pattern traits used in this study were derived from filtered feeding visits of 602 DD pigs. Using three animal models and the REML method, the genetic parameters revealed low to moderate heritability for ADFI (0.19 to 0.32) and AFIV (0.18 to 0.33), moderate heritability for ANVD (0.28 to 0.35) and AOTV (0.21 to 0.31), and high heritability for AOTD (0.73), ADFR (0.62 to 0.64), and AFRV (0.59 to 0.63). The addition of a common spatial pen effect in models 2 and 3 had a substantial impact, ranging from 8% to 23%, on the total variability of most feeding pattern traits, with the exception of AOTD, which only had a percentage variance of 0.30% due to the pen effect. The genetic and phenotypic correlation revealed that ADFI had consistent moderate to high genetic and phenotypic correlation with production and feed efficiency (FE) traits. However, selection against ADFI would negatively affect on-test ADG. Interestingly, the AOTD had no genetic correlation with ADG (0.04), low to moderate positive genetic correlation with FCR (0.27) and all RFI measures (0.24 to 0.33), and moderate negative correlation with LP (−0.39), indicating that selection for DD pigs with lower AOTD would not influence on-test ADG but may increase LP and improve feed efficiency by lowering FCR and all RFI measures. However, the corresponding phenotypic correlation of AOTD with production and feed efficiency traits was mostly weak, which can be attributed to the low residual or environmental correlation between these correlated traits. At the genetic level, the feeding pattern traits showed potential in improving feed efficiency and production traits. However, further studies are needed to evaluate their impact at phenotypic level.

scholarly journals Genetic Parameters for Different Measures of Feed Efficiency and Their Relationship to Production Traits in Three Purebred Pigs

Life ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 830
Author(s):  
Kier Gumangan Santiago ◽  
Bryan Irvine Lopez ◽  
Sung-Hoon Kim ◽  
Dong-Hui Lee ◽  
Young-Gyu Cho ◽  
...  
Keyword(s):  
Genetic Correlation ◽  
Feed Intake ◽  
Feed Efficiency ◽  
Genetic Parameters ◽  
Daily Weight Gain ◽  
Phenotypic Variance ◽  
Production Traits ◽  
Feed Conversion ◽  
Muscle Area ◽  
Initial Testing

Residual feed intake (RFI) gained attention as a potential alternative to the feed conversion ratio (FCR). Thus, this study aimed to estimate genetic parameters for different feed efficiency (FE) traits (FCR, RFI1 to RFI5) and their genetic correlation to on-test daily weight gain (ADG), backfat (BFT), loin muscle area (LMA), lean percentage (LP), and total feed intake (FI) for 603 Male Duroc (DD), 295 Landrace (LL), and 341 Yorkshire (YY). The common spatial pen effect was also estimated in these traits. Five RFI measures were estimated by regressing daily feed intake on initial testing age (ITA), initial testing weight (IBW), and ADG for RFI1; other models were the same as RFI1 except for additional BFT for RFI2; LMA for RFI3; BFT and LMA for RFI4; BFT, LMA, and average metabolic body weight (AMBW) instead of IBW for RFI5. Genetic parameters estimated using two animal models and the REML method showed moderate heritability for FCR in all breeds (0.22 and 0.28 for DD, 0.31 and 0.39 for LL, 0.17 and 0.22 for YY), low heritability for the majority of RFI measures in DD (0.15 to 0.23) and YY (0.14 to 0.20) and moderate heritability for all RFI measures in LL (0.31 to 0.34). Pen variance explained 7% to 22% for FE and 0% to 9% for production traits’ phenotypic variance. The genetic correlation revealed that selection against less complex RFI1 in DD and LL and RFI2 in YY would bring the most advantageous reduction to FI (0.71 for DD, 0.49 for LL, 0.43 YY) without affecting ADG in all breeds (0.06 for DD, −0.11 for LL, 0.05 for YY), decrease in BFT, and increase in LP in DD (0.51 in BFT, −0.77 in LP) and LL (0.45 in BFT, −0.83 in LP). Therefore, inclusion of these breed-specific RFI measures in the future selection criteria would help improve feed efficiency in the swine industry.

