The dairy sector in Africa involves three forms of systems; extensive, semi-intensive and intensive, which are also classified according to the type and level of inputs: as low, medium and high, e.g. an extensive system = low inputs; intensive = high inputs, etc. Dairy breeds within these systems may be exotic or indigenous: exotic breeds are mainly Holstein-Friesian, Jersey and Ayrshire, with very few Guernsey, Brown-Swiss or Dairy Shorthorn cattle. Indigenous breeds mainly consist of African bos taurus, bos indicus (Zebu) and Sanga breeds, e.g. Indian breeds, Ankole, Tuli, N’Dama, Boran Watusi, Nguni and others, which vary in use depending on the dairy systems and geographical region. The productivity of indigenous breeds is very low, ranging from a minimum of 0.5 L to a maximum of 6–8 L per day, depending on disease prevalence, climatic conditions, availability of feed and water, lactation cycle and parity of cows (Brown, 1959; Ngono et al., 2018). By contrast, exotic breeds could perform at much higher levels, but often do not exhibit their full genetic potential in African systems due to abiotic and biotic stresses and less than optimal management conditions.

Over the past two decades in sub-Saharan Africa (SSA), various national dairy development plans have been supported by development partners, philanthropists and non-governmental organisations (NGOs). From these interventions, cross breeding of exotic with local genetics has been widely used to improve productivity. However, joint efforts have tried (with varying levels of success) to improve dairy productivity in Africa by establishing centralised dairy improvement programmes with support from development agencies and government-led efforts. For SSA in general, cow milk production is predominant, followed by goat milk, sheep milk and camel milk (Bingi and Tondel, 2015). Despite the encouraging progress in the East African region, the success of centralised dairy breeding programmes has been variable due to a lack of clear and relevant breeding objectives and strategies that are specific to production systems (Ojango et al., 2019). Centralised dairy breeding programmes have the potential to contribute to genetic improvement of exotic, indigenous or crossbred animals using open or closed nucleus breeding herds and have shown productivity levels comparable to those seen under research conditions. However, there has been limited consideration of research into farmers’ perceptions of the resulting cattle, the key traits and characteristics of different breeds, and the alignment of the breeding programmes with researchers’ interests. Uncoordinated efforts have also led to inconsistent decisions on breed choices, leading to a poor match between the chosen dairy breeds and herd management systems in terms of optimum production and resilience (Bhuiyan et al., 2017; Alilo, 2019).

Interventions to improve dairy production in Africa have recently been reviewed and redefined with more impetus through the development of national dairy platforms and national livestock masterplans for instance in Uganda (Balikowa, 2011); Kenya (Bingi and Tondel, 2015); Rwanda (Shapiro et al., 2017a; Shapiro et al., 2017b); Tanzania (Michael et al., 2018). Additional efforts have supported strategic guidance through policies and support for animal tracing and performance data recording for efficient and sustained genetic progress (DDA, 2021) and the development of multi-stakeholder value chains and commercialisation of dairy products (Michael et al., 2018; Ojango et al., 2019). East Africa is the leading milk-producing region in Africa, accounting for 68% of the continent’s milk output (ILRI, 2013). The dairy sector is one of the fastest growing agricultural sub-sectors in Eastern African countries, which has generated significant economic returns and employment opportunities along dairy value chains (Makoni et al., 2013). Kenya and Tanzania are among the biggest dairy producers in Africa, but other countries, including Rwanda (MINAGRI, 2019) and Uganda (FAOSTAT, 2019), are on a trajectory for increased dairy production to meet the growing and increasing demand (DDA, 2021). Although Ethiopia has the largest dairy cattle population in Africa, productivity remains low (Getabalew et al., 2019).

The challenges facing dairy producers in Africa are numerous, complex and vary depending on countries, regions and management systems (Njonge, 2017; Opoola et al., 2019). These challenges are exacerbated by somewhat outdated views on breeding policy based on Western notions of more extreme purebred dairy exotic breeds as being the most suitable for dairying across the continent, with a focus on peak daily MY rather than lifetime or annual MY and without reference to the limitations placed on cattle performance by often inadequate feed resources.

