Rabbits Divergently Selected for Total Body Fat Content: Changes in Proximate Composition and Fatty Acids of Different Meat Portions
Abstract
:Simple Summary
Abstract
1. Introduction
2. Materials and Methods
2.1. Animals and Experimental Design
2.2. Sample Preparation and Proximate Composition
2.3. Fatty Acid Profile and Contents
2.4. Statistical Analysis
3. Results
3.1. Proximate Composition
3.2. Fatty Acids
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Piles, M.; García, M.L.; Rafel, O.; Ramón, J.; Baselga, M. Genetics of litter size in three maternal lines of rabbits: Repeatability versus multiple-trait models. J. Anim. Sci. 2006, 84, 2309–2315. [Google Scholar] [CrossRef] [PubMed]
- Fortun-Lamothe, L. Energy balance and reproductive performance in rabbit does. Anim. Reprod. Sci. 2006, 93, 1–15. [Google Scholar] [CrossRef] [PubMed]
- Garreau, H.; Larzul, C.; Tudela, F.; Ruesche, J.; Ducqrocq, V.; Fortun-Lamothe, L. Energy balance and body reserves in rabbit females selected for longevity. World Rabbit Sci. 2017, 25, 205–213. [Google Scholar] [CrossRef]
- Blasco, A.; Nagy, I.; Hernández, P. Genetics of growth, carcass and meat quality in rabbits. Meat Sci. 2018, 145, 178–185. [Google Scholar] [CrossRef] [PubMed]
- Garreau, H.; Bolet, G.; Larzul, C.; Robert-Granie, C.; Saleil, G.; San Cristobal, M.; Bodin, L. Results of four generations of a canalising selection for rabbit birth weight. Livest. Sci. 2008, 119, 55–62. [Google Scholar] [CrossRef]
- Cullere, M.; Dalle Zotte, A. Rabbit meat production and consumption: State of knowledge and future perspectives. Meat Sci. 2018, 143, 137–146. [Google Scholar] [CrossRef] [PubMed]
- Larzul, C.; de Rochambeau, H. Comparison of ten rabbit lines of terminal bucks for growth, feed efficiency and carcass traits. Anim. Res. 2004, 53, 535–545. [Google Scholar] [CrossRef]
- Dalle Zotte, A.; Szendrő, Z. The role of rabbit meat as functional food. Meat Sci. 2011, 88, 319–331. [Google Scholar] [CrossRef]
- Ács, V.; Szendrő, K.; Garreau, H.; Donkó, T.; Matics, Z.; Nagy, I. Application possibilities of selection indices in Pannon White rabbits’ breeding programme. Ital. J. Anim. Sci. 2018, 17, 884–889. [Google Scholar] [CrossRef]
- Matics, Z.; Nagy, I.; Gerencsér, Z.; Radnai, I.; Gyovai, P.; Donkó, T.; Dalle Zotte, A.; Curik, I.; Szendrő, Z. Pannon breeding program in rabbit at Kaposvár University. World Rabbit Sci. 2014, 22, 287–300. [Google Scholar] [CrossRef] [Green Version]
- Kasza, R.; Donkó, T.; Matics, Z.; Nagy, I.; Csóka, Á.; Kovács, G.; Gerencsér, Z.; Dalle Zotte, A.; Cullere, M.; Szendrő, Z. Rabbit lines divergently selected for total body fat content: Correlated responses on growth performance and carcass traits. Animals 2020, 10, 1815. [Google Scholar] [CrossRef]
- EC-European Commission. Commission Directive 2010/63/EU of 22 September 2010 on the protection of animals used for scientific purposes. Off. J. Eur. Union 2010, 276, 33. [Google Scholar]
- Kasza, R.; Matics, Z.; Gerencsér, Z.; Donkó, T.; Radnai, I.; Szendrő, Z.; Nagy, I. Divergent selection for fat index in Pannon Ka rabbits: Genetic parameters, selection response. World Rabbit Sci. 2020, 28, 129–133. [Google Scholar] [CrossRef]
- Blasco, A.; Ouhayoun, J. Harmonization of criteria and terminology in rabbit meat research. Revised proposal. World Rabbit Sci. 1996, 4, 93–99. [Google Scholar] [CrossRef]
- AOAC-Association of Official Analytical Chemists. Official Methods of Analysis, 19th ed.; Association of Official Analytical Chemists: Arlington, VA, USA, 2012. [Google Scholar]
- EC-European Commission. Commission Directive 98/64/EC of 3 September 1998 Establishing Community Methods of Analysis for the Determination of Amino Acids, Crude Oils and Fats, and Olaquindox in Feeding Stuffs and Amending Q2 Directive 71/393/EEC. Off. J. Eur. Union 1998, 257, 14. Available online: https://op.europa.eu/en/publication-detail/-/publication/856db9b7-6f1d-4d6e-a778-c766c9fa1776 (accessed on 12 December 2021).
