scholarly journals How to improve breeding value prediction for feed conversion ratio in the case of incomplete longitudinal body weights1

2017 ◽  
Vol 95 (1) ◽  
pp. 39-48
Author(s):  
V. H. Huynh Tran ◽  
H. Gilbert ◽  
I. David
Keyword(s):  
Conversion Ratio ◽  
Feed Conversion Ratio ◽  
Breeding Value ◽  
Feed Conversion ◽  
Value Prediction

Daily methane emissions and emission intensity of grazing beef cattle genetically divergent for residual feed intake

2017 ◽  
Vol 57 (4) ◽  
pp. 627 ◽  
Author(s):  
J. I. Velazco ◽  
R. M. Herd ◽  
D. J. Cottle ◽  
R. S. Hegarty
Keyword(s):  
Feed Intake ◽  
Emission Intensity ◽  
Dry Matter ◽  
Average Daily Gain ◽  
Residual Feed Intake ◽  
Conversion Ratio ◽  
Feed Conversion Ratio ◽  
Breeding Value ◽  
Dry Matter Intake ◽  
Feed Conversion

As daily methane production (DMP; g CH4/day) is strongly correlated with dry matter intake (DMI), the breeding of cattle that require less feed to achieve a desired rate of average daily gain (ADG) by selection for a low residual feed intake (RFI) can be expected to reduce DMP and also emission intensity (EI; g CH4/kg ADG). An experiment was conducted to compare DMP and EI of Angus cattle genetically divergent for RFI and 400-day weight (400dWT). In a 6-week grazing study, 64 yearling-age cattle (30 steers, 34 heifers) were grazed on temperate pastures, with heifers and steers grazing separate paddocks. Liveweight (LW) was monitored weekly and DMP of individual cattle was measured by a GreenFeed emission monitoring unit in each paddock. Thirty-nine of the possible 64 animals had emission data recorded for 15 or more days, and only data for these animals were analysed. For these cattle, regression against their mid-parent estimated breeding value (EBV) for post-weaning RFI (RFI-EBV) showed that a lower RFI-EBV was associated with higher LW at the start of experiment. Predicted dry matter intake (pDMI), predicted DMP (pDMP) and measured DMP (mDMP) were all negatively correlated with RFI-EBV (P < 0.05), whereas ADG, EI, predicted CH4 yield (pMY; g CH4/kg DMI) were not correlated with RFI-EBV (P > 0.1). Daily CH4 production was positively correlated with animal LW and ADG (P < 0.05). The associations between ADG and its dependent traits EI and pMY and predicted feed conversion ratio (kg pDMI/kg ADG) were strongly negative (r = –0.82, –0.57 and –0.85, P < 0.001) implying that faster daily growth by cattle was accompanied by lower EI, MY and feed conversion ratio. These results show that cattle genetically divergent for RFI do not necessarily differ in ADG, EI or pMY on pasture and that, if heavier, cattle with lower RFI-EBV can actually have higher DMP while grazing moderate quality pastures.

scholarly journals Investigation of muscle transcriptomes using gradient boosting machine learning identifies molecular predictors of feed efficiency in growing pigs

2019 ◽  
Author(s):  
Farouk Messad ◽  
Isabelle Louveau ◽  
Basile Koffi ◽  
Hélène Gilbert ◽  
Florence Gondret
Keyword(s):  
Feed Efficiency ◽  
Conversion Ratio ◽  
Growing Pigs ◽  
Feed Conversion Ratio ◽  
Breeding Value ◽  
Gradient Boosting ◽  
Mrna Levels ◽  
Feed Conversion ◽  
Expression Levels ◽  
Muscle Genes

