Crossbreeding and its implication for small-scale animal agriculture in Africa: Outcomes, both positive and negative, and future prospects
Vol 5, Issue 2, 2024
VIEWS - 4820 (Abstract)
Download PDF
Abstract
African animal genetic resources are diverse and have been the subject of crossbreeding for decades to improve local livestock and poultry populations. However, the literature on crossbreeding performance has been inconsistent, with many projects failing due to various reasons. This has led to mixed support and criticism for crossbreeding in small-scale animal agriculture. The review examines the achievements, problems, and future prospects for livestock and poultry genetic improvement through crossbreeding in Africa’s small-scale animal agriculture. Community-based Breeding Practices (CBBP) can be seen as a community livestock development strategy that mobilizes local animal genetic resources and boosts smallholder livestock producers’ ability to collaborate in resource-scarce communities. Genome sequencing is seen as the future cornerstone of promoting crossbreeding in Africa, but it should be based on consideration of the socioeconomic context of small-scale animal husbandry and local livestock production conditions. Smallholder farmers, who are the major custodians of local animal biodiversity, have faced challenges such as genotype and environmental interaction, lack of funding, poor laws, and lack of farmer participation. In conclusion, the review highlights the importance of phenomics and genomic prediction in improving animal genetic resources in Africa, but it also emphasizes the need for further research and development in this area. The study suggests that modern breeding technologies (genomics and phenomics) and training of smallholder livestock farmers in improved animal husbandry management practices can be used to enhance food and nutrition security for African rural households. This review examines the effects of crossbreeding through the decades on small-scale livestock farming in Africa, including positive and negative outcomes as well as future implications.
Keywords
References
1. World Bank. World Bank Open Data. 2019. Available online: https://data.worldbank.org (accessed on 18 May 2023).
2. Oke OE, Wheto M, Uyanga VA, et al. Embryonic Development and Early Juvenile Growth of Nigerian Local Chickens in Crosses with Exotic Broiler Breeder under Humid Tropical Conditions. Asian Journal of Animal Sciences. 2021; 15(2): 60-66. doi: 10.3923/ajas.2021.60.66
3. Assan N. Growth, carcass and meat performance in goat and sheep breeds their crosses. Scientific Journal of Pure and Applied Sciences. 2020; 9(7): 936-944. doi: 10.14196/sjpas. v9i7.478
4. Dekkers JCM. Multiple trait breeding programs with genotype-by-environment interactions based on reaction norms, with application to genetic improvement of disease resilience. Genetics Selection Evolution. 2021; 53(1). doi: 10.1186/s12711-021-00687-2
5. Guijarro-Clarke C, Holland PWH, Paps J. Widespread patterns of gene loss in the evolution of the animal kingdom. Nature Ecology & Evolution. 2020; 4(4): 519-523. doi: 10.1038/s41559-020-1129-2
6. Assan N. It’s time for reimagining the future of food security in sub–Saharan Africa: Gender-Smallholder Agriculture-Climate Change nexus. Trends Journal of Sciences Research. 2022; 1(1): 76-85. doi: 10.31586/ujfs.2022.504
7. Osei-Amponsah R, Asem EK, Obese FY. Cattle crossbreeding for sustainable milk production in the tropics. International Journal of Livestock Production. 2020; 11(4): 108-113. doi: 10.5897/ijlp2020.0717
8. Moav R. Specialised sire and dam lines. I. Economic evaluation of crossbreds. Animal Science. 1966; 8(2): 193-202. doi: 10.1017/S0003356100034577
9. Marchioretto PV, Rabel RAC, Allen CA, et al. Development of genetically improved tropical-adapted dairy cattle. Animal Frontiers. 2023; 13(5): 7. doi: 10.1093/af/vfad050.
10. Bhuiyan AKFH, Shahjalal M, Islam MN, et al. Characterization, conservation and improvement of Red Chittagong Cattle of Bangladesh. Bangladesh Agricultural University Research System; 2005.
11. Paiva SR, McManus CM, Blackburn H. Conservation of animal genetic resources – A new tact. Livestock Science. 2016; 193: 32-38. doi: 10.1016/j.livsci.2016.09.010
12. Sonaiya EB, Swan ESJ. Small scale poultry production technical guide. Animal Production and Health; 2004.
13. Labroo MR, Studer AJ, Rutkoski JE. Heterosis and Hybrid Crop Breeding: A Multidisciplinary Review. Frontiers in Genetics. 2021; 12. doi: 10.3389/fgene.2021.643761
14. Wu XL, Zhao S. Editorial: Advances in Genomics of Crossbred Farm Animals. Frontiers in Genetics. 2021; 12. doi: 10.3389/fgene.2021.709483
15. FAO. Partnership for Safe Poultry in Kenya (PSPK) Program: Value Chain Analysis of Poultry in Ethiopia. Winrock International; 2010.
16. AU-IBAR. The Livestock Development Strategy for Africa 2015–2035. African Union–Inter-African Bureau for Animal Resources (AU-IBAR); 2016.