- Lee, C.M.; Trevino, B.; Chaiyawat, M. A simple and rapid solvent extraction method for determining total lipids in fish tissue. J. AOAC Int. 1996, 79, 487–492. [Google Scholar] [CrossRef]
- Dalle Zotte, A.; Cullere, M.; Martins, C.; Alves, S.P.; Freire, J.P.B.; Falcao-e-Cunha, L.; Bessa, R.J.B. Incorporation of black soldier fly (Hermetia illucens L.) larvae fat or extruded linseed in diets of growing rabbits and their effects on meat quality traits including detailed fatty acid composition. Meat Sci. 2018, 146, 50–58. [Google Scholar] [CrossRef]
- SAS-Statistical Analysis Software for Windows. Statistics, version 9.1.3, SAS Institute: Cary, NC, USA, 2008.
- Realini, C.E.; Pavan, E.; Johnson, P.L.; Font-i-Furnols, M.; Jacob, N.; Agnew, M.; Craigie, C.E.; Moon, C.D. Consumer liking of M. longissimus lumborum from New Zealand pasture-finished lamb is influenced by intramuscular fat. Meat Sci. 2021, 173, 108380. [Google Scholar] [CrossRef]
- Zomeño, C.; Blasco, A.; Hernández, P. Divergent selection for intramuscular fat content in rabbits. II. Correlated responses on carcass and meat quality traits. J. Anim. Sci. 2013, 91, 4532–4539. [Google Scholar] [CrossRef]
- Martínez-Álvaro, M.; Hernández, P.; Agha, S.; Blasco, A. Correlated responses to selection for intramuscular fat in several muscles in rabbits. Meat Sci. 2018, 139, 187–191. [Google Scholar] [CrossRef]
- Martínez-Álvaro, M.; Hernández, P.; Blasco, A. Divergent selection on intramuscular fat in rabbits: Responses to selection and genetic parameters. J. Anim. Sci. 2016, 94, 4993–5003. [Google Scholar] [CrossRef] [PubMed]
- Sosa-Madrid, B.S.; Varona, L.; Blasco, A.; Hernández, P.; Casto-Rebollo, C.; Ibáñez-Escriche, N. The effect of divergent selection for intramuscular fat on the domestic rabbit genome. Animal 2020, 14, 2225–2235. [Google Scholar] [CrossRef] [PubMed]
- EFSA Panel on Dietetic Products, Nutrition, and Allergies (NDA). Scientific opinion on dietary reference values for fats, including saturated fatty acids, polyunsaturated fatty acids, monounsaturated fatty acids, trans fatty acids, and cholesterol. EFSA J. 2010, 8, 1461. [Google Scholar]
- Aranceta, J.; Pérez-Rodrigo, C. Recommended dietary reference intakes, nutritional goals and dietary guidelines for fat and fatty acids: A systematic review. Brit. J. Nutr. 2012, 107, S8–S22. [Google Scholar] [CrossRef]
