Location: Nutrition, Growth and Physiology2016 Annual Report
Objective 1: Determine the nutrient value and environmental consequences of novel feed products. Component 1: Problem Statement 1A Objective 2: Improve determination of dynamic changes in nutrient requirements as the animal’s physiological status changes to allow for timed nutrient delivery. Component 1: Problem Statement 1A Objective 3: Determine the role of malnutrition during critical periods in developmental programming and epigenetic effects that alter lifetime production potential and product quality. Component 1: Problem Statement 1A Objective 4: Determine metabolic and physiological mechanisms responsible for variation in feed efficiency that is under genetic control. Component 1: Problem Statement 1A Objective 5: Determine age, gender, genetic, and environmental factors that account for variation in feeding activity and growth of swine Component 1: Problem Statement 1C Objective 6: Characterize the response of cattle to changes in environmental temperature with respect to various management strategies and animal risk factors. Component 1: Problem Statement 1C Obective 7: Determine the relationships between ruminal microbial communities, animal genotype, and/or methane production with feed/nutrient use efficiency and/or lactation performance in response to varying nutritional regimens in beef or dairy cattle. Component 1: Problem Statement 1A Component 2: Problem Statement 2B; Problem Statement 2D
Feed costs represent the single largest input in both beef and swine production; however, less than 20% of the feed energy is converted to edible product. Improving the efficiency that feed is converted to animal products has the potential to improve the economic efficiency of animal production while improving the sustainability of animal agriculture. To maximize feed efficiency the correct profile of nutrients are matched to meet an animal’s needs for its current biological status (growth, pregnancy, lactation, previous nutrient history, and disease). In order to provide the correct profile of nutrients, the nutrient composition of feeds and the dynamic nutrient requirements of the animal must both be identified and then synchronized. There is genetic variation amongst animals in their ability to utilize feed. Multiple genes are associated with the regulation of feed intake, and the utilization of ingested nutrients. Differential expression of these genes results in variation of feed efficiency amongst animals within populations, and these genetic differences potentially change the nutrient requirements of the animal. Nutrient status during critical periods of development (fetal and peripuberal) can permanently modify the expression of genes changing the lifetime feed efficiency of an animal. Identifying the role of nutrition in regulating gene expression is needed to develop nutrition management strategies across generations of animals in a production system.
Glucocorticoids and metabolites were measured in the serum of 451 growing steers and heifers prior-to and at weaning. The utility of these measures to predict growth rate and incidences of respiratory disease were determined (Objective 4). The expression of immune-related genes in the rumen of 16 steers with divergent growth rates were evaluated (Objective 4). Feed intake and growth was evaluated on 160 steers and heifers fed a forage ration. Plasma was sampled to evaluate the association of hormones with feed efficiency. A subset of cattle with divergent growth rates will have liver and adipose biopsies performed for transcriptomics and metabolomics. Cerebrospinal fluid was sampled from a subset of cattle with divergent feed intake to determine the association of neuropeptides with feed intake (Objective 4). One-hundred and forty-six steers were individually fed and evaluated for feed efficiency. Plasma samples were collected to determine the relationship between hormones and metabolites and feed efficiency. Liquid chromatography coupled to tandem quadrupole mass spectrometry was used to determine the relationship between endocannabinoids with feed efficiency. At slaughter, 14 steers that had low or high rates of gain at a common feed intake were sampled to conduct metabolomics profiles in plasma, muscle, adipose, and small intestine tissue using liquid chromatography tandem quadrupole-time of flight mass spectrometry (Objective 4). Individual feed intake, body weight gain, back fat depth and loin-eye data were collected on 1100 pigs. One hundred and ninety pigs were bled at day 0, 21, and 42 for serum metabolomics analysis. Transcriptomics analysis has been initiated on 40 pigs of differing feed efficiency phenotypes (Objective 4). Transcriptomics was conducted on the longissimus dorsi and rumen of 80 steers that varied in feed efficiency (Objective 4). Discovery rumen transcriptomic data was validated in a second, unrelated population of steers (Objective 4). Low cost genotyping panels have been successfully generated and tested (Objective 4). Genes involved in adipogenesis