Herd-level versus animal-level variation in methane emission prediction in grazing dairy cattle

The Resilient Dairy Genome Project-A general overview of methods and objectives related to feed efficiency and methane emissions

The Resilient Dairy Genome Project (RDGP) is an international large-scale applied research project that aims to generate genomic tools to breed more resilient dairy cows. In this context, improving feed efficiency and reducing greenhouse gases from dairy is a high priority. The inclusion of traits related to feed efficiency (e.g., dry matter intake [DMI]) or greenhouse gases (e.g., methane emissions [CH4]) relies on available genotypes as well as high quality phenotypes. Currently, 7 countries (i.e., Australia, Canada, Denmark, Germany, Spain, Switzerland, and United States) contribute with genotypes and phenotypes including DMI and CH4. However, combining data are challenging due to differences in recording protocols, measurement technology, genotyping, and animal management across sources. In this study, we provide an overview of how the RDGP partners address these issues to advance international collaboration to generate genomic tools for resilient dairy. Specifically, we describe the current state of the RDGP database, data collection protocols in each country, and the strategies used for managing the shared data. As of February 2022, the database contains 1,289,593 DMI records from 12,687 cows and 17,403 CH4 records from 3,093 cows and continues to grow as countries upload new data over the coming years. No strong genomic differentiation between the populations was identified in this study, which may be beneficial for eventual across-country genomic predictions. Moreover, our results reinforce the need to account for the heterogeneity in the DMI and CH4 phenotypes in genomic analysis.

New insights in improving sustainability in meat production: opportunities and challenges

Treating livestock as senseless production machines has led to rampant depletion of natural resources, enhanced greenhouse gas emissions, gross animal welfare violations, and other ethical issues. It has essentially instigated constant scrutiny of conventional meat production by various experts and scientists. Sustainably in the meat sector is a big challenge which requires a multifaced and holistic approach. Novel tools like digitalization of the farming system and livestock market, precision livestock farming, application of remote sensing and artificial intelligence to manage production and environmental impact/GHG emission, can help in attaining sustainability in this sector. Further, improving nutrient use efficiency and recycling in feed and animal production through integration with agroecology and industrial ecology, improving individual animal and herd health by ensuring proper biosecurity measures and selective breeding, and welfare by mitigating animal stress during production are also key elements in achieving sustainability in meat production. In addition, sustainability bears a direct relationship with various social dimensions of meat production efficiency such as non-market attributes, balance between demand and consumption, market and policy failures. The present review critically examines the various aspects that significantly impact the efficiency and sustainability of meat production.

The carbon footprint of young-beef cattle finishing systems in the Eastern Plains of the Orinoco River Basin of Colombia

Introduction

Previous research has shown increased productivity amongst sown grass pastures compared to native savanna pastures by year-round grazing for fattening of adult and young Brahman (Bos indicus)-bred cattle in the well-drained native savanna ecosystem of the Colombian Orinoquía. But there is limited information on the carbon footprint (CF) of commercial young-Brahman heifers and steers reared throughout life on well-managed Brachiaria decumbens Stapf pastures.

Methods

The present study characterized growth, lifetime enteric methane (CH4) emissions, carcass carbon dioxide equivalent (CO2-eq) CH4 efficiency intensities (i.e., emissions per kg of product), and estimated the overall CF of young cattle grazing B. decumbens pastures subject to a range of daily liveweight gains (DLWGs; 0.428 – 0.516 kg) and fattening framework (405 – 574 kg). Weaning data from seven consecutive calving seasons in a commercial Brahman breeding herd continuously grazed on B. decumbens were integrated with a Microsoft Excel® dynamic greenhouse gas emission (GHGE) simulation of stockers-yearlings, and seven fattening, and processing scenarios.

Results

The model predicted that heifers subject to low and high DLWGs (0.428 vs 0.516 kg) and steers (0.516 kg) may be successfully fattened without supplementation assuming that animals had access to a well-managed grass pasture. Depending on the fattening strategy, kg CO2-eq CH4/kg edible protein values ranged from 66.843 to 87.488 ± 0.497 for heifers and from 69.689 to 91.291 ± 0.446 for steers.

Discussion

Assuming that forage on offer is at least 1,500-2,000 kg of dry matter/ha during the rainy season, all the simulated systems showed potential for C neutrality and net-zero C emission when considering GHGEs from the soil, pasture, and animal components vs the estimated soil C capture over seven seasons. However, under a more optimistic scenario, these beef systems could accomplish substantial net gains of soil C, over the period for which field data are available. Overall, this study projects the positive impact of the design of plausible fattening strategies on grasslands for improving cattle productivity and reducing emission intensities with concomitant increases in technical efficiency.

Characterization and mitigation option of greenhouse gas emissions from lactating Holstein dairy cows in East China

BACKGROUND

This study investigated greenhouse gas (GHG) emission characteristics of lactating Holstein dairy cows in East China and provided a basis for formulating GHG emission reduction measures. GreenFeed system was used to measure the amount of methane (CH₄) and carbon dioxide (CO₂) emitted by the cows through respiration. Data from a commercial cow farm were used to observe the effects of parity, body weight, milk yield, and milk component yield on CH₄ and CO₂ emissions.

RESULTS

Mean herd responses throughout the study were as follows: 111 cows completed all experimental processes, while 42 cows were rejected because they were sick or had not visited the GreenFeed system 20 times. On average, lactating days of cows was 138 ± 19.04 d, metabolic weight was 136.5 ± 9.5 kg, parity was 2.8 ± 1.0, dry matter intake (DMI) was 23.1 ± 2.6 kg/d, and milk yield was 38.1 ± 6.9 kg/d. The GreenFeed system revealed that CH₄ production (expressed in CO₂ equivalent, CO₂-eq) was found to be 8304 g/d, [Formula: see text]/DMI was 359 g/kg, [Formula: see text]/energy-corrected milk (ECM) was 229.5 g/kg, total CO₂ production (CH₄ production plus CO₂ production) was 19,201 g/d, total CO₂/DMI was 831 g/kg, and total CO₂/ECM was 531 g/kg. The parity and metabolic weight of cows had no significant effect on total CO₂ emissions (P > 0.05). Cows with high milk yield, milk fat yield, milk protein yield, and total milk solids yield produced more total CO₂ (P < 0.05), but their total CO₂ production per kg of ECM was low (P < 0.05). The total CO₂/ECM of the medium and high milk yield groups was 17% and 27% lower than that of the low milk yield group, respectively.

CONCLUSIONS

The parity and body condition had no effect on total CO₂ emissions, while the total CO₂/ECM was negatively correlated with milk yield, milk fat yield, milk protein yield, and total milk solids yield in lactating Holstein dairy cows. Measurement of total CO₂ emissions of dairy cows in the Chinese production system will help establish regional or national GHG inventories and develop mitigation approaches to dairy production regimes.