Smallholder Dairy Production Systems Research Articles

Uncovering service gaps and patterns in smallholder dairy production systems: A data mining approach

Traditional clustering algorithms have often been used to categorize farmers but tend to overlook the underlying reasons for these groupings. Typically, clusters are formed based on common metrics such as dispersal and centrality, which provide limited insights into the relationships among key attributes. This study introduces an innovative approach using pattern and association rules analysis to better understand the characteristics of dairy production clusters. Focusing on Tanzanian smallholder farmers, the research moves beyond identifying clusters to uncovering the hidden relationships within them. Through pattern analysis, the study logically examines the behavioral mechanisms that define these clusters, highlighting service gaps that, if addressed, could enhance smallholder dairy farmers' productivity. Frequent patterns with support ranging from 57 % to 93 % and confidence levels between 85 % and 100 % were identified, revealing critical challenges faced by these farmers. For instance, farmers using Artificial Insemination—typically younger or new entrants—face constraints related to farm size, land holdings, fodder production, lack of farmer groups, and insufficient formal training in dairy care. Meanwhile, seasoned farmers deal more with institutional barriers such as limited access to marketplaces, extension services, and distant water sources. The study highlights the diverse challenges faced by different farmer groups and provides strategic recommendations for improving dairy productivity. Enhancing access to formal training, improving fodder production, supporting the formation of farmer groups, and addressing institutional barriers are key actions that could help Tanzanian smallholder dairy farmers increase milk yield and overall productivity.

Assessing lameness prevalence and associated risk factors in crossbred dairy cows across diverse management environments

BackgroundA thorough understanding of lameness prevalence is essential for evaluating the impact of this condition on the dairy industry and assessing the effectiveness of preventive strategies designed to minimize its occurrence. Therefore, this cross-sectional study aimed to ascertain the prevalence of lameness and identify potential risk factors associated with lameness in Holstein Friesian crossbred cows across both commercial and smallholder dairy production systems in Bengaluru Rural District of Karnataka, India.MethodsThe research encompassed six commercial dairy farms and 139 smallholder dairy farms, involving a total of 617 Holstein Friesian crossbred cattle. On-site surveys were conducted at the farms, employing a meticulously designed questionnaire. Lameness in dairy cattle was assessed subjectively using a locomotion scoring system. Both bivariate and binary logistic regression models were employed for risk assessment, while principal components analysis (PCA) was conducted to address the high dimensionality of the data and capture the underlying structure of the explanatory variables.ResultsThe overall lameness prevalence of 21.9% in commercial dairy farms and 4.6% in smallholder dairy farms. Various factors such as age, body weight, parity, body condition score (BCS), floor type, hock and knee injuries, animal hygiene, provision of hoof trimming, and the presence of hoof lesions were found to be significantly associated with lameness. Binary logistic regression analysis indicated that the odds of lameness in crossbred cows increased with higher parity, decreased BCS, presence of hard flooring, poor animal hygiene, and the existence of hoof lesions. These factors were identified as potential risk factors for lameness in dairy cows. Principal component analysis unveiled five components explaining 71.32% of the total variance in commercial farms and 61.21% in smallholder dairy farms. The extracted components demonstrated higher loadings of housing and management factors (such as hoof trimming and provision of footbath) and animal-level factors (including parity, age, and BCS) in relation to lameness in dairy cows.ConclusionsThe findings suggest that principal component analysis effectively reduces the dimensionality of risk factors. Addressing these identified risk factors for lameness is crucial for the strategic management of lameness in dairy cows. Future research in India should investigate the effectiveness of management interventions targeted at the identified risk factors in preventing lameness in dairy cattle across diverse environments.

Typification and differentiation of smallholder dairy production systems in smallholder mixed farming in the highlands of southern Ethiopia.