Jersey cattle were first imported into Africa via South Africa in the 1880s and have since expanded into other African countries. Although no records are available to support the exact date of the first Jersey importation into South Africa, it is generally accepted that the first Jerseys were imported by Mr. Adrian van der Byl of Roodebloem Estate, Woodstock, Cape, from Jersey Island, in the early 1880s (Willis, 2012). Jersey heifers exhibit significant calving ease while calving and low calf mortality compared to other breeds (Dhakal et al., 2013). There is information suggesting that Jerseys are disease-resistant, thermo-tolerant and well adapted to challenges of the tropical environment, including limited water, sub-optimum nutrition, pests’ infestation, vector-borne diseases, heat stress, and other issues. Additionally, Jersey cattle are known to adapt well to many types of climate, environment and management practices (Porter et al., 2016).

With reference to the tropical environment, it would therefore appear that the Jersey is a suitable breed to help reduce the impact of genotype-by-environment (or GxE) interactions exhibited by other exotic dairy breeds currently used for dairy production systems in Africa (Jersey Finance, 2020); genotype-by-environment being defined as when two different genotypes respond to environmental variation in different ways (Fikse et al., 2003). Finally, the Jersey breed would appear to give the fastest returns and profit by 5 years of age and overall performance in fertility, survival and management traits analysed for Jersey than other exotic dairy breeds (Garcia-Peniche, 2004).

The aim of this paper was firstly; to review the documented reports, absence or presence of the Jersey breed in countries in Africa, including its performance in comparison to other breeds or crosses. Secondly; to identify important parameters that can be used for decision-support including building a profit (suitability) index for African countries.

We analysed the 200 documents generated from the searches. Based on our findings, the Jersey breed was reported (either currently or historically) in 34 African countries (Figure 1). The Jersey breed was reported either as purebred cattle, or crossbred with exotic or indigenous dairy breeds occurring at different genetic levels and contributing to the 10% to over 80% of other exotic and indigenous dairy cattle. It is however, highly probable that there are many more countries where Jersey cattle are likely to be present but just not reported as so in peer-reviewed literature. However, it would not be surprising if Jersey cattle, or at least Jersey genetics, existed in all African countries.

The countries reporting Jersey cattle present within their dairy populations and across many different management systems include: Angola, Botswana, Burkina Faso, Burundi, Cameroon, Chad, Cote d’Ivoire, Democratic Republic of the Congo, Egypt, Eritrea, E-Swatini, Ethiopia, Gambia, Guinea, Ghana, Lesotho, Kenya, Liberia, Libya, Madagascar, Malawi, Mozambique, Namibia, Nigeria, Rwanda, Senegal, Seychelles, Somalia, South Africa, Sudan, Tanzania, Uganda, Zambia and Zimbabwe.

In all countries reporting Jersey cattle, their proportion relative to other breeds is considerable. Recent data on Jersey breed proportions in other dairy herds in Africa is limited. Previous studies in Kenya (Kang’ethe et al., 2020), South Africa (Theron and Mostert, 2009), Ethiopia (Effa et al., 2013), Rwanda (Manzi et al., 2012), Sudan (Osman and Russel, 1974), Tanzania (Moyo and Mpofu, 1998), Cameroon (Djoko et al., 2003), Ivory Coast (Letenneur, 1978), Nigeria (Adebayo and Oseni, 2016), The Gambia (Diack et al., 2005), Malawi (Banda, 1996), Zimbabwe (Missanjo et al., 2012) and Egypt (Cunningham and Syrstad, 1987) have reported various descriptive statistics, genetic correlations and estimation of genetic parameters and variance components. Recently, genomic diversity and population structure of the Jersey breed amongst other breeds has been evaluated (Chagunda et al., 2018). South Africa and Kenya have extensively reported on the performance of Jersey breed with other breeds in diverse dairy production systems (Staal et al., 2001; Banga and Maiwashe, 2013; Kibiego et al., 2015). Comprehensive and detailed information on data types and evaluation types carried out in these countries is available in Opoola et al. (2021). This difference in cattle populations may reflect the relative intensification of dairy production in South Africa and Kenya compared to other African countries. In addition, genetic parameters such as; estimates for desirable and heritable traits, genetic correlation, genomic diversity and population structure have also been reported for Brown-Swiss and some Indigenous breeds in South Africa (de Ponte Bouwer et al., 2013; Makina, 2015). The proportion of Jersey cattle within national dairy populations relative to other breeds, across African countries other than Kenya or South Africa were not readily available at the time of carrying out this review, with no cited or reported information available in public domains. This lack of clarity on the extent of the Jersey population by country therefore leads to a call for improved data recording, monitoring and publication of Jersey cattle use in Africa’s dairy management systems. However, documented production and reproduction performance traits for other dairy breeds exist (Table 1), with cited and documented average (±standard deviation) performances of the Jersey breed amongst other dairy breeds in Africa.