17. Panel MM. Meat, Milk and More: Policy Innovations to Shepherd Inclusive and Sustainable Livestock Systems in Africa. International Food Policy Research Institute; 2020. doi: 10.2499/9780896293861
18. Aryee SND, Osei-Amponsah R, Adjei OD, et al. Production practices of local pig farmers in Ghana. Int J Livest Prod. 2019; 10(6): 175–81. doi: 10.5897/ijlp2019.0583
19. Rewe TO, Herold P, Kahi AK, et al. Breeding Indigenous Cattle Genetic Resources for Beef Production in Sub-Saharan Africa. Outlook on Agriculture. 2009; 38(4): 317-326. doi: 10.5367/000000009790422205
20. Ibeagha-Awemu EM, Jann OC, Weimann C, et al. Genetic diversity, introgression and relationships among West/Central African cattle breeds. Genetics Selection Evolution. 2004; 36(6). doi: 10.1186/1297-9686-36-6-673
21. Guèye EF. The Role of Family Poultry in Poverty Alleviation, Food Security and the Promotion of Gender Equality in Rural Africa. Outlook on Agriculture. 2000; 29(2): 129-136. doi: 10.5367/000000000101293130
22. Mack S, Hoffmann D, Otte J. The contribution of poultry to rural development. World’s Poultry Science Journal. 2005; 61(1): 7-14. doi: 10.1079/wps200436
23. Akinola LAF, Essien A. Relevance of rural poultry production in developing countries with special reference to Africa. World’s Poultry Science Journal. 2011; 67(4): 697-705. doi: 10.1017/s0043933911000778
24. Alders RG, Pym RAE. Village poultry: still important to millions, eight thousand years after domestication. World’s Poultry Science Journal. 2009; 65(2): 181-190. doi: 10.1017/s0043933909000117
25. Alders RG, Dumas SE, Rukambile E, et al. Family poultry: Multiple roles, systems, challenges, and options for sustainable contributions to household nutrition security through a planetary health lens. Maternal & Child Nutrition. 2018; 14(S3). doi: 10.1111/mcn.12668
26. Capote J. Introductory chapter: Goats in arid and mountain areas. In: Sustainable Goat Production in Adverse Environments: Volume II: Local Goat Breeds. Springer Cham; 2017.
27. Skapetas B, Bampidis V. Goat Production in the World: Present Situation and Trends. Livestock Research for Rural Development. 2016; 28(11): 7.
28. Lebbie SHB. Goats under household conditions. Small Ruminant Research. 2004; 51(2): 131-136. doi: 10.1016/j.smallrumres.2003.08.015
29. FAO. Domestic Animal Diversity Information System (DAD-IS). FAO; 2017.
30. Aziz M. Present status of the world goat populations and their productivity. Lohmann Inform. 2014; 45(2): 42-52.
31. Dubeuf JP, Morand-Fehr P, Rubino R. Situation, changes and future of goat industry around the world. Small Ruminant Research. 2004; 51(2): 165-173. doi: 10.1016/j.smallrumres.2003.08.007
32. Wu Q, Zhao Z. Inhibition of PAI-1: a new anti-thrombotic approach. Current Drug Targets-Cardiovascular & Hematological Disorders. 2002; 2(1): 27-42.
33. Wei M, Van der Steen HAM, Van der Werf JHJ, et al. Relationship between purebred and crossbred parameters. Journal of Animal Breeding and Genetics. 1991; 108(1-6): 253-261. doi: 10.1111/j.1439-0388. 1991.tb00183.x
34. Bijma P, Bastiaansen JW. Standard error of the genetic correlation: how much data do we need to estimate a purebred-crossbred genetic correlation? Genetics Selection Evolution. 2014; 46(1). doi: 10.1186/s12711-014-0079-z
35. Dekkers JCM. Marker-assisted selection for commercial crossbred performance1. Journal of Animal Science. 2007; 85(9): 2104-2114. doi: 10.2527/jas.2006-683
36. Sørensen MK, Norberg E, Pedersen J, et al. Invited Review: Crossbreeding in Dairy Cattle: A Danish Perspective. Journal of Dairy Science. 2008; 91(11): 4116-4128. doi: 10.3168/jds.2008-1273
37. Falconer DS, Mackay TFC. Introduction to Quantitative Genetics, 4th ed. Pearson Education Limited; 1996.
38. Mäki-Tanila A. An overview on quantitative and genomic tools for utilising dominance genetic variation in improving animal production. Agricultural and Food Science. 2008; 16(2): 188. doi: 10.2137/145960607782219337
39. Tesema Z, Taye M, Kebede D. Current status of livestock crossbreeding in Ethiopia: Implications for research and extension Journal of Applied Animal Science. 2020; 13: 2.
