Dairy Systems Research Articles

Strategies of positive deviants in fodder conservation among smallholder dairy farming systems in highlands and midlands of Kenya.

Fodder scarcity and low quality affect the productivity of dairy cattle in Kenya yet only few smallholder dairy farmers show positive deviance in fodder conservation. Information on the strategies of such positive deviant (PD) farmers is scanty. The objective of this study was to determine strategies that distinguish PDs from peers (non-PDs) in fodder conservation among smallholder dairy farmers in highlands and midlands of Kenya. A cross-sectional survey was conducted among farms producing and conserving fodder in Tharaka Nithi County. Multistage sampling procedures was used; purposive sampling of the Sub-counties and locations, random selection of villages and proportional selection of 246 farms through snowball chain referral. Data were collected on demographic, socio-economic, farm characteristics and fodder conservation. Farms were categorized as PDs (n = 24) or non-PDs (n = 97). The PDs conserved fodder adequate to last dry season (about 3 months) and had milk yield 15kg/cow/day and above, while non-PDs do not qualify for both criteria. Chi-square and T-test were used to analyze categorical and continuous variables respectively. Logit regression was used to examine independent variables that influence probability of PDs. Farmers with high school and tertiary education who accessed extension services were PDs while non-PDs had non-formal and primary education and access extension less. Farms conserving hay and silage dominated PDs. Land in hectare (ha) and herd sizes in Tropical Livestock Unit (TLU) distinguished PDs (1.7ha and 9.0 TLU) from non-PDs (0.7ha and 3.3 TLU). The strategies that distinguished PDs from non-PDs were allocating land to fodder production, high milk yield kg/cow/day, large herd size and access to extension services. Increasing access to extension and resources (land) raised chances of PDs in fodder conservation. Knowledge of PDs strategies is important for fodder conservation, improve productivity and inform direction of future research.

Association Between Dairy Production System and Milk Functionality Based on Analysis of miRNAs in Exosomes from Milk.

Dairy farming practices significantly affect the nutritional and functional properties of milk. This study compares miRNAs in milk exosomes from extensive and intensive dairy systems and explores their potential implications for human consumers. Extensive systems are believed to produce milk of higher quality with better animal welfare compared to intensive systems. Milk samples from eight extensive and nine intensive dairy farms were analysed. Milk-derived extracellular vesicles were isolated through sequential ultracentrifugation and characterised through Dynamic Light Scattering and Nanosight to determine the size and the concentration of the extracellular vesicles, in addition to immunoblotting to ensure the presence of exosome-specific proteins in their membrane. miRNA levels were quantified using RT-qPCR, and metabolic pathways associated with miRNAs showing significant differences between farm groups were analysed. EVs from extensive farms had higher concentrations. Notably, bta-miR-451 levels were significantly higher in milk from extensive farms (p = 0.021). Like human miRNA hsa-miR-451, it is linked to pathways related to Parkinson's disease and cancer. Our research suggests that milk production in extensive systems not only provides socioeconomic and environmental benefits but may also have positive effects on human health. Further research is warranted to explore the bioactive potential of these miRNAs and their implications for human health.

Powering sustainability: A techno-economic analysis of photovoltaic systems in dairy farming

ABSTRACT Dairy farming plays an indispensable role in the socio-economic growth of rural India. But, the modernization and sustainable growth of dairy farming relies critically upon the availability of reliable and affordable renewable electric energy. However, lack of access to electricity is a major challenge that needs to be addressed to encourage sustainable dairy farming. In this direction, the deployment of solar photovoltaic (PV) systems in dairy farms has enormous potential to combat the existing critical challenges of fossil fuels and rural energy crises. This investigation assesses the techno-economic viability of PV systems through detailed mathematical modeling and electrical load estimation using the MATLAB simulation environment. The study determines the availability of maximum of solar radiations at each instant, and optimizes the inclined surface to extract maximum solar power. The outcomes of the study reveal that deploying an off-grid PV system consisting of 20 PV modules of 335 Wp, 24 batteries of each 150 Ah, and a 10 kVA inverter meets the average electric load of 9.5 MWh/year for twenty-five years with one-day autonomy. The economic analysis comprised the life-cycle cost (LCC), annualized life-cycle cost (ALCC), and costs of electricity (COE) of the study under reference as US$13050, US$323.1, and US$ 0.02596/kWh, respectively. The study results in saving of 0.285 MT CO2 emissions for the total life span. The resulted stand-alone PV system is both economically and technically viable. The present results reinforce the dispersal of green energy measures for their implementation in rural dairy farms having similar climate conditions in the Indian context.