The present study aimed to classify smallholder dairy production systems by analyzing land allocation for various crop types and characterizing them based on integration with specific crops which is gap in earlier studies. A total of 360 smallholder farmers were interviewed to generate firsthand information in addition to using secondary data sources. The classification utilized K-means clustering, while discriminant analysis was applied to accentuate the distinct characteristics of dairy production systems (DPSs). Subsequently, for a particular crop to be considered dominant, the minimum farmland allocation had to exceed 30%. Based on this, the 360 respondent farmers in the study areas were categorized into four distinct DPSs: diversified crop-based (DCB) at 31%, enset-based (EB) at 28%, cereal-based (CB) at 24% and cash crop-based (CCB) with coffee, khat, vegetables, fruits, and sugarcane accounting for 17%. Within the CCB dairy production system, where cash crops were cultivated most dominantly, averaging 56% of the farmland, farmers reported the highest annual income and, consequently, acquired more improved dairy cows, facilitating their entry into intensive dairy production. Ownership of improved dairy cattle breeds, use of agro-industrial byproducts as feed, practicing stall feeding and better housing are observed practices in this DPS that relate to the intensification of dairy production. This positive relationship was observed between the commercialization of crops and the intensification of dairy production in the CCB dairy production system. In the EB dairy system, enset dominates with a 33% area share, leading to increased residues for cattle feed. They keep large herds of local cattle, limited crossbreeding experience, and prefer conventional feeding. The CB system allocates 47% of land to cereals, justifying cereal residues as primary dairy feed. Cultivating grasses like Pennisetum pedicellatum and Phalaris arundinacea is also highly valued in the system. The DCB system, with diverse crops (none exceeding 30%), implies varied residues for dairy feed. These findings reveal unique characteristics across dairy systems, indicating a positive correlation between crop commercialization and dairy intensification. Hence, understanding each type of DPS and its characteristics will help development experts or those in charge of designing agricultural policy to establish the best strategic plans for enhancing the productivity of dairy cattle under smallholder conditions.

Assessment of carbon footprint of milk production and identification of its major determinants in smallholder dairy farms in Karnataka, India

Indian dairy enterprise is dominated by smallholder dairy farms that contribute 72% of the country's total milk production. These smallholder dairy farms are often considered to emit substantial greenhouse gases (GHG) but are poor in productive performances. Therefore, it is crucial to estimate the carbon footprint (CF) of milk production of the smallholder Indian dairy farms. The primary objectives of the study were (1) Assessing the CF of milk production of smallholder dairy farms through life cycle analysis in south-interior Karnataka, India; (2) Identifying the hotspots of GHG emissions and significant factors influencing the CF of milk production in smallholder dairy production system. The study accounted GHG emissions from different sources and considered multiple functions of the smallholder production system. Estimations were made based on primary data collected from 47 farms and associated secondary data. For estimating the CF of milk production, the emissions of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) on a CO2-equivalent (CO2-eq) basis from feed production, enteric fermentation, manure management, transport and energy usage were allocated to fat- and protein-corrected milk (FPCM) based on mass balance, price (crop byproducts and residues) and feed digestibility. Principal component analysis and stepwise linear regression analysis were performed to identify the major factors influencing the CF. The average total GHG emissions (kg CO2-eq yr-1 farm-1) attributable to milk production based on mass, economic, and digestibility allocations were 8,936, 8,641, and 8,759, respectively. The contributions of CH4, N2O, and CO2 to the total farm GHG emission were 70.6%, 20.5%, and 7.69%, respectively. The major emission hotspots were CH4 emission from enteric fermentation (66.8%) and GHG emission from feed production (23.0%). The average CF of cradle-to-dairy cooperative milk production varied from 1.45 to 1.81 kg CO2-eq kg FPCM-1. The CF of milk production was more than 2-fold greater, when milk yield was below 3,500 kg lactating cow-1 yr-1. The FPCM yield 100 kg body weight-1, dry matter intake, and CH4 emission from manure management were the strongest determinants of the CF and explained 83.4% of the observed variation. The study emphasized the importance of considering multiple functions of a mixed crop-livestock-based dairy production system for estimating CF per unit of product. The results suggest that maintaining high-yielding dairy animals and adopting appropriate feeding strategies for better feed utilization are the possible effective interventions for reducing the CF of milk production.

