Genetic analysis of rumination time based on an analysis of 77,697 Israeli dairy cows

Reduction of methane emission may become necessary for sustainable milk production. Several studies indicate a relationship between rumination time and the level of methane emission. The objectives of the current study were to estimate environmental factors affecting daily rumination time in high-yielding dairy cattle, genetic parameters for rumination time across parities, and environmental and genetic correlations between rumination time and economic traits, and to predict the consequence of inclusion of this trait in the Israeli breeding index. The data included more than 30 million daily records from 77,697 Israeli Holstein cows for rumination time and milk production. A lactation measure of daily rumination time per cow was computed as the mean of the residuals from a linear model analysis with rumination time as the dependent variable. The independent variables were parity and the square root, linear, quadradic and inverse of DIM by parity. Because of the shape of the lactation curve for rumination time, separate linear model analyses were performed for records up to 40 DIM and records with >40 DIM. The phenotypic correlation between first- and second-parity lactations for rumination time was almost 0.8, and close to 0.7 for milk. The heritability of lactation rumination time was close to 0.44 for parities 1 to 3. Heritability for milk production decreased from 0.5 in first parity to 0.3 in third parity. For both traits, genetic correlations among parities were all >0.9. Thus, for routine genetic analysis of rumination time, records in the different parities can be considered the same trait. The genetic correlation between rumination time and milk on first parity was 0.25 and increased slightly with increase in parity. Genetic correlations between rumination time, based on the first 40 DIM, were economically unfavorable with retained placenta but economically favorable with metritis, ketosis, and displaced abomasum. Genetic correlations between rumination time and the 9 traits included in the Israeli breeding index (milk, fat, and protein production; SCS; female fertility; herd-life; milk production persistency; calving ease; and calf mortality) were all economically favorable, except for the correlation of 0.17 with SCS. With the current index, daily rumination time with a current mean of 536 min and SD of 90 min is expected to increase by 11 min/d after 10 yr of selection. Inclusion of this trait with a positive index weight equivalent to 10% of the index should increase rumination time by 19 min. All changes in expected gains due to inclusion of rumination time in the index were economically positive, except for fat and SCS. Inclusion of rumination time in the index should result in 1 kg less gain in fat, a miniscule gain of 0.03 for SCS; and gains of 1.5 kg protein, 0.3% female fertility, and 5 d herd-life. Even though the case for a genetic correlation between rumination time and methane emission is still weak, inclusion of this trait in the commercial index may be justified, considering that equipment is now commercially available for routine recording at reasonable cost.

Estimates of genetic parameters for rumination time, feed efficiency, and methane production traits in first-lactation Holstein cows

The large-scale recording of traits such as feed efficiency (FE) and methane emissions (ME) for use in genetic improvement programs is complex, costly, and time-consuming. Therefore, heritable traits that can be continuously recorded in dairy herds and are correlated with FE and ME traits could provide useful information for genetic evaluation. Rumination time has been suggested to be associated with FE, methane production (MeP; ME in g/d), and production traits at the phenotypic level. Therefore, the objective of this study was to investigate the genetic relationships among rumination time (RT), FE, methane and production traits using 7,358 records from 656 first-lactation Holstein cows. The estimated heritabilities were moderate for RT (0.45 ± 0.14), MeP (0.36 ± 0.12), milk yield (0.40 ± 0.08), fat yield (0.29 ± 0.06), protein yield (0.32 ± 0.07), and energy-corrected milk (0.28 ± 0.07), but were low and nonsignificant for FE (0.15 ± 0.07), which was defined as the residual of the multiple linear regression of DMI on energy-corrected milk and metabolic body weight. A favorable negative genetic correlation was estimated between RT and MeP (-0.53 ± 0.24), whereas a positive favorable correlation was estimated between RT and energy-corrected milk (0.49 ± 0.11). The estimated genetic correlation of RT with FE (-0.01 ± 0.17) was not significantly different from zero but showed a trend of a low correlation with dry matter intake (0.21 ± 0.13). These results indicate that RT is genetically associated with MeP and milk production traits, but high standard errors indicate that further analyses should be conducted to verify these findings when more data for RT, MeP, and FE become available.

Associations of Grazing and Rumination Behaviours with Performance Parameters in Spring-Calving Dairy Cows in a Pasture-Based Grazing System

This study investigated the relationship of the length of time spent grazing and ruminating with the performance parameters of spring-calved grazing dairy cows (n = 162) over the lactation period for three lactation seasons (n = 54 per season). The cows were Holstein Friesian (HFR), Jersey (JE), and a crossbreed of Holstein Friesian/Jersey (KiwiCross), with 18 cows from each breed. The cows were either in their 1st, 2nd, 3rd, or 4th lactation year, and had different breeding worth (BW) index values (103 < BW > 151). The cows were managed through a rotational grazing scheme with once-a-day milking in the morning at 05:00 h. The cows were mainly fed on grazed pastures consisting of perennial ryegrass (Lolium perenne), red clover (Trifolium pretense), and white clover (Trifolium repens), and received additional feeds on various days in the summer and autumn seasons. This study used an automated AfiCollar device to continuously record the grazing time and rumination time (min/h) of the individual cows throughout the lactation period (~270 days) for three consecutive years (Year-1, Year-2, and Year-3). The milk yield, milk fat, milk protein, milk solids, liveweight, and body condition score data of the individual animals for the study years were provided by the farm. PROC CORR was used in SAS to determine the correlation coefficients (r) between the behaviour and production parameters. A general linear model fitted with breed × lactation year, individual cows, seasons, feed within the season, grazing time, rumination time, as well as their interactions, was assessed to test the differences in milk yield, milk fat, milk protein, milk solids, liveweight, and body condition score. The type I sum of squares values were used to quantify the magnitude of variance explained by each of the study factors and their interactions in the study variables. Grazing time exhibited positive associations with MY (r = 0.34), MF (r = 0.43), MP (r = 0.22), MS (r = 0.39), LW (r = -0.47), and BCS (r = -0.24) throughout the study years. Rumination time was associated with MY (r = 0.64), MF (r = 0.57), MP (r = 0.52), and MS (r = 0.57) in all study years, while there were no effects of rumination time on LW (r = 0.26) and BCS (r = -0.26). Grazing time explained up to 0.32%, 0.49%, 0.17%, 0.31%, 0.2%, and 0.02%, and rumination time explained up to 0.39%, 6.73%, 4.63%, 6.53%, 0.44%, and 0.17% of the variance in MY, MF, MP, MS, LW, and BCS, respectively.