were tested for association with gain and feed intake on heifer adipose samples (Objective 4). Analyzed and reported data from functional genomics studies of the transcriptomes of duodenum, jejunum, ileum, mesenteric fat, and spleen of 16 steers that varied in feed efficiency (Objective 4). An experiment was conducted to determine the effects of feeding monensin in drylot pregnant heifers on methane production and total energy balance. Methane production was measured every 21 days. (Objective 1) Rumen fluid was collected from 344 steers in the germ plasm evaluation population to determine the effects of rumen microbiome on feed efficiency (Objective 4). A Latin square experiment (two replicated 4 X 4) was conducted to determine the effects of feeding ferric citrate on methane production, nutrient balance, and total energy balance in growing feedlot steers (Objective 1). An experiment was conducted to determine the effects of different calf systems on animal performance and carcass characteristics of beef steers, and to evaluate cover crop establishment, crop production, and estimated crop use during the grazing season (Objective 1). Individual feed intake and weight change was collected on 332 cows that represent 18 different breeds (Objective 7). Production records were recorded on 458 cows that had been developed under two different regimens as heifers (Objective 3). Production records were collected on 240 cows that had experienced different fetal nutrition (Objective 3). Four replications of 239 pigs a mix of barrows and gilts of three different sire lines (Landrace, Yorksire, Duroc) were placed in one of six pens (39 pigs per pen). Pigs were placed in the pens at approximately 8 weeks of age and were removed from the pens at approximately 24 weeks of age. Feeding behavior was collected using a feed behavior monitoring system; data was collected on a 20-second basis. Weights were collected prior to the pigs entering the pens and at 22 weeks of age (Objective 5). Data was collected on 236 pigs of 3 different sire lines (Landrace, Yorkshire, Duroc). Weights were collected at 4 points throughout the growing out period age (Objective 5). Five barrows and five gilts of each of three sire lines (Landrace, Yorkshire, and Duroc) at each of five ages were used to collect data. Top and side profile images were collected. The images were analyzed for each of the eight dimensions documented in the current standards age (Objective 5). An active RFID system was adapted for use in a swine barn. The system was installed, and calibration and validation tests were performed. Two system tests were conducted. The first test, 32 tags were placed in a similar location, average errors in the x, y, and z axis were determined. During the second tests, 32 tags were randomly placed in 1 of 40 locations on a 1x1 meter grid within a single 6.4 by 4.3 m swine pen. The test was completed three times. Average errors in the x, y, and z axis were determined. A pig validation test was completed. Four gilts (120 kg) were tagged and placed in a 6.4 by 4.3 m pen. Digital images were taken in the x and y direction. Pig location was determined by both systems to determine the errors in the system age (Objective 5). Activity level of individual pigs that differed in genetic line or temperament score was measured. A group of 39 pigs was chosen. Three barrows and three gilts of each genotype were tagged with an active RFID tag. Data was collected for a period of 7 days. Pigs were temperament scored at 22 weeks by assessing their activity. Four high temperament and four low temperament were chosen for the study. The pigs were tagged and data was collected for a period of 7 days age (Objective 5).
1. Cattle that differ in feed efficiency have different bacterial communities (microbiota) in their digestive tracts. Feed represents the single largest input cost in beef production and feed not converted to animal products potentially can have a negative environmental impact. ARS researchers at Clay Center, Nebraska, determined that the bacterial communities change in different places of the digestive tract and those communities change in animals that utilize feed differently. This research suggests that some of the variation in feed utilization may be associated with the host bacterial community.
2. The method of grain processing and the level of feeding coproducts change the efficiency that nutrients are retained by beef cattle. Feed represents the single largest input cost in beef production and feed not converted to animal products potentially can have a negative environmental impact. ARS researchers at Clay Center, Nebraska, determined that nutrient value of corn can be changed depending on how it is processed. Feeding distillers grains can improve performance but may increase nitrogen elimination. The nutrient value of distillers grains within a ration changes depends on the level that it is being fed. To accurately predict animal performance, the estimated quality of the feed needs to be adjusted based on the inclusion rate.
