Determination Of Sources Of Variation And Prediction Of Feed Intake And Efficiency In Dairy Cows
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Determination Of Sources Of Variation And Prediction Of Feed Intake And Efficiency In Dairy Cows
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Author : Malia J. Caputo
language : en
Publisher:
Release Date : 2023
Determination Of Sources Of Variation And Prediction Of Feed Intake And Efficiency In Dairy Cows written by Malia J. Caputo and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
Feed is the single greatest expense on a dairy farm, representing approximately half the cost of dairy production over the last ten years. Increasing feed efficiency can reduce feed costs while maintaining milk production levels, improving profitability and sustainability of dairy production. Residual feed intake (RFI) is a measure of feed efficiency that represents the unexplained variation in feed intake after accounting for known energy sinks (i.e., milk energy output, body size, body weight change) within a group of cows managed similarly. Dry matter intake (DMI) is required to determine RFI, yet it is labor intensive and cost prohibitive to collect on most privately-owned dairies. Accurate prediction models of DMI could replace physical measurement, allowing for phenotypic feed efficiency determination on privately-owned dairies. When comparing multiple predictive approaches, traditional linear regression approaches performed as well as, or better than, more advanced techniques. Incorporation of behavioral sensor variables, but not blood metabolites, improved models of DMI, representing an opportunity to improve current models of DMI. Deeper understanding of the mechanisms that contribute to variation in feed efficiency would provide further insight into genetic selection for feed efficiency and can lead to the development of management and nutrition strategies to improve feed efficiency. Postpartum health may influence RFI, given the relationship with energy balance; however, no relationship exists between postpartum health disorders and same-lactation RFI, indicating that genetically selecting for RFI will not inadvertently select for negative health outcomes. Post-absorptive nutrient metabolism was previously identified in beef cattle as a source of variation in RFI, but was not investigated in lactating dairy cows. Between cows divergent in RFI, the blood circulating profile of metabolites differed, indicating differences in fatty acid or amino acid oxidation and providing evidence that post-absorptive nutrient metabolism is a source of variation in RFI of dairy cows. Differences in liver tissue pathways related to oxidative stress, cell cycling, and immune function, and differences in muscle fatty acid and glucose metabolism were identified, suggesting tissue-specific differences that contribute to variation in RFI. This dissertation details deeper understanding of post-absorptive nutrient metabolism as a source of variation in RFI, and ongoing effort will contribute to improving the feed efficiency of the dairy breed, which could have measurable impacts profitability and sustainability of dairy production.
Development And Evaluation Of Feed Intake And Energy Balance Prediction Models For Lactating Dairy Cattle
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Author : Dwight Kenneth Roseler
language : en
Publisher:
Release Date : 1994
Development And Evaluation Of Feed Intake And Energy Balance Prediction Models For Lactating Dairy Cattle written by Dwight Kenneth Roseler and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with categories.
Genomic And Genetic Evaluation Of Feed Efficiency And Stillbirth In Dairy Cattle
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Author :
language : en
Publisher:
Release Date : 2016
Genomic And Genetic Evaluation Of Feed Efficiency And Stillbirth In Dairy Cattle written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
Feed efficiency is an economically important trait in the dairy cattle industry, and feed costs accounts for more than 50% of total production costs. Prediction of genetic breeding value has been a focus of animal breeding since the beginning of the 20th century. Because of ongoing genetic selection for productivity and improvement in herd management, the efficiency of converting feed to milk in U.S. dairy cattle has doubled over the past 60 years due to dilution of maintenance. It is widely recognized that additional selection based on biological differences between individuals in feed efficiency is highly desirable. The emergence of high dimensional genomic data offers opportunities for selection and evaluation of feed efficiency directly through whole genome-enabled prediction. This thesis centers on genetic evaluation and prediction of traits related to feed efficiency in dairy cattle using whole genome molecular markers. We investigated various whole genome prediction approaches tailored to capturing total genetic variation, with the goal of enhancing predictive performance for feed efficiency and related traits. In particular, this thesis includes three studies. In the first study, a semi-supervised learning approach was introduced, and its prediction accuracy was assessed using residual feed intake (RFI) data. The second study compared an interaction model with within- and across-environment components using data from multiple environments to estimate genomic variances and assess the accuracy of genomic predictions for RFI and its component traits. The third study involved genetic evaluation of direct and maternal stillbirth rate, a trait that contributes to whole farm production efficiency, using data of Brown Swiss, Jersey, and Holstein bulls. Our results indicate that, while selection on feed efficiency in dairy cattle using whole genome molecular markers is promising, low accuracy of prediction remains an ongoing challenge due to the limited size of the reference population. Pooling data across countries or production systems is an option for increasing size of the reference population, but genotype by environment interactions and population stratification must be addressed. Ongoing collection of individual feed intake records is necessary to improve prediction accuracy, in terms of increasing the size of the reference population and ensuring that reference animals are closely related to the current selection candidates.
