The effect of improving cow productivity, fertility, and longevity on the global warming potential of dairy systems

Invited review: Quantifying multiple burdens of dairy cattle production diseases and reproductive inefficiency-Current knowledge and proposed metrics

The economic burden of diseases and reproductive inefficiency in dairy cattle is evident and has been quantified. Dairy diseases and reproductive inefficiency are however associated with other issues as well, including animal welfare, environmental pressure, and public health risks. Quantifying these other issues is becoming important to help farmers make decisions. Quantification of the noneconomic burdens of diseases and reproductive inefficiency is rare and lacks an overview of approaches and metrics. The first aim of this paper is to provide trends for associating diseases and reproductive inefficiency with economic and noneconomic burdens of disease. The second aim is to provide a review of approaches and metrics used to quantify the noneconomic burdens of disease and reproductive inefficiency. For the economic burden of diseases and reproductive performance, only an overview of the approaches used to quantify the burden is provided. The final aim is to propose approaches and metrics for future quantification of noneconomic burdens caused by individual diseases. A literature search was conducted in Web of Science to identify scientific articles on mastitis, lameness, metabolic disorders, and reproductive inefficiency in dairy cows. The search was restricted to articles published between January 1, 2010 and December 31, 2022 and resulted in 7,565 articles. The total number of articles that mentioned the economic, animal welfare, public health, and environmental burden was 1,253, 428, 291, and 77, respectively. An increase in the percentage of articles mentioning the economic, animal welfare, and public health burden was observed between 2010 and 2022. Despite the 2,049 articles that mentioned one of the burdens, the results showed that approximately 10% of the articles quantified one or more of these burdens. The economic burden of diseases and reproductive inefficiency has been quantified in 154 articles and very few articles quantified the noneconomic burdens (9 articles for environment, 29 articles for public health, and 2 articles for animal welfare). Eleven articles were identified that quantified multiple burdens, and in all these studies the economic burden was combined with a noneconomic burden through a modeling approach (mainly simulation). We propose to link the noneconomic burdens to biological simulation models, and thus develop bioburden simulation models. Well-established approaches and metrics can be used to quantify economic, environmental, and public health burdens. For the economic impact, costs per cow per year can be assessed. A life cycle assessment can be performed for environmental impact and the public health impact can be assessed by a defined daily dose for antimicrobial use and disability-adjusted life years for zoonotic diseases. Regarding animal welfare, approaches and metrics to quantify the welfare impact of a diseased animal are not well established. For animal welfare, we propose a welfare-adjusted life years approach. The mentioned approaches and metrics are a proposal, and it is up to the scientific community to use them or, based on empirics and research experience, propose changes so that we will end up with robust approaches and metrics that enable us to compare research results and provide more evidence for animal health decision makers.

Effect of extended heat stress in dairy cows on productive and behavioral traits

This study evaluates the response of dairy cows to short and extended heat stressing conditions (from 1 to 28 days), as expressed in changes in their behavior. Due to climate change, heat stress and strong heat waves are frequently affecting the productivity and behavior of dairy cows. In the five years under study from 2018 to 2022, two were characterized by extremely strong heat waves occurring in the region analyzed in this study (Northern Italy). The dairy cattle farm involved in this study is located in Northern Italy and includes about 1 600 Holstein Friesian lactating dairy cows. Phenotypic data were provided by the Afimilk system and compromised behavioral and productive traits. Behavioral traits analyzed were activity, rest time, rest bouts, rest ratio, rest per bout and restlessness. Production traits were daily milk yield, average milking time, somatic cell count, fat percentage, protein percentage and lactose percentage. Climate data came from the National Aeronautics and Space Administration/Prediction of Worldwide Energy Resources database. Heat stress was analyzed considering Temperature-Humidity Index (THI) averaged over 28 different time windows of continuous heat stress. Results showed that rest time and milk yield were the two traits most affected by the increased THI. Rest time was immediately affected by high THI, showing a marked decrease already from 1d window and maintaining this all over the other windows. Furthermore, results show that rest time and rest ratio were only slightly negatively correlated with milk yield (-0.14 and -0.15). In addition, heat stress has a different effect depending on parity and lactation stages on the studied traits. In conclusion, the results indicate that heat stress increases activity and compromises milk production, rest time and milk quality traits. Results further suggest that rest time can be a better parameter than activity to describe the effects of heat stress on dairy cattle. The novel approach used in this study is based on the use of different time windows (up to 28 days) before the emergence of undesired THI and allows to identify the traits that are immediately influenced by the undesirable THI values and those that are influenced only after a prolonged heat stress period.

Enhancing Metabolism and Milk Production Performance in Periparturient Dairy Cattle through Rumen-Protected Methionine and Choline Supplementation

For dairy cattle to perform well throughout and following lactations, precise dietary control during the periparturient phase is crucial. The primary issues experienced by periparturient dairy cows include issues like decreased dry matter intake (DMI), a negative energy balance, higher levels of non-esterified fatty acids (NEFA), and the ensuing inferior milk output. Dairy cattle have always been fed a diet high in crude protein (CP) to produce the most milk possible. Despite the vital function that dairy cows play in the conversion of dietary CP into milk, a sizeable percentage of nitrogen is inevitably expelled, which raises serious environmental concerns. To reduce nitrogen emissions and their production, lactating dairy cows must receive less CP supplementation. Supplementing dairy cattle with rumen-protected methionine (RPM) and choline (RPC) has proven to be a successful method for improving their ability to use nitrogen, regulate their metabolism, and produce milk. The detrimental effects of low dietary protein consumption on the milk yield, protein yield, and dry matter intake may be mitigated by these nutritional treatments. In metabolic activities like the synthesis of sulfur-containing amino acids and methylation reactions, RPM and RPC are crucial players. Methionine, a limiting amino acid, affects the production of milk protein and the success of lactation in general. According to the existing data in the literature, methionine supplementation has a favorable impact on the pathways that produce milk. Similarly, choline is essential for DNA methylation, cell membrane stability, and lipid metabolism. Furthermore, RPC supplementation during the transition phase improves dry matter intake, postpartum milk yield, and fat-corrected milk (FCM) production. This review provides comprehensive insights into the roles of RPM and RPC in optimizing nitrogen utilization, metabolism, and enhancing milk production performance in periparturient dairy cattle, offering valuable strategies for sustainable dairy farming practices.

