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Marina H, Arranz JJ, Suárez-Vega A, Pelayo R, Gutiérrez-Gil B, Toral PG, Hervás G, Frutos P, Fonseca PAS. Assessment of milk metabolites as biomarkers for predicting feed efficiency in dairy sheep. J Dairy Sci 2024; 107:4743-4757. [PMID: 38369116 DOI: 10.3168/jds.2023-23984] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 01/11/2024] [Indexed: 02/20/2024]
Abstract
Estimating feed efficiency (FE) in dairy sheep is challenging due to the high cost of systems that measure individual feed intake. Identifying proxies that can serve as effective predictors of FE could make it possible to introduce FE into breeding programs. Here, 39 Assaf ewes in first lactation were evaluated regarding their FE by 2 metrics, residual feed intake (RFI) and feed conversion ratio (FCR). The ewes were classified into high, medium and low groups for each metric. Milk samples of the 39 ewes were subjected to untargeted metabolomics analysis. The complete milk metabolomic signature was used to discriminate the FE groups using partial least squares discriminant analysis. A total of 41 and 26 features were selected as the most relevant features for the discrimination of RFI and FCR groups, respectively. The predictive ability when utilizing the complete milk metabolomic signature and the reduced data sets were investigated using 4 machine learning (ML) algorithms and a multivariate regression method. The orthogonal partial least squares algorithm outperformed other ML algorithms for FCR prediction in the scenarios using the complete milk metabolite signature (R2 = 0.62 ± 0.06) and the 26 selected features (R2 = 0.62 ± 0.15). Regarding RFI predictions, the scenarios using the 41 selected features outperformed the scenario with the complete milk metabolite signature, where the multilayer feedforward artificial neural network (R2 = 0.18 ± 0.14) and extreme gradient boosting (R2 = 0.17 ± 0.15) outperformed other algorithms. The functionality of the selected metabolites implied that the metabolism of glucose, galactose, fructose, sphingolipids, amino acids, insulin, and thyroid hormones was at play. Compared with the use of traditional methods, practical applications of these biomarkers might simplify and reduce costs in selecting feed-efficient ewes.
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Affiliation(s)
- H Marina
- Dpto. Producción Animal, Facultad de Veterinaria, Universidad de León, Campus de Vegazana s/n, 24007 León, Spain
| | - J J Arranz
- Dpto. Producción Animal, Facultad de Veterinaria, Universidad de León, Campus de Vegazana s/n, 24007 León, Spain.
| | - A Suárez-Vega
- Dpto. Producción Animal, Facultad de Veterinaria, Universidad de León, Campus de Vegazana s/n, 24007 León, Spain
| | - R Pelayo
- Dpto. Producción Animal, Facultad de Veterinaria, Universidad de León, Campus de Vegazana s/n, 24007 León, Spain
| | - B Gutiérrez-Gil
- Dpto. Producción Animal, Facultad de Veterinaria, Universidad de León, Campus de Vegazana s/n, 24007 León, Spain
| | - P G Toral
- Instituto de Ganadería de Montaña (CSIC-University of León), Finca Marzanas s/n, 24346 Grulleros, León, Spain
| | - G Hervás
- Instituto de Ganadería de Montaña (CSIC-University of León), Finca Marzanas s/n, 24346 Grulleros, León, Spain
| | - P Frutos
- Instituto de Ganadería de Montaña (CSIC-University of León), Finca Marzanas s/n, 24346 Grulleros, León, Spain
| | - P A S Fonseca
- Dpto. Producción Animal, Facultad de Veterinaria, Universidad de León, Campus de Vegazana s/n, 24007 León, Spain
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Espinales C, Baldeón M, Bravo C, Toledo H, Carballo J, Romero-Peña M, Cáceres PJ. Strategies for Healthier Meat Foods: An Overview. Prev Nutr Food Sci 2024; 29:18-30. [PMID: 38576885 PMCID: PMC10987382 DOI: 10.3746/pnf.2024.29.1.18] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 12/15/2023] [Accepted: 12/27/2023] [Indexed: 04/06/2024] Open
Abstract
Functional food products remain the focus of current market trends toward healthier nutrition. The consumption of meat-based functional foods has been a topic of interest in food innovation since some of these products generate controversy due to their possible adverse effects on health. However, studies have demonstrated that meat-based functional products are considered an opportunity to improve the nutritional profile of meat products through the addition of biologically valuable components and to meet the specific needs of consumers. In this sense, some strategies and techniques are applied for processing and developing functional meat products, such as modifying carcass composition through feeding, reformulating meat products, and processing conditions. This review focuses on presenting developed and evaluated strategies that allow the production of healthy and functional meat foods, which application has successfully achieved the sensory, nutritional, and technological parameters mainly affected by such application.
