Promoting Sustainable Utilization and Genetic Improvement of Indonesian Local Beef Cattle Breeds: A Review
Abstract
:1. Introduction
2. Indonesian Beef Production and Marketing Systems
3. The Need for Cattle That Are Well Adapted to Tropical Beef Production Systems
- Bos taurus (British/European breeds that evolved in cooler British and European climates, e.g., Angus, Hereford/Limousin, Simmental);
- Bos indicus (breeds that evolved on the Indian sub-continent, e.g., Ongole, Brahman, Nelore);
- Tropically adapted taurine breeds (southern African Sanga, e.g., Afrikaner, Mashona; West African humpless, e.g., N’dama; and Criollo breeds of Latin America and the Caribbean, e.g., Romosinuano);
- Tropically adapted Bos indicus × Bos taurus composite breeds (e.g., Santa Gertrudis, Braford, Charbray);
- Tropically adapted taurine × British/Continental composite breeds (e.g., Bonsmara, Belmont Red, Senepol);
- East African zebu breeds (e.g., Boran); and
- The first cross (F1) between Bos indicus and Bos taurus, which has attributes that are different from other breed types, particularly in harsher environments.
4. Indonesian Cattle Breeds
4.1. Bali Cattle (Bos javanicus)
4.2. Ongole Grade Cattle (PO)
4.3. Madura Cattle
4.4. Challenges to Improving These Indonesian Cattle Breeds
5. Achieving Genetic Improvement by Crossbreeding
- Generation of direct heterosis or hybrid vigor, measured as the extra performance of the crossbreds relative to their parental breeds. The percentage increase in performance ranges from 0–10% for growth traits and 5–25% for fertility traits [64], but the effect of heterosis on the total production system can be greater than this, as effects accumulate over traits e.g., [65]:
- The averaging of breed effects, to breed an animal of intermediate size to fit a particular management cycle or market demand and could involve either regular systems of crossing or the creation of composite breeds e.g., [65];
- Maternal heterosis where crossbred cows exhibit considerable heterosis in their ability to rear fast-growing, viable offspring;
- Sire-dam complementation, where the crossbreeding system aims to use breeding cows of small to intermediate mature size (though not so small for dystocia to be a problem) as well as being fertile. When a large terminal sire breed is used over a smaller dam, the proportion of available feed directed to growing animals is increased for the benefit of the entire production system, particularly where breeding occurs through AI; and
- Breed complementarity whereby breeds used for the crossbreeding program are specifically selected so the strengths of one breed are used to complement or mask the weaknesses of another breed.
The Value of Crossbreeding to Genetically Improve Indonesia’s Cattle Herds
6. Achieving Genetic Improvement by Within-Breed Selection
6.1. Developing Breeding Objectives for Indonesia’s Cattle Smallholder Farmers
6.2. Requirements for Within-Breed Selection Programs for Indonesia’s Smallholder Beef Farmers
- Accurately recorded phenotypes: The main limitation to genomic and traditional within-breed selection in extensively managed livestock such as beef cattle is the difficulty and expense of measuring animals in appropriately sized contemporary groups for the full range of economically important productive and adaptive traits. Unless the genetic improvement programs are adequate in terms of contemporary group size and structure, the measurements will not enable useful predictions of genetic merit. A related paper [77] provides a detailed description of the phenotypes that should ideally be included in cattle breeding objectives and the feasibility of recording them in smallholder farmer herds in low-middle income countries. As indicated by [77], measurement of most phenotypes required for genetic improvement programs in smallholder herds is generally not feasible. Hence, those authors recommended establishing reference populations that are genetically linked, but managed separately, to smallholder cattle herds. The feasibility of setting up reference populations for this purpose in Indonesia is explored further below.