3. A method was developed to monitor sow posture and behaviors. Some of the piglet mortality is a consequence of injuries that occur when sows change their posture and piglets are subsequently crushed. ARS researchers at Clay Center, Nebraska, developed a method to monitor sow behaviors to allow for the evaluation of alternative housing and equipment of sows to reduce piglet mortality.
4. There are differences in the genes expressed in the digestive tract of steers that utilized feed differently. Feed represents the single largest input cost in beef production and feed not converted to animal products potentially can have a negative environmental impact. ARS researchers at Clay Center, Nebraska, determined that there are differences in gene expression in cattle that vary in feed efficiency and indicate potential physiological mechanisms that may influence feed efficiency. Understanding which physiological mechanisms are involved with improved feed efficiency allows for the development of management strategies that promote these mechanisms and/or these mechanisms can be used as biological types that can be genetically selected for to improve feed efficiency.
5. The feed additive, zilpaterol hydrochloride, did not affect susceptibility to heat stress or mobility. Concern has been expressed that feeding beta-agonist at the end of the feeding period may have negative impacts on animal well-being. ARS researchers at Clay Center, Nebraska, and the University of Nebraska, Lincoln, Nebraska, found no differences in susceptibility to heat stress or mobility between cattle fed zilpaterol hydrochloride and cattle not fed the feed additive.
6. There are positive relationships between the concentration of the metabolic hormones leptin and feed intake and body weight gain. Feed represents the single largest input cost in beef production and feed not converted to animal products potentially can have a negative environmental impact. ARS researchers at Clay Center, Nebraska, determined that leptin may be an indicator of feed intake and growth making it a candidate for predicting feed utilization by beef cattle.
Kern, R.J., Lindholm-Perry, A.K., Freetly, H.C., Snelling, W.M., Kern, J.W., Keele, J.W., Miles, J.R., Foote, A.P., Oliver, W.T., Kuehn, L.A., Ludden, P.A. 2016. Transcriptome differences in the rumen of beef steers with variation in feed intake and gain. Gene. 586:12-26.
Foote, A.P., Hales, K.E., Tait Jr, R.G., Berry, E.D., Lents, C.A., Wells, J. E., Lindholm-Perry, A.K., Freetly, H.C. 2016. Relationship of glucocorticoids and hematological measures with feed intake, growth, and efficiency of finishing beef cattle. Journal of Animal Science. 94(1):275-283. doi: 10.2527/jas2015-9407
Myer, P.R., Wells, J., Smith, T.P., Kuehn, L.A., Freetly, H.C. 2016. Microbial community profiles of the jejunum from steers differing in feed efficiency. Journal of Animal Science. 94(1):327-338. doi: 10.2527/jas2015-9839.
Hales, K.E., Jaderborg, J.P., Crawford, G.I., DiCostanzo, A., Spiehs, M.J., Brown-Brandl, T.M., Freetly, H.C. 2015. Effects of dry-rolled or high-moisture corn with twenty-five or forty-five percent wet distillers' grains with solubles on energy metabolism, nutrient digestibility, and macromineral balance in finishing beef steers. Journal of Animal Science. 93(10):4995-5005. doi: 10.2527/jas2015-9301
Myer, P.R., Wells, J.E., Smith, T.P.L., Kuehn, L.A., Freetly, H.C. 2015. Cecum microbial communities from steers differing in feed efficiency. Journal of Animal Science. 93(11):5327-5340. doi: 10.2527/jas2015-9415
Kern, R.J., Lindholm-Perry, A.K., Freetly, H.C., Kuehn, L.A., Rule, D.C., Ludden, P.A. 2016. Rumen papillae morphology of beef steers relative to gain and feed intake and the association of volatile fatty acids with kallikrein gene expression. Livestock Science. 187:24-30.