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Affiliation(s)
- Cindy Espinales
- Facultad de Ingeniería en Mecánica y Ciencias de la Producción, Escuela Superior Politécnica del Litoral (ESPOL), Guayaquil EC090112, Ecuador
| | - María Baldeón
- Facultad de Ingeniería en Mecánica y Ciencias de la Producción, Escuela Superior Politécnica del Litoral (ESPOL), Guayaquil EC090112, Ecuador
| | - Cinthya Bravo
- Facultad de Ingeniería en Mecánica y Ciencias de la Producción, Escuela Superior Politécnica del Litoral (ESPOL), Guayaquil EC090112, Ecuador
| | - Howard Toledo
- Facultad de Ingeniería en Mecánica y Ciencias de la Producción, Escuela Superior Politécnica del Litoral (ESPOL), Guayaquil EC090112, Ecuador
| | - José Carballo
- Institute of Food Science, Technology and Nutrition (ICTAN-CSIC), Madrid 28040, Spain
| | - María Romero-Peña
- Facultad de Ingeniería en Mecánica y Ciencias de la Producción, Escuela Superior Politécnica del Litoral (ESPOL), Guayaquil EC090112, Ecuador
- Saskatchewan Food Industry Development Centre (SFIDC), Saskatoon S7M 5V1, Canada
| | - Patricio J. Cáceres
- Facultad de Ingeniería en Mecánica y Ciencias de la Producción, Escuela Superior Politécnica del Litoral (ESPOL), Guayaquil EC090112, Ecuador
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3
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Jiang W, Mooney MH, Shirali M. Unveiling the Genetic Landscape of Feed Efficiency in Holstein Dairy Cows: Insights into Heritability, Genetic Markers, and Pathways via Meta-Analysis. J Anim Sci 2024; 102:skae040. [PMID: 38354297 PMCID: PMC10957122 DOI: 10.1093/jas/skae040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 02/09/2024] [Indexed: 02/16/2024] Open
Abstract
Improving the feeding efficiency of dairy cows is a key component to improve the utilization of land resources and meet the demand for high-quality protein. Advances in genomic methods and omics techniques have made it possible to breed more efficient dairy cows through genomic selection. The aim of this review is to obtain a comprehensive understanding of the biological background of feed efficiency (FE) complex traits in purebred Holstein dairy cows including heritability estimate, and genetic markers, genes, and pathways participating in FE regulation mechanism. Through a literature search, we systematically reviewed the heritability estimation, molecular genetic markers, genes, biomarkers, and pathways of traits related to feeding efficiency in Holstein dairy cows. A meta-analysis based on a random-effects model was performed to combine reported heritability estimates of FE complex. The heritability of residual feed intake, dry matter intake, and energy balance was 0.20, 0.34, and 0.22, respectively, which proved that it was reasonable to include the related traits in the selection breeding program. For molecular genetic markers, a total of 13 single-nucleotide polymorphisms and copy number variance loci, associated genes, and functions were reported to be significant across populations. A total of 169 reported candidate genes were summarized on a large scale, using a higher threshold (adjusted P value < 0.05). Then, the subsequent pathway enrichment of these genes was performed. The important genes reported in the articles were included in a gene list and the gene list was enriched by gene ontology (GO):biological process (BP), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis. Three GO:BP terms and four KEGG terms were statistically significant, which mainly focused on adenosine triphosphate (ATP) synthesis, electron transport chain, and OXPHOS pathway. Among these pathways, involved genes such as ATP5MC2, NDUFA, COX7A2, UQCR, and MMP are particularly important as they were previously reported. Twenty-nine reported biological mechanisms along with involved genes were explained mainly by four biological pathways (insulin-like growth factor axis, lipid metabolism, oxidative phosphorylation pathways, tryptophan metabolism). The information from this study will be useful for future studies of genomic selection breeding and genetic structures influencing animal FE. A better understanding of the underlying biological mechanisms would be beneficial, particularly as it might address genetic antagonism.