Abstract Background Improving feed efficiency (FE) is a major challenge in pig production. This complex trait is characterized by a high variability. Therefore, the identification of predictors of FE may be a relevant strategy to reduce phenotyping efforts in breeding and selection programs. The aim of this study was to investigate the suitability of expressed muscle genes in prediction of FE traits in growing pigs. The approach considered different transcriptomics experiments to cover a large range of FE values and identify reliable predictors. Results Microarrays data were obtained from longissimus muscles of two lines divergently selected for residual feed intake (RFI). Pigs (n = 71) from three experiments belonged to generations 6 to 8 of selection, were fed either a diet with a standard composition or a diet rich in fiber and lipids, received feed ad libitum or at restricted level, and weighed between 80 and 115 kg at slaughter. For each pig, breeding value for RFI was estimated (RFI-BV), and feed conversion ratio (FCR) and energy-based feed conversion ratio (FCRe) were calculated during the test periods. Gradient boosting algorithms were used on the merged muscle transcriptomes to identify very important predictors of FE traits. About 20,405 annotated molecular probes were commonly expressed in longissimus muscle across experiments. Six to 267 expressed muscle genes covering a variety of biological processes were found as important predictors for RFI-BV (R2=0.63-0.65), FCR (R2=0.61-0.70) and FCRe (R2=0.49-0.52). The error of prediction was less than 8% for FCR. Altogether, 56 predictors were common to RFI-BV and FCR. Expression levels of 24 target genes were further measured by qPCR. Linear regression confirmed the good accuracy of combining mRNA levels of these genes to fit FE traits (RFI-BV: R2=0.73, FRC: R2=0.76; FCRe: R2=0.75). Stepwise regression procedure highlighted 10 genes (FKBP5, MUM1, AKAP12, FYN, TMED3, PHKB, TGF, SOCS6, ILR4, and FRAS1) in a linear combination predicting FCR and FCRe. In addition, FKBP5 and expression levels of five other genes (IGF2, SERINC3, CSRNP3, EZR and RPL16) significantly contributed to RFI-BV. Conclusion It was possible to identify few genes expressed in muscle that might be reliable predictors of feed efficiency.

scholarly journals Investigation of muscle transcriptomes using gradient boosting machine learning identifies molecular predictors of feed efficiency in growing pigs

2019 ◽  
Author(s):  
Farouk Messad ◽  
Isabelle Louveau ◽  
Basile Koffi ◽  
Hélène Gilbert ◽  
Florence Gondret
Keyword(s):  
Feed Efficiency ◽  
Conversion Ratio ◽  
Growing Pigs ◽  
Feed Conversion Ratio ◽  
Breeding Value ◽  
Gradient Boosting ◽  
Mrna Levels ◽  
Feed Conversion ◽  
Expression Levels ◽  
Muscle Genes

Abstract Background Improving feed efficiency (FE) is a major challenge in pig production. This complex trait is characterized by a high variability. Therefore, the identification of predictors of FE may be a relevant strategy to reduce phenotyping efforts in breeding and selection programs. The aim of this study was to investigate the suitability of expressed muscle genes in prediction of FE traits in growing pigs. The approach considered different transcriptomics experiments to cover a large range of FE values and identify reliable predictors. Results Microarrays data were obtained from longissimus muscles of two lines divergently selected for residual feed intake (RFI). Pigs (n = 71) from three experiments belonged to generations 6 to 8 of selection, were fed either a diet with a standard composition or a diet rich in fiber and lipids, received feed ad libitum or at restricted level, and weighed between 80 and 115 kg at slaughter. For each pig, breeding value for RFI was estimated (RFI-BV), and feed conversion ratio (FCR) and energy-based feed conversion ratio (FCRe) were calculated during the test periods. Gradient boosting algorithms were used on the merged muscle transcriptomes to identify very important predictors of FE traits. About 20,405 annotated molecular probes were commonly expressed in longissimus muscle across experiments. Six to 267 expressed muscle genes covering a variety of biological processes were found as important predictors for RFI-BV (R2=0.63-0.65), FCR (R2=0.61-0.70) and FCRe (R2=0.49-0.52). The error of prediction was less than 8% for FCR. Altogether, 56 predictors were common to RFI-BV and FCR. Expression levels of 24 target genes were further measured by qPCR. Linear regression confirmed the good accuracy of combining mRNA levels of these genes to fit FE traits (RFI-BV: R2=0.73, FRC: R2=0.76; FCRe: R2=0.75). Stepwise regression procedure highlighted 10 genes (FKBP5, MUM1, AKAP12, FYN, TMED3, PHKB, TGF, SOCS6, ILR4, and FRAS1) in a linear combination predicting FCR and FCRe. In addition, FKBP5 and expression levels of five other genes (IGF2, SERINC3, CSRNP3, EZR and RPL16) significantly contributed to RFI-BV. Conclusion It was possible to identify few genes expressed in muscle that might be reliable predictors of feed efficiency.

