Browsing by Subject "Dairy cattle"

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Enhancing individual animal resilience to environmental disturbances to address low productivity in dairy cattle performing in sub-Saharan Africa
(2023) Oloo, Richard D.; Ojango, Julie M. K.; Ekine-Dzivenu, Chinyere C.; Gebreyohanes, Gebregziabher; Mrode, Raphael; Mwai, Okeyo A.; Chagunda, Mizeck G. G.
The current review examines potential solutions to enhance the sustainability and productivity of the dairy sector in sub-Saharan Africa (SSA) with an emphasis on breeding for resilience. Additionally, the paper explores various indicators for measuring resilience and provides insights into the data that can be utilized to quantify resilience in SSA’s dairy production systems. Dairy production contributes significantly to food and nutritional security and employment in SSA. However, besides the general lack of enabling policy and institutional environments, production is negatively affected by environmental challenges such as high temperatures and heat stress, diseases and parasites, unreliable rainfall patterns, shortages of feeds and forages and undue preference for taurine cattle breeds regardless of their poor adaptability to prevailing local conditions. Fostering the resilience capacity of dairy animals is imperative to combat climate-related adversities and maintain productivity. This can only be achieved if reliable and practical methods for quantifying and analyzing resilience in SSA are described and undertaken. This study has reviewed variance of deviations, root mean square of deviations, autocorrelation of deviations, skewness of deviations, slope of the reaction norm and its absolute value as possible indicators of resilience in SSA. While previous research has reported genetic variation and favorable correlations of these indicators with health, fitness, and fertility traits, their potential in SSA environments requires further investigation. Besides, labor- and cost-effective phenotypic data collection is essential for characterization of resilience using these indicators. Through this study, we propose frequently collected data on milk production traits, body fat-related traits, and activity patterns as suitable in the sub-Saharan Africa context. The African Asian Dairy Genetic Gains Project by the International Livestock Research Institute (ILRI) offers a valuable opportunity to collate data from diverse dairy systems in SSA for testing the potential of these indicators. Insights from this study are helpful in improving resilience of dairy animals in SSA, which would contribute to poverty alleviation, animal welfare improvement, and better preparedness in lieu of climate change in SSA.
Genomic dissection of the correlation between milk yield and various health traits using functional and evolutionary information about imputed sequence variants of 34,497 German Holstein cows
(2024) Schneider, Helen; Krizanac, Ana-Marija; Falker-Gieske, Clemens; Heise, Johannes; Tetens, Jens; Thaller, Georg; Bennewitz, Jörn
Background: Over the last decades, it was subject of many studies to investigate the genomic connection of milk production and health traits in dairy cattle. Thereby, incorporating functional information in genomic analyses has been shown to improve the understanding of biological and molecular mechanisms shaping complex traits and the accuracies of genomic prediction, especially in small populations and across-breed settings. Still, little is known about the contribution of different functional and evolutionary genome partitioning subsets to milk production and dairy health. Thus, we performed a uni- and a bivariate analysis of milk yield (MY) and eight health traits using a set of ~34,497 German Holstein cows with 50K chip genotypes and ~17 million imputed sequence variants divided into 27 subsets depending on their functional and evolutionary annotation. In the bivariate analysis, eight trait-combinations were observed that contrasted MY with each health trait. Two genomic relationship matrices (GRM) were included, one consisting of the 50K chip variants and one consisting of each set of subset variants, to obtain subset heritabilities and genetic correlations. In addition, 50K chip heritabilities and genetic correlations were estimated applying merely the 50K GRM. Results: In general, 50K chip heritabilities were larger than the subset heritabilities. The largest heritabilities were found for MY, which was 0.4358 for the 50K and 0.2757 for the subset heritabilities. Whereas all 50K genetic correlations were negative, subset genetic correlations were both, positive and negative (ranging from -0.9324 between MY and mastitis to 0.6662 between MY and digital dermatitis). The subsets containing variants which were annotated as noncoding related, splice sites, untranslated regions, metabolic quantitative trait loci, and young variants ranked highest in terms of their contribution to the traits’ genetic variance. We were able to show that linkage disequilibrium between subset variants and adjacent variants did not cause these subsets’ high effect. Conclusion: Our results confirm the connection of milk production and health traits in dairy cattle via the animals’ metabolic state. In addition, they highlight the potential of including functional information in genomic analyses, which helps to dissect the extent and direction of the observed traits’ connection in more detail.