- FAO/WHO. Expert Consultation on Fats and Fatty Acids in Human Nutrition. In Proceedings of the Interim Summary of Conclusions and Dietary Recommendations on Total fat & Fatty Acids, Geneva, Switzerland, 10–14 November 2008. [Google Scholar]
- Benatmane, F.; Kouba, M.; Youyou, A.; Mourot, J. Effect of a linseed diet on lipogenesis, fatty acid composition and stearoyl-CoA-desaturase in rabbits. Animal 2011, 5, 1993–2000. [Google Scholar] [CrossRef]
- Castellini, C.; Dal Bosco, A.; Mattioli, S.; Davidescu, M.; Corazzi, L.; Macchioni, L.; Rimoldi, S.; Terova, G. Activity, expression, and substrate preference of the δ6-desaturase in slow-or fast-growing rabbit genotypes. J. Agric. Food Chem. 2016, 64, 792–800. [Google Scholar] [CrossRef]
- Guillou, H.; Zadravec, D.; Martin, P.G.; Jacobsson, A. The key roles of elongases and desaturases in mammalian fatty acid metabolism: Insights from transgenic mice. Prog. Lipid Res. 2010, 49, 186–199. [Google Scholar] [CrossRef]
- Sprecher, H.; Chen, Q. Polyunsaturated fatty acid biosynthesis: A microsomal-peroxisomal process. Prostag. Leukotr. Ess. 1999, 60, 317–321. [Google Scholar] [CrossRef]
- Martínez-Álvaro, M.; Paucar, Y.; Satué, K.; Blasco, A.; Hernández, P. Liver metabolism traits in two rabbit lines divergently selected for intramuscular fat. Animal 2018, 12, 1217–1223. [Google Scholar] [CrossRef]
(a) Meat Cut | LTL | FL | ||||||||
Generation (Gen) | Line | n Samples | Moisture | Protein | Lipids | Ash | Moisture | Protein | Lipids | Ash |
1 | Lean | 15 | 75.4 | 19.6 | 3.68 | 1.35 | 72.5 b,c | 16.7 | 9.58 c,d,e | 1.24 |
Fat | 15 | 75.0 | 19.9 | 3.79 | 1.32 | 72.2 b,c,d | 16.7 | 9.96 b,c,d,e | 1.14 | |
SE 1 | 0.16 | 0.15 | 0.09 | 0.01 | 0.35 | 0.11 | 0.42 | 0.03 | ||
p-Line | ns 2 | ns | ns | ns | ns | ns | ns | ns | ||
2 | Lean | 15 | 75.9 | 19.1 | 3.61 | 1.42 | 72.9 a,b | 16.9 | 8.95 d,e | 1.24 |
Fat | 15 | 75.3 | 19.5 | 3.78 | 1.41 | 70.5 d,e | 16.6 | 11.7 a,b,c | 1.16 | |
SE | 0.13 | 0.10 | 0.05 | 0.02 | 0.34 | 0.15 | 0.39 | 0.01 | ||
p-Line | ns | ns | ns | ns | 0.004 | ns | 0.003 | ns | ||
3 | Lean | 15 | 74.4 | 20.4 | 3.73 | 1.48 | 70.6 c,d,e | 17.7 | 10.3 a,b,c,d | 1.34 |
Fat | 15 | 74.2 | 20.3 | 3.96 | 1.57 | 68.8 d,e | 17.4 | 12.4 a | 1.34 | |
SE | 0.12 | 0.10 | 0.06 | 0.06 | 0.36 | 0.13 | 0.43 | 0.03 | ||
p-Line | ns | ns | ns | ns | ns | ns | ns | ns | ||
4 | Lean | 15 | 75.2 | 19.4 | 3.96 | 1.45 | 74.6 a | 16.2 | 7.93 e | 1.19 |