Table 2 shows favourable estimates demonstrating a Jersey and Jersey cross-breed advantage in pooled data analysed across the breeds for fertility traits such as; average number of completed lactations, age at first calving, first calving interval, average calving interval, number of inseminations per conception, feed efficiency and survival traits. Although pooled data for milk production, lifetime MY and CI were not always favourable in Jersey/Jersey-cross data compared to the Holstein-Friesian and Guernsey breeds, the data suggested that Jerseys and their crosses were more likely to attain shorter age at first calving, survive longer and complete more lactations over their lifetime than the other dairy breeds in most African dairy systems.

Based on the reviewed materials, and compared to other dairy breeds, the Jersey breed is reported to be hardy, resilient and adapted to a wide range of climatic and geographical conditions (Hilton and Briggs, 1980; Berry and Buckley, 2016) and diverse production systems (Effa et al., 2013; Huson et al., 2020). Morphologically, the Jersey breed appears in varied colours of dark brown to light brown, including strains that show white patches (Buchanan, 2002). The patches of white hair and lighter skin pigment (known as “broken coloured”) make these strains less well adapted for hotter climatic conditions due to greater susceptibility to sun exposure. All Jersey cattle have a characteristic black muzzle, surrounded by a mealy coloured band of hair and hard black hooves. These hard black hooves assist in minimising locomotion issues due to low housing spaces, poorly managed surfaces, with heavy rains causing soil erosion and sloping into where these cattle are kept. The Jersey cattle is habitually docile and inquisitive by nature, often dominating the social order and most always coexist with other larger dairy breeds (Phillips, 2014). This allow them to obtain a greater share of feed among other herds as well as better manageability and cooperation from the milking parlour (Jersey Finance, 2020). Although this is not necessarily an advantage in African systems per se, it means that the Jersey cattle may out-compete other breeds within the herd when resources are relatively scarce, as may occur in smallholder systems.

Jerseys are the smallest of the common exotic dairy breeds, weighing between 380 and 450 kg (Oklahoma State University Board of Regents, 2008) though more modern strains developed in the western hemisphere are larger, weighing up to 550 kg (Porter et al., 2016). The relatively lighter weight of Jersey cattle compared to many other breeds (Dhakal et al., 2013) is again an advantage in African systems where feed resources are scarce in most smallholder systems. A smaller animal needs less feed to maintain herself and is therefore more able to produce milk under conditions where feed resources may be limited, then her heavier counterparts (Vance et al., 2013). This also has environmental benefits as, per kg of milk produced, Jersey cattle have lower GHG emissions and requires fewer total resources (Capper and Cady, 2012).

In higher-income countries (Western Europe, North America and Australia), the dairy sector has made considerable progress in adopting genetics that confer advantages in body size, adaptability, resilience, productivity and quality of dairy products from breeds such as Jerseys because they are potentially more efficient than Holstein-Friesian cattle. Oldenbroek (1986) showed that the Jersey breed appeared to have a higher efficiency than expected; possibly due to the higher yield and feed intake per unit of BW compared to other breeds. Furthermore, Kasbergen (2013) indicated that compared with the Holstein, Jersey cows were more economically efficient, generating more income per kg of milk, due to the higher milk components (average solids non-fat% of 9.42% versus 8.78%), higher pregnancy rate, feed efficiency and increased income over feed cost (∼30%). The Jersey breed is able to convert low feed energy to an adequate milk volume and quality (Capper and Cady, 2012), which is especially important for smallholder farms that practice low-input dairy systems by default (Gollin, 2014; Abin et al., 2018). Furthermore, Jersey cattle show increased resilience to tick and vector-borne diseases aiding smallholder farms to reduce veterinary and other maintenance costs, and serve as a triple-purpose breed (dairy, meat and/or draught purposes) (Porter et al., 2016). The Jersey breed adapts well to the hot and dry environment with less of a compromise on milk performance and productivity, compared to other dairy breeds (Buchanan, 2002). The breed is also known to be cost-effective to manage and adapts well to a low-input system when compared to other exotic dairy breeds (Abin et al., 2018). Depending on the management system practiced, milk yield per unit of production input can be very cost-effective, providing an excellent source of nutrients for human consumption in addition to a potential source of income and revenue to meet smallholder farmers’ financial commitments (Herrero et al., 2014).