Transforming the feeding regime towards low-input increases the environmental impact of organic milk production on a case study farm in central germany

Abstract Purpose Despite the direct effect of the feeding regime on the environmental impacts of dairy farming systems, its level of intensity, particularly in organic systems, has rarely been investigated. This study compares the environmental impact of a high-input feeding regime with a grassland-based, low-input feeding regime scenario within an organic milk production system conducted on Gladbacherhof, the research farm of Justus Liebig University Giessen, in Central Germany. Methods An integrated Life Cycle Assessment (LCA) analysis was performed from a cradle-to-farm gate perspective to quantify five environmental impacts, namely Global Warming (GW), Non-Renewable Energy Use (NREU), Land Use (LU), Terrestrial Acidification (TA), and Freshwater Eutrophication (FE). All agronomic data of the Gladbacherhof research farm, averaged over the years 2010–2017, were included. When not directly measured on the farm, ecoinvent data were included. Results and discussion Contrary to our hypothesis, the results suggest that a grassland-based low-input system has a higher environmental impact as compared to a high-input system for each of the five impact categories when using fat and protein-corrected milk (FPCM) as the functional unit. A 50% reduction in concentrates and exclusion of maize silage from the feed ration in the modelled low-input production system lead to a 20% drop in milk yield. To balance the energy content in low-input feeding ration, longer grazing period and higher amount of hay, alfalfa, and grass silage are required. This in turn results in higher emissions from enteric fermentation, manure management, and feed production and hence in higher environmental impact, particularly for GW, TA, and FE. Conclusions This study is one of the few that directly explores the environmental impact of feeding intensity in an organic milk production system. Nevertheless, there is a lack of research on consolidated emission factors for several greenhouse gas (GHG) sources in organic livestock and cropping systems to perform more robust carbon footprint calculations that comply with the Intergovernmental Panel on Climate Change (IPCC) Tier 3 GHG reporting guidelines. To generalize the results at the regional or national scale, direct comparisons with a larger number of organic farms representative of high-input and low-input intensities are still essential.

Net zero initiative in U.S. beef and dairy systems: integrative on-farm recommendations for greenhouse gas reduction

Abstract Beef and dairy production systems play an important role in society, providing a variety of ecosystem services. U.S. beef and dairy production systems require being aligned with the global and national effort to stabilize the anthropogenic greenhouse gas (GHG) emissions in the atmosphere. This study adapted the nominal group technique framework to design a roadmap to achieving a net-zero GHG cattle supply chain in the U.S. with an emphasis on farm recommendations. Scientists with diverse expertise in sustainable beef and dairy production proposed, categorized, described, defined, and prioritized strategies that have the potential to significantly reduce GHG emissions, improve production system efficiencies, and promote sustainability. These strategies were presented to different stakeholders and classified according to the marginal GHG reduction, expected return on investment, and market readiness. Thus, strategies were defined for cow-calf and stocker, feedlot, and dairy operations, according to the characteristics of the cattle systems in the U.S. This net-zero roadmap presents a broad range of options for promoting sustainable cattle production in the U.S. Priority items for a research agenda to facilitate progress towards implementing this net-zero roadmap are described according to the dairy or beef production system and including the modulation of rumen fermentation, precision diet management, manure management, increasing animal and system efficiency, and genetic evaluation and selecting of efficient animals. The expected return on investment and market readiness of the proposed strategies depend on the technology type and system localization. Progress toward the net-zero goal depends on the widespread adoption of appropriate mitigation strategies. Future research programs must prioritize identified research needs to promote the wide adoption of the proposed strategies.