Fat | 15 | 75.2 | 19.2 | 4.18 | 1.42 | 71.7 b,c,d | 15.2 | 11.9 a,b | 1.14 | |
SE | 0.10 | 0.08 | 0.05 | 0.02 | 0.35 | 0.16 | 0.43 | 0.02 | ||
p-Line | 1.000 | 1.000 | 0.683 | 1.000 | <0.0001 | 0.004 | <0.0001 | 0.946 | ||
p-Gen | <0.0001 | <0.0001 | <0.0001 | 0.0024 | <0.0001 | <0.0001 | 0.006 | <0.0001 | ||
p-Line x Gen | ns | ns | ns | ns | 0.015 | ns | 0.004 | ns | ||
SE | 0.68 | 0.60 | 0.35 | 0.19 | 1.63 | 0.72 | 1.89 | 0.13 | ||
(b) Meat Cut | HL | AW | ||||||||
Generation (Gen) | Line | n Samples | Moisture | Protein | Lipids | Ash | Moisture | Protein | Lipids | Ash |
1 | Lean | 15 | 75.1 | 18.6 | 5.01 | 1.37 | 70.4 | 19.0 | 9.46 | 1.2 |
Fat | 15 | 74.8 | 18.4 | 5.45 | 1.36 | 68.9 | 18.7 | 11.3 | 1.17 | |
SE | 0.16 | 0.17 | 0.18 | 0.03 | 0.52 | 0.14 | 0.60 | 0.01 | ||
p-Line | ns | ns | ns | ns | ns | ns | ns | ns | ||
2 | Lean | 15 | 75.2 | 18.3 | 5.20 | 1.28 | 72.2 | 17.9 | 8.75 | 1.20 |
Fat | 15 | 74.4 | 18.5 | 5.85 | 1.26 | 69.7 | 17.3 | 11.8 | 1.13 | |
SE | 0.14 | 0.06 | 0.11 | 0.01 | 0.41 | 0.21 | 0.50 | 0.03 | ||
p-Line | 0.038 | ns | ns | ns | 0.045 | ns | 0.024 | ns | ||
3 | Lean | 15 | 74.1 | 19.0 | 5.52 | 1.44 | 70.0 | 18.4 | 10.4 | 1.29 |
Fat | 15 | 73.3 | 19.0 | 6.27 | 1.41 | 67.2 | 17.8 | 13.8 | 1.26 | |
SE | 0.13 | 0.06 | 0.14 | 0.02 | 0.47 | 0.17 | 0.56 | 0.02 | ||
p-Line | ns | ns | ns | ns | 0.013 | ns | 0.008 | ns | ||
4 | Lean | 15 | 76.2 | 17.4 | 5.10 | 1.33 | 75.6 | 16.1 | 7.26 | 1.13 |
Fat | 15 | 75.0 | 17.6 | 5.98 | 1.41 | 72.3 | 15.7 | 10.9 | 1.12 | |
SE | 0.17 | 0.11 | 0.13 | 0.02 | 0.41 | 0.15 | 0.45 | 0.01 | ||
p-Line | <0.001 | ns | 0.017 | ns | 0.002 | ns | 0.003 | ns | ||
p-Gen | <0.0001 | <0.0001 | 0.005 | <0.0001 | <0.0001 | <0.0001 | <0.0001 | <0.0001 | ||
p-Line x Gen | ns | ns | ns | ns | ns | ns | ns | ns | ||
SE | 0.73 | 0.61 | 0.70 | 0.11 | 2.16 | 0.91 | 2.51 | 0.11 |
Generation (Gen) | 3 | 4 | p-Gen | |||||||
---|---|---|---|---|---|---|---|---|---|---|
Line | Lean | Fat | SE 1 | p-Line | Lean | Fat | SE | p-Line | SE | |
Fatty Acid Profile | % Fatty Acid | % Fatty Acid | ||||||||
n. samples | 15 | 15 | 15 | 15 | ||||||
C14:0 | 1.52 | 1.83 | 0.07 | ns 2 | 1.09 | 1.78 | 0.09 | <0.001 | 0.016 | 0.07 |
C16:0 | 21.3 | 21.6 | 0.30 | ns | 22.8 | 24.1 | 0.20 | 0.040 | <0.001 | 0.24 |
C17:0 | 0.64 | 0.56 | 0.01 | ns | 0.75 | 0.59 | 0.03 | 0.006 | 0.050 | 0.02 |