Genetic evaluation of Frieswal cattle for first lactation milk yield from smallholder dairy production systems in Kerala, India

The present investigation was undertaken to determine the genetic worth of Frieswal (62.5% HF × 37.5% Sahiwal) young bulls through progeny testing under field conditions in Kerala state, India. A total of 65 Frieswal bulls were evaluated based on 1037 first lactation records of their daughters calved over a period of 15 years from 1995 to 2010 were used for the study. The overall average breeding value for the first lactation 305-days milk yield was estimated as 2229.19±50.91 kg with a range of 2193.74±66.59 to 2280.62±66.59 kg. Out of 65 bulls inducted in 7 different sets, 33 bulls (50.7%) had breeding values higher than the herd average (2229.19 kg). The number of daughters per bull varied from 7 to 51 whereas the average number of daughters per bull was 16. The genetic superiority and percentage genetic superiority of the top 25 bulls (38.46%) over population ranged from 6.26 to 51.43 and 0.28 to 2.30, respectively. The least squares analysis of variance revealed that the year of calving had a significant effect on the first lactation milk yield of daughters. The increasing trend of first lactation milk yield over year / bull set observed in the present study indicates the successful implementation of large-scale progeny testing programme under field conditions.

Genetic survey in smallholder dairy production system of Southern province of Zambia.

Milk production among the smallholder dairy farmers in Zambia is reported to be low despite improvements in milk collection infrastructure and unmet demand by the populace. This study was conducted to characterize cattle breeds and the breeding strategies of the smallholder dairy production system in the Southern province of Zambia. The study was conducted using questionnaires to obtain responses from identified respondents in six districts considered the main dairy cattle producing areas. One hundred and twenty questionnaires were administered and available for descriptive statistical analysis. The cattle genetic groups included local (Tonga and Angoni) breeds and their crosses (40.0%); beef (Boran and Brahman) breeds and their crosses (23.3%); Friesian breed and its crosses (28.8%); Jersey breed and its crosses (4.9%); and Fleckvieh breed (3.0%). Calving rate was found to be to be between 36% and 50% for the dairy herds. Compared to the other genetic groups, it was noted that Friesian and its crosses had higher milk production (3.55 L vs. 1.4L). The low milk yield reported could be attributed to the period of study, which coincided with the long dry season between April and October. The Friesian and its crosses recorded earlier age at first calving (2.65 vs. 2.8 years), shorter longevity (10.5 vs. 12.25 years), and shorter lactation length (7.5 vs. 9.25 months). Jersey and its crosses, on the other hand, had an above average performance for all indices of economic importance such as milk production, lactation length, age at first calving, longevity, and number of calves produced. The results indicated natural mating was practised by 85% of the farmers. Farmer-preferred traits include size and conformation (23%); performance and colour (16% and 15%, respectively) in the choice of a bull. Selection by farmers were thus based on simple observation without pedigree or performance-based genetic evaluation. It was apparent that the smallholder dairy production system is in a shifting trend to transform the mainly local and beef breed animals into dairy herds through crossing with exotic dairy breeds. The production system is, however, faced with the challenges of water and feed supply to meet nutritional requirements, and high disease burden. Jersey breed was found to be a logical choice for the resource poor smallholder dairy farmers. The development and management of the smallholder dairy breeding schemes should be all-inclusive and directed at the prevalent production systems with the aim of also improving the feeding and management practices.

DAIRY CATTLE REPRODUCTIVE PERFORMANCE UNDER DIFFERENT PRODUCTION SYSTEM IN ETHIOPIA: NIGERIA’S BILATERAL TRADE RELATIONS WITH CHINA: AN ASSESSMENT, 2010 – 2019