Response to selection and genotype–environment interaction in mink (Neovison vison) selected on ad libitum and restricted feeding

2011 ◽  
Vol 91 (2) ◽  
pp. 231-237 ◽  
Author(s):  
Vivi Hunnicke Nielsen ◽  
Steen Henrik Møller ◽  
Bente Krogh Hansen ◽  
Peer Berg
Keyword(s):  
Conversion Ratio ◽  
Feed Conversion Ratio ◽  
Breeding Value ◽  
Environment Interaction ◽  
Restricted Feeding ◽  
Response To Selection ◽  
Feed Conversion ◽  
Genotype Environment Interaction ◽  
Ad Libitum ◽  
Ad Libitum Feeding

Nielsen, V. H., Møller, S. H., Hansen, B. K. and Berg, P. 2011. Response to selection and genotype-environment interaction in mink (Neovison vison) selected on ad libitum and restricted feeding. Can. J. Anim. Sci. 91: 231–237. Mink were selected for high November weight (AL line) and low feed conversion ratio (FC line) on ad libitum feeding and for high November weight on restricted feeding (RF line). After three generations of selection, the average estimated breeding value for November weight was 533, 326, and 150 g in males and 168, 82, and −85 g in females in the AL, RF, and FC lines. The breeding value for feed conversion ratio was −1.39, −0.84 and −0.68 kg feed kg−1 gain in males and −0.39, −0.31 and −0.23 kg feed kg−1 gain in females in the selection lines. In generation 4, the AL, RF and FC lines were tested on both ad libitum and restricted feeding. The estimated breeding value for November weight in males in the AL line (533 g) was significantly greater than that in the RF line (384 g) on ad libitum feeding. The corresponding values on restricted feeding were 297 and 326 g, respectively, which were not significantly different. This indicates genotype×environment interaction. In the AL line, selection improved feed conversion ratio by increased appetite. In the RF line, it was improved by increased feed utilization. Environmental sensitivity in males, estimated from breeding values for November weight was 236 g in the AL line and 58 g in the RF line suggesting that the RF line was more robust to changes in feeding conditions. A smaller litter size in the AL line (4.1) than in the RF line (5.6) indicates that selection for large weight affects reproduction.

scholarly journals Investigation of muscle transcriptomes using gradient boosting machine learning identifies molecular predictors of feed efficiency in growing pigs

2019 ◽  
Author(s):  
Farouk Messad ◽  
Isabelle Louveau ◽  
Basile Koffi ◽  
Hélène Gilbert ◽  
Florence Gondret
Keyword(s):  
Feed Efficiency ◽  
Conversion Ratio ◽  
Growing Pigs ◽  
Feed Conversion Ratio ◽  
Breeding Value ◽  
Gradient Boosting ◽  
Mrna Levels ◽  
Feed Conversion ◽  
Expression Levels ◽  
Muscle Genes