Does Replacing Maize with Barley Affect the Animal Performance and Rumen Fermentation, including Methane Production, of Beef Cattle Fed High-Concentrate Diets On-Farm?

Ruminants fed high-concentrate diets produce less enteric methane than those fed high-forage diets, but not all grains are equally effective in reducing methane production. This study aimed to examine, in farm conditions, the effects of a partial substitution of maize with barley on animal performance and rumen fermentation, including methane production, of intensively reared beef calves (ca. 0.9:0.1 concentrate to forage ratio). Ninety-six beef calves were fed a concentrate with 45.5% maize and 15% barley (n = 48; M) or a concentrate with 15.5% maize and 45% barley (n = 48; B). Both the concentrate and barley straw were offered ad libitum. The type of concentrate did not have a significant effect (p > 0.05) on final live weight, average daily gain, carcass dressing percentage or intake of concentrate and straw. Dry matter and organic matter digestibility were higher (p < 0.05) for the M (75.4% and 76.6%) than for the B (71.0% and 73.1%) treatment, but with no effect on digestible organic matter intake. In general, the majority cereal in the concentrate did not affect rumen fermentation, including methane production, or the degradability of dry matter and starch. A partial substitution of maize with barley in the concentrate offered to beef calves does not seem a promising strategy to decrease the emissions of enteric methane on-farm.

Dutch dairy farmers' perspectives on culling reasons and strategies

Since the abolishment of the milk quota system in Europe in 2014 and the introduction of environmental policies such as the phosphate rights system in the Netherlands, the reasons for culling dairy cows might have changed. The aim of this study was to determine the culling reasons for dairy cattle and to identify farmers' culling strategies and their intentions regarding the alteration of indicated culling strategies. To this end, an online questionnaire was distributed among dairy farmers nationally that resulted in 207 responses. Results showed that the most frequent culling reasons were related to problems with reproduction, udder, and hoof health. Primiparous cows were primarily culled for miscellaneous reasons such as injury, reproduction failure, and low milk yield. Multiparous cows were culled predominantly for reproduction failure, udder health and hoof health reasons. Most respondents indicated that they consider formulating a culling strategy, based on certain rules of thumb regarding the most common reasons for culling. Most farmers also reported that culling decisions on their farms were perceived to be unavoidable, though reproductive culling decisions are primarily voluntary. Most respondents stated that they intended to reduce the culling rate for better economic gain did not intend to alter the amount of replacement stock reared. The applied rules of thumb regarding culling strategies do not seem to have changed since the policy changes in dairy farming. The question remains whether farmers' rules of thumb might have made them unaware of the actual economic consequences of their culling strategies under the altered situation.

Climate change and socio-economic assessment of PLF in dairy farms: Three case studies

Precision Livestock Farming (PLF) techniques include sensors and tools to install on livestock farms and/or animals to monitor them and support the decision making process of farmers, finally early detecting alerting conditions and improving the livestock efficiency. Direct consequences of this monitoring include enhanced animal welfare, health and productivity, improved farmer lifestyle, knowledge, and traceability of livestock products. The indirect consequences, instead, include improved Carbon Footprint and socio-economic indicators of livestock products. In this context, the aim of this paper is to develop an indicator applicable to dairy cattle farming that takes into account concurrently these indirect consequences. The indicator was developed combining the three sustainability pillars (with specific criteria): environmental (carbon footprint), social (5 freedoms of animal welfare and antimicrobial use) and economic (cost of technology and manpower use). The indicator was then tested on 3 dairy cattle farms located in Italy, where a baseline traditional scenario (BS) was compared with an alternative scenario (AS) where PLF techniques and improved management solutions were adopted. The results highlighted that the carbon footprint reduced in all AS by 6-9 %, and the socio-economic indicators entailed improvements in animals and workers welfare with some differences based on the tested technique. Investing in PLF techniques determines positive effects on all/almost all the criteria adopted for the sustainability indicator, with case-specific aspects to consider. Being a user-friendly tool that supports the testing of different scenarios, this indicator could be used by stakeholders (policy makers and farmers in particular) to identify the best direction towards investments and incentive policies.

The association of herd performance indicators with dairy cow longevity: An empirical study

The associations between reproductive performance, milk yield and health status with the risk of culling, and thus with a cow's longevity, have been well documented at the individual cow level. Associations at individual cow level may, however, not be valid at herd level due to interrelated herd management aspects and/or policy restrictions. The objective of this study was to explore the association of herd performance indicators with herd-level dairy cow longevity under Dutch production conditions. Longevity was expressed by three different measures, viz. age at culling, lifetime milk production of culled cows and culling rate. The evaluated herd performance indicators included factors on milk production, youngstock rearing, reproduction and health performance as registered on 10 719 Dutch commercial dairy herds during the period 2007-2016. Averaged over herds and the evaluated period, the age of culled milking cows was 2 139 days (5.8 years, SD±298 days), the lifetime milk production of culled cows was 31 238 kg (SD±7,494 kg), and the culling rate was 0.24 (SD±0.08). A mixed linear regression modelling approach was applied to evaluate the association of each of the three longevity measures with the selected herd performance indicators. The results indicated that only four herd performance indictors (herd size, herd expansion, heifer ratio and the proportion of cows with potential subclinical ketosis) shared significant associations with all three longevity variables. Generally, the strength of the associations between each of the evaluated longevity measures and herd performance indicators was only limited. The absence of strong associations between the longevity measures and herd performance indicators reveal that there is potential of extending cattle longevity without affecting the herd performance in terms of milk production, reproduction and health. Moreover, only part of the observed variance in longevity among the herds over time was explained by the herd performance variables, indicating that differences in longevity at herd level may predominantly be determined by other factors, like farmers' attitude and strategic management.