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Affiliation(s)
- Wentao Jiang
- Institute for Global Food Security, School of Biological Sciences, Queen’s University Belfast, Belfast, BT9 5DL, UK
- Agri-Food and Biosciences Institute, Large Park, Hillsborough, BT26 6DR, UK
| | - Mark H Mooney
- Institute for Global Food Security, School of Biological Sciences, Queen’s University Belfast, Belfast, BT9 5DL, UK
| | - Masoud Shirali
- Institute for Global Food Security, School of Biological Sciences, Queen’s University Belfast, Belfast, BT9 5DL, UK
- Agri-Food and Biosciences Institute, Large Park, Hillsborough, BT26 6DR, UK
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Madilindi MA, Zishiri OT, Dube B, Banga CB. Genetic parameter estimates for daily predicted gross feed efficiency and its association with energy-corrected milk in South African Holstein cattle. Trop Anim Health Prod 2023; 55:339. [PMID: 37770720 PMCID: PMC10539442 DOI: 10.1007/s11250-023-03741-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 09/12/2023] [Indexed: 09/30/2023]
Abstract
Genetic parameters for daily predicted gross feed efficiency (pGFE) and energy corrected milk (ECM) in the first three parities of South African Holstein cattle were estimated by repeatability animal models. Data comprised of 11,068 test-day milk production records of 1,575 Holstein cows that calved between 2009 and 2019. Heritability estimates for pGFE were 0.12 ± 0.06, 0.09 ± 0.04 and 0.18 ± 0.05 in early, mid and late lactation, respectively. Estimates were moderate for primiparous (0.21 ± 0.05) and low for multiparous (0.10 ± 0.04) cows. Heritability and repeatability across all lactations were 0.14 ± 0.03 and 0.37 ± 0.03, respectively. Genetic correlations between pGFE in different stages of lactation ranged from 0.87 ± 0.24 (early and mid) to 0.97 ± 0.28 (early and late), while a strong genetic correlation (0.90 ± 0.03) was found between pGFE and ECM, across all lactations. The low to moderate heritability estimates for pGFE suggest potential for genetic improvement of the trait through selection, albeit with a modest accuracy of selection. The high genetic correlation of pGFE with ECM may, however, assist to improve accuracy of selection for feed efficiency by including both traits in multi-trait analyses. These genetic parameters may be used to estimate breeding values for pGFE, which will enable the trait to be incorporated in the breeding objective for South African Holstein cattle.
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Affiliation(s)
- Matome A Madilindi
- Discipline of Genetics, College of Agriculture, Engineering and Science, University of KwaZulu-Natal, Private Bag X54001, Durban, 4000, South Africa.
- ARC-Animal Production, Private Bag X2, Irene, 0062, South Africa.