The lifetime productivity of Jersey cattle will vary considerable depending on genetic merit, production system feed availability and quality, health and overall performance in different global regions. Although Jersey cows may produce less total milk on a daily basis than (Buchanan, 2002), for example, Holstein-Friesian cattle in European or North American systems, the increased milk solids content and resilience of the breed has significant impacts at the lifetime level, particularly in tropical or sub-tropical systems (Stelwagen, 2011; Nandolo, 2015). Krishanender et al. (2014) reported that lifetime productivity (whether measured as daily MY, annual MY or lifetime MY) was higher in pure and crossbred Jerseys than in other exotic or indigenous breeds in sub-temperate systems. Furthermore, Jersey cows have been reported to demonstrate significantly better lifetime daily yield (Boothby et al., 2020), age at first calving and survival rates (Buckley et al., 2014) compared to Holstein-Friesians in UK production systems. In dairy cows, certain terminologies often used interchangeably can be a bit confusing and ambiguous. Therefore, owing to the ambiguity, we define the following terms; longevity, herd life and productive life. Hu et al. (2021) defines longevity in dairy cows as the time from a cow’s first calving to when she exits the herd or does not have sufficient productivity. Herd life refers to the days from birth of a calf, produces her first calf; and to her culling or death (Hu et al., 2021; Zhang et al., 2021) and productive life refers to the days from the cow’s first calving to culling or death (Raguz et al., 2011). The proportion of days in milk over the total lifetime and the herd life of Jersey cattle were also increased compared to Holstein-Friesian, Brown-Swiss and Guernsey breeds (p < 0.01) in the study published by Garcia-Peniche (2004) for seven regions in the United States. With regards to Jersey crossbred cattle, Effa et al. (2013) reported better in the lifetime yield of F₁ offspring of Jersey x Boran cows (13,546.50 ± 812.3 L) compared to F₁ Holstein-Friesian × Boran cows (12,816.7 ± 817.0 L). The estimates for productive life, herd life, and AFC were also reported as more favourable for F₁ Jersey × Boran crossbreds than in the F₁ Holstein-Friesian × Boran crossbreds (Effa et al., 2013). Hunde et al. (2015) also observed a favourable mean AFC of 29.9 months (±0.17) in pure Jersey cattle compared to estimates of 40.9 months (±0.33) from Yalew et al. (2011) in pure Holstein-Friesian cattle managed in the Central Highlands of Ethiopia. However, after the F₁ offspring, it is difficult to ascertain the genetic capacity and potential for productivity and fertility of subsequent generations (Alilo, 2018), as the Jersey genetics may be diluted out or affected by other breeds within the population.

Milk yields from Jersey cattle are in excess of 13 times their BW per lactation (David Clarke Livestock, 2021), a remarkable feat of efficiency given the increased milk fat and protein concentrations compared to other dairy breeds. For example, Bland et al. (2015) and Carroll et al. (2006) noted that Jersey milk contained 18% more protein, 25% more fat and 20% more calcium than milk produced from other dairy breeds; Holstein-Friesian and Brown-Swiss. This increase in milk solids content contributed to the greater cheese yield per kg of Jersey milk (compared to Holstein-Friesian milk) cited by Capper and Cady (2012) and therefore to improved production efficiency and reduced environmental impacts in North American production systems. This is of obvious importance from a food security and sustainability perspective within LMIC, as improving the nutritional status of some of the world’s poorest people leads to myriad health, development and social benefits.

Resistance to climate extremes is a key element of suitability for African production systems, with the most suitable cattle able to maintain productivity despite variation in temperature or humidity (Ekine-Dzivenu et al., 2020). A report by Phillips (2014) comparing heat stress responses in Jerseys and Holstein-Friesian dairy cows raised near the Mooi river of South Africa, showed that during the warmer months, Jersey cows exhibited a 5.35 L/cow/month reduction in total milk production compared to 5.76 L/cow/month in Holstein-Friesians, despite the higher genetic merit of the Holstein-Friesian cows. Moreover, the MY of Jersey and Holstein-Friesian cows on their third-and-over-lactation was 85% and 78%, respectively showing a remarkable yield persistence and improvement over time based on 305-day lactation (Phillips, 2014).