Daylong acoustic recordings of grazing and rumination activities in dairy cows

Monitoring livestock feeding behavior may help assess animal welfare and nutritional status, and to optimize pasture management. The need for continuous and sustained monitoring requires the use of automatic techniques based on the acquisition and analysis of sensor data. This work describes an open dataset of acoustic recordings of the foraging behavior of dairy cows. The dataset includes 708 h of daily records obtained using unobtrusive and non-invasive instrumentation mounted on five lactating multiparous Holstein cows continuously monitored for six non-consecutive days in pasture and barn. Labeled recordings precisely delimiting grazing and rumination bouts are provided for a total of 392 h and for over 6,200 ingestive and rumination jaw movements. Companion information on the audio recording quality and expert-generated labels is also provided to facilitate data interpretation and analysis. This comprehensive dataset is a useful resource for studies aimed at exploring new tools and solutions for precision livestock farming.

Comparison between the Behavior of Low-Yield Holstein-Friesian and Brown Swiss Cows under Barn and Pasture Feeding Conditions

Cow pasturing poses many logistical and nutritional problems. Animals have more difficulty accessing pasture feed and require more time to consume the equivalent amount of dry matter compared to total mixed ration (TMR) feed from a feed table. The study was conducted during August 2016-October 2017 on 64 Holstein-Friesian (HF) cows and 54 Brown Swiss (BS) cows. All animals were equipped with CowManager sensor devices, and the cows' behaviors were recorded: time spent on feed intake, rumination, physical activity, and rest. In winter, cows were mainly fed hay, while in summer, they took forage from the pasture or freshly cut forage provided in the barn. The study showed that the time of day had a significant (p < 0.001) effect on the cows' feeding behaviors. The study also showed behavioral differences between HF and BS breeds. HF cows, regardless of the location and type of feed provided, spent more time on feed intake and chewed less compared to the BS breed. These differences were observable in all studied lactation groups. Animals were most willing to take forage two hours before sunrise and two hours before sunset and showed an increased willingness to take feed immediately after leaving the milking parlor.

Individual differences in digesta retention and their relation to chewing in cattle-A pilot investigation

While information on individual differences in digesta mean retention time (MRT) might be interesting when selecting phenotypes for digestive efficiency, MRT measurements are prohibitively labour-intensive for large-scale application. Therefore, more easily measured proxies of MRT might be helpful. We used the opportunity of an experiment applying saliva stimulant in cattle to investigate the effect of different individual chewing behaviour on fluid and particle MRT with a consistent diet. Four non-lactating cattle (670-850 kg body mass [BM]) were used in a 4 × 4 Latin square design, treated with the saliva stimulant pilocarpine in dosages of 0, 1, 2.5 and 5 mg/kg BM per day. The cattle were fed hay with dry matter intake (DMI) assigned according to their metabolic body weight. MRT in the whole gastrointestinal tract (GIT), the reticulorumen (RR) and the distal tract were measured using Co-EDTA, Cr-mordanted fibre and La-mordanted fibre as markers representing fluid, small particles (2 mm) and large particles (1 cm), respectively. The chewing behaviour was measured via noseband pressure sensor and expressed as chewing frequency (chews per time) and chewing intensity (chews per DMI), both for total chewing (ingestion plus rumination) and rumination chewing alone. The animals differed considerably in chewing behaviour and MRT measures. BM did not show a significant effect on chewing behaviour and MRT measures, though it tended to negatively correlated to total chewing intensity. Chewing intensity exerted a significant negative influence on MRT of fluid and particles in the RR, which was not the case for chewing frequency. Chewing frequency showed a significant relationship with MRT of large particles in the GIT. We suggest that chewing behaviour could influence MRT in two ways: (i) by affecting saliva production via the masticatory-salivary reflex and subsequently, the fluid inflow to the RR; (ii) by contributing to particle size reduction. Should the link between chewing behaviour and MRT be corroborated in larger studies, chewing measures, with their large interindividual variation, could emerge as an easy-to-measure proxy for MRT characteristics.

Effects of extrinsic factors on some rumination patterns: A review

The rumen and its activity, rumination, are the characterizing traits of the suborder Ruminantia, and it is accompanied by related feeding habits and consequent animal behavior. Several extrinsic (not related to the animal itself) factors affect rumination behavior; most are reflected in rumination timing (considering overall daily duration as well as circadian differences in rumination patterns): age, environmental factors, and diet. For these reasons, great efforts have been sustained at the research level for monitoring rumination patterns. Currently, some research outcomes are applied at the farm level; others are still at the experimental level. All of these efforts are finalized mainly for the use of rumination pattern recording as an effective prediction tool for the early detection of health and welfare problems, both in a single head and at the herd level. Moreover, knowledge of the effects of extrinsic factors on rumination physiology represents a great challenge for improving the efficiency of ruminant livestock management, from the diet to the housing system, from parasites to heat stress. The present review deals mainly with the worldwide raised ruminant species.