| | - Oliver T Zishiri
- Discipline of Genetics, College of Agriculture, Engineering and Science, University of KwaZulu-Natal, Private Bag X54001, Durban, 4000, South Africa
| | - Bekezela Dube
- ARC-Animal Production, Private Bag X2, Irene, 0062, South Africa
| | - Cuthbert B Banga
- Department of Animal Sciences, Faculty of Science, Tshwane University of Technology, Private Bag X680, Pretoria, 0001, South Africa
- Department of Agriculture and Animal Health, University of South Africa, Private Bag X6, Florida, 1710, South Africa
- Department of Animal Sciences, Faculty of Animal and Veterinary Sciences, Botswana University of Agriculture and Natural Resources, Private Bag 0027, Gaborone, Botswana
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Baruselli PS, de Abreu LÂ, de Paula VR, Carvalho B, Gricio EA, Mori FK, Rebeis LM, Albertini S, de Souza AH, D’Occhio M. Applying assisted reproductive technology and reproductive management to reduce CO 2-equivalent emission in dairy and beef cattle: a review. Anim Reprod 2023; 20:e20230060. [PMID: 37720728 PMCID: PMC10503887 DOI: 10.1590/1984-3143-ar2023-0060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 07/31/2023] [Indexed: 09/19/2023] Open
Abstract
Methane emission from beef and dairy cattle combined contributes around 4.5-5.0% of total anthropogenic global methane. In addition to enteric methane (CH4) produced by the rumen, cattle production also contributes carbon dioxide (CO2) (feed), nitrous oxide (N2O) (feed production, manure) and other CH4 (manure) to the total greenhouse gas (GHG) budget of beef and dairy production systems. The relative contribution in standard dairy systems is typically enteric CH4 58%, feed 29% and manure 10%. Herds with low production efficiency can have an enteric CH4 contribution up to 90%. Digestibility of feed can impact CH4 emission intensity. Low fertility herds also have a greater enteric CH4 contribution. Animals with good feed conversion efficiency have a lower emission intensity of CH4/kg of meat or milk. Feed efficient heifers tend to be lean and have delayed puberty. Fertility is a major driver of profit in both beef and dairy cattle, and it is highly important to apply multi-trait selection when shifting herds towards improved efficiency and reduced CH4. Single nucleotide polymorphisms (SNPs) have been identified for feed efficiency in cattle and are used in genomic selection. SNPs can be utilized in artificial insemination and embryo transfer to increase the proportion of cattle that have the attributes of efficiency, fertility and reduced enteric CH4. Prepubertal heifers genomically selected for favourable traits can have oocytes recovered to produce IVF embryos. Reproductive technology is predicted to be increasingly adopted to reduce generation interval and accelerate the rate of genetic gain for efficiency, fertility and low CH4 in cattle. The relatively high contribution of cattle to anthropogenic global methane has focussed attention on strategies to reduce enteric CH4 without compromising efficiency and fertility. Assisted reproductive technology has an important role in achieving the goal of multiplying and distributing cattle that have good efficiency, fertility and low CH4.
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Affiliation(s)
- Pietro Sampaio Baruselli
- Departamento de Reprodução Animal, Faculdade de Medicina Veterinária e Zootecnia, Universidade de São Paulo, São Paulo, SP, Brasil
| | - Laís Ângelo de Abreu
- Departamento de Reprodução Animal, Faculdade de Medicina Veterinária e Zootecnia, Universidade de São Paulo, São Paulo, SP, Brasil
| | - Vanessa Romário de Paula
- Instituto Paulista de Ensino e Pesquisa, Empresa Brasileira de Pesquisa Agropecuária – EMBRAPA, Juiz de Fora, MG, Brasil
| | - Bruno Carvalho
- Instituto Paulista de Ensino e Pesquisa, Empresa Brasileira de Pesquisa Agropecuária – EMBRAPA, Juiz de Fora, MG, Brasil
| | - Emanuelle Almeida Gricio
- Departamento de Reprodução Animal, Faculdade de Medicina Veterinária e Zootecnia, Universidade de São Paulo, São Paulo, SP, Brasil
| | - Fernando Kenji Mori
- Departamento de Reprodução Animal, Faculdade de Medicina Veterinária e Zootecnia, Universidade de São Paulo, São Paulo, SP, Brasil
| | - Lígia Mattos Rebeis
- Departamento de Reprodução Animal, Faculdade de Medicina Veterinária e Zootecnia, Universidade de São Paulo, São Paulo, SP, Brasil
| | - Sofía Albertini
- Departamento de Reprodução Animal, Faculdade de Medicina Veterinária e Zootecnia, Universidade de São Paulo, São Paulo, SP, Brasil
| | | | - Michael D’Occhio
- School of Life and Environmental Sciences, Faculty of Science, The University of Sydney, Sydney, Australia