Reproductive performance of dairy cattle in terms of age at first service (AFS), age at first calving (AFC), calving interval (CI), day open (DO), and a number of service preconceptions (NSPC) in the different production system in Ethiopia is reviewed. The reproductive performance parameter of dairy cattle like age at first serves (AFS), age at first calving (AFC), calving interval (CI), Day opens (DO), and the number of service preconceptions (NSPC) under different production system is quite different. Age at first calving (AFC) in pastoral and agro-pastoral and intensive dairy production systems were 43.5±1.5months and 33.2 months, respectively. Days open (DO) in pastoral and agro-pastoral, smallholder dairy production, and urban and dairy products for local cows were 141±7 days, 185±51.2days, and 199.8±11.60 days, respectively. 85 to 115days considered as optimum for a dairy herd, 116 to 130 days indicate slight problems, 131 to 145 days moderate problems. This, indicated that days open in the different production system is not within the normal range. Similarly, for cross dairy cows in an intensive dairy production system was157.8 days. The calving interval (CI) in pastoral and agro-pastoral, smallholder dairy production systems, urban and pre-urban for local cows were 14.63±10 months, 14.36± 1.03 months, and 22.17±0.79 months, respectively. Whereas urban and pre-urban and intensive dairy production for cross dairy cows were12.42±5.9 months, 15.820±.41months, and 14.56 months, respectively. NSPC for Horro x Jersey (1.8) and Horror (2.1) are not within the normal range, But for Borana (1.6), Fogera (1.28), Friesian x Zebu (1.56) were within the normal range. This difference might be due to poor management in terms of nutrition, health care, housing, heat detection, timely insemination, and breeding as well as environmental factors. It could be concluded that proper management in terms of nutrition, health care, housing, heat detection, and timely insemination would improve reproductive performance under different production systems. Besides this, to boost dairy cattle reproductive performance, intensification of dairy cattle production should be promoted in Ethiopia to meet the increasing demand for dairy products and to reduce imports of dairy commodities. Thus, all coordinated works of all concerned bodies should be in place to boost production and productivity and thereby enhance the livelihood of the dairy farmers.

Diversity in smallholder dairy production systems in the Brazilian semiarid region: Farm typologies and characteristics of raw milk and water used in milking

Smallholder dairy farms (SDF) producers are being challenged by market demands combined with competition and limited access to productive and market inputs, contributing for reducing its participation in the dairy activity. Thus a sustainability assessment for SDF development is necessary, opening the opportunity for recognizing the diversity between production systems. Farm typologies are often used for this purpose. The objective was to develop a typological analysis of the smallholder dairy farms in the Brazilian semiarid region and evaluate characteristics of raw milk and water used in milking. A semi-structured questionnaire containing social, physical, livestock, herd management, technological, productive, and economic indicators with 49 variables was applied in 28 SDF. Of these, 23 were selected, and collections of milk and water used for milking management were performed. Three multivariate analysis techniques were used: exploratory factor analysis, hierarchical cluster analysis, and canonical discriminant analysis. Three production systems have been identified: Conventional system: Mature illiterate and rural farmers, small herds and farms, low technological level, less intensive management, and low milk production with in nature marketing (15 farms; 53.6%); Traditional system: Mature farmers with basic education, farms managed with hired labor, large herds and areas, extensive management, low technological level, high production of milk for the manufacture of cheese (6 farms; 21.43%); and Emerging system: Young farmers with a high level of education, small herds and farms, intensive management, intermediate technological level, and high milk production and productivity with in nature marketing (7 farms; 25.0%). The social, physical, livestock, herd management and technological, and productive indicators showed discriminatory power (P < 0.05) to differentiate the typologies. Milk and water traits were similar (P > 0.05) among the production systems. The average values of the milk composition are in the threshold of the Brazilian legislation, unlike the somatic cell count (CSS) and standard plate count (SPC). Antibiotic residue was not found in milk from any SDF.The water used in milking management was characterized by high counts of aerobic mesophilic bacteria and total and thermotolerant coliforms, hard water, and neutral pH. For the continuity of SDF in the Brazilian semiarid, it is essential (i) participation of young people in the sector; (ii) feed planning for the dry period; (iii) herd health calendar according to legislation; (iv) water treatment (chlorination) and use of alkaline detergent for use in milking management, and (v) formal marketing of milk and its derivatives. Finally, our results can be used to inform and support public decision-makers responsible for the formulation and implementation of livestock development policy in the Brazilian semiarid region and being useful for other drylands.

Popularisation of Clean Milk Production Practices through Farm Field School Approach

Small and marginal farmers of India contribute 80 per cent milk production. Quality milk production needs to be accomplished in smallholder dairy production system by adopting mastitis prevention measures through promotion of clean milk production (CMP) practices and techniques. In this milieu, Krishi Vigyan Kendra, Namakkal conducted a farm field school (FFS) on CMP at Samayasangali village of Pallipalayam taluka of Namakkal district. Farm school was conducted for twenty five women on fortnight interval focused on clean milk production practices along with scientific dairy farm management. The impact assessment was carried out with well-structured pre tested interview schedule and found that cent percent participant farm women were aware of clean milk production practices taught and more than half (60%) of them adopted regular teat dip for udder wash, cleaning of hands and utensils before milking and a small percentage (3%) of them adopted fortnightly usage of CMT kit for assessing subclinical mastitis.