From a lifecycle and efficiency point of view, the Jersey often has an advantage over larger breeds in terms of spending a greater proportion of her total life in lactation (Buchanan, 2002; Stelwagen, 2011). This is facilitated by an early age at puberty, better detection of oestrus behaviour, an early AFC and better calving interval, with a dry period that is suited to the herd and system (Parkinson et al., 2019). Traditionally, a 12-month calving interval has been considered to be ideal in many intensive dairy systems (Zeddies, 1982; Strandberg and Oltenacu, 1989), yet in dairy systems where feed or forage is limited, there may occasionally be some benefits to extending lactation if this results in a successful conception and pregnancy (Ratnayake et al., 1998). The bulk of the literature surveyed reported that purebred and crossbred Jersey cows reach puberty at an earlier age (Berry and Buckley, 2016) than other large sized exotic breeds, which may be a function of their smaller body size and therefore relatively higher body fat at a given age compared to larger-framed cattle. However, reproductive performance after puberty was also cited by Berry and Buckley (2016) as being better in Jersey cattle, with higher pregnancy rates, an earlier AFC and a reduced calving interval compared to other exotic or indigenous breeds. Conception rates and the number of inseminations per conception were also cited as improved in Jersey cattle, compared to other dairy breeds. Kasbergen (2013) reported that Jersey cows exhibited higher overall conception rate (CR) of 32% vs 29% CR for Holstein cows raised in the hot and dry climate of California, USA.

Dhakal et al. (2013) noted an improved ease for pure Jersey (JJ) and Holstein (HH) sires and dams mating to produce Jersey × Holstein (JH) and Holstein x Jersey (HJ) crosses, and other Jersey crosses (>50% JJ) in comparison with pure Holsteins and other Holstein crosses (>50% HH), in a study based on a pasture-based system in the USA. Pure Jerseys required calving assistance in only 7.5% of births from primiparous cows and 3.4% of births from multiparous cows, with Jersey crosses (>50%) requiring assistance in 8.3% of births from primiparous cows and 5.6% of births from multiparous cows. In comparison, calving assistance were more common in pure Holsteins (21.6% of births from primiparous cattle and 7.2% from multiparous), and in Holstein crosses (>50% HH) with 12.9% of primiparous births and 7.9% of multiparous births requiring assistance respectively. Crossing Jerseys directly with Holsteins also had a significant effect with assistance required in 8.8% (HJ) and 8.6% (JH) of births from primiparous cattle and 3.8% (HJ) and 4.8% (JH) of births in multiparous cattle. Calf mortality was also significantly lower in pure Jerseys (12.5% in primiparous cows and 5.6% in multiparous) compared with pure Holsteins (15.7% and 12.9% respectively).

The fertility attributes of the Jersey breed increases profitability of annual and lifetime milk production, longevity and number of subsequent calvings, as well as decreasing the time and impact on-farm resources (U.S. Jersey, 2014). Garcia-Peniche (2004) analysed fertility traits in Jersey cattle compared with other breeds in herds across multiple geographic and climatic regions of the USA and reported that in herds with a single breed of cattle, AFC in Jerseys averaged 778 (±3.1 ¹ ) days, compared with 830 (±4.4) days for Brown Swiss and 803 (±3.0) days for Holsteins. In addition, the mean first calving interval in Jersey herds, measured in seven geographic regions, ranged from 390 (±5.1) days to 426 (±5.6) days, in comparison with a range across the same regions for Holstein herds of 409 (±3.4) days to 461 (±4.9) days. Evaluations of the performance of the Jersey breed in Africa by Opoola et al. (2020) also reported lower mean AFC in Jerseys compared with Holsteins in Kenya (909 days ± 31.44 for Jerseys vs. 972 days ± 3.93 for Holsteins) and South Africa (861 days ± 1.21 for Jerseys vs. 873 days ± 1.02 for Holsteins). In the same analysis, Jerseys also exhibited shorter mean calving intervals compared with Holsteins in both Kenya (457 days ± 28.77 for Jerseys, vs 475 days ± 6.12 for Holsteins) and South Africa (405 days ± 0.88 for Jerseys vs. 429 days ± 0.85 for Holsteins). Mostert et al. (2010) also showed decreases in the annual calving interval in Jersey cows (0.50 days/year) compared to increases in Holstein-Friesians (1.25 days/year), Ayrshire (0.71 days/year) and Guernseys (0.57 days/year). These would be expected to improve overall productivity and are thought to have been due to the inclusion of calving intervals and AFC standards in the selection of bull dams implemented by the Jersey Society since the early nineties in South Africa’s dairy breeding programme.