A systematic review and meta-analysis of cow-level factors affecting milk urea nitrogen and urinary nitrogen output under pasture-based diets

With dairy cattle farming under pressure to lower its environmental footprint it is important to find effective on-farm proxies for evaluation and monitoring of management practices aimed at reducing the risk of nitrogen (N) losses and optimizing N use efficiency of dairy farm systems. Urinary N (UN) is regarded as the most potent source of N emissions. In contrast to confinement systems, there have been few studies from pasture-based systems associating on-farm animal and nutritional factors with UN output. Thus, the aims of this meta-analysis were to collate a database from pasture-based research to: (a) investigate the associations of management, dietary, and animal variables with MUN concentration, and daily UN output; (b) describe the MUN-UN association; and (c) assess whether animal, management, and dietary factors influence the relationship. We developed a data set consisting of 95 observations representing 919 lactating dairy cattle fed pasture-based diets, which was compiled from 32 unique research publications that reported both MUN and UN output. Multi-level, mixed meta-analysis regression techniques were used to analyze the data. Initially, all variables were assessed as the sole fixed effect in a 2-level random effects model, accounting for within publication heterogeneity. Meta-regression techniques were then used to assess the relationship of all variables with MUN and UN output, respectively, accounting for 3 sources of variability: the sampling error of the individual observation, within publication heterogeneity, and among publication heterogeneity. At the univariable level, despite more than 10 dietary, animal, or management variables being significantly associated with MUN, none explained a large amount of the MUN variation. The variables that explained the greatest amount of variation were dietary crude protein (CP) content and the nitrogen: metabolizable energy content ratio, which explained about 33% and 31% of the variation in MUN concentrations, respectively. Combining factors in multiple regressions improved the model fit, such that the variation within publications explained by dietary CP and N intake increased to 40.0% in the final multiple meta-regression model. For UN output, individual variables explained a greater proportion of variance reported among observations, compared with MUN, whereby diet CP content (pseudo R2 = 66.1%), N to metabolizable energy intake ratio (pseudo R2 = 64.0%), N intake (pseudo R2 = 58.3%), and MUN (pseudo R2 = 43.5%) explained the greatest amount of the total variation. Milk urea nitrogen, N intake and dry matter intake were associated with UN output in the final multiple meta-regression model. Substantial heterogeneity existed in both MUN and UN among publications, with among publication heterogeneity accounting for 73.4% of all the variation noted in MUN, and 88.6% of all the variation in UN output. As such, the meta-analyses could not predict MUN and UN to any great extent. It is recommended that a consistent approach to measuring and reporting MUN concentrations and UN output is carried out for all future research in pasture-based systems.

Epidemiology of antimicrobial resistance in commensal E. coli from healthy dairy cattle on a Mediterranean pasture-based system of Australia: A cross-sectional study