Life cycle assessment of Parmigiano Reggiano PDO cheese with product environmental footprint method: A case study implementing improved slurry management strategies

The environmental impact of Parmigiano Reggiano PDO cheese was quantified using the Product Environmental Footprint Category Rules (PEFCRs) in a Traditional System (TS) and in an Improved Management System (IMS). The TS differs from IMS with respect to slurry management (raw slurry storage vs anaerobic digestion and storage of the liquid fraction of digestate) and application of nutrients to the field (by slurry tanker with a diverter plate vs soil injection at pre-sowing and side dressing). Two additional scenarios were evaluated by considering the possible environmental enhancement achievable by reducing enteric methane production and by using soybean grain produced in Italy as the protein source for animals' diets. The environmental impact was quantified both for 1 kg of fat and protein corrected milk (FPCM) and for the production of 10 g dry matter equivalent of cheese as single score. For the first assessment, the environmental impact results were 124 and 112 μPt kg FPCM^-1 for TS and IMS, respectively. In the second case, it was 10.8 μPt and 9.9 μPt 10 g dry matter equivalent^-1 of cheese, for TS and IMS, respectively. The specific cost for reducing the GHG emissions in this production chain was equal to 34 € Mg^-1 milk produced. Finally, although specific studies should consider the reduction of enteric methane emissions and the use of soybean grain nationally produced as feed source, the scenarios evaluated in this study highlighted some potential for environmental improvements. Even small environmental improvements to the Parmigiano Reggiano PDO cheese supply chain can bring substantial improvements to the sustainability of the food market, because of the widespread demand on the global market of Parmigiano Reggiano and of its chance of attracting consumers who are sensitive to environmental problems.

Review: Preference elicitation methods for appropriate breeding objectives

Breeding objectives of livestock and other agricultural species are usually profit maximising. The selection emphasis placed on specific traits to achieve a breeding objective is often informed by the financial value of a trait to a farm system. However, there are alternative, and complementary approaches to defining both the breeding objective and the selection emphasis placed on traits that are included in associated selection tools. These are based on the preferences of stakeholders, which are often heterogeneous and include broader values and motivations than profit. In this regard, stated preference methods are useful when considering traits that have either no discernible market value or whose value is not fully transferred via the market. Such approaches can guide more appropriate breeding decisions that are amenable to changing societal values, for example with reduced negative environmental externalities. However, while stated preference methods offer promising conceptualisations of value in genetic improvement programmes, there is still a substantial knowledge gap in terms of the current state of research and a catalogue of publications to date. This paper reviews publications of stated preference approaches in the field of livestock breeding (and some relevant crop breeding examples), providing a knowledge base of published applications and promoting their continued development and implementation towards the formulation of appropriate breeding objectives and selection indices. A systematic review of 84 peer-reviewed publications and an aggregate ranking of traits for the most commonly studied subject (cattle) reveals uncertainty in preference estimates which may be driven by (i) a diverse set of non-standardised methodologies, (ii) common oversights in the selection, inclusion and description of traits, and (iii) inaccurate representations of the respondent population. We discuss key considerations to help overcome these limitations, including avoiding methodological confinement to a disciplinary silo and reducing complexity so that the values of broader respondent groups may be accounted for.

Effect of Nutritional Variation and LCA Methodology on the Carbon Footprint of Milk Production From Holstein Friesian Dairy Cows

The UK livestock industry urgently needs to reduce greenhouse gas (GHG) emissions to contribute to ambitious climate change policy commitments. Achieving this requires an improved understanding of emission sources across a range of production systems to lower the burden associated with livestock products. Life cycle assessment (LCA) methods are used in this study to model milk production from two genetic merits of Holstein Friesian cows managed in two novel and two conventional UK dairy systems. Select merit cows sired by bulls with high predicted transmission for fat plus protein yield are compared with Control merit animals sired from UK average merit bulls. Cows were managed in conventional housed and grazed dairy systems with novel Byproduct and Homegrown feeding regimes. A LCA was used to quantify the effect of allocation and management of feed components on the carbon footprint of milk production. Natural variation in nutritional quality of dairy system rations was investigated to quantify uncertainty in the carbon footprint results. Novel production system data are used to assess the effect of introducing home grown legumes and co-product feeds. Control merit footprints across each of the management regimes were significantly higher (p&lt;0.001) in comparison with a high production Select merit, on average by 15%. Livestock emissions (enteric, manure management and deposition) and embedded emissions (purchased feeds, fertiliser, and pesticides) were also significantly higher from control merit cows (p&lt;0.01). Mass and economic allocation methods, and land use functional units, resulted in differences in performance ranking of the dairy systems, with larger footprints resulting from mass allocation. Pairwise comparisons showed GHG's from the systems to be significantly different in total and source category emissions, with significant differences in mean embedded emissions found between most management systems (p&lt;0.05). Monte Carlo simulated system footprints considering the effect of variation in feed digestibility and crude protein also differed significantly from system footprints using standard methods (p &lt; 0.001). Dairy system carbon footprint results should be expressed using multiple units and where possible calculations should incorporate variation in diet digestibility and crude protein content.

Environmental Impacts of Milking Cows in Latvia

Increasing pressures surrounding efficiency and sustainability are key global drivers in dairy farm management strategies. However, for numerous resource-based, social, and economic reasons sustainable intensification strategies are herd-size dependent. In this study, we investigated the environmental impacts of Latvia’s dairy farms with different management practices. The herd size-dependent management groups varied from extensively managed small herds with 1–9 cows, extending to stepwise more intensively managed herds with 10–50, 51–100, 100–200, and over 200 milking cows. The aim is to compare the environmental impacts of different size-based production strategies on Latvia’s dairy farms. The results show that the gross greenhouse gas emissions differ by 29%: from 1.09 kg CO2 equivalents (CO2e) per kg of raw milk for the farms with 51–100 cows, down to 0.84 kg CO2e/kg milk for farms with more than 200 cows. However, the land use differs even more—the largest farms use 2.25 times less land per kg of milk than the smallest farms. Global warming potential, marine eutrophication, terrestrial acidification, and ecotoxicity were highest for the mid-sized farms. If current domestic, farm-based protein feeds were to be substituted with imported soy feed (one of the most popular high-protein feeds) the environmental impacts of Latvian dairy production would significantly increase, e.g., land use would increase by 18% and the global warming potential by 43%. Environmental policy approaches for steering the farms should consider the overall effects of operation size on environmental quality, in order to support the best practices for each farm type and steer systematic change in the country. The limitations of this study are linked to national data availability (e.g., national data on feed production, heifer breeding, differences among farms regards soil type, manure management, the proximity to marine or aquatic habitats) and methodological shortcomings (e.g., excluding emissions of carbon sequestration, the use of proxy allocation, and excluding social and biodiversity impacts in life-cycle assessment). Further research is needed to improve the data quality, the allocation method, and provide farm-size-specific information on outputs, heifer breeding, manure storage, and handling.