- Genetic parameters for all traits in breeding objectives: As indicated in an earlier section of this review, the only known within-breed selection program to focus on improvement of an objective trait in Indonesia is that undertaken for Bali cattle and based only on cattle growth. Heritabilities for live weights at different ages and genetic correlations between them are reported by [89,90,91]. However, there are no known genetic parameters for other traits for beef cattle reared under Indonesian production systems. There are, though, many reports from the scientific literature providing heritabilities and genetic correlations between most economically important traits, though the estimates based on adaptive traits and new traits (e.g., carcass and beef quality, efficiency of feed utilization, methane emissions) are more limited than those derived for growth and reproductive performance. Hence, the best approach to establish within-breed selection programs for use in Indonesia would be to initially use published estimates from other tropical and sub-tropical environments, with the aim of ultimately estimating relevant parameters from Indonesia’s cattle herds in future. This approach would enable within-breed selection programs for the full range of economically important traits to commence, once the other challenges to establishing such programs have been overcome. A positive aspect of such an approach is that benefits would accrue not only to within-breed genetic improvement, but also to crossbred populations, as reported by [84].
- Data analyses and estimation of genomic breeding values: The previously-mentioned related paper [77] also provides a detailed description of optimal models for predicting genomic estimated breeding values (GEBVs) and the value of genomic data in replacing recorded pedigree information. It additionally compares the positive and negative aspects of different approaches (BayesR, GBLUP) to estimating GEBVs, as applied specifically to genetic improvement programs for low-middle income countries, as well as describing the benefits of imputing full sequence information from lower density Single Nucleotide Polymorphism (SNP) panels.
- Establishing infrastructure and human capacity building: As outlined by [77], two problems of major significance to genetic evaluation systems for smallholder farmers in low-middle income countries are: (i) the lack of infrastructure required to undertake on-farm management and phenotyping of animals, laboratory testing of animal samples, data capture and storage and lack of computing facilities and appropriate software programs; and (ii) lack of human capacity, particularly in areas of technological capability and data analysis and interpretation. As those authors describe, new developments in the use of information and communication technologies are starting to address the issues of on-farm management and phenotyping of animals, whilst the development of livestock reference populations and formation of international collaborations currently hold greatest promise of addressing the remainder of these challenges.
- Possibility of establishing cattle reference populations in Indonesia: The related paper [77] also provides detailed descriptions of the role and value of livestock reference populations that have been established in multiple developed and developing countries globally, specifically to overcome the difficulty and expense of obtaining accurate phenotypes in large and well-designed cohort groups. The value of forming such reference populations in Indonesia would be increased considerably if they could also be combined with international collaborations to enable sharing of computing platforms, data storage, analytical software, joint data analyses and human capacity development in all aspects of genetic improvement programs as also described by [77]. To date though, there are currently no known reference populations for smallholder beef cattle in any low-middle income country, primarily due to lack of the significant funding required for their establishment and the significant length of time required to achieve genetic improvement in those herds, which have an average generation interval of 4–6 years [77]. For Indonesia to establish such populations, this would mean not only identifying new sources of funding to support establishment of such populations, but potentially an even greater challenge in securing sufficiently large areas of suitable cattle grazing land in such a highly urbanized country to enable adequate numbers of beef cattle to be managed and recorded within well-designed cohort groups. The land area challenge and potential solutions will be examined in greater detail as part of a design phase, assuming the new sources of funding can be achieved.
- Could international collaborations help overcome these challenges?: As described in detail by [77] and summarized previously in this paper, international collaborations with genetic evaluation providers servicing smallholder farmers in other countries in tropical areas would help Indonesia overcome most of the challenges currently facing Indonesia. Additional benefits from international collaborations would include the need for fewer animals with recorded phenotypes and for less common cattle breeds (e.g., Bali and Madura cattle) where data are very limited, as evidenced by recent cross-country studies where pooled data were used to accurately estimate GEBVs for tick resistance in African and Australian breeds of cattle with limited data. The exceptional challenges that would remain for Indonesia are perhaps the most challenging though, as they are based on the need for new funding to help establish and maintain the resource populations over perhaps 10–20 years and access to the areas of land on which those populations would need to be managed. However, if the resource populations were able to be established, it is anticipated that, after the initial 10–20 years of operation, new business models would be implemented to allow farmers and other beef value chain participants who benefit directly from the genetic improvement to assume control and ongoing funding of the populations, as is now starting to occur in other countries.