C18:0 | 5.98 | 5.44 | 0.11 | ns | 9.51 | 8.29 | 0.20 | <0.001 | <0.001 | 0.14 |
SFAs 3 | 30.1 | 30.6 | 0.35 | ns | 35.5 | 35.9 | 0.20 | ns | <0.001 | 0.29 |
C16:1 | 1.73 | 2.81 | 0.17 | <0.001 (1.08 8) | 0.83 | 2.26 | 0.17 | <0.001 (1.43) | <0.001 | 0.01 |
C18:1 n-9 | 26.7 | 28.1 | 0.43 | ns | 20.5 | 24.1 | 0.49 | <0.001 | <0.001 | 0.39 |
C22:1 n-9 | 0.03 | 0.06 | 0.02 | ns | 0.34 | 0.20 | 0.03 | 0.030 | <0.001 | 0.03 |
MUFAs 4 | 30.0 | 32.7 | 0.54 | 0.018 (2.70) | 23.9 | 28.8 | 0.61 | <0.001 (4.90) | <0.001 | 0.45 |
C18:2 n-6 | 23.6 | 23.0 | 0.24 | 0.677 | 23.8 | 22.8 | 0.32 | 0.267 | <0.001 | 0.28 |
C18:3 n-3 | 1.57 | 1.69 | 0.04 | ns | 1.10 | 1.47 | 0.08 | 0.009 | <0.001 | 0.06 |
C20:3 n-6 | 0.16 | 0.13 | 0.03 | ns | 0.48 | 0.32 | 0.03 | 0.044 | <0.001 | 0.03 |
C20:4 n-6 | 2.57 | 2.06 | 0.13 | ns | 5.31 | 3.37 | 0.31 | <0.001 | <0.001 | 0.20 |
C20:5 n-3 | 0.03 | 0.03 | 0.01 | ns | 0.22 | 0.14 | 0.02 | 0.007 | <0.001 | 0.01 |
PUFAs 5 | 28.3 | 27.1 | 0.34 | ns | 31.6 | 28.8 | 0.43 | 0.001 | <0.001 | 0.34 |
UFAs 6/SFAs | 1.91 | 1.95 | 0.02 | ns | 1.57 | 1.60 | 0.02 | ns | <0.001 | 0.02 |
n-6 | 26.6 | 25.4 | 0.34 | ns | 30.0 | 26.9 | 0.44 | <0.001 | <0.001 | 0.33 |
n-3 | 1.65 | 1.73 | 0.03 | ns | 1.59 | 1.87 | 0.08 | ns | ns | 0.06 |
n-6/n-3 | 16.2 | 14.8 | 0.30 | ns | 20.1 | 15.1 | 0.91 | 0.001 | 0.015 | 0.59 |
PI 7 | 38.7 | 36.1 | 0.68 | ns | 51.5 | 42.6 | 1.29 | <0.001 | <0.001 | 0.85 |
Identified, % | 88.9 | 90.5 | 91.0 | 93.5 |
Generation (Gen) | 3 | 4 | p-Gen | |||||||
---|---|---|---|---|---|---|---|---|---|---|
Line | Lean | Fat | SE 1 | p-Line | Lean | Fat | SE | p-Line | SE | |
Fatty Acid Profile | % Fatty Acid | % Fatty Acid | ||||||||
n. samples | 15 | 15 | 15 | 15 | ||||||
C14:0 | 1.90 | 2.06 | 0.06 | ns 2 | 1.65 | 2.11 | 0.07 | 0.001 | ns | 0.06 |
C16:0 | 20.4 | 21.2 | 0.33 | ns | 23.1 | 24.5 | 0.26 | ns | <0.001 | 0.29 |
C18:0 | 5.87 | 5.56 | 0.11 | ns | 8.47 | 7.59 | 0.14 | 0.001 | <0.001 | 0.11 |
SFAs 3 | 30.5 | 31.0 | 0.40 | ns | 35.1 | 35.9 | 0.24 | ns | <0.001 | 0.33 |
C16:1 | 1.65 | 2.45 | 0.13 | 0.003 (0.80 8) | 1.29 | 2.69 | 0.17 | <0.001 (1.40) | ns | 0.11 |
C18:1 n-9 | 29.9 | 30.2 | 0.20 | ns | 22.9 | 25.9 | 0.40 | <0.001 | <0.001 | 0.26 |
MUFAs 4 | 33.1 | 34.5 | 0.30 | ns | 26.4 | 30.8 | 0.56 | <0.001 | <0.001 | 0.33 |
C18:2 n-6 | 27.0 | 26.0 | 0.34 | ns | 26.7 | 23.8 | 0.43 | 0.001 | 0.015 | 0.34 |
C18:3 n-3 | 2.07 | 2.18 | 0.05 | ns | 1.71 | 1.71 | 0.08 | ns | <0.001 | 0.06 |