A life cycle assessment study of dairy farms in northern Germany: The influence of performance parameters on environmental efficiency

Recently, consumers concerns towards an environmental friendly food production are growing. The dairy sector contributes to the production of important greenhouse gases such as methane. The life cycle assessment (LCA) method enables to quantify the emissions and the use of resources throughout the entire life cycle of a product. The aim of the current study was to investigate the influence of performance parameters on the level of important environmental impacts (global warming potential (GWP), freshwater eutrophication (FE), terrestrial acidification (TA) and agricultural land occupation (ALO)) associated with milk production. Therein, the environmental impacts were analyzed using LCA considering two separate datasets (total, continuous) from Northern German farms throughout the years 2004-2013. Therefore, the performance parameters determining the level of environmental impacts were identified using the partial least square method. Thereby, a differentiated analysis among regions with various soil characteristics (Heath, Hill, Marsh) was conducted additionally. Further, linear mixed models were applied to each of the environmental impact categories. Energy-corrected milk yield (ECM), ECM from roughage, feed efficiency and the use of concentrates were identified as the most important determinants of environmental impacts. In general, an increase in productivity, especially an increase in ECM per cow and an increase in the amount of ECM produced per area of agricultural land accompanied with an improvement in environmental efficiency. The type of feed used had the major impact on the level of environmental impacts, whereby both concentrates and roughage had disadvantages. These results were in line with previous studies. Although, this study provides additional information relating the most important determinants of different environmental impacts, including a differentiated consideration of the relationship between performance parameters and environmental efficiency among regions. Further analyses on specific soil characteristics and their impact on environmental efficiency are recommended. In line with the concept of eco-efficiency, useful mitigation strategies in practice need to be applied depending on individual framework conditions.

Invited review: Academic and applied approach to evaluating longevity in dairy cows

In its simplest form, longevity is defined as the ability to live a long life. Within the dairy industry, longevity has been defined and measured in many different ways, and the aim of this review is to disentangle the definitions and provide some clarity. Using a more standardized approach for defining and measuring longevity, both in academic discussions and on-farm application, we suggest using herd life (days) for time from birth until culling, and length of productive life (days) for time from first calving until culling. Despite identified benefits of extending the length of productive life, global trends in the time spent by dairy cattle in the herd have mostly been negative. Factors influencing herd life, such as health, rearing, environmental conditions, and management, are often ignored when longevity goals are evaluated, thereby underestimating the effect these factors have on defining overall longevity. Also, production efficiency, herd profitability, and welfare are not necessarily served by the longest life but rather by the optimized length of herd life instead. The majority of research has focused on the role of genetics on longevity. In this review, we provide insight into influences affecting dairy cow herd life as well as farm- and cow-level factors associated herewith. Finally, we suggest using herd life, including reproduction, production, health, and youngstock performance, for farm-level evaluation and length of productive life for time spent in the lactating herd.

Maintaining production while reducing local and global environmental emissions in dairy farming

While milk is a major agricultural commodity, dairy farming also supports a large share of global beef production. In Life Cycle Assessment (LCA) studies of dairy farming systems, dairy-beef production is often ignored or 'allocated off', which may give a distorted view of production efficiencies. This study combines LCA with Data Envelopment Analysis (DEA) to develop an indicator of eco-efficiency for each of 738 UK dairy farms (3624 data points in 15 years) that aggregates multiple burdens and expresses them per unit of milk and dairy-beef produced. Within the DEA framework, the importance (weight) of dairy-beef relative to milk is iteratively increased to quantify the environmental losses from heavily focussing on milk-production, via e.g. higher yields per cow, with consequent lower burdens per unit of milk, yet with lower dairy-beef production levels, where burdens for beef production are externalized. Then, the relationship between DEA eco-efficiency and a series of indicators of dairy farming intensity at animal- and farm-levels was studied with Generalized Additive Models (GAM). For all sets of DEA weights (proportion of deviance explained ranged between 68% and 82%) indicate that milk yield per cow and forage area, and larger dairy herds all have a positive effect on eco-efficiency, while concentrate fed per unit of milk and the forage area both have a negative effect (p < 0.05 for all modelled relationships). These findings suggest that more intensive and consolidated dairy farms can positively impact on eco-efficiency. However, as the DEA weight for dairy-beef relative to milk increases, the relationship between environmental efficiency and farming specialization (expressed as L milk per kg dairy-beef produced) reverses from positive to negative. In conclusion, dairy-beef production is pivotal in determining the wider environmental efficiency of dairy (and ruminant food) systems, and its under-representation in efficiency studies has generated a misleading approach to meeting emission targets.

A Survey of Dairy Cattle Behavior in Different Barns in Northern Italy

Simple Summary

The climate crisis is accompanied by an increasing number of heat waves that negatively affect the behavior of dairy cows and their welfare. To understand if and how this is affecting farms in Northern Italy, a survey was carried out on eight cattle farms located in the Lombardy region. Three periods were monitored for one year (thermoneutral, hot and cold seasons) using environmental sensors installed in the barn and accelerometers mounted on the hind leg of groups of cows. From the results, it emerged that cows react to high air temperature and humidity conditions by reducing their lying time, which negatively affects milk production. Four out of the eight investigated farms showed that the negative effects caused by heat stress were evident. Hence, the farmer should consider the possibility of improving the barn structure, for example with an efficacious forced ventilation system. Cattle welfare is the first step towards healthy and productive cows.