Investigations on major gene by polygene and gene by environment interaction in German Holstein dairy cattle
(2014) Streit, Melanie; Bennewitz, Jörn
Putative interaction effects between DGAT1 K232A mutation and the polygenic terms (all genes except DGAT1) were investigated in chapter one. This was done for five milk production traits (milk yield, protein yield, fat yield, protein percentage and fat percentage) in the German Holstein dairy cattle population. Therefore, mixed models are used. The test for interaction relied on the comparison of polygenic variance components depending on the sire?s genotypes at DGAT1 K232A. Found substitution effects were highly significant for all traits. Significant interactions between DGAT1 K232A and the polygenic term were found for milk fat and protein percentage. These interactions could be used in breeding schemes. Depending on the DGAT1 K232A genotypes of the sample, in which the sire will be used, three polygenic breeding values of a sire can be calculated. Because the genotypes of the samples are often unknown and usually heterogeneous, this is not a practical approach. Rank correlations between the three polygenic EBVs were always above 0.95, which suggested very little re-ranking. GxE were studied in chapter two. For this, reaction norm random regression sire models were used in the German Holstein dairy cattle population. Around 2300 sires with a minimum of 50 daughters per sire and at minimum seven first-lactation test day observations per daughter were analyzed. As traits, corrected test day records for milk yield, protein yield, fat yield and somatic cell score (SCS) were used. As environmental descriptors, we used herd test day solutions (htds) for milk traits, milk energy yield or SCS. Second-order orthogonal polynomial regressions were applied to the sire effects. Results showed significant slope variances of the reaction norms, which caused a non-constant additive genetic variance across the environmental ranges considered, which pointed to the presence of minor GxE effects. When the environment improved, the additive genetic variance increased, meaning higher (lower) htds for milk traits (SCS). This was also influenced by pure scaling effects, because the non-genetic variance increased in an improved environment and the heritability was less influenced by the environment. For the environmental ranges considered in this study, GxE effects caused very little re-ranking of the sires. To obtain unbiased genetic parameters, it was important to model heterogeneous residual variances. A large genome-wide association analysis was conducted in chapter three to identify SNPs that affect general production (GP) and environmental sensitivity (ES) of milk traits. Around 13 million daughter records were used to calculate sire estimates for GP and ES with help of linear reaction norm models. Daughters were offspring from 2297 sires. The sires were genotyped with a 54k SNP chip. As environmental descriptor, the average milk energy yield performance of the herds at the time where the daughter observations were recorded was used. The sire estimates were used as observations in genome-wide association analyses using 1797 sires. With help of an independent validation set (500 sires of the same population), significant SNPs were confirmed. To separate GxE scaling and other GxE effects, the observations were log-transformed. GxE effects could be found with help of reaction norm models and numerous significant SNPs could be validated for GP and ES, whereas many SNPs affecting GP also affected ES. ES of milk traits is a typical quantitative trait, which is controlled by many genes with small effects and few genes with larger effect. Effects of some SNPs for ES were not removable by log-transformation of observations, indicating that these are not solely scaling effects. Positions of founded clusters were often in well-known candidate regions affecting milk traits. No SNPs, which show effects for GP and ES in opposite directions could be found. Environmental descriptor in GxE analyses is often modelled by average herd milk production levels. Another possibility could be the level of hygiene and udder health. In chapter four, the same models were used as in chapter three. A genome-wide association analysis was done using htds for SCS as an environmental descriptor. With help of this, several SNP clusters affecting intercept and slope could be detected and confirmed. Many SNPs or clusters affecting intercept and slope could be identified, but in total, the number of SNPs affecting intercept was larger. The same SNPs could be detected and validated with and without considering GxE in reaction norm models. Some SNPs affecting only slope were found. For slope, nearly the same SNPs could be found with SCS as an environmental descriptor as presented in chapter three, although both environmental descriptors were only slightly correlated.
Mapping genes for resilient dairy cows by means of across-breed genome-wide association analysis
(2025) Keßler, Franziska; Zölch, Maximilian; Wellman, Robin; Bennewitz, Jörn
Background: Indicator traits based on variance and autocorrelation of longitudinal data are increasingly used to measure resilience in animal breeding. While these traits show promising heritability and can be routinely collected, their genetic architecture remains poorly understood. We conducted GWAS for three resilience indicators across German Holstein ( n = 2,300), Fleckvieh ( n = 2,330), and Brown Swiss ( n = 1,073) dairy cattle ( Bos Taurus ) populations. The indicators included variance ( ) and autocorrelation ( ) of deviations of observed from predicted daily milk yield and variance of relative daily milk yield ( ). Additionally, we analysed a selection index combining these traits. Prior to GWAS, we examined population structure through multi-dimensional scaling (MDS) and LD patterns, revealing distinct genetic clusters for each breed and similar LD decay patterns. Results: The GWAS results confirmed the polygenic nature of resilience, with multiple genomic regions showing significant associations. Notable signals were detected on BTA5 ( ), BTA14 ( ), BTA2 and BTA8 ( ) for single indicator traits. For selection index resilience, strong suggestive SNPs are located on BTA4 , BTA16 , BTA21 , and BTA27 . Detected regions overlapped with previously reported QTLs for performance, reproduction, longevity and health, providing new insights into the biological pathways underlying dairy cattle resilience. Conclusions: Our findings demonstrate that resilience indicators have a complex genetic architecture with both breed-specific and shared components, supporting their potential use in selective breeding programs while highlighting the importance of careful trait definition.