Field And Laboratory Methods For Grassland And Animal Production Research
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Author : L. 't Mannetje
language : en
Publisher: CABI
Release Date : 2000
Field And Laboratory Methods For Grassland And Animal Production Research written by L. 't Mannetje and has been published by CABI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Electronic books categories.
Considers a range of methods used by plant and animal production scientists to study grassland vegetation and animal performance. This volume replaces a previous title, ''Measurement of Grassland Vegetation and Animal Production'', published in 1978, but incorporates many new topics.
Ruminant Nutrition
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Author : Robert Jarrige
language : en
Publisher: John Libbey Eurotext
Release Date : 1989
Ruminant Nutrition written by Robert Jarrige and has been published by John Libbey Eurotext this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989 with Nature categories.
Deals with feed evaluation systems, the nutrient requirements of ruminant livestock and the feeding value of a wide range of feedstuffs. This book lists about 800 typical forages, 65 crop residues and 120 concentrate and by-product feeds. It is suitable for teachers, specialist scientists and industrialists.
Feed Efficiency In Swine
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Author : John F. Patience
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-10-15
Feed Efficiency In Swine written by John F. Patience and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-15 with Science categories.
'Feed efficiency in swine' has been prepared as a comprehensive treatise on the current state of our understanding of this topic which is so important to the pork industry. Each chapter is written by international authorities who understand both the science and application of their topic area. The book provides detailed insight into the many factors affecting feed efficiency, ranging from diet processing to herd health, from nutrition to physiology and from day-to-day barn management to the adoption of advanced technologies. The authors explain such practical aspects as the challenge of interpreting feed efficiency information obtained on farm or the role of liquid feeding. The authors also delve into more scientific topics such as amino acid or energy metabolism or animal physiology. This book is written for people who have a technical interest in pork production, including nutritionists, geneticists, farm management specialists, veterinarians, other academics and, of course, pork producers.
Determining Biological Sources Of Variation In Residual Feed Intake In Brahman Heifers During Confinement Feeding And On Pasture
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Author : Robert O. Dittmar
language : en
Publisher:
Release Date : 2008
Determining Biological Sources Of Variation In Residual Feed Intake In Brahman Heifers During Confinement Feeding And On Pasture written by Robert O. Dittmar and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.
Objectives were to characterize residual feed intake (RFI) and determine the phenotypic correlation between performance, feed efficiency, and other biological measurements in Brahman heifers, as well as the relationship between RFI determined in confinement and measurements of grazing activity on pasture. Three separate 70 d feeding trials were performed, and RFI was determined as the residual between actual and predicted dry matter intake (DMI) for a given level of production. Brahman heifers (n = 103; 5-to-9 mo of age) were individually limit-fed a pelleted 12% CP complete ration daily in Calan gates. Weekly body weight (BW) and DMI data were collected, and predicted DMI was determined by linear regression of actual DMI on mid-test metabolic BW. Ytterbium chloride was used to evaluate digestive kinetics, and fecal samples were collected to determine fecal volatile fatty acids (VFA) concentration and determine apparent dry matter digestibility (DMD) utilizing acid insoluble ash as an internal marker. Measurements of temperament were evaluated on all heifers at weaning. High (n = 6) and low (n = 6) RFI heifers (Exp. I) grazed fescue and ryegrass to determine variation in grazing behavior, DMI, and apparent DMD. Data from all three experiments were pooled, and RFI was not correlated with average daily gain (ADG), DMI, BW, partial efficiency of gain, feed conversion ration, fecal VFA concentration, or any measures of temperament. There were no significant differences in digestive kinetics between the RFI efficiency groups. Fecal samples taken for acid detergent insoluble ash (ADIA) determination were not collected at frequent enough intervals to account for weekly variation in fecal ADIA concentration. Pasture measurements were not different between the efficiency groups for heifers evaluated for grazing behavior, as well as estimated intake as a proportion of BW, or apparent DMD. Results of this study suggest that Bos indicus cattle appear to have similar efficiency traits as Bos taurus and Bos indicus influenced cattle, making this measure of efficiency equally as valid for use in both types of cattle. This indicates that selection based on RFI can be made to increase feed efficiency without affecting ADG or BW in Brahman cattle.