Global Warming and Dairy Cattle: How to Control and Reduce Methane Emission

Agriculture produces greenhouse gases. Methane is a result of manure degradation and microbial fermentation in the rumen. Reduced CH4 emissions will slow climate change and reduce greenhouse gas concentrations. This review compiled studies to evaluate the best ways to decrease methane emissions. Longer rumination times reduce methane emissions and milk methane. Other studies have not found this. Increasing propionate and reducing acetate and butyrate in the rumen can reduce hydrogen equivalents that would otherwise be transferred to methanogenesis. Diet can reduce methane emissions. Grain lowers rumen pH, increases propionate production, and decreases CH4 yield. Methane generation per unit of energy-corrected milk yield reduces with a higher-energy diet. Bioactive bromoform discovered in the red seaweed Asparagopsis taxiformis reduces livestock intestinal methane output by inhibiting its production. Essential oils, tannins, saponins, and flavonoids are anti-methanogenic. While it is true that plant extracts can assist in reducing methane emissions, it is crucial to remember to source and produce plants in a sustainable manner. Minimal lipid supplementation can reduce methane output by 20%, increasing energy density and animal productivity. Selecting low- CH4 cows may lower GHG emissions. These findings can lead to additional research to completely understand the impacts of methanogenesis suppression on rumen fermentation and post-absorptive metabolism, which could improve animal productivity and efficiency.

Identification of Changes in Rumination Behavior Registered with an Online Sensor System in Cows with Subclinical Mastitis

The aim of the present study is to determine the relationship between subclinical mastitis and rumination behavior registered with an online sensor system. Based on the findings of the general clinical examination of 650 milking cows, 10 cows with subclinical mastitis (SCM) and 10 clinically healthy cows (HG) were selected (without clinical signs of any diseases). Rumination behavior biomarkers were registered with RumiWatch noseband sensors (RWS; ITIN + HOCH GmbH, Fütterungstechnik, Liestal, Switzerland). Sensors were implanted on the first day after calving. Data from the RWS 13 days before diagnosis of SCM and 13 days after diagnosis of SCM were compared with HG data from the same period. Healthy cows were checked alongside SCM cows on the same days. In our study, we found that healthy cows spent more time engaging in rumination and drinking (p < 0.05) and also had more boluses per rumination. Moreover, among cows with subclinical mastitis, rumination time from day 4 to day 0 decreased by 60.91%, drinking time decreased by 48.47%, and the number of boluses per rumination decreased by 8.67% (p < 0.05). The results indicate that subclinical affects time and rumination chews registered with sensor systems. However, additional studies with larger numbers of animals are required to confirm these results. Furthermore, the impact of heat stress, estrus, and other effects on rumination behavior biomarkers should be evaluated.

The Value of ‘Cow Signs’ in the Assessment of the Quality of Nutrition on Dairy Farms

The aim of this review is to provide dairy farm advisors, consultants, nutritionists, practitioners, and their dairy farmer clients with an additional toolkit that can be used in the assessment of the quality of their dairy cattle nutrition. Cow signs are behavioral, physiological, and management parameters that can be observed and measured. They are detected by examining and observing the cattle. Other physiological parameters such as fecal scoring, rumen fill, and body condition scoring are also included in ‘cow signs’. The assessment should be both qualitative and quantitative; for example, is the cattle individual lame and what is the severity of lameness. The ‘diagnosis’ of a problem should be based on establishing a farm profile of ‘cow signs’ and other relevant information. Information gathered through assessment of cow signs should be used as an advisory tool to assist and improve decision making. Cow signs can be used as part of an investigation and or farm audit.

The Effect of Rumination Time on Milk Performance and Methane Emission of Dairy Cows Fed Partial Mixed Ration Based on Maize Silage

Simple Summary

Greenhouse gas emission has attracted considerable public attention in recent years, driving the search for genetic, nutritional, and management strategies to reduce methane emissions and increase the sustainability of milk production. Rumination activity has an important function in feed particle size reduction, condition of feeding behavior, and feed intake as well as in stabilizing rumen fluid pH through saliva production. A total of 365 high-yielding Polish Holstein -Friesian multiparous dairy cows were included in the study covering 24 to 304 days of lactation. Next, the data from the cows were assigned to three groups based on daily rumination time: low rumination up to 412 min/day (up to 25th rumination percentile), medium rumination from 412 to 527 min/day (between the 25th and 75th percentile), and high rumination above 527 min/day (from the 75th percentile). We showed that a longer rumination time leads to a lower methane emission level. Therefore, strategies that increase chewing activity may be used to reduce the environmental impact of dairy cows production.

Abstract

The objective of this study was to determine the effect of the rumination time on milk yield and composition as well as methane emission during lactation in high-yielding dairy cows fed a partial mixed ration based on maize silage without pasture access. A total of 365 high-yielding Polish Holstein-Friesian multiparous dairy cows were included in the study covering 24 to 304 days of lactation. Methane emission, rumination time, and milk production traits were observed for the period of 12 months. Next, the data from the cows were assigned to three groups based on daily rumination time: low rumination up to 412 min/day (up to 25th rumination percentile), medium rumination from 412 to 527 min/day (between the 25th and 75th percentile), and high rumination above 527 min/day (from the 75th percentile). Rumination time had no effect on milk yield, energy-corrected milk yield, or fat and protein-corrected milk yield. High rumination time had an effect on lower fat concentration in milk compared with the medium and low rumination groups. The highest daily CH₄ production was noted in low rumination cows, which emitted 1.8% more CH₄ than medium rumination cows and 4.2% more than high rumination cows. Rumination time affected daily methane production per kg of milk. Cows from the high rumination group produced 2.9% less CH₄ per milk unit compared to medium rumination cows and 4.6% in comparison to low rumination cows. Similar observations were noted for daily CH₄ production per ECM unit. In conclusion, a longer rumination time is connected with lower methane emission as well as lower methane production per milk unit in high-yielding dairy cows fed a maize silage-based partial mixed ration without pasture access.