40. Vance ER, Ferris CP, Elliott CT, et al. Comparison of the performance of Holstein-Friesian and Jersey × Holstein-Friesian crossbred dairy cows within three contrasting grassland-based systems of milk production. Livestock Science. 2013; 151: 66–79. doi: 10.1016/j.livsci.2012.10.011
41. Schultz B, Serão N, Ross JW. Genetic improvement of livestock, from conventional breeding to biotechnological approaches. Animal Agriculture. Published online 2020: 393-405. doi: 10.1016/b978-0-12-817052-6.00023-9
42. Mapiye C, Mwale M, Mupangwa JF, et al. A Research Review of Village Chicken Production Constraints and Opportunities in Zimbabwe. Asian-Australasian Journal of Animal Sciences. 2008; 21(11): 1680-1688. doi: 10.5713/ajas.2008. r.07
43. Wondmeneh E. Genetic improvement in indigenous chicken of Ethiopia [PhD thesis]. Wageningen University; 2015.
44. Islam MA, Nishibori M. Crossbred Chicken for Poultry Production in the Tropics. The Journal of Poultry Science. 2010; 47(4): 271-279. doi: 10.2141/jpsa.010033
45. Mekki D, Youif M, Abdel R, Musa. Growth performance of indigenous x exotic crosses of chicken and evaluation of general and specific combining ability under Sudan condition. International Journal of Poultry Science. 2005; 4: 468-471.
46. Mtileni BJ, Muchadeyi FC, Maiwashe A, et al. Characterisation of production systems for indigenous chicken genetic resources of South Africa Appl. Animal husbandry Programs for Rural Development. 2009; 2: 18-22.
47. Springbett A, MacKenzie K, Woolliams J, Bishop S. The contribution of genetic diversity to the spread of infectious diseases in livestock populations. Genetics. 2003; 165: 1465-1474. doi: 10.1093/genetics/165.3.1465
48. Mpenda FN, Schilling MA, Campbell Z, et al. The genetic diversity of local African chickens: A potential for selection of chickens resistant to viral infections. Journal of Applied Poultry Research. 2019; 28(1): 1-12. doi: 10.3382/japr/pfy063
49. Msoffe P, Mtambo M, Minga U, et al. Productivity and natural disease resistance potential of free ranging local chicken ecotypes in Tanzania. Livestock Research for Rural Development. 2002; 14.
50. Lyimo C, Weigend A, Janßen-Tapken U, et al. Assessing the genetic diversity of five Tanzanian chicken ecotypes using molecular tools. South African Journal of Animal Science. 2014; 43(4): 499. doi: 10.4314/sajas. v43i4.7
51. Mohammed MD, Abdalsalam YI, Kheir AM. Comparison of the egg characteristics of different Sudanese indigenous chicken types. International Journal of Poultry Science. 2015; 4, 455-457.
52. Duguma R. Phenotypic characterization of some indigenous chicken ecotypes of Ethiopia. Livestock Research for Rural Development. 2006; 18: 21-25.
53. Badubi S, Rakereng M, Marumo M. Morphological characteristics and feed resources available for indigenous chickens in Botswana. Livestock Research for Rural Development. 2006; 18: 205-211.
54. Adekoya K. Morphological characterization of five Nigerian indigenous chicken types. Journal of Scientific Research and Development. 2013; 14: 55-56.
55. Dahloum L, Moula N, Halbouche M, et al. Phenotypic characterization of the indigenous chickens (Gallus gallus) in the northwest of Algeria. Archives Animal Breeding. 2016; 59(1): 79-90. doi: 10.5194/aab-59-79-2016
56. Assan N. Opportunities and Challenges in Use of Imported Livestock than Utilization of Local Animal Genetic Resources in Zimbabwe: A Review. Journal of Animal Production Advances. 2013; 3(4). doi: 10.5455/japa.20130411110239
57. Khawaja T, Khan SH, Mukhtar N, Parveen A. Comparative study of growth performance, meat quality and haematological parameters of Fayoumi, Rhode Island Red and their reciprocal crossbred chickens. Italian Journal of Animal Science. 2012; 11(2). doi: 10.4081/ijas.2012.e39
58. Kgwatalala PM, Segokgo P. Growth Performance of Australorp x Tswana Crossbred Chickens under an Intensive Management System. International Journal of Poultry Science. 2013; 12(6): 358-361. doi: 10.3923/ijps.2013.358.361
59. Hailu A, Kyallo M, Yohannes T, et al. Genetic Diversity and Population Structure of Indigenous Chicken Ecotypes (Gallus gallus domesticus) in Ethiopia using LEI0258 Microsatellite. International Journal of Poultry Science. 2020; 19(3): 102-110. doi: 10.3923/ijps.2020.102.110
60. Habimana R, Ngeno K, Mahoro J, et al. Morphobiometrical characteristics of indigenous chicken ecotype populations in Rwanda. Tropical Animal Health and Production. 2020; 53(1). doi: 10.1007/s11250-020-02475-4
61. Padhi MK, Chatterjee RN, Rajkumar U. A study on performance of a crossbred chicken developed using both exotic and indigenous breeds under backyard system of rearing. Poultry Science. 2014; 2(2): 26-29.