Abstract Background Improving feed efficiency (FE) is a major challenge in pig production. This complex trait is characterized by a high variability. Therefore, the identification of predictors of FE may be a relevant strategy to reduce phenotyping efforts in breeding and selection programs. The aim of this study was to investigate the suitability of expressed muscle genes in prediction of FE traits in growing pigs. The approach considered different transcriptomics experiments to cover a large range of FE values and identify reliable predictors. Results Microarrays data were obtained from longissimus muscles of two lines divergently selected for residual feed intake (RFI). Pigs (n = 71) from three experiments belonged to generations 6 to 8 of selection, were fed either a diet with a standard composition or a diet rich in fiber and lipids, received feed ad libitum or at restricted level, and weighed between 80 and 115 kg at slaughter. For each pig, breeding value for RFI (RFI-BV) was estimated, and feed conversion ratio (FCR) and energy-based feed conversion ratio (FCRe) were calculated during the test periods. Gradient boosting algorithms were used on the merged muscle transcriptomes to identify very important predictors of FE traits. About 20,405 annotated molecular probes were commonly expressed in longissimus muscle across experiments. Six to 267 expressed muscle genes covering a variety of biological processes were found as important predictors for RFI-BV (R2=0.63-0.65), FCR (R2=0.61-0.70) and FCRe (R2=0.49-0.52). The error of prediction was less than 8% for FCR. Altogether, 56 predictors were common to RFI-BV and FCR. Expression levels of 24 target genes were further measured by qPCR. Linear regression confirmed the good accuracy of combining mRNA levels of these genes to fit FE traits (RFI-BV: R2=0.73, FRC: R2=0.76; FCRe: R2=0.75). Stepwise regression procedure highlighted 10 genes (FKBP5, MUM1, AKAP12, FYN, TMED3, PHKB, TGF, SOCS6, ILR4, and FRAS1) in a linear combination predicting FCR and FCRe. In addition, FKBP5 and expression levels of five other genes (IGF2, SERINC3, CSRNP3, EZR and RPL16) significantly contributed to RFI-BV. Conclusion It was possible to identify few genes expressed in muscle that might be reliable predictors of feed efficiency.

PREDICTION OF DAILY GAIN, BACKFAT THICKNESS AND FEED CONVERSION RATIO AMONG CROSSBRED TERMINAL SIRES BETWEEN PUREBRED DUROC, PIETRAIN, AND LANDRACE BY CBE 4.0 SOFTWARE

2018 ◽  
Vol 1 (29) ◽  
pp. 72-81
Author(s):  
Hop Van Nguyen ◽  
Tinh Huu Nguyen ◽  
Hoa Van Tran ◽  
Kinh Van La
Keyword(s):  
Research And Development ◽  
High Reliability ◽  
Conversion Ratio ◽  
Feed Conversion Ratio ◽  
Backfat Thickness ◽  
Feed Conversion ◽  
Significant Difference ◽  
Pig Farm ◽  
Development Center ◽  
Daily Gain

The objective of the study is to compare the practical results with the predicted results by Crossbreeding Effects (CBE) software on pig crossbred based on daily gain, backfat thickness and feed conversion ratio. Another purpose of this study is to predict those three traits among some expected hybridization. This research was conducted on pig farm at Binh Thang Research and Development center from 2013 to 2017. In this study, for each pair of purebred Duroc and Pietrain, Duroc and Landrace, Pietrain and Landrace, twelve hybridizations were analyzed, nine unhybridizations were predicted by CBE software. The results showed that there was no significant difference between the predicted and actual data. With some unhybridization crossbred , the predictions showed high reliability (P<0.05). Based on the predicted data of CBE software , some traits of the crossbred animals would not be improved, therefore, it was not necessary to conduct these hybridizations

scholarly journals KAJIAN PEMANFAATAN SEKAM PADI YANG DIFERMENTASI EFFECTIVE MICROORGANISM-4 (EM-4) DISUPLEMENTASI DAUN SIRIH (Piper betle L) TERHADAP PERFORMANS DAN KARKAS ITIK BALI UMUR 22 MINGGU