Association of Feed Efficiency, Feeding Rate, and Behaviour with the Milk Performance of Dairy Cows

Identification of the associations of cow feed efficiency with feeding behaviour and milk production is important for supporting recommendations of strategies that optimise milk yield. The objective of this study was to identify associations between measures of feed efficiency, feed intake, feeding rate, rumination time, feeding time, and milk production using data collected from 26 dairy cows during a 3 month period in 2018. Cows averaged (mean ± standard deviation) 2.2 ± 1.7 lactations, 128 ± 40 days in milk, 27.5 ± 5.5 kg/day milk, 1.95 ± 0.69 kg feed/1 kg milk—the measure used to express feed conversion ratio (FCR), 575 ± 72 min/day rumination time, and 264 ± 67 min/day feeding time during the observation period. The coefficient of variation for rumination time (min/d) was 12.5%. A mixed linear model was selected for analyses. The most feed inefficient cows with the highest FCR (≥2.6 kg feed/1 kg milk) showed the lowest milk yield (24.8 kg/day), highest feed intake (78.8 kg), highest feeding rate (0.26 kg/min) and BCS (3.35 point). However, the relative milk yield (milk yield per 100 kg of body weight) was the highest (4.01 kg/day) in the most efficient group with the lowest FCR (≤1.4 kg feed/1 kg milk). Our study showed that the most efficient cows with the lowest FCR (≤1.4 kg feed/1 kg milk) had the highest rumination time (597 min/day; p < 0.05), feeding time (298 min/day; p < 0.05), rumination/activity ratio (4.39; p < 0.05) and rumination/feeding ratio (2.04; p < 0.05). Less active cows (activity time 164 min/day; p < 0.05) were the most efficient cows with the lowest FCR (≤1.4 kg feed/1 kg milk). The behavioural differences observed in this study provide new insight into the association of feed behaviour and feed efficiency with milk performance. Incorporating feeding behaviour into the dry matter intake model can improve its accuracy in the future and benefit breeding programmes.

Comparing noninvasive sampling techniques with standard cannula sampling method for ruminal microbial analysis

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Ruminal cannula is the gold standard for sampling rumen contents but is limited to few animals.

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Noninvasive methods are needed as proxy for cannula to enable sampling larger numbers of cows.

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Saliva, rumination bolus, tube-derived rumen samples, and feces were compared with cannula samples.

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Microbial community in the solid fraction of tube samples mirrored that of cannula samples.

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Rumination bolus may serve as a proxy for cannula samples under certain conditions.

Rumen microbes play an important role in the conversion of indigestible plant material to energy and protein in dairy cows. Sampling for ruminal contents via cannula is considered the gold standard technique for microbial analysis, but the technique requires ruminally cannulated animals and specialized animal facilities. The purpose of this study was to determine whether other sampling methods and locations along the digestive tract may serve as noninvasive proxies to the cannula method for microbial analysis. Six ruminally cannulated lactating Holstein dairy cows were adapted to a standard total mixed ration for 2 wk and sampled during the third week. Sampling locations and methods included salivary content, rumination bolus (regurgitated digesta collected from the cow's mouth), feces, and rumen contents via stomach tube and cannula. Stomach tube and cannula samples differ in proportions of solid and liquid material and were therefore separated into whole (as collected), liquid, and solid fractions. Samples were collected at 0 (before feeding), 2, 4, 6, 8, and 12 h after feeding over 2 d. All samples were extracted for total genomic DNA and selected samples for metabolically active DNA (RNA), PCR-amplified for the V1-V2 region of the 16S rRNA bacterial gene, and analyzed for bacterial diversity using the QIIME2 pipeline followed by statistical analysis in R (https://www.R-project.org/). In DNA-based analysis, at the community level, saliva, rumination bolus, and fecal samples clustered in separate groups, whereas all fractions of stomach tube and cannula samples clustered together, indicating that microbial communities of stomach tube and cannula samples were homogeneous. Rumination bolus samples at 6, 8, and 12 h after feeding clustered with stomach tube and cannula samples, indicating that rumination bolus samples may be an alternative for cannula samples; however, time of sampling is critical for sampling of bolus digesta. Results of the RNA-based analysis of rumination bolus samples and solid samples from cannula and stomach tube at 0 and 6 h after feeding were similar. We concluded that the solid fraction of samples obtained via the stomach tube method may serve as a proxy for the solid fraction of whole ruminal contents obtained via cannula for DNA-based microbial investigations. Both rumination bolus and stomach tube solid samples may serve as proxies for cannula solid samples for RNA-based microbial analysis.