Genetic parameter estimates for feeding pattern and production traits in pigs

1997 ◽  
Vol 1997 ◽  
pp. 31-31
Author(s):  
A.D. Hall ◽  
W.G. Hill ◽  
P.R. Bampton ◽  
A.J. Webb
Keyword(s):  
Feed Intake ◽  
Genetic Parameters ◽  
Genetic Parameter ◽  
Feeding Pattern ◽  
Parameter Estimates ◽  
Group Housing ◽  
Production Traits ◽  
Production Environment ◽  
Feeding Patterns ◽  
Potential Benefits

Until recently, to enable accurate recording of feed intake, pigs were kept in individual pens. The advent of electronic feeders has allowed accurate records of feed intake and feeding patterns in group housing which is more similar to that found in the production environment. The objectives of this study were to estimate genetic parameters for these feeding pattern traits and their correlations with production traits to show potential benefits in selection.

scholarly journals PSVIII-38 Late-Breaking Abstract: Estimating genetic parameters of feed efficiency traits in American mink

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 347-347
Author(s):  
Pourya Davoudi ◽  
Duy Ngoc Do ◽  
Guoyu Hu ◽  
Siavash Salek Ardestani ◽  
Younes Miar
Keyword(s):  
Body Weight ◽  
Genetic Correlation ◽  
Feed Intake ◽  
Feed Efficiency ◽  
Fixed Effects ◽  
Genetic Parameters ◽  
American Mink ◽  
Genetic Correlations ◽  
Final Body Weight ◽  
Selection For

Abstract Feed cost is the major input cost in the mink industry and thus improvement of feed efficiency through selection for high feed efficient mink is necessary for the mink farmers. The objective of this study was to estimate the heritability, phenotypic and genetic correlations for different feed efficiency measures, including final body weight (FBW), daily feed intake (DFI), average daily gain (ADG), feed conversion ratio (FCR) and residual feed intake (RFI). For this purpose, 1,088 American mink from the Canadian Center for Fur Animal Research at Dalhousie Faculty of Agriculture were recorded for daily feed intake and body weight from August 1 to November 14 in 2018 and 2019. The univariate models were used to test the significance of sex, birth year and color as fixed effects, and dam as a random effect. Genetic parameters were estimated via bivariate models using ASReml-R version 4. Estimates of heritabilities (±SE) were 0.41±0.10, 0.37±0.11, 0.33±0.14, 0.24±0.09 and 0.22±0.09 for FBW, DFI, ADG, FCR and RFI, respectively. The genetic correlation (±SE) was moderate to high between FCR and RFI (0.68±0.15) and between FCR and ADG (-0.86±0.06). In addition, RFI had low non-significant (P > 0.05) genetic correlations with ADG (0.04 ± 0.26) and BW (0.16 ± 0.24) but significant (P < 0.05) high genetic correlation with DFI (0.74 ± 0.11) indicating that selection for lower RFI will reduce feed intake without adverse effects on the animal size and growth rate. The results suggested that RFI can be implemented in genetic/genomic selection programs to reduce feed intake in the mink production system.

scholarly journals Realized Sampling Variances of Estimates of Genetic Parameters and the Difference Between Genetic and Phenotypic Correlations

Genetics ◽  
1996 ◽  
Vol 143 (3) ◽  
pp. 1409-1416 ◽  
Author(s):  
Kenneth R Koots ◽  
John P Gibson
Keyword(s):  
Genetic Correlation ◽  
Genetic Parameters ◽  
Genetic Parameter ◽  
Genetic Correlations ◽  
Phenotypic Correlation ◽  
Parameter Estimates ◽  
Sampling Variance ◽  
Phenotypic Correlations ◽  
Genetic And Phenotypic Correlations ◽  
Heritability Estimates

Abstract A data set of 1572 heritability estimates and 1015 pairs of genetic and phenotypic correlation estimates, constructed from a survey of published beef cattle genetic parameter estimates, provided a rare opportunity to study realized sampling variances of genetic parameter estimates. The distribution of both heritability estimates and genetic correlation estimates, when plotted against estimated accuracy, was consistent with random error variance being some three times the sampling variance predicted from standard formulae. This result was consistent with the observation that the variance of estimates of heritabilities and genetic correlations between populations were about four times the predicted sampling variance, suggesting few real differences in genetic parameters between populations. Except where there was a strong biological or statistical expectation of a difference, there was little evidence for differences between genetic and phenotypic correlations for most trait combinations or for differences in genetic correlations between populations. These results suggest that, even for controlled populations, estimating genetic parameters specific to a given population is less useful than commonly believed. A serendipitous discovery was that, in the standard formula for theoretical standard error of a genetic correlation estimate, the heritabilities refer to the estimated values and not, as seems generally assumed, the true population values.

scholarly journals 146 Survey of residual feed intake in Katahdin and Texel lambs in a feedlot environment

2020 ◽  
Vol 98 (Supplement_2) ◽  
pp. 75-76
Author(s):  
Camren l Maierle ◽  
Andrew R Weaver ◽  
Eugene Felton ◽  
Scott P Greiner ◽  
Scott A Bowdridge
Keyword(s):  
Feed Intake ◽  
Feed Efficiency ◽  
Large Scale ◽  
Residual Feed Intake ◽  
Production Traits ◽  
Meaningful Improvement ◽  
Average Intake ◽  
Test Population ◽  
Feeding Trials ◽  
Genetic Evaluations