The literature surveyed within this study showed that, compared to other breeds, Jersey cattle had improved survival-related traits in terms of longevity, herd life, the number of completed lactations and total days in milk (Wakhungu et al., 2006; Effa et al., 2013; Muller and de Waal, 2016). The longevity of dairy cattle attracts a great deal of debate worldwide, as there is no “ideal” number of lactations for a cow to complete within her lifetime (De Vries, 2020; Hu et al., 2021). The low number of lactations (1–3) completed by many cows in intensive systems attracts criticism, yet some researchers claim that keeping a cow for extended periods of time reduces the opportunity to make genetic gains (Capper and Cady, 2012; Parkinson et al., 2019). The decision of when to cull a cow is often based on economic factors (Lehenbauer and Oltjen, 1998). Therefore a breed like the Jersey, which is able to maintain productivity, longer life (more lactations), less need for replacement and a calf born every lactation that can be sold, can increase the total number of cows for smallholders. Less replacement costs for Jerseys compared to other breeds could be of economic and environmental value, as well as mitigating consumer concerns about cows being culled at relatively young ages. This is particularly important in smallholder systems in Africa as these cows are often the main source of income, status and high-quality protein (Ojango et al., 2019), therefore there are obvious economic, nutritional and social benefits to increased longevity. Muller and de Waal (2016) showed improved longevity and survival of first lactation cows to the fifth lactation at 34% for Jersey cows compared to 23% for Holstein cows bred in the Western Cape of South Africa. The effect of breed on longevity is not confined to African systems: research from the USA by Garcia-Peniche (2004) compared multiple longevity traits in herds of different breeds across geographic regions and reported increased average days of completed lactation in purebred Jersey herds with 633 (standard deviation SD; 291) days vs pure Brown-Swiss with 554 (SD 280.2) days and pure Holstein herds with 592 (SD 280) days. Jerseys also averaged increased survival rates in the herd from birth up to 5 years of age; 45% (SD 0.5) in pure Jersey herds vs. 38% (SD 0.49) in Holstein herds and 42% (SD 0.49) in Brown-Swiss herds.

Jersey crossbreds have also been demonstrated to perform favourably for longevity traits in tropical countries (Gebregziabher and Mulugeta, 2006; Effa et al., 2013; Hunde et al., 2015). In the tropical highlands of Ethiopia, estimates for longevity traits for F₁ Jersey × Boran crosses showed significantly longer mean total life (4270 days ± 135), herd life (3108 days ± 147) and productive life (2387 days ± 126) when compared with F₁ Friesian × Boran crosses (Effa et al., 2013). F₁ Friesian × Boran crosses had mean total life of 4200 days (±135), mean herd life of 2877 days (±148), and mean productive life of 2145 days (±127). The F₁ Jersey × Boran crosses also showed higher mean lifetime MY in litres (13547 ± 812, compared to 12817 ± 817 for F₁ Friesian × Boran), though mean total MY in terms of litres per day of total life was broadly comparable at 3.04 L ± 0.2 ² in F₁ Jersey x Boran crosses vs 3.00 L ± 0.2 ³ in F₁ Friesian × Boran crosses (Effa et al., 2013).

Jerseys are efficient at converting feed into milk, which means that Jersey cows can produce a greater volume of milk per kg of DMI (Effa et al., 2013). This is a major advantage in terms of overall dairy sustainability, as feed efficiency has been cited as one of the key determinants of GHG emissions and resource use (Thoma et al., 2013), as well as farm profitability (Kasbergen, 2013). Carroll et al. (2006) reported that Jersey cows produced more fat corrected milk (FCM) and solids corrected milk (SCM) per kg of DMI than the Holstein and Brown-Swiss breeds. This was due to the greater efficiency of milk fat production per unit of DMI within Jersey cattle. In addition, Sneddon et al. (2011) reported that feed conversion efficiency (FCE) estimates, measured as grams of milk solids (milk fat plus milk protein) per kilogram of DMI were also higher in Jersey (112 g MS/kg DMI) than Holstein-Friesian cows (97 g MS/kg DMI). Sneddon et al. (2011) further showed that Jersey cows have significantly higher DMI per kilogram of BW compared to Holstein-Friesian and F₁ of Holstein-Friesian × Jersey cows (3.81, 3.23 and 3.64 g DMI/kg BW, respectively); a result supported by Beecher et al. (2013). The small-framed Jersey cow has a lesser maintenance requirement than her large-framed herd mates. This favours her increased feed intake per unit of BW thus linking her ability to partition a greater proportion of feed nutrients into milk production.