Abstract

Due to its increasing pressure on dairy cows, studies that investigate how to cope with heat stress are needed. The heat stress affects multiple aspects of cows’ lives, among which their behavior and welfare. In this study, a survey was carried out in eight farms located in Northern Italy to monitor and evaluate the environmental aspects of the barns and the behavioral responses of dairy cows. For one year, three periods were monitored: thermoneutral (T_S), hot (H_S) and cold (C_S) seasons. Temperature and relative humidity were measured by environmental sensors, and lying vs. standing time, number of lying bouts and their average duration were collected by accelerometers. The temperature-humidity index (THI) was quantified inside and outside of the barn. Results show that at the increase of the THI, behavioral adaptations occurred in all the farms, especially with a reduction of lying time and an increase of respiration rate. Four of the eight farms need interventions for improving the cows’ welfare. Here, environmental problems should be solved by introducing or improving the efficacy of the forced ventilation or by modifying the barn structure. Monitoring dairy barns with sensors and Precision Livestock Farming techniques can be helpful for future livestock farming to alert farmers on the need for their interventions to respond immediately to unwanted barn living conditions.

Dairy Cow Health and Greenhouse Gas Emission Intensity

The purpose of this review is to identify the main influencing factors related to dairy cow health as it impacts the intensity of greenhouse gas emissions considering known data presented in the literature. For this study, we define the emission intensity as CO2 equivalents per kilogram of milk. In dairy cows, a high dry matter (DM) intake (25 kg/d) leads to an higher absolute methane emission compared to a lower DM intake (10 kg/d). However, the emission intensity is decreased at a high performance level. The emissions caused by DM intake to cover the energy requirement for maintenance are distributed over a higher milk yield. Therefore, the emission intensity per kilogram of product is decreased for high-yielding animals with a high DM intake. Apart from that, animal diseases as well as poor environmental or nutritional conditions are responsible for a decreased DM intake and a compromised performance. As a result, animal diseases not only mean reduced productivity, but also increased emission intensity. The productive life-span of a dairy cow is closely related to animal health, and the impact on emission intensity is enormous. A model calculation shows that cows with five to eight lactations could have a reduced emission intensity of up to 40% compared to animals that have left the herd after their first lactation. This supports the general efforts to increase longevity of dairy cows by an improved health management including all measures to prevent diseases.

Genome-wide association mapping for dominance effects in female fertility using real and simulated data from Danish Holstein cattle

Exploring dominance variance and loci contributing to dominance variation is important to understand the genetic architecture behind quantitative traits. The objectives of this study were i) to estimate dominance variances, ii) to detect quantitative trait loci (QTL) with dominant effects, and iii) to evaluate the power and the precision of identifying loci with dominance effect through post-hoc simulations, with applications for female fertility in Danish Holstein cattle. The female fertility records analyzed were number of inseminations (NINS), days from calving to first insemination (ICF), and days from the first to last insemination (IFL), covering both abilities to recycle and to get pregnant in the female reproductive cycle. There were 3,040 heifers and 4,483 cows with both female fertility records and Illumina BovineSNP50 BeadChip genotypes (35,391 single nucleotide polymorphisms (SNP) after quality control). Genomic best linear unbiased prediction (BLUP) models were used to estimate additive and dominance genetic variances. Linear mixed models were used for association analyses. A post-hoc simulation study was performed using genotyped heifers’ data. In heifers, estimates of dominance genetic variances for female fertility traits were larger than additive genetic variances, but had large standard errors. The variance components for fertility traits in cows could not be estimated due to non-convergence of the statistical model. In total, five QTL located on chromosomes 9, 11 (2 QTL), 19, and 28 were identified and all of them showed both additive and dominance genetic effects. Among them, the SNP rs29018921 on chromosome 9 is close to a previously identified QTL in Nordic Holstein for interval between first and last insemination. This SNP is located in the 3’ untranslated region of gene peptidylprolyl isomerase like 4 (PPIL4), which was shown to be associated with milk production traits in US Holstein cattle but not known for fertility-related functions. Simulations indicated that the current sample size had limited power to detect QTL with dominance effects for female fertility probably due to low QTL variance. More females need to be genotyped to achieve reliable mapping of QTL with dominance effects for female fertility.

Breeding animals to feed people: The many roles of animal reproduction in ensuring global food security

As the population grows and shifts demographically, the resulting increase in demand for beef and milk necessitates improvements in the sustainability of ruminant livestock production systems. Ruminant livestock contribute to ensuring global food security because they have the ability to up-cycle non-human-edible products into meat and milk products with notable nutritional value. However, ruminant livestock also pose a challenge to global food sustainability because they are resource-intensive to produce and contribute substantially to agricultural greenhouse gas emissions. As such, improving environmental impacts of ruminant livestock production globally is an essential goal. There are a number of strategies that can be employed to enhance sustainability of ruminant production systems; however, improving reproductive efficiency is among the more efficient, because an increase in reproductive success will reduce the number of cows needed to produce a target quantity of beef. This reduction in the cow herd size helps limit the number of unproductive animals retained in the herd, thereby reducing the environmental maintenance cost of livestock production. Additionally, proper application of reproductive technologies enables faster and more targeted advances in genetic gains, which can be leveraged to produce phenotypes that are resource-use-efficient and well-adapted to their production environment. Optimizing reproductive efficiency can be accomplished through improved genetic selection for fertility and fecundity; applying more effective use of assisted reproductive technologies; and coupling reproductive and nutritional management to optimize likelihood of reproductive success. Collectively, applying these approaches will be essential when working to ensure ruminant livestock's contribution to global food security.