C20:3 n-3 | 0.00 | 0.00 | 0.00 | ns | 0.19 | 0.20 | 0.03 | ns | <0.001 | 0.03 |
C20:4 n-6 | 1.23 | 1.15 | 0.06 | ns | 2.74 | 1.94 | 0.18 | 0.009 | <0.001 | 0.12 |
C22:2 n-6 | 0.00 | 0.00 | 0.00 | ns | 0.14 | 0.10 | 0.02 | ns | <0.001 | 0.02 |
PUFAs 5 | 30.9 | 30.0 | 0.40 | ns | 32.3 | 28.5 | 0.53 | <0.001 | ns | 0.40 |
UFAs 6/SFAs | 2.11 | 2.09 | 0.03 | ns | 1.66 | 1.65 | 0.02 | ns | <0.001 | 0.03 |
n-6 | 28.7 | 27.7 | 0.38 | ns | 30.3 | 26.7 | 0.47 | <0.001 | ns | 0.36 |
n-3 | 2.15 | 2.22 | 0.04 | ns | 2.04 | 2.13 | 0.04 | ns | ns | 0.04 |
n-6/n-3 | 13.6 | 12.5 | 0.24 | ns | 15.0 | 12.6 | 0.36 | <0.001 | 0.040 | 0.26 |
PI 7 | 38.0 | 36.9 | 0.55 | ns | 44.4 | 38.0 | 0.94 | <0.001 | <0.001 | 0.65 |
Identified, % | 94.5 | 95.4 | 94.1 | 95.2 |
Generation (Gen) | 3 | 4 | p-Gen | |||||||
---|---|---|---|---|---|---|---|---|---|---|
Line | Lean | Fat | SE 1 | p-Line | Lean | Fat | SE | p-Line | SE | |
Fatty Acid Profile | % Fatty Acid | % Fatty Acid | ||||||||
n. samples | 15 | 15 | 15 | 15 | ||||||
C12:0 | 0.37 | 0.38 | 0.03 | ns 2 | 0.41 | 0.26 | 0.03 | 0.037 | 0.290 | 0.03 |
C14:0 | 1.94 | 2.08 | 0.05 | ns | 2.19 | 2.59 | 0.07 | 0.008 | <0.001 | 0.06 |
C16:0 | 20.3 | 20.7 | 0.26 | ns | 24.2 | 25.9 | 0.50 | ns | <0.001 | 0.39 |
C18:0 | 6.42 | 5.85 | 0.12 | ns | 7.89 | 6.89 | 0.17 | 0.001 | <0.001 | 0.12 |
SFAs 3 | 30.9 | 30.8 | 0.24 | ns | 36.9 | 37.6 | 0.70 | ns | <0.001 | 0.53 |
C14:1 | 0.02 | 0.10 | 0.01 | 0.011 (0.08 8) | 0.10 | 0.18 | 0.02 | 0.010 (0.08) | <0.001 | 0.01 |
C16:1 | 1.40 | 2.10 | 0.12 | 0.013 (0.70) | 1.40 | 3.06 | 0.19 | <0.001 (1.66) | 0.004 | 0.11 |
C18:1 n-9 | 28.0 | 28.5 | 0.16 | ns | 25.5 | 28.0 | 0.35 | <0.001 | <0.001 | 0.22 |
C22:1 n-9 | 0.01 | 0.01 | 0.00 | ns | 0.10 | 0.07 | 0.01 | 0.030 | <0.001 | 0.01 |
MUFAs 4 | 31.1 | 32.6 | 0.26 | ns | 28.9 | 33.2 | 0.55 | <0.001 | 0.074 | 0.31 |
C18:2 n-6 | 28.8 | 27.7 | 0.29 | 0.889 | 25.5 | 22.1 | 1.03 | 0.107 | <0.001 | 0.73 |
C18:3 n-6 | 0.10 | 0.10 | 0.01 | ns | 0.18 | 0.11 | 0.01 | <0.001 | <0.001 | 0.01 |
C20:4 n-6 | 1.85 | 1.74 | 0.07 | ns | 1.58 | 0.88 | 0.11 | <0.001 | <0.001 | 0.08 |
PUFAs 5 | 33.7 | 32.7 | 0.33 | ns | 29.6 | 25.3 | 1.20 | ns | <0.001 | 0.85 |
UFAs 6/SFAs | 2.11 | 2.12 | 0.02 | ns | 1.61 | 1.58 | 0.04 | ns | <0.001 | 0.70 |
n-6 | 31.4 | 30.2 | 0.32 | ns | 27.5 | 23.3 | 1.12 | 0.045 | <0.001 | 0.79 |