Body Condition Score, Rumination, Intake, Milk Production and Milk Composition of Grazing Dairy Cows Supplemented with Rumen-Protected Lysine and Methionine

The study utilised a pasture grazing based, voluntary traffic automatic milking system to investigate milk production of cows fed a pasture-based diet and supplemented with a pellet formulated with vs. without rumen-protected lysine and methionine (RPLM). The study adopted a switch-over design (over two periods of 5 and 10 weeks, respectively) and used 36 cows and equally allocated them into two experimental groups. The RPLM (Trial) pellet had 2% lower crude protein, but similar metabolizable energy content compared to the Control pellet. Pellet intake was 10.0 and 9.4 kg/day/cow. Milk yield was 36.2 and 34.4 kg/day/cow (p = 0.23), and energy corrected milk was 35.1 and 33.8 kg/day/cow (p = 0.076), and milk solids was 2.55 and 2.46 kg/cow/day (p = 0.073) in the Control and Trial groups, respectively. Milk fat%, milk protein%, milk fat: protein ratio, milking frequency and rumination time were not different between the two groups (p > 0.05). In period 1, plasma glucose was 3.1 mmol/L for both groups and milk urea were 150 and 127 mg/L in the Control and Trial groups, respectively. Both plasma glucose (as a proxy for energy supply) and milk urea (as a proxy for nitrogen use efficiency; NUE) were not different between groups (p > 0.05). This study showed that under a grazing pasture system, feeding lactating dairy cows a low protein pellet with RPLM supplementation, maintained milk production performance and NUE, compared with cows fed a high protein Control pellet diet with no RPLM. Further research should assess the long-term (seasonal) effects of feeding a diet formulated with RPLM on cow intake, health and reproductive performance.

Does grazing management provide opportunities to mitigate methane emissions by ruminants in pastoral ecosystems?

Agriculture, and livestock production in particular, is criticized for being a contributor to global environmental change, including emissions of greenhouse gases (GHG). Methane (CH₄) from grazing ruminants accounts for most of livestock's carbon footprint because a large share of them are reared under suboptimal grazing conditions, usually resulting in both low herbage intake and animal performance. Consequently, the CH₄ quota attributed to animal maintenance is spread across few or no animal outputs, increasing the CH₄ intensity [g CH₄/kg live weight (LW) gain or g CH₄/kg milk yield]. In this review, the generalized idea relating tropical pastures with low quality and intrinsically higher CH₄ intensity is challenged by showing evidence that emissions from animals grazing tropical pastures can equal those of temperate grasses. We demonstrate the medium-to-high mitigation potential of some grazing management strategies to mitigate CH₄ emissions from grazing ruminants and stress the predominant role that sward canopy structure (e.g., height) has over animal behavioral responses (e.g., intake rate), daily forage intake and resulting CH₄ emissions. From this ecological perspective, we identify a grazing management concept aiming to offer the best sward structure that allows animals to optimize their daily herbage intake, creating opportunities to reduce CH₄ intensity. We show the trade-off between animal performance and CH₄ intensity, stressing that mitigation is substantial when grazing management is conducted under light-to-moderate intensities and optimize herbage intake and animal performance. We conclude that optimizing LW gain of grazing sheep and cattle to a threshold of 0.14 and 0.7 kg/day, respectively, would dramatically reduce CH₄ intensity to approximately 0.2 kg CH₄/kg LW gain, as observed in some intensive feeding systems. This could represent a mitigation potential of around 55% for livestock commodities in pasture-based systems. Our results offer new insights to the debate concerning mitigation of environmental impacts of pastoral ecosystems.

Methane Emissions and Milk Fatty Acid Profiles in Dairy Cows Fed Linseed, Measured at the Group Level in a Naturally Ventilated Housing and Individually in Respiration Chambers

Simple Summary

Cows emit the greenhouse gas methane (CH₄) as a result of microbial feed digestion. Methane emissions can be reduced by adopting nutritional strategies, such as dietary supplementation of linseed. Additionally, the oil in linseed increases the proportion of favorable fatty acids in milk fat. This study evaluated the effect of linseed on CH₄ emission and milk fatty acid composition measured in a group of cows in a naturally ventilated barn and in individual cows in respiration chambers. The substantially higher proportions of favorable fatty acids in the milk of linseed-fed cows were detected in individual milk samples and in the milk of the herd. Therefore, the analysis of bulk milk could be a suitable control instrument for retailers. Visualizing the course of CH₄ emissions over a whole day showed slightly lower CH₄ values in linseed-supplemented individuals and groups. However, we found no significant reduction of CH₄ as a result of linseed supplementation. Feed supplements in concentrations that are effective in reducing CH₄ must show whether the reduction potential is comparable when determined at the group and individual levels.

Abstract

The present study evaluated the effects of linseed supplementation on CH₄ emission and milk fatty acid composition in dairy cows measured at the group level in an experimental dairy loose housing using a tracer gas technique and individually in tied stalls and respiration chambers. Cows (2 × 20) were maintained in two separate sections under loose-housing conditions and received a diet supplemented with extruded linseed (L) lipids (29 g·kg⁻¹ dry matter) or a control (C) diet containing corn flour. Subsequently, 2 × 6 cows per dietary group were investigated in a tied-housing system and respiration chambers. Substantially higher proportions of favorable milk fatty acids were recovered in L cows when compared with C cows at the group level, making the analysis of bulk milk a suitable control instrument for retailers. Linseed supplementation resulted in a slightly lower diurnal course of CH₄ emission intensity than the control at the group and individual levels. However, we found no more than a trend for a CH₄ mitigating effect, unlike in other studies supplementing similar linseed lipid levels. Feed supplements in concentrations that lead to a significant reduction in CH₄ emissions must show whether the reduction potential determined at the group and individual levels is comparable.