Boyd, B.M., Shackelford, S.D., Hales, K.E., Brown-Brandl, T.M., Bremer, M.L., Spangler, M.L., Wheeler, T.L., King, D.A., Erickson, G.E. 2015. Effects of shade and feeding zilpaterol hydrochloride to finishing steers on performance, carcass quality, heat stress, mobility, and body temperature. Journal of Animal Science. 93(12):5801-5811. doi: 10.2527/jas2015-9613.
Foote, A.P., Tait Jr, R.G., Keisler, D.H., Hales, K.E., Freetly, H.C. 2016. Leptin concentrations in finishing beef steers and heifers and their association with dry matter intake, average daily gain, feed efficiency, and body composition. Domestic Animal Endocrinology. 55:136-141.
Foote, A.P., Hales, K.E., Kuehn, L.A., Keisler, D.H., King, D.A., Shackelford, S.D., Wheeler, T.L., Freetly, H.C. 2015. Relationship of leptin concentrations with feed intake, growth, and efficiency in finishing beef steers. Journal of Animal Science. 93(9):4401-4407.
Lindholm-Perry, A.K., Kern, R.J., Kuehn, L.A., Snelling, W.M., Miles, J.R., Oliver, W.T., Freetly, H.C. 2015. Differences in transcript abundance of genes on BTA15 located within a region associated with gain in beef steers. Gene. 572(1):42-48. doi:10.1016/j.gene.2015.06.076.
Myer, P.R., Wells, J., Smith, T.P., Kuehn, L.A., Freetly, H.C. 2015. Microbial community profiles of the colon from steers differing in feed efficiency. SpringerPlus. 4:454.
Oliver, W.T., Wells, J. 2015. Lysozyme as an alternative to growth promoting antibiotics in swine production. Journal of Animal Science and Biotechnology. 6:35.
Sales, G.T., Green, A.R., Gates, R.S., Brown-Brandl, T.M., Eigenberg, R.A. 2015. Quantifying detection performance of a passive low-frequency RFID system in an environmental preference chamber for laying hens. Computers and Electronics in Agriculture. 114:261-268.
Hales, K.E., Shackelford, S.D., Wells, J., King, D.A., Pyatt, N.A., Freetly, H.C., Wheeler, T.L. 2016. Effects of dietary protein concentration and ractopamine hydrochloride on performance and carcass characteristics of finishing beef steers. Journal of Animal Science. 94(5):2097-2102. doi:10.2527/jas2015-0225
Lao, F., Brown-Brandl, T.M., Stinn, J.P., Liu, K., Teng, G., Xin, H. 2016. Automatic recognition of lactating sow behaviors through depth image processing. Computers and Electronics in Agriculture. 125:56-62.
Lents, C.A., Brown-Brandl, T.M., Rohrer, G.A., Oliver, W.T., Freking, B.A. 2016. Plasma concentrations of acyl-ghrelin are associated with average daily gain and feeding behavior in grow-finish pigs. Domestic Animal Endocrinology. 55:107-113.
Lindholm-Perry, A.K., Butler, A.R., Kern, R.J., Hill, R., Kuehn, L.A., Wells, J., Oliver, W.T., Hales, K.E., Foote, A.P., Freetly, H.C. 2016. Differential gene expression in the duodenum, jejunum and ileum among crossbred beef steers with divergent gain and feed intake phenotypes. Animal Genetics. 47(4):408-427. doi: 10.1111/age.12440.
Myer, P.R., Kim, M.S., Freetly, H.C., Smith, T.P. 2016. Evaluation of 16S rRNA amplicon sequencing using two next-generation sequencing technologies for phylogenetic analysis of the rumen bacterial community in steers. Journal of Microbiological Methods. 127:132-140. doi: 10.1016/j.mimet.2016.06.004.
Foth, A.J., Brown-Brandl, T.M., Hanford, K.J., Miller, P.S., Garcia Gomez, G., Kononoff, P.J. 2015. Energy content of reduced-fat dried distillers grains with solubles for lactating dairy cows. Journal of Dairy Science. 98:7142-7152.
Brown-Brandl, T.M., Eigenberg, R.A. 2015. Determination of minimum meal interval and analysis of feeding behavior in shaded and open lot feedlot heifers. Transactions of the ASABE. 58(6):1833-1839.