Investigating the impact of information on the efficiency of smallholder dairy production systems in India and the lessons for livestock extension policy

Investigating the impact of information on the efficiency of smallholder dairy production systems in India and the lessons for livestock extension policy

Effective Mainstreaming of Agricultural Emissions into Climate Action Agenda: The Case of Institutions and Smallholder Dairy Production Systems, Western Kenya

Small-scale farming production systems are integral drivers of global sustainability challenges and the climate crisis as well as a solution space for the transition to climate compatible development. However, mainstreaming agricultural emissions into a climate action agenda through integrative approaches, such as Climate Smart Agriculture (CSA), largely reinforces adaptation–mitigation dualism and pays inadequate attention to institutions’ linkage on the generation of externalities, such as Greenhouse Gas (GHG) emissions. This may undermine the effectiveness of local–global climate risk management initiatives. Literature data and a survey of small-scale farmers’ dairy feeding strategies were used in the simulation of GHG emissions. The effect of price risks on ecoefficiencies or the amount of GHG emissions per unit of produced milk is framed as a proxy for institutional feedbacks on GHG emissions and effect at scale. This case study on small-scale dairy farmers in western Kenya illustrates the effect of local-level and sectoral-level institutional constraints, such as market risks on decision making, on GHG emissions and the effectiveness of climate action. The findings suggest that price risks are significant in incentivising the adoption of CSA technologies. Since institutional interactions influence the choice of individual farmer management actions in adaptation planning, they significantly contribute to GHG spillover at scale. This can be visualised in terms of the nexus between low or non-existent dairy feeding strategies, low herd productivity, and net higher methane emissions per unit of produced milk in a dairy value chain. The use of the Sustainable Food Value Chain (SFVC) analytical lens could mediate the identification of binding constraints, foster organisational and policy coherence, as well as broker the effective mainstreaming of agricultural emissions into local–global climate change risk management initiatives. Market risks thus provide a systematic and holistic lens for assessing alternative carbon transitions, climate financing, adaptation–mitigation dualism, and the related risk of maladaptation, all of which are integral in the planning and implementation of effective climate action initiatives.

What drives the adoption of fodder innovation(s) in a smallholder dairy production system? Evidence from a cross-sectional study of dairy farmers in India

The study in India involving 384 households found that 42.7% of dairy farmers adopted new forage varieties when varieties were released. The farmer’s resources, their caste, access to markets for milk and price received for milk had positive effects on the decision to adopt. Management of farms by women had negative effects on the adoption decision. Increased forage yield and ease of propagation and establishment were important reasons for adoption of varieties, e.g. the relative advantage of pearl millet × Napier grass (Cenchrus americanus × C. purpureus) vs. hedge lucerne (Desmanthus virgatus). Thus, researchers need to address these issues when developing new germplasm, if farmers are to readily adopt new varieties, especially in the case of resource-poor farmers.

Genomic evaluations using data recorded on smallholder dairy farms in low- to middle-income countries

Breeding has increased genetic gain for dairy cattle in advanced economies but has had limited success in improving dairy cattle in low- to middle-income countries (LMIC). Genetic evaluations are a central component of delivering genetic gain, because they separate the genetic and environmental effects of animals' phenotypes. Genetic evaluations have been successful in advanced economies because of large data sets and strong genetic connectedness, provided by the widespread use of artificial insemination (AI) and accurate recording of pedigree information. In smallholder dairy production systems of many LMICs, the limited use of AI and small herd sizes results in a data structure with insufficient genetic connectedness between herds to facilitate genetic evaluations based on pedigree. Genomic information keeps track of shared haplotypes rather than shared relatives captured by pedigree records. Therefore, genomic information could capture “hidden” genetic relationships, that are not captured by pedigree information, to strengthen genetic connectedness in LMIC smallholder dairy data sets. This study's objective was to use simulation to quantify the power of genomic information to enable genetic evaluation using LMIC smallholder dairy data sets. The results from this study show that (1) genetic evaluations using genomic information were more accurate than those using pedigree information in populations with a high effective population size and weak genetic connectedness; and (2) genetic evaluations modeling herd as a random effect had higher or equal accuracy than those modeling herd as a fixed effect. This demonstrates the potential of genomic information to be an enabling technology in LMIC smallholder dairy production systems by facilitating genetic evaluations with in situ records collected from herds of ≤4 cows. The establishment of routine genomic evaluations could allow the development of LMIC breeding programs comprising an informal set of nucleus animals distributed across many small herds within the target environment. These nucleus animals could be used for genetic evaluation, and the best animals could be disseminated to participating smallholder dairy farms. Together, this could increase the productivity, profitability, and sustainability of LMIC smallholder dairy production systems.