Mitigation of greenhouse gases in dairy cattle via genetic selection: 1. Genetic parameters of direct methane using noninvasive methods and proxies of methane

Records of methane emissions from 1,501 cows on 14 commercial farms in 4 regions of Spain were collected from May 2018 to June 2019. Methane concentrations (MeC) were measured using a nondispersive infrared methane detector installed within the feed bin of the automatic milking system during 14- to 21-d periods. Rumination time (RT; min/d) was collected using collars with a tag that registered time (minutes) spent eating and ruminating. The means of MeC and methane production (MeP) were 1,254.28 ppm and 182.49 g/d, respectively; mean RT was 473.38 min/d. Variance components for MeC, MeP, and RT were estimated with REML using pedigree and genomic information in a single-step model. Heritabilities for MeC and MeP were 0.11 and 0.12, respectively. Rumination time showed a slightly larger heritability estimate (0.17). The genetic correlation between MeP and MeC was high (>0.95), suggesting that selection on either trait would lead to a positive correlated response on the other. Negative correlations were estimated between RT and MeC (-0.24 ± 0.38) and MeP (-0.43 ± 0.35). Methane concentration and MeP had slightly positive correlations with milk yield (0.17 ± 0.39 and 0.21 ± 0.36), protein percentage (0.08 ± 0.32 and 0.30 ± 0.45), protein yield (0.22 ± 0.41 and 0.31 ± 0.35), fat percentage (0.02 ± 0.40 and 0.27 ± 0.36), and fat yield (0.27 ± 0.28 and 0.29 ± 0.28) from bivariate analyses. Rumination time had positive correlations with milk yield (0.41 ± 0.75) and protein yield (0.26 ± 0.57) and negative correlations with fat yield (-0.45 ± 0.32), protein percentage (-0.15 ± 0.38), and fat percentage (-0.40 ± 0.47). A positive approximated genetic correlation was estimated between fertility and MeC (0.10 ± 0.05) and MeP (0.18 ± 0.05), resulting in slightly higher CH₄ production when selecting for better fertility [days open estimated breeding values (EBV) are expressed with mean 100 and SD 10, inversely related to days from calving to conception; that is, greater days open EBV implies better fertility]. Positive correlations were also estimated for stature with MeC and MeP (0.30 ± 0.04 and 0.43 ± 0.04, respectively). Other type traits (chest width, udder depth, angularity, and capacity) were positively correlated with methane traits, possibly because of higher milk yield and higher feed intake from these animals. Rumination time showed positive EBV correlations with production traits and type traits, and negative correlations with somatic cell count and body condition score. Based on the genetic correlations and heritabilities estimated in this study, methane is measurable and heritable, and estimates of genetic correlations suggest no strong opposition to current breeding objectives in Spanish Holsteins.

Systematic Review and Meta-Analysis: Identification of Factors Influencing Milking Frequency of Cows in Automatic Milking Systems Combined with Grazing

More dairy farms (up to more than one in four in some countries) are equipped with automatic milking systems (AMS) worldwide. Because of the positive impacts of grazing, e.g., on animal welfare or on production costs, numerous researchers have published papers on the combination of AMS with grazing. However, pasture-based AMS usually causes a reduction in milking frequency (MF) compared to indoors systems. The objectives of this meta-analysis were to review publications on the impacts of pasture-based AMS on MF and mitigation strategies. First, data from 43 selected studies were gathered in a dataset including 14 parameters, and on which a Principal Component Analysis (PCA) was performed, leading to the description of four clusters summarizing different management practices. Multiple pairwise comparisons were performed to determine the relationship between the highlighted parameters of MF on milk yield (MY). From these different analyses, the relationship between MF and MY was confirmed, the systems, i.e., Clusters 1 and 2, that experienced the lowest MF also demonstrated the lowest MY/cow per day. In these clusters, grazed grass was an essential component of the cow's diet and low feeding costs compensated MY reduction. The management options described in Clusters 3 and 4 allowed maintenance of MF and MY by complementing the cows' diets with concentrates or partial mixed ration supplied at the AMS feeding bin or provided at barn. The chosen management options were closely linked to the geographical origin of the papers indicating that other factors (e.g., climatic conditions or available grasslands) could be decisional key points for AMS management strategies.

Estimation of spatial and temporal variability of pasture growth and digestibility in grazing rotations coupling unmanned aerial vehicle (UAV) with crop simulation models

Systematic monitoring of pasture quantity and quality is important to match the herd forage demand (pasture removal by grazing or harvest) to the supply of forage with adequate nutritive value. The aim of this research was to monitor, assess and manage changes in pasture growth, morphology and digestibility by integrating information from an Unmanned Aerial Vehicle (UAV) and two process-based models. The first model, Systems Approach to Land Use Sustainability (SALUS), is a process-based crop growth model used to predict pasture regrowth based on soil, climate, and management data. The second model, Morphogenetic and Digestibility of Pasture (MDP), uses paddock-scale values of herbage mass as input to predict leaf morphogenesis and forage nutritive value. Two field experiments were carried out on tall fescue- and ryegrass-based pastures under rotational grazing with lactating dairy cattle. The first experiment was conducted at plot scale and was used to calibrate the UAV and to test models. The second experiment was conducted at field scale and was used to test the UAV’s ability to predict pasture biomass under grazing rotation. The Normalized Difference Vegetation Index (NDVI) calculated from the UAV’s multispectral reflectance (n = 72) was strongly correlated (p < 0.001) to plot measurements of pasture biomass (R² = 0.80) within the range of ~226 and 4208 kg DM ha^-1. Moreover, there was no difference (root mean square error, RMSE < 500 kg DM ha^-1) between biomass estimations by the UAV (1971±350 kg ha^-1) and two conventional methods used as control, the C-Dax proximal sensor (2073±636 kg ha^-1) and ruler (2017±530 kg ha^-1). The UAV approach was capable of mapping at high resolution (6 cm) the spatial variability of pasture (16 ha). The integrated UAV-modeling approach properly predicted spatial and temporal changes in pasture biomass (RMSE = 509 kg DM ha^-1, CCC = 0.94), leaf length (RMSE = 6.2 cm, CCC = 0.62), leaf stage (RMSE = 0.7 leaves, CCC = 0.65), neutral detergent fiber (RMSE = 3%, CCC = 0.71), digestibility of neutral detergent fiber (RMSE = 8%, CCC = 0.92) and digestibility of dry matter (RMSE = 5%, CCC = 0.93) with reasonable precision and accuracy. These findings therefore suggest potential for the present UAV-modeling approach for use as decision support tool to allocate animals based on spatially and temporally explicit predictions of pasture biomass and nutritive value.

