Céad Mile Fáilte go T-Stór (Welcome to T- Stór)
T-Stór is Teagasc’s Open Access Repository, maintained by the Teagasc Library Service. Stór is the Gaelic word for Repository or Store or Warehouse, and T-Stór is an online “store” of Teagasc Research outputs and related documents. T-Stór collects preserves and makes freely available scholarly communication, including peer-reviewed articles, working papers and conference papers created by Teagasc researchers. Where material has already been published it is made available subject to the open-access policies of the original publishers. About Teagasc
Communities in T-Stór
Select a community to browse its collections.
Blood and faecal biomarkers to assess dietary energy, protein and amino acid efficiency of utilization by growing and finishing pigsBackground Diet evaluation and optimization is a slow and expensive process and it is not possible to do it at a farm level. This study aimed to use the blood serum metabolite (BSM) and faecal volatile fatty acid (VFA) profiles as potential biomarkers to identify changes in protein, amino acid and energy dietary content in growing and finishing pig diets at farm level. Results Two studies were conducted. The first study (S1) included 20 pens of 11 pigs (87.0 ± 4.10 kg; 18 weeks old) assigned to 5 diets: control (C1), high or low crude protein (HP1 and LP1, respectively), and high or low net energy (HE1 and LE1, respectively). The second study (S2) included 28 pens of 11 pigs (41.3 ± 2.60 kg; 12 weeks old) assigned to 7 diets: control (C2), high or low crude protein (HP2 and LP2, respectively), high or low amino acid (HA2 and LA2, respectively), and high or low net energy (HE2 and LE2, respectively). Pigs were followed for 10 (S1) and 20 (S2) days, and blood and faecal samples were collected at 20 (S1) and 14 (S2) weeks of age. Data were analysed using general linear models and receiver operating characteristic curve analysis. Urea nitrogen showed the best results as a biomarker. Urea nitrogen was higher in pigs fed high protein diets, HP1 (13.6 ± 0.95 mg/dL) and HP2 (11.6 ± 0.61), compared to those fed low protein diets, LP1 (6.0 ± 0.95) and LP2 (5.2 ± 0.61; P < 0.001), showing good discrimination ability (Area under the curve (AUC) = 98.4 and 100%, respectively). These differences were not observed between diets LA2 (6.5 ± 0.61) and HA2 (8.7 ± 0.61; P > 0.05; AUC = 71.9%), which were formulated based on the ideal protein profile but with no excess of protein. Creatinine, triglycerides, branched-chain fatty acids, albumin, propionic acid, and cholesterol showed differences between at least 2 diets but only in one of the studies. Conclusions Urea nitrogen showed high accuracy to detect excess of crude protein in growing and finishing pig diets. Other biomarkers like BCFA showed promising results and need to be further studied.
Modelling transmission of Mycobacterium avium subspecies paratuberculosis between Irish dairy cattle herdsBovine paratuberculosis is an endemic disease caused by Mycobacterium avium subspecies paratuberculosis (Map). Map is mainly transmitted between herds through movement of infected but undetected animals. Our objective was to investigate the effect of observed herd characteristics on Map spread on a national scale in Ireland. Herd characteristics included herd size, number of breeding bulls introduced, number of animals purchased and sold, and number of herds the focal herd purchases from and sells to. We used these characteristics to classify herds in accordance with their probability of becoming infected and of spreading infection to other herds. A stochastic individual-based model was used to represent herd demography and Map infection dynamics of each dairy cattle herd in Ireland. Data on herd size and composition, as well as birth, death, and culling events were used to characterize herd demography. Herds were connected with each other through observed animal trade movements. Data consisted of 13 353 herds, with 4 494 768 dairy female animals, and 72 991 breeding bulls. We showed that the probability of an infected animal being introduced into the herd increases both with an increasing number of animals that enter a herd via trade and number of herds from which animals are sourced. Herds that both buy and sell a lot of animals pose the highest infection risk to other herds and could therefore play an important role in Map spread between herds.