7. The Critical Role of Genomic Information in Designing and Implementing New Beef Cattle Genetic Improvement Programs in Indonesia
- Determine whether the Indonesian breeds are unique and hence, require conservation as pure breeds;
- Definitively confirm the breed composition of Madura and PO cattle, thereby assisting in decisions about how best to use those cattle in future genetic improvement programs targeting productivity of Indonesian cattle herds;
- Confirm whether chromosome imbalance will potentially cause problems with crossbreeding of Bos javanicus with Bos indicus or Bos taurus;
- Assist in the design of within-breed selection, crossbreeding and conservation programs for these breeds; and
- Provide the basic information needed for ongoing studies to identify genes or genomic regions in those cattle breeds that account for large proportions of genetic variation in economically important traits.
8. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Breed Type | Bos taurus | Adapted Bos taurus | Bos indicus | F1 Brahman × British | Bos javanicus (Bali) f | ||
---|---|---|---|---|---|---|---|
British g | European e,g | Sanga g | Indian g | African g | Indonesian | ||
Temperatea | |||||||
Growth | 4 | 5 | 3 | 3 | 2 | 4 | 3 |
Fertility | 5 | 4 | 4 | 3 | 4 | 5 | 4 |
Tropicala | |||||||
Growth | 2 | 2 | 3 | 4 | 2 | 4 | 3 |
Fertility | 2 | 2 | 5 | 3 | 4 | 5 | 5 |
Mature size | 4 | 5 | 3 | 4 | 3 | 4 | 3 |
Meat quality b | 5 | 4 | 5 | 3 | 4 | 4 | unknown |
Resistance to environmental stressors | |||||||
Cattle ticks c | 1 | 1 | 4 | 5 | 5 | 4 | 4 |
Worms d | 3 | 3 | 3 | 5 | 4 | 4 | unknown |
Eye disease | 2 | 3 | 3 | 5 | 4 | 4 | unknown |
Heat | 2 | 2 | 5 | 5 | 5 | 5 | 5 |
Drought | 2 | 1 | 5 | 5 | 5 | 4 | 5 |
Trait | Number of Animals | Mean ± sd | Production System [Reference] |
---|---|---|---|
Birth weight (kg) | 59 309 | 30.91 ± 1.97 31.09 ± 5.31 | Govt. facility, Kendal, Central Java [36] Farmers, Kebumen, Central Java [37] |
Weaning weight (kg) | 59 165 1819 | 110.10 ± 11.20 102.10 ± 12.19 98.87 ± 1.97 | Govt. facility, Kendal, Central Java [36] Govt. facility, Grati, East Java [38] Farm, Tanjungsari, Lampung [39] |
Yearling weight (kg) | 165 | 127.30 ± 0.27 | Govt facility, Grati, East Java [38] |
First mating (month) | 1407 35 | 23.06 ± 0.93 22–28 | Farmers, Kebumen, Central Java [40] Govt facility, Ciamis, West Java [41] |
First calving (month) | 1407 | 32.46 ± 0.90 | Farmers, Kebumen, Central Java [40] |
Post-partum mating (month) | 1407 | 4.37 ± 0.64 | Farmers, Kebumen, Central Java [40] |
Service per conception | 103 1407 55 60 | 2.38 ± 0.86 1.97 ± 0.20 2.11 1.18 ± 0.39 | Farmers, Tuban, East Java [42] Farmers, Kebumen, Central Java [40] Govt facility, Ciamis, West Java [43] Farmers, Lamongan, East Java [44] |
Calving interval | 103 55 | 16.94 ± 2.19 15.39 ± 2.43 | Farmers, Tuban, East Java [42] Govt facility, Ciamis, West Java [43] |
Trait | Mean ± s.d. | Number of Animals | Breed (Type) | Reference |
---|---|---|---|---|
Birth weight (kg) | 16.89 ± 2.86 | 60 | Madura | [53] |
16.25 ± 2.37 | 77 | Madura male | [54] | |
17.08 ± 2.40 | 60 | Madura female | [54] | |
Weaning weight (kg) | 90.32 ± 3.42 | 186 | Madura | [55] |
97 ± 13.77 | 84 | Madura | [56] | |
151.58 ± 36.98 | 24 | Madura (Sonok) female | [57] | |
Yearling weight (kg) | 122.17 ± 6.15 | 186 | Madura | [55] |