Is rumination time an indicator of methane production in dairy cows?

As long as large-scale recording of expensive-to-measure and labor-consuming traits, such as dry matter intake (DMI) and CH₄ production (CH₄P), continues to be challenging in practical conditions, alternative traits that are already routinely recorded in dairy herds should be investigated. An ideal indicator trait must, in addition to expressing genetic variation, have a strong correlation with the trait of interest. Our aim was to estimate individual level and phenotypic correlations between rumination time (RT), CH₄P, and DMI to determine if RT could be used as an indicator trait for CH₄P and DMI. Data from 343 Danish Holstein cows were collected at the Danish Cattle Research Centre for a period of approximately 3 yr. The data set consisted of 14,890 records for DMI, 15,835 for RT, and 6,693 for CH₄P. Data were divided in primiparous cows only (PC) and all cows (MC), and then divided in lactation stage (early, mid, late, and whole lactation) to analyze the changes over lactation. Linear mixed models, including an animal effect but no pedigree, were used to estimate the correlations among traits. Phenotypic and individual level correlations between RT and both CH₄P and DMI were close to zero, regardless of lactation stage and data set (PC or MC). However, CH₄P and DMI were highly correlated, both across lactation stages and data sets. In conclusion, RT is unsuitable to be used as an indicator trait for either CH₄P or DMI. Our study failed to validate RT as a useful indicator trait for both CH₄P and DMI, but more studies with novel phenotypes can offer different approaches to select and incorporate important yet difficult to record traits into breeding goals and selection indexes.

Invited review: Current perspectives on eating and rumination activity in dairy cows

Many early studies laid the foundation for our understanding of the mechanics of chewing, the physiological role of chewing for the cow, and how chewing behavior is affected by dietary characteristics. However, the dairy cow has changed significantly over the past decades, as have the types of diets fed and the production systems used. The plethora of literature published in recent years provides new insights on eating and ruminating activity of dairy cows. Lactating dairy cows spend about 4.5 h/d eating (range: 2.4-8.5 h/d) and 7 h/d ruminating (range: 2.5-10.5 h/d), with a maximum total chewing time of 16 h/d. Chewing time is affected by many factors, most importantly whether access to feed is restricted, intake of neutral detergent fiber from forages, and mean particle size of the diet. Feed restriction and long particles (≥19 mm) have a greater effect on eating time, whereas intake of forage neutral detergent fiber and medium particles (4-19 mm) affects rumination time. It is well entrenched in the literature that promoting chewing increases salivary secretion of dairy cows, which helps reduce the risk of acidosis. However, the net effect of a change in chewing time on rumen buffing is likely rather small; therefore, acidosis prevention strategies need to be broad. Damage to plant tissues during mastication creates sites that provide access to fungi, adhesion of bacteria, and formation of biofilms that progressively degrade carbohydrates. Rumination and eating are the main ways in which feed is reduced in particle size. Contractions of the rumen increase during eating and ruminating activity and help move small particles to the escapable pool and into the omasum. Use of recently developed low-cost sensors that monitor chewing activity of dairy cows in commercial facilities can provide information that is helpful in management decisions, especially when combined with other criteria. Although accuracy and precision can be somewhat variable depending on sensor and conditions of use, relative changes in cow behavior, such as a marked decrease in rumination time of a cow or sustained low rumination time compared with a contemporary group of cows, can be used to help detect estrus, parturition, and some illnesses. This review provides a comprehensive understanding of the dietary, animal, and management factors that affect eating and ruminating behavior in dairy cows and presents an overview of the physiological importance of chewing with emphasis on recent developments and practical implications for feeding and managing the modern housed dairy cow.

Does the diurnal pattern of enteric methane emissions from dairy cows change over time?

Diet manipulation and genetic selection are two important mitigation strategies for reducing enteric methane (CH4) emissions from ruminant livestock. The aim of this study was to assess whether the diurnal pattern of CH4 emissions from individual dairy cows changes over time when cows are fed on diets varying in forage composition. Emissions of CH4 from 36 cows were measured during milking in an automatic (robotic) milking station in three consecutive feeding periods, for a total of 84 days. In Periods 1 and 2, the 36 cows were fed a high-forage partial mixed ration (PMR) containing 75% forage, with either a high grass silage or high maize silage content. In Period 3, cows were fed a commercial PMR containing 69% forage. Cows were offered PMR ad libitum plus concentrates during milking and CH4 emitted by individual cows was sampled during 8662 milkings. A linear mixed model was used to assess differences among cows, feeding periods and time of day. Considerable variation was observed among cows in daily mean and diurnal patterns of CH4 emissions. On average, cows produced less CH4 when fed on the commercial PMR in feeding Period 3 than when the same cows were fed on high-forage diets in feeding Periods 1 and 2. The average diurnal pattern for CH4 emissions did not significantly change between feeding periods and as lactation progressed. Emissions of CH4 were positively associated with dry matter (DM) intake and forage DM intake. It is concluded that if the management of feed allocation remains constant then the diurnal pattern of CH4 emissions from dairy cows will not necessarily alter over time. A change in diet composition may bring about an increase or decrease in absolute emissions over a 24-h period without significantly changing the diurnal pattern unless management of feed allocation changes. These findings are important for CH4 monitoring techniques that involve taking measurements over short periods within a day rather than complete 24-h observations.