Nitrogen excretion and utilisation of dairy cows grazing temperate semi- natural grasslands
(2024) Perdana-Decker, Sari; Velasco, Elizabeth; Werner, Jessica; Dickhoefer, Uta
Diets reliant on grazed, temperate herbage are prone to greater nitrogen (N) losses via urine than balanced stall-fed diets which poses a greater risk for N emissions. Measures for improving the N utilisation in grazing-based dairy cattle systems are predominantly investigated on homogenous clover-ryegrass pastures with high herbage yields and nutritional quality. In contrast, grazing-based systems reliant on less external inputs (e.g., synthetic fertilisers or concentrates) using semi-natural grassland as main feed source, such as in large parts of Central Europe, received less attention. The N utilisation and excretion of grazing cows in low-input dairy farms were, thus, investigated on nine commercial organic dairy farms in South Germany across one to four periods per farm. The dataset captured a diverse set of dairy production systems comprising 323 individual animal observations. A mean (± one SD) milk production, DM intake (DMI), and pasture DMI of 23.9 kg (± 5.35), 21.0 kg (± 3.21), and 11.3 kg/d (± 4.83), respectively, was determined. Feed intake was estimated using titanium dioxide and faecal CP concentration as markers of faecal excretion and diet digestibility, respectively. Milk N use efficiency (MNE; i.e., milk N secretion as share of N intake) averaged 24.7 g/100 g N intake (± 5.91), which is greater than observations in temperate, high-input grazing systems but lower than in cows receiving balanced diets in the barn. The MNE and another seven indicators of N utilisation and excretion displayed a wide range of values. The grazing management factors explaining this variation were, thus, identified via backward elimination. The supplementation strategy had the greatest potential for manipulating N utilisation and excretion of dairy cows. Increasing shares of fresh forages (i.e., meadow grass or clover-grass leys) as well as of hay in supplement DMI increased N utilisation (e.g., MNE) and decreased urinary N excretion (e.g., urinary N to creatinine ratio), while increasing shares of concentrates in supplement DMI are related to lower N losses via urine. At the same time, increases in total supplement DMI reduced N utilisation and increased urinary N excretion. Hence, full-time grazing combined with supplementation of fresh forage and hay in the barn is a viable option for low-input, grazing-based dairy operations with moderate levels of N losses.
Production and use of forages from permanent pastures in grazing-based dairy cattle systems in Southwest Germany
(2024) Velasco Gutierez, Elizabeth; Dickhoefer, Uta
A steadily growing world population and its rising standard of living are putting pressure on agricultural systems to provide food of good quality while minimizing environmental impacts. As a result, traditional practices such as grazing are becoming more popular in dairy systems. Permanent grasslands cover 34 % of the agricultural area in the European Union (EU). Semi-natural grasslands (SNG) are defined as permanent grasslands formerly used for mowing or grazing that have not been substantially modified by agricultural practices. The federal State of Baden-Wuerttemberg in Germany has a great proportion of SNG compared to other federal States in the country. The use of forage on SNG in grazing-based dairy cattle systems has the potential to produce milk sustainably, by respecting the environment, closing nutrient cycles, and promoting animal welfare, while ensuring high-quality forage production. However, there is limited data on the performance and practical use of SNG in grazing-based dairy cattle systems. This doctoral thesis aims at characterizing, evaluating, and quantifying the forage on SNG in grazing-based dairy cattle systems in Southwest Germany focusing on (1) forage availability, (2) feed energy self-sufficiency, and (3) feed supplementation in on-farm approach To characterize grazing-based dairy cattle systems and evaluate the potential of SNG for grazing and milk production, semi-quantitative interviews were conducted on 27 farms in the summer of 2018. Above-ground forage biomass from pastures was harvested and analyzed for nutrient composition. Farms differed regarding land endowment and use, dairy herd size, and thus stocking rates. Farmers implemented rotational (n = 12), short-grass (n = 10), continuous (n = 3), or strip (n = 2) grazing systems with < 8 h (n = 4), 8-12 h (n = 14), and > 12 h (n = 9) of daily pasture access during the grazing season. During the summer of 2018, available pasture forage (kg dry matter (DM)/ha) ranged from only 122 to 1,208. Crude protein (CP) and metabolizable energy (ME) concentrations varied greatly with 85 to 282 g and 7.9 to 11.0 MJ/kg DM, respectively. Diet digestibility estimated from fecal CP content ranged from 59.2 to 72.2 g/100 g organic matter (OM). Some farms succeeded in maintaining milk yields constant despite the lack