62. Amao SR. Effect of crossing Fulani ecotype with Rhode Island chicken on growth performance and reproductive traits in southern guinea savanna region of Nigeria. American Journal of Animal and Veterinary Sciences. 2017; 4(2): 14-18.
63. Fisinin VI, Kavtarashvili AS. Heat stress in poultry. II methods and techniques for prevention and alleviation (review). Sel’skokhozyaistvennaya Biologiya. 2015; 50: 431–43. doi: 10.15389/agrobiology.2015.4.431eng
64. Dong J, He C, Wang Z, et al. A novel deletion in KRT75L4 mediates the frizzle trait in a Chinese indigenous chicken. Genetics Selection Evolution. 2018; 50(1). doi: 10.1186/s12711-018-0441-7
65. Yunis R, Cahaner A. The effects of the naked neck (Na) and frizzle (F) genes on growth and meat yield of broilers and their interactions with ambient temperatures and potential growth rate. Poultry Science. 1999; 78(10): 1347-1352. doi: 10.1093/ps/78.10.1347
66. Lin H, Jiao HC, Buyse J, et al. Strategies for preventing heat stress in poultry. World’s Poultry Science Journal. 2006; 62(1): 71-86. doi: 10.1079/wps200585
67. Raju MVLN, Shyam Sunder G, Chawak MM, et al. Response of naked neck (Nana) and normal (nana) broiler chickens to dietary energy levels in a subtropical climate. British Poultry Science. 2004; 45(2): 186-193. doi: 10.1080/00071660410001715786
68. Darwin CR. The Variation of Animals and Plants Under Domestication, 1st ed. John Murray; 1868.
69. Duah KK, Essuman EK, Boadu VG, et al. Comparative study of indigenous chickens on the basis of their health and performance. Poultry Science. 2020; 99(4): 2286-2292. doi: 10.1016/j.psj.2019.11.049
70. Oyeniran VJ, Iyasere OS, Durosaro SO, et al. An exploratory study on differences in maternal care between two ecotypes of Nigerian indigenous chicken hens. Frontiers in Veterinary Science. 2022; 9. doi: 10.3389/fvets.2022.980609
71. Mothibedi K, Nsoso S, Waugh E, et al. Growth Performance of Purebred Naked Neck Tswana and Black Australorp x Naked Neck Tswana Crossbred Chickens under an Intensive Management System in Botswana. International Journal of Livestock Research. 2016; 6(8): 6. doi: 10.5455/ijlr.20160608010644
72. Magothe TM, Muhuyi WB, Kahi AK. Influence of major genes for crested-head, frizzle-feather and naked-neck on body weights and growth patterns of indigenous chickens reared intensively in Kenya. Tropical Animal Health and Production. 2009; 42(2): 173-183. doi: 10.1007/s11250-009-9403-y
73. Ssewannyana E, Onyait AO, Ogwal OkoTJ, Masaba J. Strategies for improving the meat and egg productivity of indigenous chickens in Kumi and Apac districts, Uganda. Uganda Journal of Agricultural Sciences. 2006; 12: 31-35.
74. Kadigi HJS, Phoya RKDN, Safalaoh A. Comparative performance of Black Australorp, Malawian local chicken and their f1 crossbred roasters. Indian Journal of Animal Science. 1998; 68: 366-367.
75. FAO. The Second Report on The State of the World’s Animal Genetic Resources for Food and Agriculture. In: Commission on Genetic Resources for Food and Agriculture Assessments. FAO; 2015.
76. Mwacharo J, Otieno C, Okeyo MA. Suitability of Blood Protein Polymorphisms in Assessing Genetic Diversity in Indigenous Sheep in Kenya. In: Applications of Gene-Based Technologies for Improving Animal Production and Health in Developing Countries. Springer; 2005.
77. Amao SR. Growth performance traits of meat-type chicken progenies from a broiler line sire and Nigerian indigenous chickens’ dams reared in southern guinea savanna condition of Nigeria. License This work is licensed under a Creative Commons Attribution 4.0 International License. 2020; 56(289): 66-73.
78. Adedeji TA, Amusan SA, Adebambo OA. Effect of chicken genotype on growth performance of pure and cross red progenies in the development of a broiler line. International Journal of Agriculture Innovations and Research. 2015; 4(1): 134-138.
79. Adeleke MA, Peters SO, Ozoje MO, et al. Genetic parameter estimates for body weight and linear body measurements in pure and crossbred progenies of Nigerian indigenous chickens. Livestock research for rural development. 2011; 23(1): 1-7.
80. Amao SR, Zalia IL, Oluwagbemiga KS. Effects of crossbred sires of normal feather Rhode Island Red on different dams of Nigerian indigenous chickens for fertility, hatchability and early growth performance. Discovery Agriculture. 2019; 5: 119-126.
