Dataset Information

Data describing cattle performance and feed characteristics to calculate enteric methane emissions in smallholder livestock systems in Bomet County, Kenya.

ABSTRACT: This dataset describes the performance of cattle in smallholder livestock systems of Bomet county in western Kenya. Information on live weight, milk production and quality, herd dynamics, and other production parameters were collected from field visits. Animals were weighed on scales; milk yield was recorded using a Mazzican® milk collection and transport vessel provided to each farm and milk was analyzed for butterfat content (%). Pasture biomass yield was determined, and feed samples collected for each agro-ecological zone and nutrient composition was determined for nitrogen (N) using the Kjeldahl method and gross energy (GE) using a bomb calorimeter. Distance covered while grazing was determined using GPS collars fitted to several animals for three consecutive days per area. Enteric methane (CH₄) emissions factors (EF) were estimated for five animal classes to develop site-specific EFs as per the Intergovernmental panel on climate change (IPCC) protocol. This dataset has the potential to be used, amongst other purposes, for animal-scale life cycle assessment (LCA) to evaluate the efficacy of various greenhouse gas (GHG) mitigation options.

SUBMITTER: Ndung'u PW

PROVIDER: S-EPMC8661481 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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Data describing cattle performance and feed characteristics to calculate enteric methane emissions in smallholder livestock systems in Bomet County, Kenya.

Ndung'u Phyllis Wanjugu PW Kirui Peter P Takahashi Taro T du Toit Cornelius Jacobus Lindeque CJL Merbold Lutz L Goopy John Patrick JP

Data in brief 20211204

This dataset describes the performance of cattle in smallholder livestock systems of Bomet county in western Kenya. Information on live weight, milk production and quality, herd dynamics, and other production parameters were collected from field visits. Animals were weighed on scales; milk yield was recorded using a Mazzican® milk collection and transport vessel provided to each farm and milk was analyzed for butterfat content (%). Pasture biomass yield was determined, and feed samples collected ...[more]

PMID: 34934787

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Project description:IntroductionLivestock diseases are a big challenge for the livelihood of pastoralists in sub-Saharan Africa because they reduce livestock productivity and increase mortality. Based on the literature available there is limited understanding on how pastoralists prioritize these diseases in the context of their culture, ecosystems and livelihoods. A study was conducted to provide insights on lay prioritization of animal diseases by pastoralists in Kenya.MethodologyA qualitative study was undertaken between March and July 2021. Thirty in-depth interviews and six focus group discussions (FGDs) were conducted with community members to explore community attitudes on livestock diseases prioritization. Male and female livestock keepers were purposively selected and interviewed and they were all long-term residents of the area. Fourteen key informant interviews (KIIs) were conducted with professionals from different key sectors to provide detailed stakeholder perspectives on livestock diseases. The interviews were analyzed thematically using the QSR Nvivo software to identify the emerging themes related to the study objectives.ResultsThe pastoralists prioritized livestock diseases based on effect on their economic wellbeing, cultural values and utilization of ecosystem services. There were gender variabilities in how diseases were prioritized among the pastoralists. Men cited high priority diseases as foot and mouth disease and contagious bovine pleuropneumonia due to their regular occurrence and effect on livelihood. Notably, women regarded coenuruses as very important because it affected sheep and goats with a high mortality rate and lumpy skin disease because it rendered the meat from the carcasses inedible. Malignant catarrhal fever and trypanosomiasis were noted as some of the common diseases in the livestock-wildlife interface but not cited as priority diseases. Challenges related to disease control in pastoralist contexts exist including limited access to livestock treatment services, inadequate information on disease impact and complex environmental factors.ConclusionThis study sheds light on the body of knowledge in Kenya regarding livestock diseases and their prioritization by livestock keepers. This could aid in the development of a common disease control framework and prioritization at the local level which would take into consideration the dynamic socio-cultural, ecological, livelihood and economic contexts of the communities.