The effects of improved performance in the U.S. dairy cattle industry on environmental impacts between 2007 and 2017

The U.S. dairy industry considerably reduced environmental impacts between 1944 and 2007, primarily through improved dairy cow productivity. However, although milk yield per cow has increased over the past decade, whole-system environmental impact analyses have not been conducted over this time period, during which environmental modeling science has improved considerably. The objective of this study was to compare the environmental impact of U.S. dairy cattle production in 2007-2017. A deterministic model based on population demographics, metabolism, and nutrient requirements of dairy cattle was used to estimate resource inputs, nutrient excretion, and greenhouse gas (GHG) emissions per 1.0 × 106 t (one million metric t or MMT) of energy-corrected milk (ECM) produced in 2007 and 2017. System boundaries extended from the manufacture and transport of cropping inputs to milk at the farm gate. Milk transport, processing, and retail were not included. Dairy systems were modeled using typical management practices, herd population dynamics, and production data from U.S. dairy farms. Cropping data were sourced from national databases. The resources required to produce 1.0 MMT ECM in 2017 were considerably reduced relative to those required in 2007, with 2017 production systems using 74.8% of the cattle, 82.7% of the feedstuffs, 79.2% of the land, and 69.5% of the water as compared to 2007. Waste outputs were similarly reduced, with the 2017 U.S. dairy industry producing 79.4%, 82.5%, and 85.7% of the manure, N, and P excretion, respectively. Dairy production in 2017 emitted 80.9% of the CH4 and 81.5% of the N2O per 1.0 MMT ECM compared to 2007. Enteric and manure emissions contributed the major proportion (80%) of GHG emissions per unit of milk, with lesser contributions from cropping (7.6%) and fertilizer application (5.3%). The GHG emissions per 1.0 MMT ECM produced in 2017 were 80.8% of equivalent milk production in 2007. Consequently, although total U.S. ECM production increased by 24.9% between 2007 and 2017, total GHG emissions from this milk production increased by only 1.0%. In line with previous historical analyses, the U.S. dairy industry has made remarkable productivity gains and environmental progress over time. To maintain this culture of continuous improvement, the dairy industry must build on gains made to date and demonstrate its commitment to reducing environmental impacts while improving both economic viability and social acceptability.

Effects of Ketosis in Dairy Cows on Blood Biochemical Parameters, Milk Yield and Composition, and Digestive Capacity

Introduction

This study aimed to characterise the effects of ketosis on milk yield and composition and digestive capacity in transition dairy cows.

Material and Methods

Seven ketotic and seven healthy cows were housed in individual stalls for six days. Samples of plasma, milk, refused total mixed ration, and faeces were collected, and the blood biochemical parameters, milk yield and composition, dry matter intake, and faecal dry matter (FDM) production were determined.

Results

Compared with healthy cows, the ketotic cows had significantly higher concentrations of milk fat and citrate, but lower levels of milk protein and lactose. The cows exhibited a need for acid detergent fibre in forage and better digestion of neutral detergent fibre, starch, crude protein, and phosphorus than healthy cows, but more fat and gross energy were excreted in their faeces. Ketotic cows had higher energy-corrected milk yields and lower FDM than healthy cows.

Conclusion

Lower feed intake coinciding with the requirement to maintain high milk production is considered to be the cause of ketosis in dairy cows. Ketotic cows exhibited lower dry matter fat digestion.

Greenhouse gas emission intensity based on lifetime milk production of dairy animals, as affected by ration-balancing program

Smallholder dairying in India and other developing countries relies on low- and medium-productive animals, and the feeding is mainly based on crop residues and other agro-industrial by-products. The diets are generally nutritionally imbalanced, resulting in productive and reproductive inefficiencies. This also negatively affects the emission intensity (Ei). For the past 3 years, the National Dairy Development Board of India has been implementing large-scale ration-balancing (RB) program in field animals. The effect of feeding balanced rations on Ei was explored. A cradle to farm-gate life-cycle assessment, taking into account the lifespan milk production, was conducted on 163 540 lactating cows and 163 550 buffaloes in northern, southern, eastern and western India. The life-cycle assessment boundary included feed production, enteric fermentation and manure management during various stages of life. On the basis of economic allocation, emissions of methane (CH4) from enteric fermentation, CH4 from manure management, nitrous oxide from manure management and greenhouse gas (GHG), i.e. carbon dioxide (CO2), CH4 and nitrous oxide from feed production, contributed 69.9%, 6.3%, 9.6% and 14.2% in cows, and 71.6%, 7.4%, 12.6% and 8.4% in buffaloes, respectively, to the baseline (before RB) lifetime total GHG emissions. Average Ei based on economic, mass and digestibility allocation for ‘baseline versus after RB’ were 1.6 versus 1.1, 1.8 versus 1.2 and 1.7 versus 1.2 kg CO2-equivalent/kg fat and protein-corrected milk in cows and 2.3 versus 1.5, 2.5 versus 1.6 and 2.4 versus 1.5 kg CO2-equivalent/kg fat and protein-corrected milk in buffaloes, respectively. Feeding-balanced rations significantly improved milk production, but reduced Ei of milk on lifetime basis by 31.2% and 34.7% in cows and buffaloes, respectively. Implementation of RB program has shown considerable potential to reduce GHG emission intensity under smallholding dairy production system of India.

Effect of production quotas on economic and environmental values of growth rate and feed efficiency in sea cage fish farming

In sea cage fish farming, production quotas aim to constrain the impact of fish farming on the surrounding ecosystem. It is unknown how these quotas affect economic profitability and environmental impact of genetic improvement. We combined bioeconomic modelling with life cycle assessment (LCA) to calculate the economic (EV) and environmental (ENV) values of thermal growth coefficient (TGC) and feed conversion ratio (FCR) of sea bass reared in sea cages, given four types of quota commonly used in Europe: annual production (Qprod), annual feed distributed (Qannual_feed), standing stock (Qstock), and daily feed distributed (Qdaily_feed). ENV were calculated for LCA impact categories climate change, eutrophication and acidification. ENV were expressed per ton of fish produced per year (ENV(fish)) and per farm per year (ENV(farm)). Results show that irrespective of quota used, EV of FCR as well as ENV(fish) and ENV(farm) were always positive, meaning that improving FCR increased profit and decreased environmental impacts. However, the EV and the ENV(fish) of TGC were positive only when quota was Qstock or Qdaily_feed. Moreover, the ENV(farm) of TGC was negative in Qstock and Qdaily_feed quotas, meaning that improving TGC increased the environmental impact of the farm. We conclude that Qstock quota and Qdaily_feed quota are economically favorable to a genetic improvement of TGC, a major trait for farmers. However, improving TGC increases the environmental impact of the farm. Improving FCR represents a good opportunity to balance out this increase but more information on its genetic background is needed to develop breeding programs improving FCR.