Performance of traditionally-managed Bunaji (White Fulani) cattle under smallholder dairy production systems in Oyo State, South-West, Nigeria

The remarkable reduction in tsetse fly and its vector trypanosomosis in the South-West zone of Nigeria have led to the development of smallholder dairy production which is predominantly practised by the Fulani agropastoralists in the zone. This study was conducted by the administration of structured questionnaires to farmers in the Derived savannah area of Oyo State in the South-West zone of Nigeria with aim of assessing the performance of traditionally managed Bunaji (White Fulani) cattle in this newly encroached zone by the Fulani pastoralists from the northern parts of the country. The survey showed that milk offtake or partial milk yield (0.6 kg/day), pregnancy rate (53.2%), calving rate (49.5%), calf crop (37.11%) and body condition score (4.3) were low and typical of tropical breeds of cattle. Also, average age at first calving (47.8 months) and calving interval (18.1 months) were on the high side. Majority (80%) of the dams produced their young ones during the wet season while a few ones (20%) calved during the dry season. Diarrhoea (84%), helminthosis (72%) and sand eating (64%) were the major diseases of calves in wet and dry season, respectively; whereas in addition to diarrhoea and sand eating, low milk production (90%) was peculiar to adult cattle in dry season. Calves’ overall mortality was 24.11% with majority (73.77%) occurring during the first week of life; it was higher in wet season (86.89%) compared to the dry season (13.11%). Overall mortality for adult cattle was 5.83% with the mortality, in contrast to the calves’ mortality, being higher in dry season (69.39%) than in wet season (30.61%), and the females (91.84%) more susceptible than the males (8.16%). The results indicate that the performance of traditionally-managed cattle in smallholder dairy production systems in Oyo State, South-West, Nigeria is poor and below their genetic potentials due to poor management.

Evaluation of Dairy Cattle Productivity in Smallholder Farms in Nyeri County, Kenya

Dairy cattle production contributes approximately 4.5% of the Kenyan National Gross Domestic Product, creates jobs along the value chain and plays a key role in food security. However, average milk yield per cow is still low under smallholder dairy production system despite concerted efforts to improve productivity. The purpose of this study was to evaluate the productivity of smallholder dairy farms in 2 sub-counties of Nyeri County. A semi structured questionnaire was administered to collect data on feed resources and feeding systems, breeds and breeding systems, calf management, age at first service (AFS), age at first calving (AFC), calving interval (CI), milk yield (MY) and lactation length (LL) in smallholder dairy farms. Data was analysed using Statistical Package for Social Sciences (SPSS). The dominant feed resources and feeding system were roughages (mostly Napier grass), concentrates and mineral supplements (87.2%) and stall feeding (74.2%). Majority of the farmers kept Friesians (82.2%) with (94.5%) using artificial insemination. Most of the farmers (83.5%) fed 2-4 litres of colostrum to the calves and the method of feeding was majorly bucket feeding (93.0%). High proportion of farmers (97.7%) fed the colostrum from 0-6 hours after calving and (59.6%) weaned calves at 3 months. The AFS was mainly 18-20 months and above, while the mean AFC, CI, and LL were 28.7±2.84, 15.2±5.11 and 10.0±4.90 months, respectively. The mean milk yield was 10.7±5.85 litres/cow/day. The main challenges to dairy cattle production were feed shortages (30.6%), low farmgate milk prices (28.3%) and high cost of concentrate feeds (17.8%). It was concluded that performance of dairy cattle in the study area was poor attributed mostly to feed shortages and low milk prices. To improve productivity, feed availability and cost together with farmgate price of milk should be addressed.