An index framework founded on the future profit potential of female beef cattle to aid the identification of candidates for cullingMeticulous culling decisions, coupled with careful breeding decisions, are fundamental to shifting a population distribution in the favorable direction and improving profit per cow. Nevertheless, there is a paucity of easy-to-use dynamic tools to aid in culling decisions in beef cattle. The motivation for the present study was to develop a monetary-based culling tool, here referred to as the Beef Female’s Profit Potential (BFPP), to identify females for culling. The BFPP reflects the expected lifetime profitability of an individual female in a herd for the expected remainder of her lifetime; this profit included that of the beef female herself as well as her progeny. The BFPP index framework was composed of 4 subindexes reflecting the value of an animal: (1) as a nulliparae (this was voided if the cow had already calved), (2) for the remainder of her current parity, (3) summed across each of her expected remaining parities, and (4) when she is retained within the herd and not voluntarily culled. Each subindex was comprised of different components reflecting both genetic and non-genetic effects associated with each female. Transition matrices predicting the expected longevity of each female and their expected month of calving were also utilized in calculating the expected remaining lifetime profitability of each female. The BFPP index was validated on 21,102 beef cows as well as their harvested progeny from 875 herds by stratifying the cows, within herd, into 4 strata based on their BFPP. The mean of the within-herd correlation between the BFPP and the Irish national replacement (i.e., breeding) index was, on average, 0.45 indicating the shortcomings of the breeding index as a culling tool. Cows within the top BFPP stratum had a genetic expectation of accruing almost an additional €36 profit per calving, relative to cows within the worst stratum; when validated on the cow’s own calving interval and survival performance as well as their progeny’s carcass performance, the actual phenotypic value was estimated to be an additional €32 profit per calving. A proportion of this additional profit was due to the harvested progeny of the high BFPP cows having, on average, heavier, more conformed carcasses with less fat cover relative to their poor BFPP contemporaries. This BFPP framework is a useful and easy-to-use tool to aid in producer decision making on the choice of females to voluntarily cull but also on which replacement heifers to graduate into the mature herd.
Formulation of a decision support tool incorporating both genetic and non-genetic effects to rank young growing cattle on expected market valueWhile breeding indexes exist globally to identify candidate parents of the next generation, fewer tools exist that provide guidance on the expected monetary value of young animals. The objective of the present study was therefore to develop the framework for a cattle decision-support tool which incorporates both the genetic and non-genetic information of an animal and, in doing so, better predict the potential market value of an animal, whatever the age. Two novel monetary indexes were constructed and their predictive ability of carcass value was compared to that of the Irish national Terminal breeding index, typical of other terminal indexes used globally. A constructed Harvest index was composed of three carcass-related traits [i.e., 1) carcass weight, 2) carcass conformation and 3) carcass fat, each weighted by their respective economic value] and aimed at purchasers of animals close to harvest; the second index, termed the Calf index, also included docility and feed intake (weighted by their respective economic value), thus targeting purchasers of younger calves for growing (and eventually harvesting). Genetic and non-genetic fixed and random effect model solutions fromthe Irish national genetic evaluations underpinned all indexes. The two novel indexes were formulated using three alternative estimates of an animal's total merit for comparative purposes: 1) an index based solely on the animal's breed solutions, 2) an index which also included within-breed animal differences, and 3) an index which, as well as considering additive and non-additive genetic effects, also included non-genetic effects (referred to as production values [PVs]). As more information (i.e., within breed effects and subsequently non-genetic effects) was included in the total merit estimate, the correlations strengthened between the two proposed indexes and the animal's calculated carcass market value; the correlation coefficients almost doubled in strength when total merit was based on PV-based estimates as compared to the breed solutions alone. Including phenotypic liveweight data, collected during the animal's life, strengthened the predictive ability of the indexes further. Based on the results presented, the proposed indexes may fill the void in decision support when purchasing or selling cattle. In addition, given the dynamic nature of indexes, they have the potential to be updated in real-time as information becomes available.