Relative emissions intensity of dairy production systems: employing different functional units in life-cycle assessment

This study aimed to assess the merit and suitability of individual functional units (FU) in expressing greenhouse gas emissions intensity in different dairy production systems. An FU provides a clearly defined and measurable reference to which input and output data are normalised. This enables the results from life-cycle assessment (LCA) of different systems to be treated as functionally equivalent. Although the methodological framework of LCA has been standardised, selection of an appropriate FU remains ultimately at the discretion of the individual study. The aim of the present analysis was to examine the effect of different FU on the emissions intensities of different dairy production systems. Analysis was based on 7 years of data (2004 to 2010) from four Holstein-Friesian dairy systems at Scotland’s Rural College’s long-term genetic and management systems project, the Langhill herd. Implementation of LCA accounted for the environmental impacts of the whole-farm systems and their production of milk from ‘cradle to farm gate’. Emissions intensity was determined as kilograms of carbon dioxide equivalents referenced to six FU: UK livestock units, energy-corrected milk yield, total combined milk solids yield, on-farm land used for production, total combined on- and off-farm land used for production, and the proposed new FU–energy-corrected milk yield per hectare of total land used. Energy-corrected milk was the FU most effective for reflecting differences between the systems. Functional unit that incorporated a land-related aspect did not find difference between systems which were managed under the same forage regime, despite their comprising different genetic lines. Employing on-farm land as the FU favoured grazing systems. The proposed dual FU combining both productivity and land use did not differentiate between emissions intensity of systems as effectively as the productivity-based units. However, this dual unit displayed potential to quantify in a simple way the positive or negative outcome of trade-offs between land and production efficiencies, in which improvement in emissions intensity using one FU may be accompanied by deterioration using another FU. The perceived environmental efficiencies of different dairy production systems in terms of their emissions intensities were susceptible to change based upon the FU employed, and hence the FU used in any study needs to be taken into account in the interpretation of results.

Weather influences feed intake and feed efficiency in a temperate climate

A key goal for livestock science is to ensure that food production meets the needs of an increasing global population. Climate change may heighten this challenge through increases in mean temperatures and in the intensity, duration, and spatial distribution of extreme weather events, such as heat waves. Under high ambient temperatures, livestock are expected to decrease dry matter intake (DMI) to reduce their metabolic heat production. High yielding dairy cows require high DMI to support their levels of milk production, but this may increase susceptibility to heat stress. Here, we tested how feed intake and the rate of converting dry matter to milk (feed efficiency, FE) vary in response to natural fluctuations in weather conditions in a housed experimental herd of lactating Holstein Friesians in the United Kingdom. Cows belonged to 2 lines: those selected for high genetic merit for milk traits (select) and those at the UK average (control). We predicted that (1) feed intake and FE would vary with an index of temperature and humidity (THI), wind speed, and the number of hours of sunshine, and that (2) the effects of (1) would depend on the cows' genetic merit. Animals received a mixed ration, available ad libitum, from automatic feed measurement gates. Using >73,000 daily feed intake and FE records from 328 cows over 8 yr, we found that select cows produced more fat- and protein-corrected milk, and had higher DMI and FE than controls. Cows of both lines decreased DMI and fat- and protein-corrected milk but, importantly, increased FE as THI increased. This suggests that improvements in the efficiency of converting feed to milk may partially offset the costs of reduced milk yield owing to a warmer climate, at least under conditions of mild heat stress. The rate of increase in FE with THI was steeper in select cows than in controls, which raises the possibility that select cows use more effective coping tactics. This is, to our knowledge, the first longitudinal study on the effects of weather on FE. Understanding how weather influences feed intake and efficiency can help us to develop management and selection practices that optimize productivity under unfavorable weather conditions. This will be an important aspect of climate resilience in future.

Reproductive Systems for North American Dairy Cattle Herds

Reproductive inefficiency compromises the profitability of dairy herds and the health and longevity of individual cows. In the average dairy herd, the combination of estrus detection and ovulation synchronization protocols yields the best economic return. Genomic selection of animals is particularly profitable in situations in which little is known about their genetic potential. Biosensor systems in milking parlors may allow for the design of reproductive strategies tailored for cows according to their physiologic needs while optimizing economic return.

Modelling the Effect of Diet Composition on Enteric Methane Emissions across Sheep, Beef Cattle and Dairy Cows

Enteric methane (CH ₄ ) is a by-product from fermentation of feed consumed by ruminants, which represents a nutritional loss and is also considered a contributor to climate change. The aim of this research was to use individual animal data from 17 published experiments that included sheep ( n = 288), beef cattle ( n = 71) and dairy cows ( n = 284) to develop an empirical model to describe enteric CH ₄ emissions from both cattle and sheep, and then evaluate the model alongside equations from the literature. Data were obtained from studies in the United Kingdom (UK) and Australia, which measured enteric CH ₄ emissions from individual animals in calorimeters. Animals were either fed solely forage or a mixed ration of forage with a compound feed. The feed intake of sheep was restricted to a maintenance amount of 875 g of DM per day (maintenance level), whereas beef cattle and dairy cows were fed to meet their metabolizable energy (ME) requirement (i.e., production level). A linear mixed model approach was used to develop a multiple linear regression model to predict an individual animal's CH ₄ yield (g CH ₄ /kg dry matter intake) from the composition of its diet. The diet components that had significant effects on CH ₄ yield were digestible organic matter (DOMD), ether extract (EE) (both g/kg DM) and feeding level above maintenance intake: CH ₄ (g/kg DM intake) = 0.046 (±0.001) × DOMD - 0.113 (±0.023) × EE - 2.47 (±0.29) × (feeding level - 1), with concordance correlation coefficient ( CCC ) = 0.655 and RMSPE = 14.0%. The predictive ability of the model developed was as reliable as other models assessed from the literature. These components can be used to predict effects of diet composition on enteric CH ₄ yield from sheep, beef and dairy cattle from feed analysis information.