This is referred to as the “dilution of maintenance” effect, whereby, as MY increases, the maintenance nutrient requirement is spread over the greater volume of milk, and therefore the nutrient use per kg of milk is reduced. This has significant environmental consequences, as discussed later in this report.

The greater milk fat yield of Jersey cows also has been linked with improved heterosis for milk fat yield genes in Jersey crossbreds, compared with other dairy breeds. Improved heterosis for fat yield percentage has been reported for Jersey × Boran crossbreds (5.10 ± 0.15%), by contrast to purebred Holstein-Friesian (4.77 ± 0.03%) and Boran cattle (5.01 ± 0.03%) under Ethiopian conditions (Hunde, 2019). This is of obvious advantage in terms of milk nutritional composition in its role in providing high-quality nutrition to smallholders and their families, but also in terms of commanding a greater price for milk sold for processing or consumption off-farm.

Jersey cattle exhibit a number of positive attributes in terms of productivity and efficiency, yet for a truly sustainable future, dairy producers must ensure that they have an economically viable, environmentally responsible and socially acceptable system in place. Although there is no “one size fits all” dairy system or collection of management practices that will results in sustainability for all farmers, the better an individual cow or herd can perform, the more sustainable it is likely to be. In this context, sustainability means using fewer resources (feed, land, fertilisers, fossil fuels) and having a lower carbon footprint (kg of GHG) per kg of solids-corrected milk. This should also result in a relatively lower cost of production, which is crucial for current and future economic viability, particularly in smallholder systems. Given that the concept of sustainability is a crucial dimension for all food systems, any production system that sets baseline and demonstrate improved sustainability is also likely to gain greater social acceptability. This is an obvious challenge in LMIC, where smallholders often lack access to the technological resources or infrastructure to assess the sustainability of their operation. Facilitating ways to measure and benchmark sustainability metrics on smallholder operations is therefore an important knowledge gap, which warrants significant investment.

The sustainability of dairy systems has been investigated by multiple authors with regards to genetics, nutrition, management and farming system, yet the data relating to sustainability of specific cattle breeds is lacking in the literature. The one exception is a paper by Capper and Cady (2012) which compared the environmental impacts of Jersey vs Holstein cattle under typical U.S. management systems. The study, a modelling exercise using publicly available data, quantitated the resource use and GHG emissions associated with producing the milk required to yield 500,000 t of cheese. Although Jersey cows had a lower daily MY than Holsteins (20.9 vs 29.1 kg), they were more efficient and had increased milk solids content for cheese yield, lower mature body weight and calving interval (8.0 kg milk/kg cheese; 454 kg BW; 13.7 months) than Holstein cows (9.9 kg milk/kg cheese; 680 kg BW; 14.1 months). In addition, Jersey cows exhibiting favourable age at first calving (25.3 vs. 26.1 months) coupled with improved longevity (3.00 vs. 2.54 lactations) meant that the Jersey cows had a greater production efficiency than their Holstein counterparts. Consequently, per kg of cheese yield, feed use was reduced by 19.8%, land use by 18.9%, water use by 31.6%, and the GHG emissions were 20.5% lower when milk from Jersey cattle was used rather than Holsteins. Although it was not quantified within the paper, the reductions in resource use per kg of cheese would also be expected to improve economic viability of Jersey compared to Holstein systems. It could be argued that the difference between Jersey and Holsteins might be less pronounced in a U.S. intensive system than in some of the far more extensive African conditions described within this review, therefore differences in the impacts described by Capper and Cady (2012) might be greater under tropical or sub-tropical conditions.