81. Szalay IT, Phuong TNL, Barta I, et al. Conservation Aspects of Meat Producing Ability and Heterosis in Crosses of Two Natively Different Local Hungarian Chicken Breeds. International Journal of Poultry Science. 2016; 15(11): 442-447. doi: 10.3923/ijps.2016.442.447
82. Abebe KB. A review of the potential and constraints for crossbreeding as a basis for goat production by smallholder farmers in Ethiopia. Bulletin of the National Research Centre. 2022; 46(1). doi: 10.1186/s42269-022-00763-7
83. Wilson RT. Crossbreeding of Cattle in Africa. Journal of Agriculture and Environmental Sciences. 2018; 6(1). doi: 10.15640/jaes. v7n1a3
84. Ryan SM, Unruh JA, Corrigan ME, et al. Effects of concentrate level on carcass traits of Boer crossbred goats. Small Ruminant Research. 2007; 73(1-3): 67-76. doi: 10.1016/j.smallrumres.2006.11.004
85. Monau P, Raphaka K, Zvinorova-Chimboza P, et al. Sustainable Utilization of Indigenous Goats in Southern Africa. Diversity. 2020; 12(1): 20. doi: 10.3390/d12010020
86. Haas JH. Growth of Boer goat crosses in comparison with indigenous East African goats in Kenya. Tropnlandwirt. 1978; 79: 7-12.
87. Luo JT, Sahlu TC, Ameron M, Goetsch AL. Growth of Spanish, Boer × Angora, and Boer × Spanish goat kids fed milk replacer. Small Ruminant Research. 2000; 36: 189-194.
88. Merlos-Brito MI, Martínez-Rojero RD, Torres-Hernández G, et al. Evaluation of productive traits in Boer× local, Nubian× local and local kids in the dry tropic of Guerrero, Mexico. Veterinaria México. 2008; 39(3): 323-333.
89. Jiabi P, Taiyong C, Jiyum G, et al. Effects on crossbreeding Boer goat with local goats in China. Book of Abstracts of the 8th International Conference on Goats. 2004; 11: 17.
90. Waldron DF, Willingham TD, Thomson PV. Reproduction performance of Boer-cross and Spanish goat. Journal of Animal Science. 1997; 75(1): 138.
91. Rhone JA. Estimation of reproductive, production, and progeny growth differences among F1 Boer-Spanish and Spanish females [Master’s thesis]. Texas A&M University; 2005.
92. Kassahun A, Yibra Y, Fletcher I. Productivity of purebred Adal and quarterbred Saanen * Adal goats in Ethiopia. In: African Small Ruminant Research and Development. International Livestock Centr for Africa; 1989.
93. Wilson RT. Reproductive performance of African indigenous small ruminants under various management systems: A review. Animal Reproduction Science. 1989; 20: 265–286.
94. Asizua D, Mpairwe D, Kabi F, et al. Performance of grazing and supplemented Mubende goats and their crossbreds with Boer. In: Proceedings of the 5th All Africa Conference on Animal Agriculture and the 18th Meeting of the Ethiopian Society of Animal Production (ESAP 2010), 2010.
95. VanRaden PM, Tooker ME, Chud TCS, et al. Genomic predictions for crossbred dairy cattle. Journal of Dairy Science. 2020; 103(2): 1620-1631. doi: 10.3168/jds.2019-16634
96. Roschinsky R, Kluszczynska M, Sölkner J, et al. Smallholder experiences with dairy cattle crossbreeding in the tropics: from introduction to impact. Animal. 2015; 9(1): 150-157. doi: 10.1017/s1751731114002079
97. Tadesse M, Dessie T. Milk production performance of Zebu, Holstein Friesian and their crosses in Ethiopia. Livestock Research for Rural Devel; 2003.
98. Wilson RT. Fit for purpose – the right animal in the right place. Tropical Animal Health and Production. 2008; 41(7): 1081-1090. doi: 10.1007/s11250-008-9274-7
99. McDowell RE, Wilk JC, Talbott CW. Economic viability of crosses of Bos taurus and Bos indicus for dairying in warm climates. Journal of Dairy Science. 1996; 79: 1292–1303.
100. Abdulai A, Huffman WE. The Diffusion of New Agricultural Technologies: The Case of Crossbred‐Cow Technology in Tanzania. American Journal of Agricultural Economics. 2005; 87(3): 645-659. doi: 10.1111/j.1467-8276.2005. 00753.x
101. Mohamed A, Van Der WJ, Javed K. Crossbreeding effect on Frisian, Jersey and Sahiwal crosses in Pakistan. Pakistan Veterinary Journal. 2001; 21(4): 2001.
102. Osei-Amponsah R, Chauhan SS, Leury BJ, et al. Genetic Selection for Thermotolerance in Ruminants. Animals. 2019; 9(11): 948. doi: 10.3390/ani9110948
103. Abegaz SB. Milk production status and associated factors among indigenous dairy cows in Raya Kobo district, north eastern Ethiopia. Veterinary Medicine and Science 2022; 8(2):852-863. doi: 10.1002/vms3.740.
104. Aboagye GS. Phenotypic and Genetic Parameters in Cattle populations in Ghana. In: Readings on some key issues in Animal Science in Ghana. University of Ghana; 2014
105. Muller C. Crossing the Line: Opinion-Challenge the status quo. The Dairy Mail. 2014; 21(3): 9-15.
106. Leroy G, Baumung R, Boettcher P, et al. Review: Sustainability of crossbreeding in developing countries; definitely not like crossing a meadow. Cambridge University Press. 2016; 10(2): 262–273.