Use of rumination and activity data as health status and performance indicators in beef cattle during the early fattening period

The aim of this study was to measure the level of activity and rumination in young bulls and to assess whether these data can be used as indicators of health status and average daily weight gain (ADG). Two groups of animals (period 1: n=108 animals; period 2: n=106 animals) were fitted with sensors to measure daily activity and rumination, were weighed on arrival and at the end of the trial (70 days) and were checked twice daily to verify their health condition. Any clinical signs and therapies were recorded. The dishomogeneity index of rumination (DR), and the daily dishomogeneity indices of activity (DDA) and rumination (DDR), were calculated. Bulls had an ADG of 1.42±0.38kg/day and showed an average duration of daily rumination of 404±63min and an average activity of 474±46 bits, respectively. Animals characterised by low ADG had lower values of minimum daily rumination (P=0.01) and DDA (P<0.001), and a greater rumination range (P=0.007) and DR (P=0.003). Bovine respiratory disease and lameness were detected 31 and five times, respectively; among affected animals, the average daily activity, rumination and DDA were lower (P<0.05) at 3-6days before the onset of visible clinical signs, whereas DDR increased compared to the values when individuals were apparently healthy. The use of individual sensors appears promising for the early diagnosis of disease in beef cattle and for improving herd management.

Monitoring and assessment of ingestive chewing sounds for prediction of herbage intake rate in grazing cattle

Accurate measurement of herbage intake rate is critical to advance knowledge of the ecology of grazing ruminants. This experiment tested the integration of behavioral and acoustic measurements of chewing and biting to estimate herbage dry matter intake (DMI) in dairy cows offered micro-swards of contrasting plant structure. Micro-swards constructed with plastic pots were offered to three lactating Holstein cows (608±24.9 kg of BW) in individual grazing sessions (n=48). Treatments were a factorial combination of two forage species (alfalfa and fescue) and two plant heights (tall=25±3.8 cm and short=12±1.9 cm) and were offered on a gradient of increasing herbage mass (10 to 30 pots) and number of bites (~10 to 40 bites). During each grazing session, sounds of biting and chewing were recorded with a wireless microphone placed on the cows' foreheads and a digital video camera to allow synchronized audio and video recordings. Dry matter intake rate was higher in tall alfalfa than in the other three treatments (32±1.6 v. 19±1.2 g/min). A high proportion of jaw movements in every grazing session (23 to 36%) were compound jaw movements (chew-bites) that appeared to be a key component of chewing and biting efficiency and of the ability of cows to regulate intake rate. Dry matter intake was accurately predicted based on easily observable behavioral and acoustic variables. Chewing sound energy measured as energy flux density (EFD) was linearly related to DMI, with 74% of EFD variation explained by DMI. Total chewing EFD, number of chew-bites and plant height (tall v. short) were the most important predictors of DMI. The best model explained 91% of the variation in DMI with a coefficient of variation of 17%. Ingestive sounds integrate valuable information to remotely monitor feeding behavior and predict DMI in grazing cows.

Integrating spot short-term measurements of carbon emissions and backward dietary energy partition calculations to estimate intake in lactating dairy cows fed ad libitum or restricted

The objective of this study was to use spot short-term measurements of CH4 (QCH4) and CO2 (QCO2) integrated with backward dietary energy partition calculations to estimate dry matter intake (DMI) in lactating dairy cows. Twelve multiparous cows averaging 173±37d in milk and 4 primiparous cows averaging 179±27d in milk were blocked by days in milk, parity, and DMI (as a percentage of body weight) and, within each block, randomly assigned to 1 of 2 treatments: ad libitum intake (AL) or restricted intake (RI=90% DMI) according to a crossover design. Each experimental period lasted 22d with 14d for treatments adaptation and 8d for data and sample collection. Diets contained (dry matter basis): 40% corn silage, 12% grass-legume haylage, and 48% concentrate. Spot short-term gas measurements were taken in 5-min sampling periods from 15 cows (1 cow refused sampling) using a portable, automated, open-circuit gas quantification system (GreenFeed, C-Lock Inc., Rapid City, SD) with intervals of 12h between the 2daily samples. Sampling points were advanced 2h from a day to the next to yield 16 gas samples per cow over 8d to account for diurnal variation in QCH4 and QCO2. The following equations were used sequentially to estimate DMI: (1) heat production (MJ/d)=(4.96 + 16.07 ÷ respiratory quotient) × QCO2; respiratory quotient=0.95; (2) metabolizable energy intake (MJ/d)=(heat production + milk energy) ± tissue energy balance; (3) digestible energy (DE) intake (MJ/d)=metabolizable energy + CH4 energy + urinary energy; (4) gross energy (GE) intake (MJ/d)=DE + [(DE ÷ in vitro true dry matter digestibility) - DE]; and (5) DMI (kg/d)=GE intake estimated ÷ diet GE concentration. Data were analyzed using the MIXED procedure of SAS (SAS Institute Inc., Cary, NC) and Fit Model procedure in JMP (α=0.05; SAS Institute Inc.). Cows significantly differed in DMI measured (23.8 vs. 22.4kg/d for AL and RI, respectively). Dry matter intake estimated using QCH4 and QCO2 coupled with dietary backward energy partition calculations (Equations 1 to 5 above) was highest in cows fed for AL (22.5 vs. 20.2kg/d). The resulting R(2) were 0.28 between DMI measured and DMI estimated by gaseous measurements, and 0.36 between DMI measured and DMI predicted by the National Research Council model (2001). Results showed that spot short-term measurements of QCH4 and QCO2 coupled with dietary backward estimations of energy partition underestimated DMI by 7.8%. However, the approach proposed herein was able to significantly discriminate differences in DMI between cows fed for AL or RI.