Various findings underline the suitability of Jersey cattle as a means to improve dairy sustainability through adaptation to the diverse production systems found across the globe. At present, smallholder systems are significantly disadvantaged when GHG emissions are used as the sole metric of assessing sustainability, as global analyses have reported that regions containing a high proportion of smallholder farming systems have greater carbon footprints per kg or ton of milk, meat or eggs (FAO, 2010; MacLeod et al., 2013; Opio et al., 2013). The current global standard for assessing greenhouse gas emissions is prescribed by the Intergovernmental Panel on Climate Change (IPCC, 2019) using three different types of calculations (Tiers I, II and III) to assess GHG emissions, depending on data availability. Tier I require the most basic data (total livestock numbers multiplied by a default emissions factor per head) and is used in many LMIC because it’s easy to apply. However, the default values used are based on intensive systems within developed regions, which cannot necessarily be applied to different systems or breeds (Leitner et al., 2021). Tier II is intermediate and Tier III is the most demanding in terms of complexity and data requirements. Both tiers are often referred to as higher tier methods utilised in most developed countries and are generally considered to be more accurate as adequate data are available to develop, evaluate and apply higher tier methods. More appropriate and accurate methane emissions factors must be calculated to be used on farms in LMIC, considering the efficiency and productivity benefits of Jersey cattle, in order to accurately assess the implications for GHG emissions for smallholders. Additional information on the performance and contribution of Jersey breed to dairy development across Africa is available in Opoola et al. (2021).

A proposed (all-breed type) index for Africa that draws elements from the New Zealand type index, East Africa index and the UK’s spring calving index to include increased weightings for fertility, calving ease, reduced condition loss and replacement costs, and disease resistance to mastitis would be an initial step, the index could then be modified as more information is recorded and included. An index in Africa could enhance the financial value returns of animals as it provides the basis by which animals can be ranked enabling farmers to choose the appropriate cow that fit the diverse management systems in Africa.

In selected African countries, several researchers have previously performed genetic evaluation (Dube et al., 2009; Missanjo et al., 2013; Madilindi et al., 2019; Opoola et al., 2020) and most recently, genomic evaluations on the Jersey breed (Chagunda et al., 2018). Preliminary methods and statistical procedures such as least squares mean and generalised or mixed linear models have been used in data description and curation for onward data analyses (Cunningham and Syrstad, 1987; Nouala et al., 2003; Opoola et al., 2019). Parameter estimations such as variance components, heritabilities and genetic correlations for MY, AFC, calving interval, feed efficiency, adaptability and disease resilience have been determined using residual maximum likelihood approach in both biological and genetic software programmes (Nouala et al., 2003; Dube et al., 2009; Missanjo et al., 2013; Ojango et al., 2019). The estimations of these parameters for the aforementioned traits from performance data records provides opportunities to monitor genetic progress over a time period as well as optimise the implementation of sustainable breeding programmes using information available for the breed (Asimwe and Kifaro, 2007; Mostert et al., 2010; Makina, 2015; Opoola et al., 2020).

A proposed dairy profit index (DPI) that include traits of economic importance that also addresses current challenges faced by the African dairy sector will help maximise dairy productivity and improve efficiency of breeding plans for increased profits to dairy farmers. The East Africa dairy profit index developed by the Animal Breeding East Africa Ltd (ABEA, 2022) that draws elements from the New Zealand’s Breeding Worth index is a good starting point for developing individual country indexes. The index developed for each country may be different in terms of monetary currency, input and output costs. However, the criteria for selection of measurable traits of interest (e.g. production, fertility, growth, survival and disease influence, etc.) would be similar across the countries in Africa even though sire breeding values could be different due to influence of GxE.

A proposal for a Rwanda DPI would include economic weightings for measurable traits for milk yield, fertility, growth and survival, herd health and disease resistance, longevity and conformation whereby bulls and cows with known breeding values and genomic breeding values are selected on the current breeding plan.

The traits measured should include:

1. Production; daily milk yield, total days in milk, lifetime milk yield and annual milk yield.

The existence of other global dairy indexes and decision-support tools based on priority traits guides us towards building the necessary information for developing a selection index tool for Africa (or Rwanda as an exemplar). Such index development for Rwanda could optimise milk yield, fertility and body weight by ranking of suitable dairy breeds for Africa (Table 3). Table 3 shows some of the dairy profit indexes of relevance to the proposed index for Rwanda. Most of the traits have proportions assigned with respect to performance, fertility, and conformation and including health traits. The proposed decision-support tool (dairy profit Index) will be derived using both performance (phenotype) data records as well as genotype information for milk yield, fertility and body size already accounted by growth. In addition, ranking procedures that include economic weights for input costs, management and the EBV and GEBVs for the components that make up milk yield, fertility and body size in relation to growth could provide initial information for the proposed DPI for Rwanda. The derived GEBVs will guide in selecting breeding candidates and ranking bulls with favourable traits. The proposed decision-support at its first inception is expected to be an open-ended dairy profit index whereby more traits of economic importance will be included as the performance recording systems matures and data become available.