107. Gandini G, Oldenbroek K. Strategies for moving from conservation to utilisation. Utilisation and Conversation of Farm Animal Genetic Resources. Wageningen Academic Publishers; 2007.
108. Hall SJG, Bradley DG. Conserving livestock breed biodiversity. Trends in Ecology & Evolution. 1995; 10: 267–270.
109. Rege JEO, Gibson JP. Animal genetic resources and economic development: Issues in relation to economic valuation. Ecological Economics. 2003; 45(3): 319-330.
110. Otten D, Van den Weghe HF. The sustainability of intensive livestock areas (ILAS): Network system and conflict potential from the perspective of animal farmers. International Journal on Food System Dynamics. 2011; 2: 36-51.
111. Philipsson J, Rege JEO, Zonabend E, Okeyo AM. Sustainable breeding programmes for tropical farming systems. In: Animal Genetics Training Resource. International Livestockn Research Institute; 2011.
112. ZoBell D, Chapman CK. Applying principles of crossbreeding. March 2010 Cooperative Extension Service, Utah State University. (AG/Beef/2004-04), 2010.
113. Madalena FE, Peixoto MGCD, Gibson J. Dairy cattle genetics and its applications in Brazil. Livestock Research for Rural Development. 2012; 24: 97.
114. Kosgey IS. Breeding objectives and breeding strategies of small ruminants in tropics [PhD thesis]. Wageningen University; 2004.
115. Stange M, Barrett RDH, Hendry AP. The importance of genomic variation for biodiversity, ecosystems and people. Nature Reviews Genetics. 2020; 22(2): 89-105. doi: 10.1038/s41576-020-00288-7
116. Falconer DS. The Problem of Environment and Selection. The American Naturalist. 1952; 86(830): 293-298. doi: 10.1086/281736
117. Toro-Ospina AM, Faria RA, Dominguez-Castaño P, et al. Genotype–environment interaction for milk production of Gyr cattle in Brazil and Colombia. Genes & Genomics. 2022; 45(2): 135-143. doi: 10.1007/s13258-022-01273-6
118. Murani E, Gilbert H, Rauw WM. Editorial: Genotype-by-environment interaction in farm animals: from measuring to understanding. Frontiers. Genetics. 2023; 14: 1267334. doi: 10.3389/fgene.2023.1267334
119. Darwin C. The variation of animals and plants under domestication. The American Naturalist. 1868; 2(4): 208-209. doi: 10.1086/270222
120. Burrow HM. Importance of adaptation and genotype × environment interactions in tropical beef breeding systems. Animal. 2012; 6(5): 729-740. doi: 10.1017/s175173111200002x
121. Thomasen JR, Egger-Danner C, Willam A, et al. Genomic selection strategies in a small dairy cattle population evaluated for genetic gain and profit. Journal of Dairy Science. 2014; 97(1): 458-470. doi: 10.3168/jds.2013-6599
122. Wurzinger M, Gutiérrez GA, Sölkner J, et al. Community-Based Livestock Breeding: Coordinated Action or Relational Process? Frontiers in Veterinary Science. 2021; 8. doi: 10.3389/fvets.2021.613505
123. Kaumbata W, Nakimbugwe H, Haile A, et al. Scaling up community-based goat breeding programmes via multi-stakeholder collaboration. Universität Kassel; 2020.
124. Mueller J, Haile A, Getachew T, et al. Going to scale—From community-based to population-wide genetic improvement and commercialized sheep meat supply in Ethiopia. Frontiers in Genetics. 2023; 14. doi: 10.3389/fgene.2023.1114381
125. Pilling D, B´elanger J, Diulgheroff S, et al. Global status of genetic resources for food and agriculture: challenges and research needs. Genetic Resources. 2020; 1(1): 4-16. doi: 10.46265/ genresj.2020.1.4-16
126. Haile A, Wurzinger M, Mueller J, et al. Guidelines for Setting up community-based small ruminants breeding programs in Ethiopia, 2nd ed. ICARDA; 2018.
127. Muller CL. Unlock hybrid power and increase production with crossbreeding. Stockfarm. 2021; 11(11): 42-43.
128. Haile TA, Heidecker T, Wright D, et al. Genomic selection for lentil breeding: Empirical evidence. The Plant Genome. 2020; 13(1). doi: 10.1002/tpg2.20002
129. Endris M, Kebede K, Abebe A. Challenges of community based small ruminant breeding program: A review. Available online: http://www.gjasr.com/index.php/GJASR/article/view/142 (accessed on 2 November 2023).
130. Ahuya CO, Okeyo AM, Murithi FM. Productivity of crossbred goats under smallholder production system in the Eastern highlands of Kenya. Animal Science Journal. 2003; 76: 284.