Abstract Residual feed intake (RFI) is quickly becoming the preferred measurement of efficiency in many species due to its inherent independence of most other important production traits. Making meaningful improvement in feed efficiency of sheep will require a consistent methodology to accurately identify efficient individuals. Due to difficulty in measuring this trait efforts must be made to incorporate efficiency data in large-scale genetic evaluations. The aim of this study was to evaluate lambs in a feedlot with large-scale genetic evaluations for feed efficiency calculated by residual feed intake (RFI) utilizing a Growsafe™ system. RFI was calculated by subtracting expected intake from actual intake. Expected intake was determined by regressing metabolic body size of mid-test weight. Regression determined ADG on actual intake for individuals in the population. Texel (n = 58) and Katahdin (n = 118) lambs were placed in a feedlot and fed in separate feeding trials, a complete pellet ad libitum as the sole source of nutrition. In this environment Texel and Katahdin lambs had expected ADG values (0.27 kg/day, 0.32 kg/day respectively) and actual intake data (2154.17 g/day, 1909.33 g/day respectively. After a period of adaptation, Texel average intake was determined over a period of 27 consecutive days and used to calculate individual RFI within the test population. Observable ranges of RFI (-0.62 – +0.62) were seen in the Texel lambs. At the start of the Katahdin trial lambs were separated by sex and FEC treatment. After a period of adaptation, Katahdin average intake was determined over a period of 42 consecutive days and used to calculate individual RFI within the test population. Observable ranges of RFI (-0.53 – +0.50) were seen in the Katahdin lambs as well. In both feeding trials RFI appeared to be normally distributed. Use of this technology may be useful in identifying superior individuals for feed efficiency.

Genetic parameters and breed differences for feed efficiency, growth, and body composition traits of young beef bulls

2004 ◽  
Vol 84 (2) ◽  
pp. 177-185 ◽  
Author(s):  
F. S. Schenkel ◽  
S. P. Miller ◽  
J. W. Wilton
Keyword(s):  
Body Composition ◽  
Genetic Correlation ◽  
Feed Intake ◽  
Feed Efficiency ◽  
Fixed Effects ◽  
Residual Feed Intake ◽  
Backfat Thickness ◽  
Daily Weight Gain ◽  
Feed Conversion ◽  
Beef Bulls

Genetic associations between feed efficiency, growth, and live ultrasound measured body composition traits were studied in purebred beef bulls of six breeds in Ontario bull test stations from 1991 to 2000. Feed traits included average daily feed intake (FI), feed conversion ratio (FCR), and residual feed intake [feed intake adjusted for production alone (RFIp) or production and backfat thickness (RFIb)]. Growth traits were average daily weight gain (ADG), mid-test metabolic weight (MW), hip height (HH), and scrotal circumference (SC). Body composition traits included ultrasound backfat thickness (BF), longissimus muscle area (LMA), and predicted percentage of intramuscular fat (IFAT). Bulls were measured every 28 d for weight and individual feed intake, and at the end of test for ultrasound body composition traits. Number of records per trait ranged from 2284 (FI) to 13 319 (ADG). Fixed effects of test group, breed and end of test age (within breed), and random effects of animal and herd of origin were modeled using REML bivariate analyses for all traits. Heritability estimates were moderate for all traits (0.30 to 0.55), except for IFAT (0.14). The genetic correlation between RFIp and RFIb was high (0.99) within breeds, but breeds ranked differently with respect to RFIp and RFIb. Genetic correlations of RFIb with ADG and backfat thickness were essentially zero, which indicate that selection on residual feed intake could be implemented to reduce feed intake and improve feed conversion without compromising growth or changing levels of subcutaneous fat. Key words: Central test, genetic correlation, heritability, residual feed intake

Genetic variation in net feed efficiency in Hereford cattle and its association with other production traits

1999 ◽  
Vol 1999 ◽  
pp. 47-47
Author(s):  
R.M. Herd ◽  
S.C. Bishop
Keyword(s):  
Growth Rate ◽  
Genetic Variation ◽  
Feed Intake ◽  
Feed Efficiency ◽  
Genetic Correlations ◽  
Feed Consumption ◽  
Production Traits ◽  
Performance Measurements ◽  
Hereford Cattle ◽  
Rate Selection

Net feed efficiency refers to variation in feed consumption between animals net of requirements for maintenance and production, and may be measured as residual feed intake (RFI). Because RFI is independent of liveweight (LW) and growth rate, selection for improved net feed efficiency is likely to reduce feed intake with little change in growth. The purpose of this study was to establish whether there exists genetic variation in RFI in young British Hereford bulls, and to determine the phenotypic and genetic correlations of RFI with key production traits.The data consisted of performance measurements on 540 bull progeny of 154 British Hereford sires, collected over ten 200-day postweaning performance tests conducted between 1979 and 1988. The traits analysed were food intake (FI), 200 to 400-day daily gain (ADG), 400-day weight (W400), predicted carcass lean content (LEAN), lean growth rate (LGR), food conversion ratio (FI/ADG) and lean FCR (LFCR; FI/(ADG x LEAN), described by Bishop (1992).