120 ± 10.86 | 84 | Madura | [56] | |
247.55 ± 40.48 | 11 | Madura (Sonok) female | [57] | |
Mature weight (kg) | 294.3 ± 43.0 279.1 ± 89.0 392.3 ± 60.4 | 30 30 37 | Madura (Karapan) female Madura female Madura (Sonok) female | [54] [54] [54] |
First mating (month) | 198.5 ± 0.81 | 59 | Madura | [52] |
22.63 | 39 | Madura (Karapan) | [58] | |
23.40 ± 4.17 | 291 | Madura (Sonok) | [59] | |
First calving (month) | 29.96 ± 0.81 | 59 | Madura | [52] |
33.92 ± 3.88 | 291 | Madura (Sonok) | [59] | |
Post partum mating (month) | 3.44 ± 0.17 | 59 | Madura | [52] |
2.57 | 39 | Madura (Karapan) | [58] | |
3.40 | 25 | Madura (Sonok) | [58] | |
Service per conception | 1.48 ± 0.09 | 59 | Madura | [52] |
1.47 | 39 | Madura (Karapan) | [58] | |
1.59 ± 0.3 | 291 | Madura (Sonok) | [59] | |
Open Days (day) | 5.53 ± 0.65 | 291 | Madura (Sonok) | [59] |
Crossbreeding System and Key Features | Feasibility of Implementation in Indonesia |
---|---|
F1 cross: bulls of Breed A (e.g., Bos indicus) are joined to cows of unrelated Breed B (e.g., Bos taurus) to generate F1 progeny (AB). F1 AB progeny are then either sold or joined to a third unrelated breed as described in the next cross | Generating F1 crosses between unrelated breeds using AI is feasible (see discussion below) but selling all F1 females will cause problems for smallholder farmers unless they can purchase new purebred Breed B heifers to retain sufficient, productive females in their herds. If the F1 females are used for breeding, then it is essential they be joined to a well-adapted, unrelated third breed of bull to ensure their progeny are sufficiently well adapted to environmental stressors |
Backcross: F1 AB females are backcrossed to a bull of either Breed A or breed B, generating progeny that are 25% Breed A, 75% Breed B or vice versa. In subsequent joinings, 75% Breed B females are joined to purebred Breed A bulls, generating progeny that are 62.5% Breed A, 37.5% Breed B or vice versa | The major problem with a backcross program in Indonesia is that, in addition to some loss of heterosis in the F2 et seq. progeny, almost inevitably some progeny in F2 et seq. generations (i.e. those comprising 62.5% Bos taurus) will lack the resistance to environmental stressors required to ensure their productivity in smallholder farming systems |
Terminal three-breed cross: bulls of an unrelated Breed C (e.g., Bos javanicus) are joined with F1 female AB progeny to generate progeny comprising 25% Breed A, 25% Breed B and 50% Breed C | If issues associated with retaining a productive breeding herd described above can be overcome, then a 3-breed cross is expected to be as productive as the F1 AB cross, However all 3-breed cross progeny would need to be sold or used to form a composite breed. This means that, as with the F1 cross above, smallholder farmers would need to purchase replacement females to maintain the size of their breeding herds. Such a system is unlikely to be feasible amongst smallholder farmers in Indonesia |