of rainfall in that year. To quantify the forage availability of SNG as well as the feed energy self-sufficiency in seven commercial organic dairy cattle farms in Southwest Germany during the grazing season of 2019 and 2020, exclusion cages were set up in dairy cattle paddocks. Pasture samples were collected inside and outside the exclusion cages every 30 to 65 d, and analyzed by near-infrared reflectance spectroscopy for DM, CP, neutral detergent fiber (NDF), acid detergent fiber (ADF), apparent total tract digestibility organic matter (dOM), and ME. The results showed that SNG have the potential to produce a forage biomass up to 10,959 kg DM/ha and a with concentrations of CP, NDF, ADF up to 232 g/kg DM, 395 g/kg DM, and 214 g/kg DM, respectively. The concentrations of dOM and ME were up to 771 g/kg OM and 10.7 MJ/kg DM, respectively. The potential of grazing on SNG for dairy milk production was not fully exploited, although on some farms and at some times during the grazing season, grazing on SNG provided 100 % of the energy requirements of lactating dairy cattle, while on other farms, grazing on SNG provided only 2.8 % of the energy requirements. The differences in milk production from grazing SNG observed between farms were mainly due to management factors such as stocking rate and feed supplementation, while environmental factors played a minor role. To evaluate the effects of feed supplementation in grazing-based dairy cattle systems, three feeding experiments were conducted to compare feed supplementation under grazing conditions of (1) grass hay versus fresh grass-clover mixtures, (2) grass hay before or after grazing, and (3) timing of concentrate supplementation on two organic commercial dairy cattle farms in Southwest Germany in two periods in 2019 and 2020. Experiment 1 showed that the dairy cattle supplemented with fresh grass-clover mixtures had lower fecal nitrogen (N) excretion compared to the dairy cattle supplemented with grass hay. Experiment 2 demonstrated that grass hay supplementation before grazing led to a decrease in pasture organic matter intake (OMI), while grass hay supplementation in the morning (i.e., hay AM) decreased fecal N excretion in dairy cattle. Experiment 3 showed that offering less concentrate to dairy cattle before grazing resulted in higher pasture OMI in period 1, but also higher N intake and, lower fecal N excretion. The results of the feeding experiments demonstrate that simple management practices, such as the timing of feed supplementation can influence individual N utilization. The results of this doctoral thesis demonstrated that forage of SNG has the potential to produce forage biomass, adequate nutrient content, and energy concentration even under dry conditions. To maximize the use of SNG for grazing, the dynamics between forage biomass and supplemented feed should be considered, to maximize the use of SNG. Grazing management decisions play an important role in the use of forage of SNG for grazing in dairy cattle systems. The present thesis provides insights into grazing-based dairy cattle systems and valuable information on on-farm conditions in Central Europe. Future studies should be carried out in other countries and regions to obtain a more comprehensive panorama of the potential of the forage on SNG for milk production.
Toward a resilience selection index with indicator traits in German Holstein dairy cattle
(2025) Keßler, Franziska; Wellmann, Robin; Chagunda, Mizeck G. G.; Benenwitz, Jörn
Resilience expresses the ability of an individual to cope with short-term disturbances and to recover quickly by returning to the original level of performance. It can be measured by variance-based parameters and by the autocorrelation of daily milk yields in dairy cows. The design of resilience indicator traits and their heritabilities and genetic correlations have been studied in detail in recent years. There is a need to combine different resilience indicators in an index. The relevance of resilience indicator traits for incorporation into selection indices arises from their correlations with health traits and longevity. The correlations of diverse resilience indicator traits with health traits and longevity were analyzed. The resilience indicator traits were identified that would lead to the highest correlated selection response in the German selection index for health, and appropriate weights of the resilience indicator traits in a selection index for resilience were derived. Certain variance-based indicators were significantly positively correlated with most of the established health and functional traits, whereas the autocorrelation had a negligible correlation with these traits. A resilience selection index composed of 2 different variance-based resilience indicator traits was most likely to be recommended. Its correlation with overall performance was positive but moderately small. Incorporating more than 2 resilience indicator traits into the index improved the correlated response in health traits only slightly.