This study aimed to determine the prevalence of antimicrobial resistance (AMR) in commensal E. coli from healthy lactating cows and calves in the Mediterranean pasture-based feeding dairy system of Western Australia (WA). Fecal samples were collected from healthy adult lactating cows and healthy calves from dairy farms in WA. Presumptive commensal E. coli was isolated from these samples and confirmed using matrix-assisted laser-desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Broth microdilution was used to assess the prevalence and the phenotypic AMR profiles of the E. coli isolates to 8 antimicrobial agents of dairy industry and human importance. The minimum inhibitory concentration (MIC) for each isolate was interpreted using the Epidemiologic Cutoff (ECOFF) and Clinical and Laboratory Standards Institute (CLSI) breakpoints. Genomic characterization provided multi-locus sequence types and AMR genes for a selection of isolates categorised as non-wild type (NWT) by ECOFF values for the combination of ampicillin, trimethoprim-sulfamethoxazole, and tetracycline. From a total of 1,117 fecal samples (633 adult, 484 calf) collected across 26 randomly selected farms, 891 commensal E. coli isolates were recovered (541 adult, 350 calf). Commensal E. coli classified as NWT was highest for ampicillin for both adult (68.8%; 95% CI = 64.7 - 72.7) and calf feces (67.1%; 95% CI = 62.0 - 72.0). A large proportion of tetracycline NWT and trimethoprim-sulfamethoxazole NWT organisms were also identified from calf feces, being 44.0% (95% CI = 38.7 - 49.4) and 24.6% (95% CI = 20.2 - 29.4) respectively. Clinical resistance prevalence was low, being higher for calves than for adult feces (ampicillin (adult: 7.8% (95% CI = 5.7 - 10.3); calf: 30.0% (95% CI = 25.2 - 35.1), tetracycline (adult: 6.3% (95% CI = 4.4 - 8.7); calf: 40.3% (95% CI = 35.1 - 45.6), and trimethoprim-sulfamethoxazole (adult: 2.6% (95% CI = 1.4 - 4.3); calf: 22.0% (95% CI = 17.7 - 26.7)). Commensal E. coli originating from calf feces was significantly higher in NWT prevalence compared with adult feces for ciprofloxacin (P = 0.023), gentamicin (P = 0.02), tetracycline (P < 0.001), and trimethoprim-sulfamethoxazole (P < 0.001). The overall number of antimicrobials an isolate was classified as NWT toward varied among farms and was significantly higher for isolates originating from calf than adult feces (P < 0.001). The strain type and sampling source of the commensal E. coli investigated were both associated with the commonality of the resultant resistance genome. Clinical resistance and NWT classification were highest for ampicillin, tetracycline, and trimethoprim-sulfamethoxazole, all antimicrobials commonly used in the treatment of dairy cattle in Australia. Though highly variable across farms, commensal E. coli isolated from healthy dairy calf feces had significantly higher NWT and multidrug resistance (MDR) prevalence compared with feces from healthy adult lactating dairy cows. The resistant genome identified in MDR isolates, though not always consistent with the phenotype, included QnrS1 and genes encoding AmpC β-lactamase and aminoglycoside phosphotransferase.

Updated method of estimating heat load for grazing dairy cattle

ABSTRACT Understanding heat stress in dairy cows is important for ensuring their welfare and productivity. While the Temperature Humidity Index is commonly used to determine heat stress conditions it does not consider outdoor factors (e.g. wind speed and solar radiation). To address this, the Grazing Heat Load Index (GHLI) which predicts respiration rate, an indicator of heat stress, was previously developed using data from the Waikato region in New Zealand. This study updated the GHLI using a weather data and animal heat stress indicators (e.g. respiration rate and drooling), collected from dairy herds in the Northland, Waikato, Canterbury, and Southland regions. A mixed-effects linear model, which included air temperature, solar radiation and wind speed as inputs was developed using data from these diverse locations. The updated model slightly outperformed the previous model on a validation dataset when predicting respiration rate. While air temperature remained the primary driver of respiration rate, solar radiation was an exacerbating factor, whereas wind exerted a mitigating effect. Challenges persist in characterising heat stress in conditions such as high wind speed. Non-linear modelling techniques could enhance the predictive capability of the GHLI model, thereby refining heat stress assessment in pasture-based dairy systems nationwide.

Nitrogen use efficiencies, flows, and losses of typical dairy farming systems in Inner Mongolia

Dairy farming is a notable source of nitrogen (N) emissions, impacting both atmospheric and aquatic ecosystems, thus necessitating a detailed analysis of nutrient dynamics to curtail nutrient wastage. However, N flow variability and its environmental ramifications differ markedly among dairy farms, and a holistic understanding of these differences is lacking in Inner Mongolia, the biggest dairy production province in China. Utilizing data from 187 dairy farms and employing the NUFER-farm model, this study assessed N flows, N use efficiency (NUE), and N losses across four predominant dairy farming systems in Inner Mongolia. These systems include traditional pastoral dairy farms (PF), smallholder dairy farms with croplands (SF), industrial landless farms (IDF), and coupled dairy cattle and cropland-intensive farms (CDF). Our findings indicate considerable differences in N flows, NUE, and losses among the systems. On average, N deposition and N fertilizer were the primary N sources for PF and SF, respectively, whereas IDF and CDF derived over 90% of their N inputs from purchased feeds. PF and SF recycled all available manure N on-farm, whereas IDF and CDF recycled only approximately 36% of the total available manure N. N losses constituted 39–72% of total N outputs, with ammonia emissions accounting for 68–73% of total N losses across all farm types. In particular, PF had a higher N loss per kilogram of dairy product than other systems. Farm-level NUE ranged from 17 to 35%, with manure management practices showing significant variability, underscoring the potential for enhanced strategies to reduce N losses through improved manure treatment.