Project description:Greenhouse gas emissions, such as enteric methane (CH4) from ruminant livestock, have been linked to global warming. Thus, easily applicable CH4 management strategies, including the inclusion of dietary additives, should be in place. The objectives of the current study were to: (i) compile a database of animal records that supplemented monensin and investigate the effect of monensin on CH4 emissions; (ii) identify the principal dietary, animal, and lactation performance input variables that predict enteric CH4 production (g/d) and yield (g/kg of dry matter intake DMI); (iii) develop empirical models that predict CH4 production and yield in dairy cattle; and (iv) evaluate the newly developed models and published models in the literature. A significant reduction in CH4 production and yield of 5.4% and 4.0%, respectively, was found with a monensin supplementation of ≤24 mg/kg DM. However, no robust models were developed from the monensin database because of inadequate observations under the current paper's inclusion/exclusion criteria. Thus, further long-term in vivo studies of monensin supplementation at ≤24 mg/kg DMI in dairy cattle on CH4 emissions specifically beyond 21 days of feeding are reported to ensure the monensin effects on the enteric CH4 are needed. In order to explore CH4 predictions independent of monensin, additional studies were added to the database. Subsequently, dairy cattle CH4 production prediction models were developed using a database generated from 18 in vivo studies, which included 61 treatment means from the combined data of lactating and non-lactating cows (COM) with a subset of 48 treatment means for lactating cows (LAC database). A leave-one-out cross-validation of the derived models showed that a DMI-only predictor model had a similar root mean square prediction error as a percentage of the mean observed value (RMSPE, %) on the COM and LAC database of 14.7 and 14.1%, respectively, and it was the key predictor of CH4 production. All databases observed an improvement in prediction abilities in CH4 production with DMI in the models along with dietary forage proportion inclusion and the quadratic term of dietary forage proportion. For the COM database, the CH4 yield was best predicted by the dietary forage proportion only, while the LAC database was for dietary forage proportion, milk fat, and protein yields. The best newly developed models showed improved predictions of CH4 emission compared to other published equations. Our results indicate that the inclusion of dietary composition along with DMI can provide an improved CH4 production prediction in dairy cattle.

Project description:Supplementation of ruminant diets with the methane (CH4) inhibitor 3-nitrooxypropanol (3-NOP; DSM Nutritional Products, Switzerland) is a promising greenhouse gas mitigation strategy. However, most studies have used high grain or mixed forage-concentrate diets. The objective of this study was to evaluate the effects of supplementing a high-forage diet (90% forage DM basis) with 3-NOP on dry matter (DM) intake, rumen fermentation and microbial community, salivary secretion, enteric gas emissions, and apparent total-tract nutrient digestibility. Eight ruminally cannulated beef heifers (average initial body weight (BW) ± SD, 515 ± 40.5 kg) were randomly allocated to two treatments in a crossover design with 49-d periods. Dietary treatments were: 1) control (no 3-NOP supplementation); and 2) 3-NOP (control + 150 mg 3-NOP/kg DM). After a 16-d diet adaption, DM intake was recorded daily. Rumen contents were collected on days 17 and 28 for volatile fatty acid (VFA) analysis, whereas ruminal pH was continuously monitored from days 20 to 28. Eating and resting saliva production were measured on days 20 and 31, respectively. Diet digestibility was measured on days 38-42 by the total collection of feces, while enteric gas emissions were measured in chambers on days 46-49. Data were analyzed using the mixed procedure of SAS. Dry matter intake and apparent total-tract digestibility of nutrients (DM, neutral and acid detergent fiber, starch, and crude protein) were similar between treatments (P ≥ 0.15). No effect was observed on eating and resting saliva production. Relative abundance of the predominant bacterial taxa and rumen methanogen community was not affected by 3-NOP supplementation but rather by rumen digesta phase and sampling hour (P ≤ 0.01). Total VFA concentration was lower (P = 0.004) following 3-NOP supplementation. Furthermore, the reduction in acetate and increase in propionate molar proportions for 3-NOP lowered (P < 0.001) the acetate to propionate ratio by 18.9% as compared with control (4.1). Mean pH was 0.21 units lower (P < 0.001) for control than 3-NOP (6.43). Furthermore, CH4 emission (g/d) and yield (g/kg DMI) were 22.4 and 22.0% smaller (P < 0.001), respectively, for 3-NOP relative to control. Overall, the results indicate that enteric CH4 emissions were decreased by more than 20% with 3-NOP supplementation of a forage diet without affecting DM intake, predominant rumen microbial community, and apparent total-tract nutrients digestibility.

Dataset Information

Data describing cattle performance and feed characteristics to calculate enteric methane emissions in smallholder livestock systems in Bomet County, Kenya.

Publications

Data describing cattle performance and feed characteristics to calculate enteric methane emissions in smallholder livestock systems in Bomet County, Kenya.

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