Comparison of different methods for consideration of multifunctionality of Peruvian dairy cattle in Life Cycle Assessment

In Andean dairy systems, livestock generates a daily income through the sale of milk and cheese but also fulfils other roles which are crucial for rural livelihoods such as the contribution of protein to local diets, the provision of draught power and organic fertilizer, the reduction of economic risk and the accrual of savings. The objective of this study was to compare different approaches to cope with multifunctionality of livestock in Life Cycle Assessment (LCA). Based on local data from a smallholder dairy production system in the Southern Peruvian Andes environmental impacts of 1 kg energy corrected milk (ECM) were calculated with LCA methodology considering nine livestock functions: production of dairy products (1) and meat (2) for the market, production of milk for family consumption (3) and as food for calves (4), provision of organic fertilizer (5) and draught power (6), role as savings asset (7), risk insurance (8) and part of family tradition (9). Impacts were distributed among these functions using different methodological approaches: NA, no allocation; EM, economic allocation to market products; ET, economic allocation to all livestock functions; FP, allocation according to farmers´ perception and SE, system expansion (substitution). The results varied considerably depending on the method used. 1 kg of ECM contributed to global warming with 1.65, 1.38, 1.25, 0.71 and 0.89 kg CO2-equivalents using mehods NA, EM, ET, FP and SE, respectively. Similar patterns were observed for acidification and eutrophication potentials. Enteric fermentation was the main source of greenhouse gases whereas eutrophication and acidification potentials were determined by alfalfa pasture management. The results of the study showed that: (i) LCA results are highly sensitive to the number and types of livestock functions considered and the allocation criteria applied, (ii) that the economic value of livestock functions does not necessarily reflect their importance for rural livelihoods and (iii) that the application of system expansion/substitution to livestock systems is limited due to lacking equivalency of functions and products from alternative production systems.

Towards a better understanding of breeding objectives and production performance of dairy cattle in sub-Saharan Africa: a systematic review and meta-analysis

Abstract The aim of this study was to examine breeding objectives and the impact of production systems and breed types on dairy cattle performance in sub-Saharan Africa (SSA). A total of 64 research studies published between 1980 and 2018 were used for qualitative analysis (qualitative synthesis) of farmers’, scientists’ and institutional dairy trait preferences. Meta-analysis was conducted to examine the production and reproduction performance of dairy cattle in smallholder and large-scale dairy production systems. Most data used were from smallholder farmers (60%), with the remainder from large-scale farms. Linear mixed-effect models were used to estimate marginal means of production and reproduction traits for different breed types in both production systems. Overall, the results showed that there was a higher emphasis on breeding for improved fertility, increased milk yield and disease resistance. Milk content (fat and protein percentages), temperament, body conformation and total milk cell count (a mastitis indicator) were rarely mentioned in published literature, mainly because of milk pricing policies being volume based. Frequency and multivariate analyses (cluster data analysis) for desirable animal traits suggested that multiple breeding objectives are needed, based on the perceived goals of different farmers and institutions towards genetic improvement for production, reproduction, disease resistance and functional and animal welfare traits. Regardless of the breed type, commercial large-scale farms had a higher milk yield (2857.0 ± 233.3) compared with smallholder dairy farms (2419.8 ± 617.39). Estimated marginal means for lactation milk yield of the three breed types Holstein-Friesian, non-Holstein-Friesian dairy breeds (Jersey, Guernsey, Red Dane, Brown Swiss and Ayrshire) and cross-breds ( Bos taurus x Bos indicus ) were 3148.5 ± 433.00, 2995.6 ± 456.36 and 1771.1 ± 328.52, respectively. Significantly shorter age at first calving and shorter calving intervals were observed in large-scale farms in comparison to smallholder farms ( p &lt; 0.05). No significant differences were noted for age at first calving, calving interval, days open and number of services per conception between the breed types. In conclusion, the present study suggests that (i) improvement of dairy cattle has focused on reproduction, production and disease resistance traits, reflecting the breeding objectives of farmers, scientists and institutions involved in dairy production; (ii) genetics plays a large role in increased dairy productivity in SSA and (iii) future dairy research should emphasise on the interactions between improved feeding, disease control and genetics at a production level to inform profitable combinations of dairy traits.