Cow-calf reproductive, genetic, and nutritional management to improve the sustainability of whole beef production systems

Optimizing efficiency in the cow-calf sector is an important step toward improving beef sustainability. The objective of the study was to use a model to identify the relative roles of reproductive, genetic, and nutritional management in minimizing beef production systems' environmental impact in an economically viable, socially acceptable manner. An economic and environmental diet optimizer was used to identify ideal nutritional management of beef production systems varying in genetic and reproductive technology use. Eight management scenarios were compared to a least cost baseline: average U.S. production practices (CON), CON with variable nutritional management (NUT), twinning cattle (TWN), early weaning (EW), sire selection by EPD using either on-farm bulls (EPD-B) or AI (EPD-AI), decreasing the calving window (CW), or selecting bulls by EPD and reducing the calving window (EPD-CW). Diets to minimize land use, water use, and/or greenhouse gas (GHG) emissions were optimized under each scenario. Increases in diet cost attributable to reducing environmental impact were constrained to less than stakeholder willingness to pay for improved efficiency and reduced environmental impact. Baseline land use, water use, and GHG emissions were 188 m, 712 L, and 21.9 kg/kg HCW beef. The NUT scenario, which assessed opportunities to improve sustainability by altering nutritional management alone, resulted in a simultaneous 1.5% reduction in land use, water use, and GHG emissions. The CW scenario improved calf uniformity and simultaneously decreased land use, water use, and GHG emissions by 3.2%. Twinning resulted in a 9.2% reduction in the 3 environmental impact metrics. The EW scenario allowed for an 8.5% reduction in the 3 metrics. The EPD-AI scenario resulted in an 11.1% reduction, which was comparable to the 11.3% reduction achieved by EPD-B in the 3 metrics. Improving genetic selection by using AI or by purchasing on-farm bulls based on their superior EPD demonstrated clear opportunity to improve sustainability. When genetic and reproductive technologies were adopted, up to a 12.4% reduction in environmental impact was achievable. Given the modeling assumptions used in this study, optimizing nutritional management while concurrently improving genetic and reproductive efficiency may be promising avenues to improve productivity and sustainability of U.S. beef systems.

How can grass-based dairy farmers reduce the carbon footprint of milk?

The Irish dairy industry aims to increase milk production from grass-based farms following the removal of the EU milk-quota system, but is also required to minimise greenhouse gas (GHG) emissions to meet European reduction targets. Consequently, the sector is under increasing pressure to reduce GHG emissions per unit of milk, or carbon footprint (CF). Therefore, the goal of the present study was to determine the main sources of the CF of grass-based milk production and to identify mitigation strategies that can be applied to reduce farm footprints. In total, the CF of milk was estimated for 62 grass-based dairy farms in 2014. The method used to quantify GHG emissions was a life cycle assessment (LCA), independently certified to comply with the British standard for LCA (PAS 2050). The LCA method was applied to calculate annual on- and off-farm GHG emissions associated with dairy production until milk was sold from the farm in CO2-equivalent (CO2-eq). Annual GHG emissions computed using LCA were allocated to milk on the basis of the economic value of dairy products and expressed per kilogram of fat- and protein-corrected milk to estimate CF. Enteric methane was the main source of the CF of milk (46%), followed by emissions from inorganic N fertilisers (16%), manure (16%) and concentrate feedstuffs (8%). The mean CF of milk from the 62 farms was 1.26 kg of CO2-eq per kilogram of fat- and protein-corrected milk, but varied from 0.98 kg to 1.67 kg as measured using the 95% confidence interval. The CF of milk was correlated with numerous farm attributes, particularly N-fertiliser, the percentage of grazed grass in the diet, and production of milk solids. Grass-based dairy farmers can significantly improve these farm attributes by increasing herd genetic merit, extending the length of the grazing season and optimising N fertiliser use and, thereby, reduce the CF of milk.

The Impacts of Climate Change Mitigation Strategies on Animal Welfare

The objective of this review is to point out that the global dialog on reducing greenhouse gas emissions in animal agriculture has, thus far, not adequately considered animal welfare in proposed climate change mitigation strategies. Many suggested approaches for reducing emissions, most of which could generally be described as calls for the intensification of production, can have substantial effects on the animals. Given the growing world-wide awareness and concern for animal welfare, many of these approaches are not socially sustainable. This review identifies the main emission abatement strategies in the climate change literature that would negatively affect animal welfare and details the associated problems. Alternative strategies are also identified as possible solutions for animal welfare and climate change, and it is suggested that more attention be focused on these types of options when allocating resources, researching mitigation strategies, and making policy decisions on reducing emissions from animal agriculture.

Methods to determine the relative value of genetic traits in dairy cows to reduce greenhouse gas emissions along the chain

Current decisions on breeding in dairy farming are mainly based on economic values of heritable traits, as earning an income is a primary objective of farmers. Recent literature, however, shows that breeding also has potential to reduce greenhouse gas (GHG) emissions. The objective of this paper was to compare 2 methods to determine GHG values of genetic traits. Method 1 calculates GHG values using the current strategy (i.e., maximizing labor income), whereas method 2 is based on minimizing GHG per kilogram of milk and shows what can be achieved if the breeding results are fully directed at minimizing GHG emissions. A whole-farm optimization model was used to determine results before and after 1 genetic standard deviation improvement (i.e., unit change) of milk yield and longevity. The objective function of the model differed between method 1 and 2. Method 1 maximizes labor income; method 2 minimizes GHG emissions per kilogram of milk while maintaining labor income and total milk production at least at the level before the change in trait. Results show that the full potential of the traits to reduce GHG emissions given the boundaries that were set for income and milk production (453 and 441kg of CO2 equivalents/unit change per cow per year for milk yield and longevity, respectively) is about twice as high as the reduction based on maximizing labor income (247 and 210kg of CO2 equivalents/unit change per cow per year for milk yield and longevity, respectively). The GHG value of milk yield is higher than that of longevity, especially when the focus is on maximizing labor income. Based on a sensitivity analysis, it was shown that including emissions from land use change and using different methods for handling the interaction between milk and meat production can change results, generally in favor of milk yield. Results can be used by breeding organizations that want to include GHG values in their breeding goal. To verify GHG values, the effect of prices and emissions factors should be considered, as well as the potential effect of variation between farm types.