Evaluation Of A Mathematical Model In Predicting Intake Of Growing And Finishing Cattle
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Author : Brandi Marie Bourg
language : en
Publisher:
Release Date : 2008
Evaluation Of A Mathematical Model In Predicting Intake Of Growing And Finishing Cattle written by Brandi Marie Bourg and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.
The Cattle Value Discovery System (CVDS) was developed to predict growth and feed requirements of individual cattle fed in groups based on animal, diet, and environment information (Tedeschi et al., 2006). Evaluations of the CVDS using several databases of finishing cattle were conducted to determine the accuracy and precision of the model in predicted dry matter required (DMR) of pen-fed cattle. As well, the sensitivity of the model's predictions to deviations from actual ration metabolizable energy (ME) value was conducted. A meta-analysis of growing and finishing steers evaluated to model's accuracy in predicting DMR of individually fed steers, and the relationships between several model-predicted variables and actual performance and efficiency measures. Results for the first CVDS model evaluation involving pen-fed Santa Gertrudis cattle fed finishing diets revealed that accurate predictions of DMR are possible. The average mean bias for both steers and heifers was 2.43%. The sensitivity analysis of dietary ME values revealed that the model tends to consistently over- and under-predict DMR when the ME values are under- and over-estimated, respectively. However the ranking of pens was not affected by this mis-estimation of diet ME. In the second evaluations, both methods (mean body weight; MBW, dynamic iterative model; DIM) of CVDS were highly accurate and precise in allocating feed to pens of steers fed diverse types of diets and environmental conditions, with both models having a mean bias under 4%. The DIM model was slightly more accurate than the MBW model in predicting DMR. An evaluation of sources of variation revealed that for both models a large portion of the error was random, indicating that further work is needed to account for this variation. The meta-analysis study revealed that the model was able to account for 64% and 67% of the variation in observed dry matter intake (DMI) for growing and finishing steers, respectively. The two model-predicted efficiency measures, the ratio of DMR to average daily gain (ADG) and predicted intake difference (PID), were strongly to moderately correlated with their observed efficiency counterparts. In growing and finishing steers, DMR: ADG was able to account for 76% and 64% of the variation in observed feed conversion ratio (FCR) in growing and finishing studies, respectively. Strong correlations were also found between residual feed intake (RFI) and PID, suggesting that there may also be some similarity on these two measurements.
Neural Networks With R
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Author : Giuseppe Ciaburro
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-09-27
Neural Networks With R written by Giuseppe Ciaburro and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-27 with Computers categories.
Uncover the power of artificial neural networks by implementing them through R code. About This Book Develop a strong background in neural networks with R, to implement them in your applications Build smart systems using the power of deep learning Real-world case studies to illustrate the power of neural network models Who This Book Is For This book is intended for anyone who has a statistical background with knowledge in R and wants to work with neural networks to get better results from complex data. If you are interested in artificial intelligence and deep learning and you want to level up, then this book is what you need! What You Will Learn Set up R packages for neural networks and deep learning Understand the core concepts of artificial neural networks Understand neurons, perceptrons, bias, weights, and activation functions Implement supervised and unsupervised machine learning in R for neural networks Predict and classify data automatically using neural networks Evaluate and fine-tune the models you build. In Detail Neural networks are one of the most fascinating machine learning models for solving complex computational problems efficiently. Neural networks are used to solve wide range of problems in different areas of AI and machine learning. This book explains the niche aspects of neural networking and provides you with foundation to get started with advanced topics. The book begins with neural network design using the neural net package, then you'll build a solid foundation knowledge of how a neural network learns from data, and the principles behind it. This book covers various types of neural network including recurrent neural networks and convoluted neural networks. You will not only learn how to train neural networks, but will also explore generalization of these networks. Later we will delve into combining different neural network models and work with the real-world use cases. By the end of this book, you will learn to implement neural network models in your applications with the help of practical examples in the book. Style and approach A step-by-step guide filled with real-world practical examples.