Comparative study of first lactation performance of Norwegian Red crossbred cows with traditional breeds in New Zealand dairy systems

ABSTRACT Some New Zealand dairy farmers are using semen from Norwegian Red (NR) bulls to explore the performance of this breed under local grazing conditions. The objective of this study was to compare the first lactation performance of first cross NR cattle with traditional New Zealand breeds. Data were collected from six dairy farms in Southland, New Zealand, during 2022–2023 milk production seasons. Data were collected from 1178 first lactation cows including herd test of daily yields of milk, fat and protein and somatic cell counts, and persistency. Breeds included 386 NR cross (NRX), 231 Holstein Friesian (F), 84 Holstein Friesian cross (FX), 134 Holstein Friesian x Jersey (FJ) and 58 Jersey cross (JX) cows. Findings indicate F cows produced the greatest cumulative milk yield (3,744 kg), 138.6 kg more than NRX cows. There were no significant differences among the breed groups for milk yield and milk solids yield persistency and SCS (SCS = Log2 SCC). The total lactation milk yield of NRX cows was lower than that of the other breeds, excluding JX. These results pertain specifically to first lactation cows; therefore, it is necessary to undertake further analysis to evaluate the long-term productivity and longevity of NR breeds under New Zealand conditions.

Performance evaluation of Uruguayan dairy farming systems

In the last 20 years, the Uruguayan dairy sector has intensified and concentrated on higher cow productivity, maintaining the herd, smaller land, and fewer farms. The research aims are to identify, describe, and evaluate the economic performance of different types of dairy farms. A sample of 284 farms from the National Dairy Farm Survey 2019 was used (representing 2,021 dairies); using k-means Cluster analysis with the variables: cow productivity, stocking rate, land productivity, concentrate, roughage, and grass intake (per hectare). We identified six farm types, three with high participation of grass in the cows’ diets (HG, 60% or more of dry matter intake), and the other three focused on supplementation (HS); with three intensification levels (1-low, 2-intermediate and 3-high productivity per ha). For the 2018/19 season three types of farms presented the best economic performance (HS-3, HG-3, and HG-2), including those with the highest stocking rate and grass intake per hectare, and more than USD 225 Economic Farm Surplus (EFS) per hectare with the lower unitary cost. Other two types exhibited intermediate economic performance (HS-2 and HG-1) with EFS close to zero and unitary cost similar to price. And one type (HS-1) displayed the worst economic performance, with negative indicators and the largest number of farms with very low productivity.

Individualised feeding of concentrate supplement according to milk yield did not increase milk production in pasture-grazed cows near peak lactation

ABSTRACT In grazing systems, feeds other than pasture are often used to increase dry matter intake and milk production. The study aimed to evaluate the effect of individually feeding pasture-grazed dairy cows near peak lactation based on their individualised milk production compared with a flat-rate feeding regime. All cows in the flat-rate treatment were offered 4 kg wet weight (3.6 kg DM) of concentrate/d. In the individualised feeding treatment, cows were offered 6, 4, and 2 kg wet weight/d (5.4, 3.6 and 1.8 kg DM/d) in the high, moderate, and low production groups, respectively. Individualised feeding of concentrates based on cow milk production did not alter milk or milk component yield at a herd level, but increased milk yield and tended to increase yield of fat, protein, and lactose in cows in the medium milk yield tertile. Individualised feeding reduced milk protein yield in cows in the low milk yield tertile, compared with flat rate feeding. The results do not support individualised feeding in grazing dairy systems where the maximum level of concentrate offered/ is ≤ 6 kg DM/d and milk production/cow ≤30 kg milk/d or ≤2.5 kg fat and protein/d.