n-3 | 2.32 | 2.51 | 0.05 | ns | 2.10 | 2.03 | 0.09 | ns | <0.001 | 0.07 |
n-6/n-3 | 13.7 | 12.1 | 0.29 | 0.006 (1.60) | 13.4 | 11.5 | 0.28 | 0.002 (1.90) | 0.207 | 0.24 |
PI 7 | 42.8 | 41.8 | 0.46 | ns | 37.9 | 31.3 | 1.53 | 0.017 | <0.001 | 1.06 |
Identified, % | 95.7 | 96.1 | 95.4 | 96.1 |
Generation (Gen) | 3 | 4 | p-Gen | |||||||
---|---|---|---|---|---|---|---|---|---|---|
Line | Lean | Fat | SE 1 | p-Line | Lean | Fat | SE | p-Line | SE | |
Fatty Acid Profile | % Fatty Acid | % Fatty Acid | ||||||||
n. samples | 15 | 15 | 15 | 15 | ||||||
C16:0 | 20.4 | 20.8 | 0.30 | ns 2 | 27.5 | 27.4 | 0.66 | ns | <0.001 | 0.52 |
C17:0 | 0.53 | 0.51 | 0.03 | ns | 0.92 | 0.73 | 0.03 | 0.014 | <0.001 | 0.03 |
C18:0 | 5.81 | 5.45 | 0.09 | ns | 8.54 | 7.39 | 0.21 | 0.001 | <0.001 | 0.14 |
SFAs 3 | 30.5 | 30.6 | 0.34 | ns | 42.0 | 40.0 | 1.04 | ns | <0.001 | 0.78 |
C16:1 | 1.54 | 2.39 | 0.14 | 0.012 (0.85 8) | 1.60 | 3.35 | 0.21 | <0.001 (1.75) | 0.010 | 0.13 |
C22:1 n-9 | 0.04 | 0.03 | 0.01 | ns | 0.15 | 0.09 | 0.01 | 0.020 | <0.001 | 0.01 |
MUFAs 4 | 31.9 | 33.5 | 0.29 | ns | 32.4 | 35.7 | 0.59 | 0.001 | 0.024 | 0.41 |
C18:2 n-6 | 29.3 | 27.9 | 0.34 | 0.932 | 17.3 | 16.7 | 1.54 | 0.995 | <0.001 | 1.13 |
C18:3 n-6 | 0.08 | 0.09 | 0.01 | ns | 0.19 | 0.14 | 0.01 | 0.019 | <0.001 | 0.01 |
PUFAs 5 | 34.0 | 32.7 | 0.40 | ns | 20.0 | 19.2 | 1.77 | ns | <0.001 | 1.30 |
UFAs 6/SFAs | 2.17 | 2.17 | 0.03 | ns | 1.30 | 1.41 | 0.07 | ns | <0.001 | 0.05 |
n-6 | 31.5 | 30.1 | 0.39 | ns | 18.7 | 17.7 | 1.64 | ns | <0.001 | 1.20 |
n-3 | 2.49 | 2.59 | 0.04 | ns | 1.23 | 1.51 | 0.14 | ns | <0.001 | 0.10 |
n-6/n-3 | 12.7 | 11.7 | 0.26 | ns | 15.9 | 12.5 | 0.49 | <0.001 | <0.001 | 0.33 |
PI 7 | 42.4 | 40.9 | 0.57 | ns | 25.8 | 24.2 | 2.12 | ns | <0.001 | 1.58 |
Identified, % | 96.3 | 96.7 | 94.4 | 94.8 |
Generation (Gen) | 3 | 4 | p-Gen | SE | |||||
---|---|---|---|---|---|---|---|---|---|
Line | Lean | Fat | p-Line | Lean | Fat | p-Line | SE 1 | ||
n. samples | 15 | 15 | 15 | 15 | |||||
LTL: | |||||||||
SFAs 3 | 886 | 991 | ns 2 | 1202 | 1277 | ns | 34.2 | <0.001 | 24.2 |
MUFAs 4 | 871 | 1063 | 0.014 (192 6) | 810 | 1027 | 0.004 (217) | 42.8 | ns | 30.2 |
PUFAs 5 | 816 | 867 | ns | 1069 | 1020 | ns | 20.7 | <0.001 | 14.7 |
n-6 | 768 | 811 | ns | 1015 | 954 | ns | 19.8 | <0.001 | 14.0 |
n-3 | 47.8 | 55.5 | ns | 54.0 | 65.8 | ns | 3.08 | 0.010 | 2.18 |
Hind legs: | |||||||||