New Approaches To Assess And Improve Protein Efficiency In Lactating Dairy Cows
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Author : Enhong Liu
language : en
Publisher:
Release Date : 2020
New Approaches To Assess And Improve Protein Efficiency In Lactating Dairy Cows written by Enhong Liu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Electronic dissertations categories.
The long-term goal of the work is to improve protein efficiency in lactating dairy cows. To achieve this goal, four specific objectives were proposed: 1) determine the relationship of residual feed intake (RFI) to protein efficiency in lactating Holstein cows fed high or low protein diets, 2) determine whether low protein resilience (LPR) is an indicator of protein efficiency in individual dairy cows, 3) examine the association of digestibility with RFI and LPR in lactating dairy cows, and 4) quantify the importance of including body weight (BW) change in the cow response to decreased dietary protein content and develop models for predicting BW change when dietary protein is altered. Lactating Holstein cows (n= 166; 92 primiparous, 77 multiparous) with initial milk yield (MY) of 41 ± 9.8 kg/d were fed high (HP) and low (LP) protein diets in crossover experiments of two 28-35 d periods. Experiments were repeated in 69 of the 166 cows (42 primiparous, 27 multiparous) in late lactation. Low protein diets were 14% CP in peak lactation and 13% CP in late lactation and were formulated to contain adequate rumen-degraded protein to maintain rumen function. Expeller soybean meal was added to formulate the HP diet, which contained 18% CP in peak lactation and 16% CP in late lactation. Cows were milked twice daily; DMI and MY were recorded once daily. Milk composition was measured over 4 consecutive milkings weekly, and BW was measured 3 times weekly. Samples of feed ingredients, orts and feces were collected in the last 5 days of each period and analyzed to determine digestibilities of DM, NDF, and CP for each cow on each diet. Fixed effects of diet, parity, treatment sequence nested in experiment, treatment period nested in experiment, interaction of parity and diet, and random effects of experiment and cow nested within experiment were included in models to compare production of cows fed different levels of CP. Protein efficiency was calculated for each cow on each diet in both peak lactation and late lactation. Residual feed intake was estimated for each cow on each treatment based on the actual intake, milk energy output, metabolic BW, and body energy change (estimated from BW change and BCS). Low protein resilience was estimated for each cow in peak lactation and also late lactation, based on protein captured in milk and body tissue when fed the LP vs HP diet. A negative correlation was observed between RFI and protein efficiency in cows fed the HP and LP diets in peak lactation and cows fed the HP diet in late lactation. Cows with higher LPR values had similar protein efficiency on the HP diet but significantly higher protein efficiency on the LP diet. Neither RFI nor LPR was correlated with digestibility regardless of diets or lactation stages. When dietary protein content was reduced, 40-50 % of the total energy loss, 10-20 % of total protein loss, and 15-25% of total income loss were due to BW loss, indicating that considering only changes in milk production underestimates the impact of dietary protein changes. In conclusion, 1) cows with lower RFI values utilized protein more efficiently, and protein efficiency will be improved in the process of selecting dairy cattle for low RFI, 2) cows with higher LPR values are better able to maintain production and have higher protein efficiency to adapt to low-protein feeding conditions, 3) variation in digestibility cannot explain the variations of RFI or LPR among lactating dairy cows, and we suggest that post-absorptive metabolism explains most of the variation in RFI and LPR when lactating cows are fed diets with minimal NDF in peak lactation and 40% NDF in late lactation, and 4) body reserve mobilization should not be neglected when assessing the cow response to changes in dietary protein.