Temperament of the dairy cow relates to her maternal behaviour in a pasture-based extended suckling system

Cow-calf rearing is gaining interest in dairy systems as an alternative to calf separation soon after birth. One commonly articulated benefit of these ‘extended suckling’ systems is that they allow expression of highly motivated maternal behaviours. The quality of maternal expression is subject to natural variation, however, and could be influenced by the temperamental characteristics of the dam. This study assessed the relationship between cow temperamental characteristics and expression of maternal behaviours in a pasture-based extended suckling system. Sixteen dairy cows (Bos taurus) underwent social isolation, novel object and novel human tests at 4 months of pregnancy. A principal components analysis (PCA) was used to determine associations between cow responses in these tests. After parturition, the cows entered an extended suckling system (half-day contact) until calves were weaned. Cow-calf interactions at pasture were video recorded for 4 consecutive hours (∼09:00 AM – 1:00 PM) at weeks 3, 6 and 9 post-partum. These data were used to calculate a maternal behaviour score for cows by subtracting the frequency of “negative” maternal behaviours (i.e., agonistic behaviour delivered to own calf, rejecting own calf suckling attempt and rejecting attempted contact by own calf) from the frequency of “positive” maternal behaviours (i.e., nursing own calf, affiliative behaviour delivered to own calf and proximity to own calf). A Pearson correlation was then used to assess the relationship between factors scores and maternal scores. Three behavioural traits were identified from the PCA: boldness, anxiety and sociability. In general, cows delivered more affiliative behaviour to their calves than to other calves and to cows and nursed their own calf more than other calves. The maternal behaviour score varied (mean ± SD, 33 ± 13.4, minimum = 9, maximum = 49). Cows with higher loadings for boldness had a lower maternal behaviour score (p < 0.05). There was no correlation between maternal behaviour score and anxiety or sociability (p > 0.05). The lower maternal behaviour score of bold cows in this study might be influenced by their prioritisation of foraging and exploration over interactions with their calves. Despite the long-standing practice of calf separation soon after birth, the current study demonstrates that maternal abilities of pasture-based dairy dams persist. We conclude that cow temperamental characteristics are related to how the cows interacted with their calves.

Fat Profiles of Milk and Butter Obtained from Different Dairy Systems (High and Low Pasture) and Seasons (Spring and Fall): Focus on Healthy Fatty Acids and Technological Properties of Butter

Fat Profiles of Milk and Butter Obtained from Different Dairy Systems (High and Low Pasture) and Seasons (Spring and Fall): Focus on Healthy Fatty Acids and Technological Properties of Butter

Evaluation of the dairy sustainability assessment tool (DSAT) for dairy systems in East Africa

ABSTRACT Sustainability assessment of dairy systems is necessary to understand bottlenecks and to identify measures to enhance sustainability of the systems. The Dairy Sustainability Assessment Tool (DSAT) was developed with a focus on the facilitation of discussion on sustainability among dairy sector actors in East Africa. DSAT has been applied in several case studies, but the tool has not been systematically evaluated. The objectives of this study were to evaluate the strengths and weaknesses of DSAT and to compare its main features with similar dairy assessment tools for Africa. This evaluation consisted of a literature search to identify relevant assessment tools and an online survey about the tool among its users. DSAT was different from other tools compared with as it does not require input data from farm surveys as the assessments rely on expert opinion, and it can conduct assessments at farm, regional and national scales. Results also showed that DSAT was appropriate for holistic assessments of the sustainability of dairy systems in Africa by providing a good overview of threats to sustainability. Weaknesses were mainly the scoring of indicators, which tends to be subjective and the absence of numerical reference values for indicators. Therefore, improving DSAT requires addressing the identified weaknesses.