HERITABILITIES AND GENETIC CORRELATIONS FOR ULTRASONIC BACKFAT MEASUREMENTS, GROWTH AND CARCASS TRAITS IN SWINE

1982 ◽  
Vol 62 (3) ◽  
pp. 665-670 ◽  
Author(s):  
D. C. JEFFRIES ◽  
R. G. PETERSON
Keyword(s):  
Key Words ◽  
Genetic Correlation ◽  
Genetic Parameters ◽  
Average Daily Gain ◽  
Genetic Correlations ◽  
Phenotypic Correlation ◽  
Ultrasonic Measurements ◽  
Yorkshire Pigs ◽  
Daily Gain ◽  
Season Interaction

Genetic parameters were estimated for 2403 purebred Yorkshire pigs over a 2-yr period, representing 21 sires. The traits studied included average daily gain, age adjusted to 90 kg, ultrasonic measurements of backfat at the mid-back and loin positions, total and adjusted total ultrasonic backfat and corresponding carcass backfat measurements. Least squares analyses were used to estimate and adjust for the effects of sex, year-season and sex by year-season interaction. Heritabilities and genetic correlations were calculated for all traits using both half- and full-sib estimates. Adjusted age and adjusted total ultrasonic backfat measurements were found to have the highest heritabilities of the live traits in this study. Estimates of heritability for adjusted age and adjusted total ultrasonic backfat were 0.24 ± 0.10 and 0.26 ± 0.10 based on half-sib and 0.56 ± 0.07 and 0.41 ± 0.06 from full-sib analyses. The genetic correlation between these two traits was −0.07 ± 0.28 based on the half-sib method. The total phenotypic correlation was −0.01 ± 0.02. Key words: Swine, ultrasonic backfat, heritabilities, genetic correlations

scholarly journals Association of Feed Efficiency, Feeding Rate, and Behaviour with the Milk Performance of Dairy Cows

Dairy ◽  
2021 ◽  
Vol 2 (4) ◽  
pp. 684-694
Author(s):  
Lenka Krpálková ◽  
Niall O’Mahony ◽  
Anderson Carvalho ◽  
Sean Campbell ◽  
Gerard Corkery ◽  
...  
Keyword(s):  
Dairy Cows ◽  
Milk Production ◽  
Milk Yield ◽  
Feed Intake ◽  
Feed Efficiency ◽  
Feeding Behaviour ◽  
Feeding Rate ◽  
Feeding Time ◽  
Feed Conversion ◽  
Milk Performance

Identification of the associations of cow feed efficiency with feeding behaviour and milk production is important for supporting recommendations of strategies that optimise milk yield. The objective of this study was to identify associations between measures of feed efficiency, feed intake, feeding rate, rumination time, feeding time, and milk production using data collected from 26 dairy cows during a 3 month period in 2018. Cows averaged (mean ± standard deviation) 2.2 ± 1.7 lactations, 128 ± 40 days in milk, 27.5 ± 5.5 kg/day milk, 1.95 ± 0.69 kg feed/1 kg milk—the measure used to express feed conversion ratio (FCR), 575 ± 72 min/day rumination time, and 264 ± 67 min/day feeding time during the observation period. The coefficient of variation for rumination time (min/d) was 12.5%. A mixed linear model was selected for analyses. The most feed inefficient cows with the highest FCR (≥2.6 kg feed/1 kg milk) showed the lowest milk yield (24.8 kg/day), highest feed intake (78.8 kg), highest feeding rate (0.26 kg/min) and BCS (3.35 point). However, the relative milk yield (milk yield per 100 kg of body weight) was the highest (4.01 kg/day) in the most efficient group with the lowest FCR (≤1.4 kg feed/1 kg milk). Our study showed that the most efficient cows with the lowest FCR (≤1.4 kg feed/1 kg milk) had the highest rumination time (597 min/day; p < 0.05), feeding time (298 min/day; p < 0.05), rumination/activity ratio (4.39; p < 0.05) and rumination/feeding ratio (2.04; p < 0.05). Less active cows (activity time 164 min/day; p < 0.05) were the most efficient cows with the lowest FCR (≤1.4 kg feed/1 kg milk). The behavioural differences observed in this study provide new insight into the association of feed behaviour and feed efficiency with milk performance. Incorporating feeding behaviour into the dry matter intake model can improve its accuracy in the future and benefit breeding programmes.

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