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Gruber S, Rienesl L, Köck A, Egger-Danner C, Sölkner J. Importance of Mid-Infrared Spectra Regions for the Prediction of Mastitis and Ketosis in Dairy Cows. Animals (Basel) 2023; 13:ani13071193. [PMID: 37048449 PMCID: PMC10093284 DOI: 10.3390/ani13071193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 03/22/2023] [Accepted: 03/27/2023] [Indexed: 03/31/2023] Open
Abstract
Mid-infrared (MIR) spectroscopy is routinely applied to determine major milk components, such as fat and protein. Moreover, it is used to predict fine milk composition and various traits pertinent to animal health. MIR spectra indicate an absorbance value of infrared light at 1060 specific wavenumbers from 926 to 5010 cm−1. According to research, certain parts of the spectrum do not contain sufficient information on traits of dairy cows. Hence, the objective of the present study was to identify specific regions of the MIR spectra of particular importance for the prediction of mastitis and ketosis, performing variable selection analysis. Partial least squares discriminant analysis (PLS-DA) along with three other statistical methods, support vector machine (SVM), least absolute shrinkage and selection operator (LASSO), and random forest (RF), were compared. Data originated from the Austrian milk recording and associated health monitoring system (GMON). Test-day data and corresponding MIR spectra were linked to respective clinical mastitis and ketosis diagnoses. Certain wavenumbers were identified as particularly relevant for the prediction models of clinical mastitis (23) and ketosis (61). Wavenumbers varied across four distinct statistical methods as well as concerning different traits. The results indicate that variable selection analysis could potentially be beneficial in the process of modeling.
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Affiliation(s)
- Stefan Gruber
- Institute of Livestock Sciences, University of Natural Resources and Life Sciences, Vienna (BOKU), Gregor-Mendel-Straße 33, 1180 Vienna, Austria
| | - Lisa Rienesl
- Institute of Livestock Sciences, University of Natural Resources and Life Sciences, Vienna (BOKU), Gregor-Mendel-Straße 33, 1180 Vienna, Austria
- Correspondence: ; Tel.: +43-1-476-549-3201
| | - Astrid Köck
- ZuchtData EDV-Dienstleistungen GmbH, Dresdner Straße 89/19, 1200 Vienna, Austria
| | - Christa Egger-Danner
- ZuchtData EDV-Dienstleistungen GmbH, Dresdner Straße 89/19, 1200 Vienna, Austria
| | - Johann Sölkner
- Institute of Livestock Sciences, University of Natural Resources and Life Sciences, Vienna (BOKU), Gregor-Mendel-Straße 33, 1180 Vienna, Austria
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Romanzin A, Florit E, Degano L, Spanghero M. Feeding efficiency and behaviour of growing bulls from the main Italian dual-purpose breeds. ITALIAN JOURNAL OF ANIMAL SCIENCE 2022. [DOI: 10.1080/1828051x.2022.2146006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Affiliation(s)
- Alberto Romanzin
- Dipartimento di Scienze AgroAlimentari, Ambientali e Animali, University of Udine, Udine, Italy
| | - Eleonora Florit
- Dipartimento di Scienze AgroAlimentari, Ambientali e Animali, University of Udine, Udine, Italy
| | - Lorenzo Degano
- National Association of Italian Simmental breeders, Udine, Italy
| | - Mauro Spanghero
- Dipartimento di Scienze AgroAlimentari, Ambientali e Animali, University of Udine, Udine, Italy
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Bai Y, Li Y, Tang Y, Zhou R, Fan Y. Rhizopus oryzae fermentation wastewater nutrient removal coupling protein fodder production by employing Chlorella pyrenoidosa. BIORESOURCE TECHNOLOGY 2022; 362:127858. [PMID: 36037840 DOI: 10.1016/j.biortech.2022.127858] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 08/22/2022] [Accepted: 08/23/2022] [Indexed: 06/15/2023]
Abstract
The scenario was to investigate feasibilities of employing Chlorella pyrenoidosa for Rhizopus oryzae fermentation wastewater nutrient removal coupling protein fodder production. Results stated that TN, TP, NH3-N, COD, BOD removal reached 99.79%, 94.70%, 98.80%, 97.60%, 99.60% to acquire discharge permit under fed-batch manipulation, whilst the peaked protein yield (19.94 g/L) was 6.04-fold more than batch manipulation. Rhizopus oryzae fermentation wastewater feeding C. pyrenoidosa was praised as high-quality protein not only with 26.78% essential amino acids and essential amino acids/nonessential amino acids value of 0.84 but also pathogenic bacteria and heavy metal loads complying with fodder standards. In vitro digestibility of dry matter, protein, lipid, and starch achieving 80.07%, 92.13%, 95.93%, 91.9% and bioavailability of polypeptides, triglycerides, free fatty acids, and oligosaccharides displaying 98.67%, 87.12%, 93.86%, 30.21%, which were roughly-equivalent to corn/soybean fodder. The findings formed exemplifications in utilizing other microalgal systems for wastewater nutrient removal coupling chemicals production.