Influence of pH on thermal stability of mixed dairy and plant protein systems

SummaryThe growing global population has increased the protein needs and the combination of animal with plant proteins can be an effective strategy to meet future protein demand. This study aimed to investigate the impact of pH between 6.2 and 7.0 on the thermal stability of a 1:1 mixture of chickpea protein concentrate (CPC) and whey protein isolate (WPI), and their respective control. After heat treatment, CPC:WPI mixture showed an increase in viscosity (from 20.5 mPa.s at pH 7.0 to 110.8 mPa.s at pH 6.2, respectively), and particle size (from 5.7 to 56.5 μm at pH 7.0 and 6.2, respectively). The physical stability of the heat‐treated CPC:WPI mixture decreased, as the sediment increased from 3.3 mm at pH 7.0 to 7.8 mm at pH 6.2. This study highlighted the enhanced thermal stability of CPC:WPI at pHs closer to neutrality and offers valuable insights for the formulation of innovative plant protein‐enriched food.

Toward compatibility with national dairy production and climate goals through locally appropriate mitigation interventions in Kenya

CONTEXTLivestock are an important component of livelihoods in smallholder dairy systems in Africa, but are characterized by low animal productivity and large environmental impacts per unit of animal product (e.g. greenhouse gas emissions (GHG) intensities). Governments in African countries have set ambitious targets for dairy systems, but development of climate-smart strategies has been hindered by a scarcity of baseline data and local intervention trials. OBJECTIVEWe use a rich dataset from smallholder mixed dairy systems in Kenya to determine whether national climate and development goals for 2030 can be met using locally appropriate interventions. Interventions considered included improved herd management and feed interventions. METHODSWe conducted a yield gap analysis to determine the scope of the existing milk yield gaps, then evaluated the extent to which yield gaps could be closed using interventions in a second step. We outscaled our results to the national level to determine the potential impact of adopting our interventions on national dairy production and GHG emission goals using the FAO Global Livestock Environmental Assessment Model – interactive (GLEAM-i) tool. RESULTS AND CONCLUSIONSOur analysis showed that substantial yield gaps exist in Kenyan dairy systems (39 to 49% of attainable yields). These gaps could be closed by intervention packages but not by individual interventions alone. Our outscaled scenarios showed interventions can reduce milk GHG emission intensities (−6.5 to −27.4%), while absolute emissions would increase in most scenarios (−3.9 to +25.9%). To meet national milk production goals, we estimated that a large increase in animal numbers is needed by 2030 compared to 2010 (from ∼2.7 M to 4.5–7.1 M heads of cattle). However, most scenarios fell short of the emissions target (−4% to +48%) by 2030. It may be possible to narrowly meet Kenyan national milk production and GHG emission goals by 2030. SIGNIFICANCENational goals for milk production and reducing GHG emissions were only marginally compatible in Kenya. Other sectors of the economy will need to reduce emissions to ensure that food and nutrition security objectives are not jeopardized. In order to achieve national milk goals, there will be need to be a consummate increase in animal numbers even with the adoption of multiple interventions. To meet Kenya's national emissions goals, widespread adoption of several locally appropriate interventions will be required. International support will be needed to meet Kenya's conditional Nationally Determined Contributions under the 2015 Paris Agreement, as well as food and nutrition security goals.

Adoption of Sustainable Dairy Management Practices and its Effect on Farm Income: A Case of Dairy Farmers in Rubaya Sub-County, Mbarara District

Sustainable dairy management (SDM) practices aim to minimize environmental impact, promote animal welfare, ensure economic viability, and support social responsibility throughout the dairy production chain. The SDM practices that could improve sustainability of dairy farming systems in Uganda include milk management, animal health, feeding and breeding practices. Despite the numerous advantages that scientific literature reports for these dairy management practices, they are not always adopted by farmers because of various factors. The objectives of this study were to examine farmers’ adoption decisions towards Sustainable Diary Management (SDM) practices, as well as the economic impact of this adoption among dairy farmers in Rubaya Subcounty. The cross-sectional research design was applied to collect both quantitative and qualitative data using a semi-structured questionnaire. Data were collected using a household survey of 160 randomly selected respondents, from different villages within the study area. R Software Version 4.4.0 was used for data analysis. The results reveal that most of the SDM practices were adopted by over 50% of the dairy farmers. Only Artificial insemination, drying off animals, conservation fodder and concentrate feeding practices were adopted by less than 50% of the dairy farmers. The Multivariate logistic regression model results show that the adoption of SDM practices is significantly associated with varied demographic (Gender, age, household size); socio-economic (land size and household income); and institutional factors (access to agricultural credit, access to extension services, and membership to a farmer association). The study found out that adoption of SDM practices increased their farm income by UGX. 2,930,429/=, highly significant at 5% (p=0.02). The study recognizes two main pathways to increase the adoption of SDM practices: i) utilizing farmers’ knowledge and information sharing platforms; and addressing broader market and institutional failures