2018 ◽  
Vol 21 (3) ◽  
pp. 96
Author(s):  
Partama I. B. G. ◽  
T. G. Belawa Yadnya ◽  
A. A. A. S. Trisnadewi ◽  
A. A. P. P. Wibawa ◽  
I. M. Mudita
Keyword(s):  
Conversion Ratio ◽  
Feed Conversion Ratio ◽  
Piper Betle ◽  
Feed Conversion ◽  
Effective Microorganism

Penelitian bertujuan untuk mengetahui pengaruh pemanfaatan sekam padi difermentasi larutan EffectiveMicroorganism-4 (EM-4) dalam ransum disuplementasi daun sirih (Piper betle L.) terhadap performans dan karkasitik bali betina, umur 22 minggu. Penelitian menggunakan rancangan acak lengkap dengan lima perlakuan yaituransum tanpa sekam padi (A), ransum mengandung 12,50% sekam padi (B), ransum mengandung 12,50 % sekampadi difermentasi EM-4 (C), ransum mengandung 12,50% sekam padi dan daun sirih (D), serta ransum 12,50%sekam padi difermentasi EM-4 dan daun sirih (E). Setiap perlakuan terdiri atas empat ulangan dan setiap ulanganberisi lima ekor ituik bali betina, Variabel yang diamati konsumsi ransum, konsumsi antioksidan ransum, bobotbadan akhir, pertambahan bobot badan, feed conversion ratio dan karkas meliputi bobot potong, bobot karkas danpersentase karkas. Hasil penelitian menunjukkan bahwa pemberian 12,50 % sekam padi difermentasi EM-4 sertadisuplementasi daun sirih tidak berpengaruh terhadap konsumsi ransum(P>0,05), namun dapat menghasilkanbobot badan akhir, pertambahan bobot badan lebih tinggi (P<0,05), serta FCR yang lebih rendah (P<0,05) sertabobot karkas dan persentase karkas yang lebih baik daripada perlakuan yang lainnya. Dapat disimpulkan bahwapemberian sekam padi yang difermentasi EM-4 serta disuplementasi daun sirih dapat memperbaiki performansdan karkas yang lebih baik daripada perlakuan yang lainnya.

scholarly journals Effects of Different Swimming Pool Conditions and Floor Types on Growth Performance and Footpad Dermatitis in Indoor-Reared White Roman Geese

Animals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1705
Author(s):  
Shih-Chieh Liao ◽  
Pei-Xuan Lu ◽  
Shih-Yi Shen ◽  
Chih-Chang Hsiao ◽  
Ching-Yi Lien ◽  
...  
Keyword(s):  
Growth Performance ◽  
Conversion Ratio ◽  
Feed Conversion Ratio ◽  
Swimming Pool ◽  
Poultry Production ◽  
Performance Measurements ◽  
Feed Conversion ◽  
Plantar Surface ◽  
Rearing Conditions ◽  
Foot Disease

Footpad dermatitis (FPD) is a major foot disease in modern poultry production, and it affects both poultry health and animal welfare. It refers to inflammation and necrotizing lesions on the plantar surface of the footpads and toes. We investigated the effects of providing a swimming pool and different floor types on growth performance and FPD score in indoor-reared White Roman geese. Forty-eight male and 48 female White Roman geese were randomly allocated to pens with or without a swimming pool and with either mud or perforated plastic floor and reared from 15 to 84 days of age. Growth performance measurements included feed intake (FI), weight gain (WG), and feed conversion ratio (FCR). FI, WG, and FCR were significantly decreased at various growth periods in geese provided with a pool. Lower WG and bodyweight for the perforated plastic floor group were found at 15–28 and 28 days of age, respectively. The geese reared on the perforated plastic floors without a pool had higher FPD scores at 70 and 84 days of age than those with other rearing conditions. A higher incidence of FPD score 1 was observed in geese raised without a pool. In conclusion, providing a pool can improve footpad health in indoor-reared White Roman geese but may not benefit growth performance.

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