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Affiliation(s)
- Yanan Bai
- Department of Food Science and Engineering, College of Chemical Engineering, Xiangtan University, Xiangtan, China
| | - Yuqin Li
- Department of Food Science and Engineering, College of Chemical Engineering, Xiangtan University, Xiangtan, China.
| | - Yufang Tang
- Department of Food Science and Engineering, College of Chemical Engineering, Xiangtan University, Xiangtan, China
| | - Rong Zhou
- Department of Food Science and Engineering, College of Chemical Engineering, Xiangtan University, Xiangtan, China
| | - Yiwen Fan
- Department of Food Science and Engineering, College of Chemical Engineering, Xiangtan University, Xiangtan, China
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Prediction of dry matter intake and gross feed efficiency using milk production and live weight in first-parity Holstein cows. Trop Anim Health Prod 2022; 54:278. [PMID: 36074215 DOI: 10.1007/s11250-022-03275-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 08/31/2022] [Indexed: 10/14/2022]
Abstract
Direct measurement of dry matter intake (DMI) presents a major challenge in estimating gross feed efficiency (GFE) in dairy cattle. This challenge can, however, be resolved through the prediction of DMI and GFE from easy-to-measure traits such as milk production (i.e. milk yield, energy-corrected milk (ECM), butterfat, protein, lactose) and live weight (LW). The main objective of this study was, therefore, to investigate the feasibility of predicting dry matter intake and gross feed efficiency for first-parity Holstein cows using milk production traits and LW. Data comprised of 30 daily measurements of DMI and milk production traits, and 25 daily LW records of a group of 100 first-parity Holstein cows, fed a total mixed ration. Gross feed efficiency was calculated as kg ECM divided by kg DMI. The initial step was to estimate correlations of milk production traits and LW with DMI and GFE, to identify the best potential predictors of DMI and GFE. Subsequently, a forward stepwise regression analysis was used to develop models to predict DMI and GFE from LW and milk production traits, followed by within-herd validations. Means for DMI, butterfat yield (BFY) and LW were 21.91 ± 2.77 kg/day, 0.95 ± 0.14 kg/day and 572 ± 15.58 kg/day, respectively. Mean GFE was 1.32 ± 0.22. Dry matter intake had positive correlations with milk yield (MY) (r = 0.32, p < 0.001) and LW (r = 0.76, p < 0.0001) and an antagonistic association with butterfat percent (BFP) (r = - 0.55, p < 0.001). On the other hand, GFE was positively associated with MY (r = 0.36, p < 0.001), BFP (r = 0.53, p < 0.001) and BFY (r = 0.83, p < 0.0001), and negatively correlated with LW (r = - 0.23, p > 0.05). Dry matter intake was predicted reliably by a model comprising of only LW and MY (R2 = 0.79; root mean squared error (RMSE) = 1.05 kg/day). A model that included BFY, MY and LW had the highest ability to predict GFE (R2 = 0.98; RMSE = 0.05). Live weight and BFY were the main predictor traits for DMI and GFE, respectively. The best models for predicting DMI and GFE were as follows: DMI (kg/day) = - 54.21 - 0.192 × MY (kg/day) + 0.146 × LW (kg/day) and GFE (kg/day) = 4.120 + 0.024 × MY (kg/day) + 1.000 × BFY (kg/day) - 0.008 × LW (kg/day). Thus, daily DMI (kg/day) and GFE can be reliably predicted from LW and milk production traits using these developed models in first-parity Holstein cows. This presents a big promise to generate large quantities of data of individual cow DMI and GFE, which can be used to implement genetic improvement of feed efficiency.
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