Predicting future adoption of early-stage innovations for smart farming: A case study investigating critical factors influencing use of smart feeder technology for potential delivery of methane inhibitors in pasture-grazed dairy systems

Globally, livestock farmers are challenged with reducing greenhouse gas emissions to mitigate climate change. A potential option for pasture-based dairy farmers involves including methane-inhibiting compounds in the diet. A novel approach to deliver these compounds with the required frequency and precision is via smart-feeders, an existing smart farming technology used to feed supplements automatically to animals in-paddock. For this innovation to be successful, however, it must integrate with farm systems and provide farmers with a positive value proposition. The aim of this study was to examine the farm system and technology factors influencing potential uptake of in-paddock smart technologies for delivering methane inhibitors in pasture-grazed systems. We utilized an adoption prediction tool (ADOPT) to model the adoption outcomes of smart-feeders as methane inhibitor delivery mechanisms on dairy farms, with input from industry experts and farmers via focus groups. The results indicated low adoption of smart-feeders in a pasture-based system context. This was further explored with a sensitivity analysis of seven critical ADOPT factors which were identified as influential through the farmer focus groups. We modelled the impact of the seven critical ADOPT factors for two smart-feeder concepts to evaluate their relative adoption potential. The adoption modelling showed that while factors such as technology cost and function were important, adoption would also be highly influenced by future regulation settings, innovation uncertainty, and the alignment with farmer values and worldviews about their farm system. This research highlighted that in-paddock delivery technology, and processes for its use on-farm, represents an early-stage innovation and therefore is vital that farmers and other stakeholders are involved in further development to ensure adoption factors are addressed.

Grid-Connected Photovoltaic System for Generating Energy to Dairy Farm Activities

Minas Gerais is the leading milk-producing state in Brazil, and many dairy activities are supplied with electricity by the cable aerial network of the electrical energy state company. Given that the Brazilian energy matrix relies primarily on hydroelectric power, studies on the potential of other renewable energy sources in the context of dairy farms are innovative. Additionally, frequent disturbances and interruptions have motivated the installation of solar energy systems on dairy farms. However, the scarcity of technical and scientific studies demonstrating the benefits of electricity generated from photovoltaic panels in Minas Gerais has caused dairy farmers to fear potential financial losses. In this study, grid-connected photovoltaic systems in dairy farms were evaluated, considering three fixed tilt angles for the panels (latitude - 10°, latitude, and latitude + 10°) and electrical energy demands of dairy activities associated with two herd sizes (100 and 150 cows). Meteorological databases and mathematical models were used to predict daily global radiation on tilted panels in dairy farms of two Brazilian municipalities of Minas Gerais State (Lavras and Paracatu). Energy consumption related to dairy activities was monitored for 12 months. For both municipalities, the best results were verified with the tilt angle of panels equal to the local latitude - 10°. The municipality with the lowest latitude (Paracatu) showed higher electricity generation potential. In all simulated scenarios, a greater energy surplus was found from late spring to early autumn (Southern Hemisphere), when the higher electricity generation by the photovoltaic panels met the elevated electrical energy demand of the dairy farms. A high energy surplus was also verified during midwinter, where lower energy consumption by the dairy farms compensated for the reduced availability of solar radiation. The proposed methodology can be adapted to other dairy farms, agricultural and urban buildings.