Genetic evaluation of test-day milk yields from smallholder dairy production systems in Kenya using genomic relationships

Efforts to improve dairy production in smallholder farming systems of East Africa over the past decade have had limited impact because of the lack of records on performance to guide targeted breeding programs. Estimates of genetic parameters in these systems are lacking. Using data generated through a project (“Germplasm for Dairy Development in East Africa”) in Kenya and a genomic relationship matrix from genotypic records, we examined the potential impact of different models handling contemporary groups or herd effects on estimates of genetic parameters using a fixed regression model (FRM) for test-day (TD) milk yields, and the covariance structure for TD milk yield at various stages of lactation for animals using a random regression model (RRM). Models in which herd groups were defined using production levels derived from the data fitted the data better than those in which herds were grouped depending on management practices or were random. Lactation curves obtained for animals under different production categories did not display the typical peak yield characteristic of improved dairy systems in developed countries. Heritability estimates for TD milk yields using the FRM varied greatly with the definition of contemporary herd groups, ranging from 0.05 ± 0.03 to 0.27 ± 0.05 (mean ± standard error). The analysis using the RRM fitted the data better than the FRM. The heritability estimates for specific TD yields obtained by the RRM were higher than those obtained by the FRM. Genetic correlations between TD yields were high and positive for measures within short consecutive intervals but decreased as the intervals between TD increased beyond 60 d and became negative with intervals of more than 5 mo. The magnitude of the genetic correlation estimates among TD records indicates that using TD milk records beyond a 60-d interval as repeated measures of the same trait for genetic evaluation of animals on smallholder farms would not be optimal. Although each individual smallholder farmer retains only a few animals, using the genomic relationship between animals to link the large number of farmers operating under specified environments provides a sufficiently large herd-group for which a breeding program could be developed.

Application of Multiple Unsupervised Models to Validate Clusters Robustness in Characterizing Smallholder Dairy Farmers

The heterogeneity of smallholder dairy production systems complicates service provision, information sharing, and dissemination of new technologies, especially those needed to maximize productivity and profitability. In order to obtain homogenous groups within which interventions can be made, it is necessary to define clusters of farmers who undertake similar management activities. This paper explores robustness of production cluster definition using various unsupervised learning algorithms to assess the best approach to define clusters. Data were collected from 8179 smallholder dairy farms in Ethiopia and Tanzania. From a total of 500 variables, selection of the 35 variables used in defining production clusters and household membership to these clusters was determined by Principal Component Analysis and domain expert knowledge. Three clustering algorithms, K-means, fuzzy, and Self-Organizing Maps (SOM), were compared in terms of their grouping consistency and prediction accuracy. The model with the least household reallocation between clusters for training and testing data was deemed the most robust. Prediction accuracy was obtained by fitting a model with fixed effects model including production clusters on milk yield, sales, and choice of breeding method. Results indicated that, for the Ethiopian dataset, clusters derived from the fuzzy algorithm had the highest predictive power (77% for milk yield and 48% for milk sales), while for the Tanzania data, clusters derived from Self-Organizing Maps were the best performing. The average cluster membership reallocation was 15%, 12%, and 34% for K-means, SOM, and fuzzy, respectively, for households in Ethiopia. Based on the divergent performance of the various algorithms evaluated, it is evident that, despite similar information being available for the study populations, the uniqueness of the data from each country provided an over-riding influence on cluster robustness and prediction accuracy. The results obtained in this study demonstrate the difficulty of generalizing model application and use across countries and production systems, despite seemingly similar information being collected.

Impacts of dairy cooperatives in smallholder dairy production systems: a case study in Assam

This paper assesses the impact of membership of dairy cooperative societies (DCS) on the performance of smallholder dairy production systems in Assam using matching techniques. Findings show that membership of DCS contributes towards improving yields of dairy animals, farm income and employment; and also, to household milk consumption. Nonetheless, it does not have a significant impact on technology adoption. The milk prices offered by dairy cooperatives are also less compared to the prices in wet market. These results indicate towards the need to improve dairy farmers linkages through cooperatives or other such instituions.