131. Kahi AK, Rewe TO, Kosgey IS. Sustainable Community-Based Organizations for the Genetic Improvement of Livestock in Developing Countries. Outlook on Agriculture. 2005; 34(4): 261-270. doi: 10.5367/000000005775454706
132. Peacock C. Dairy goat development in East Africa: A replicable model for smallholders? Small Ruminant Research. 2008; 77(2-3): 225-238. doi: 10.1016/j.smallrumres.2008.03.005
133. Gutu Z, Haile A, Rischkowsky BA, et al. Evaluation of community-based sheep breeding programs in Ethiopia. 2015.
134. Haile A, Wurzinger M, Mueller J, et al. Guidelines for Setting up community-based small ruminants breeding programs in Ethiopia, 2nd ed. Beirut, Lebanon: ICARDA; 2018.
135. Mueller JP, Rischkowsky B, Haile A, et al. Community‐based livestock breeding programmes: essentials and examples. Journal of Animal Breeding and Genetics. 2015; 132(2): 155-168. doi: 10.1111/jbg.12136
136. Haile A, Getachew T, Mirkena T, et al. Community-based sheep breeding programs generated substantial genetic gains and socioeconomic benefits. Animal. 2020; 14(7): 1362-1370. doi: 10.1017/s1751731120000269
137. Abate Z, Kirmani M, Getachew T, Haile A. Growth, reproductive performance and survival rate of Bonga sheep and their crossbreds in Southern Ethiopia. Livestock Research for Rural Development. 2020; 32(9): 1-10.
138. Sartas M, Kangethe E, Dror I. Complete scaling readiness study of tropical poultry genetic solutions strategy in Ethiopia, Tanzania and Nigeria. International Livestock Research Institute; 2021.
139. Culver KW, Labow MA. Genomics. Macmillan Science Library; 2002.
140. Stock J, Bennewitz J, Hinrichs D, et al. A Review of Genomic Models for the Analysis of Livestock Crossbred Data. Frontiers in Genetics. 2020; 11. doi: 10.3389/fgene.2020.00568
141. Li Z, Wu XL, Guo W, et al. Estimation of genomic breed composition of individual animals in composite beef cattle. Animal Genetics. 2020; 51(3): 457-460. doi: 10.1111/age.12928
142. Wang Y, Wu XL, Li Z, et al. Estimation of Genomic Breed Composition for Purebred and Crossbred Animals Using Sparsely Regularized Admixture Models. Frontiers in Genetics. 2020; 11. doi: 10.3389/fgene.2020.00576
143. Rexroad C, Vallet J, Matukumalli LK, et al. Genome to Phenome: Improving Animal Health, Production, and Well-Being – A New USDA Blueprint for Animal Genome Research 2018–2027. Frontiers in Genetics. 2019; 10. doi: 10.3389/fgene.2019.00327
144. Aryee SND, Owusu-Adjei D, Osei-Amponsah R, et al. Sustainable genomic research for food security in sub-Saharan Africa. Agriculture & Food Security. 2021; 10(1). doi: 10.1186/s40066-021-00287-9
145. Wu XL, Zhao SH. Advances in Genomics of Crossbred Farm Animals. Frontiers Media SA; 2021. doi: 10.3389/978-2-88971-357-8
146. Qanbari S, Simianer H. Mapping signatures of positive selection in the genome of livestock. Livestock Science. 2014; 166: 133-143. doi: 10.1016/j.livsci.2014.05.003
147. Ibanez-Escriche N, Simianer H. From the Editors: Animal breeding in the genomics era. Animal Frontiers. 2016; 6(1): 4-5. doi: 10.2527/af.2016-0001
148. Marshall K, Gibson JP, Mwai O, et al. Livestock Genomics for Developing Countries – African Examples in Practice. Frontiers in Genetics. 2019; 10. doi: 10.3389/fgene.2019.00297
149. Singh PK, Singh P, Singh RP, Singh RL. From gene to genomics: tools for improvement of animals. In: Advances in Animal Genomics. Academic Press; 2021.
150. Gouveia JJ de S, Silva MVGB da, Paiva SR, et al. Identification of selection signatures in livestock species. Genetics and Molecular Biology. 2014; 37(2): 330-342. doi: 10.1590/s1415-47572014000300004
151. Huson HJ, Kim ES, Godfrey RW, et al. Genome-wide association study and ancestral origins of the slick-hair coat in tropically adapted cattle. Frontiers in Genetics. 2014; 5. doi: 10.3389/fgene.2014.00101
152. Somavilla AL. Prediction of genomic-enabled breeding values and genome-wide association study for feedlot average daily weight gain in Nelore cattle.
153. Joost HG, Schürmann A. The genetic basis of obesity-associated type 2 diabetes (diabesity) in polygenic mouse models. Mammalian Genome. 2014; 25(9-10): 401-412. doi: 10.1007/s00335-014-9514-2
154. Reshma RS, Das DN. Molecular markers and its application in animal breeding. In: Advances in Animal Genomics. Academic Press; 2021.