Formation of composites or stabilized crossbreeds: an alternative to the 3-breed cross described above could be to inter-se mate bulls and females having the same (or additional) breeds in their genetic composition e.g., join F1 Breed A × B bulls with F1 Breed C × Breed D females to produce F2 progeny with 25% of each of Breeds A, B, C and D and then continue to inter-sé join the 25% A × B × C × D progeny over subsequent generations | Providing the progeny of these crosses were sufficiently resistant to the stressors of tropical climate, development and maintenance of a composite breed in this type of design would capture the benefits of heterosis and the system could be managed in a relatively straightforward way by smallholder farmers. Ideally, a progeny test program could be introduced in Indonesia to identify genetically superior animals in such a stabilized composite breed (see later section in this paper). And if the third unrelated breed type included a representative breed(s) from the tropically adapted taurine breeds (Table 1), then expected recombination losses due to epistasis would be significantly reduced relative to F2 et seq. crosses between Bos indicus × Bos taurus |
Breed | Weaning Weight (Kg) | Yearling Weight (Kg) | Average Daily Gain 1 (Kg/day) | Body Measurement (cm) 2 | ||
---|---|---|---|---|---|---|
Wither Height | Body Length | Chest Girth | ||||
Bali (in Bali) | 85.61 ± 14.30 1 | 135.09 ± 24.22 1 | 0.36 ± 0.24 | 107 ± 7.58 | 112.6 ± 11.67 | 149.2 ± 8.64 |
Simmental | 235.50 | 430.00 | - | - | - | - |
Limousin | 225.00 | 394.50 | - | - | - | - |
Brahman | 223.50 | 372.00 | - | - | - | - |
PO | 102.13 | 134.30 | - | - | - | - |
F1 Simmental × Bali | 131.61 | 179.21 | 0.26 ± 0.12 | 119.8 ± 4.76 | 123 ± 2.55 | 155.2 ± 14.15 |
105.65 ± 5.27 3 | 200.43 ± 21.52 3 | |||||
121.67 ± 16.18 4 | 230.98 ± 30.23 4 | |||||
F1 Limousin × Bali | 128.75 | 176.80 | 0.38 ± 0.06 | 119.2 ± 2.95 | 120.4 ± 10.04 | 153.6 ± 3.85 |
F1 Brahman × Bali | 115.90 | 157.60 | 0.45 ± 0.21 | 120.71 ± 4.31 | 127.43 ± 13.21 | 163 ± 12.9 |
F1 PO × Bali | 111.66 | 148.25 | 0.41 ± 0.25 | 120.4 ± 3.36 | 124 ± 7.04 | 339.2 ± 43.61 |
Reproductive Performance | Bali | F1 Bali × Simmental | F1 Bali × Limousin |
---|---|---|---|
Days open (days) | 81 ± 10 | 125 ± 23 | - |
Calving interval (days) | 363 ± 20 | 412 ± 36 | 387 |
Pregnancy rate (%) | 94.2 ± 3.8 | 78.9 ± 5.3 | - |
Calving rate (%) | 88.5 ± 4.1 | 76.3 ± 6.3 | 75 |
Pre-weaning mortality (%) | 8.7 ± 0.4 | 17.2 ± 1.2 | 5.6 |
Observation year | 2015 | 2015 | 2019 |
Reference | [69] | [68] | [75] |
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Widyas, N.; Widi, T.S.M.; Prastowo, S.; Sumantri, I.; Hayes, B.J.; Burrow, H.M. Promoting Sustainable Utilization and Genetic Improvement of Indonesian Local Beef Cattle Breeds: A Review. Agriculture 2022, 12, 1566. https://doi.org/10.3390/agriculture12101566
Widyas N, Widi TSM, Prastowo S, Sumantri I, Hayes BJ, Burrow HM. Promoting Sustainable Utilization and Genetic Improvement of Indonesian Local Beef Cattle Breeds: A Review. Agriculture. 2022; 12(10):1566. https://doi.org/10.3390/agriculture12101566
Chicago/Turabian StyleWidyas, Nuzul, Tri Satya Mastuti Widi, Sigit Prastowo, Ika Sumantri, Ben J. Hayes, and Heather M. Burrow. 2022. "Promoting Sustainable Utilization and Genetic Improvement of Indonesian Local Beef Cattle Breeds: A Review" Agriculture 12, no. 10: 1566. https://doi.org/10.3390/agriculture12101566
APA StyleWidyas, N., Widi, T. S. M., Prastowo, S., Sumantri, I., Hayes, B. J., & Burrow, H. M. (2022). Promoting Sustainable Utilization and Genetic Improvement of Indonesian Local Beef Cattle Breeds: A Review. Agriculture, 12(10), 1566. https://doi.org/10.3390/agriculture12101566