SFAs | 1369 | 1579 | ns | 1556 | 1869 | 0.001 | 56.0 | <0.001 | 39.6 |
MUFAs | 1488 | 1757 | 0.012 (269) | 1160 | 1609 | <0.001 (449) | 58.9 | <0.001 | 41.6 |
PUFAs | 1378 | 1513 | ns | 1419 | 1479 | ns | 39.8 | ns | 28.2 |
n-6 | 1282 | 1400 | ns | 1329 | 1373 | ns | 35.3 | ns | 25.0 |
n-3 | 96.3 | 113 | ns | 90.0 | 106 | ns | 5.30 | ns | 3.74 |
Forelegs: | |||||||||
SFAs | 2602 | 3226 | ns | 2578 | 4014 | <0.001 | 165 | 0.024 | 117 |
MUFAs | 2625 | 3414 | 0.003 (789) | 2015 | 3546 | <0.001 (1531) | 150 | ns | 106 |
PUFAs | 2839 | 3385 | ns | 2117 | 2678 | 0.045 | 143 | <0.001 | 101 |
n-6 | 2640 | 3122 | ns | 1974 | 2463 | ns | 130 | <0.001 | 91.7 |
n-3 | 199 | 263 | 0.011 (64) | 151 | 216 | 0.013 (65) | 13.9 | 0.001 | 10.1 |
Abdominal wall: | |||||||||
SFAs | 2613 | 3540 | 0.014 (927) | 2712 | 3852 | 0.002 (1140) | 206 | ns | 146 |
MUFAs | 2746 | 3895 | <0.001 (1149) | 2078 | 3450 | <0.001 (1372) | 200 | 0.007 | 141 |
PUFAs | 2914 | 3727 | 0.023 | 1185 | 1816 | ns | 190 | <0.001 | 134 |
n-6 | 2696 | 3427 | 0.025 | 1112 | 1673 | ns | 173 | <0.001 | 122 |
n-3 | 218 | 300 | 0.013 (82) | 73 | 143 | 0.048 (70) | 18.0 | <0.001 | 12.8 |
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Cullere, M.; Szendrő, Z.; Matics, Z.; Gerencsér, Z.; Kasza, R.; Donkó, T.; Dalle Zotte, A. Rabbits Divergently Selected for Total Body Fat Content: Changes in Proximate Composition and Fatty Acids of Different Meat Portions. Animals 2022, 12, 2396. https://doi.org/10.3390/ani12182396
Cullere M, Szendrő Z, Matics Z, Gerencsér Z, Kasza R, Donkó T, Dalle Zotte A. Rabbits Divergently Selected for Total Body Fat Content: Changes in Proximate Composition and Fatty Acids of Different Meat Portions. Animals. 2022; 12(18):2396. https://doi.org/10.3390/ani12182396
Chicago/Turabian StyleCullere, Marco, Zsolt Szendrő, Zsolt Matics, Zsolt Gerencsér, Rozália Kasza, Tamás Donkó, and Antonella Dalle Zotte. 2022. "Rabbits Divergently Selected for Total Body Fat Content: Changes in Proximate Composition and Fatty Acids of Different Meat Portions" Animals 12, no. 18: 2396. https://doi.org/10.3390/ani12182396
APA StyleCullere, M., Szendrő, Z., Matics, Z., Gerencsér, Z., Kasza, R., Donkó, T., & Dalle Zotte, A. (2022). Rabbits Divergently Selected for Total Body Fat Content: Changes in Proximate Composition and Fatty Acids of Different Meat Portions. Animals, 12(18), 2396. https://doi.org/10.3390/ani12182396