155. Wray-Cahen D, Bodnar A, Rexroad C, et al. Advancing genome editing to improve the sustainability and resiliency of animal agriculture. CABI Agriculture and Bioscience. 2022; 3(1). doi: 10.1186/s43170-022-00091-w
156. van Marle-Köster E, Visser C. Genetic Improvement in South African Livestock: Can Genomics Bridge the Gap Between the Developed and Developing Sectors? Frontiers in Genetics. 2018; 9. doi: 10.3389/fgene.2018.00331
157. Houle D, Govindaraju DR, Omholt S. Phenomics: the next challenge. Nature Reviews Genetics. 2010; 11(12): 855-866. doi: 10.1038/nrg2897
158. Zhao C, Zhang Y, Du J, et al. Crop Phenomics: Current Status and Perspectives. Frontiers in Plant Science. 2019; 10. doi: 10.3389/fpls.2019.00714
159. Jannink JL, Lorenz AJ, Iwata H. Genomic selection in plant breeding: from theory to practice. Briefings in Functional Genomics. 2010; 9(2): 166-177. doi: 10.1093/bfgp/elq001
160. Araus JL, Cairns JE. Field high-throughput phenotyping: the new crop breeding frontier. Trends in Plant Science. 2014; 19(1): 52-61. doi: 10.1016/j.tplants.2013.09.008
161. Steibel JP. Henomics in Animal Breeding. In: Zhang Q (editor). Encyclopedia of Smart Agriculture Technologies. Springer, Cham; 2023.
162. Pérez-Enciso M, Steibel JP. Phenomes: the current frontier in animal breeding. Genetics Selection Evolution. 2021; 53(1). doi: 10.1186/s12711-021-00618-1
163. de Vienne D, Coton C, Dillmann C. The genotype–phenotype relationship and evolutionary genetics in the light of the Metabolic Control Analysis. Biosystems. 2023; 232: 105000. doi: 10.1016/j.biosystems.2023.105000
164. Jangra S, Chaudhary V, Yadav RC, et al. High-Throughput Phenotyping: A Platform to Accelerate Crop Improvement. Phenomics. 2021; 1: 31–53. doi: 10.1007/s43657-020-00007-6
165. Spangler ML. Animal Breeding and Genetics: Introduction. In: Spangler ML (editor). Animal Breeding and Genetics. Encyclopedia of Sustainability Science and Technology Series. Springer; 2023.
166. Baes C, Schenkel F. The Future of Phenomics. Animal Frontiers. 2020; 10(2): 4-5. doi: 10.1093/af/vfaa013
167. Yang Y, Saand MA, Huang L, et al. Applications of Multi-Omics Technologies for Crop Improvement. Frontiers in Plant Science. 2021; 12. doi: 10.3389/fpls.2021.563953
168. Chakraborty D, Sharma N, Kour S, et al. Applications of Omics Technology for Livestock Selection and Improvement. Frontiers in Genetics. 2022; 13. doi: 10.3389/fgene.2022.774113
169. Hamdi Y, Zass L, Othman H, et al. Human OMICs and Computational Biology Research in Africa: Current Challenges and Prospects. OMICS: A Journal of Integrative Biology. 2021; 25(4): 213-233. doi: 10.1089/omi.2021.0004
170. Kim SW, Yuen AHL, Poon CTC, et al. Cross-sectional anatomy, computed tomography, and magnetic resonance imaging of the banded houndshark (Triakis scyllium). Scientific Reports. 2021; 11(1). doi: 10.1038/s41598-020-80823-y
Refbacks
- There are currently no refbacks.
Copyright (c) 2024 Never Assan, Enock Muteyo, Edmore Masama, Takudzwa Mafigu, Tinashe Mujati
License URL: https://creativecommons.org/licenses/by/4.0/
This site is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Prof. Zhengjun Qiu
Zhejiang University, China
Cheng Sun
Academician of World Academy of Productivity Science; Executive Chairman, World Confederation of Productivity Science China Chapter, China
Processing Speed (2023)
-
-
-
- <7 days: submission to initial review decision;
-
- 41 days: received to accepted
- 56 days: received to online
-
-
Modern agricultural technology is evolving rapidly, with scientists collaborating with leading agricultural enterprises to develop intelligent management practices. These practices utilize advanced systems that provide tailored fertilization and treatment options for large-scale land management.
This journal values human initiative and intelligence, and the employment of AI technologies to write papers that replace the human mind is expressly prohibited. When there is a suspicious submission that uses AI tools to quickly piece together and generate research results, the editorial board of the journal will reject the article, and all journals under the publisher's umbrella will prohibit all authors from submitting their articles.
Readers and authors are asked to exercise caution and strictly adhere to the journal's policy regarding the usage of Artificial Intelligence Generated Content (AIGC) tools.
Asia Pacific Academy of Science Pte. Ltd. (APACSCI) specializes in international journal publishing. APACSCI adopts the open access publishing model and provides an important communication bridge for academic groups whose interest fields include engineering, technology, medicine, computer, mathematics, agriculture and forestry, and environment.