104,967 research outputs found
Genetic profile of total body energy content of Holstein cows in the first three lactations
Full text linkWeekly total body energy content (TBEC) was calculated for 444 Holstein cows in their first 3 lactations. These calculations were based on body lipid and protein changes predicted from weekly changes in body condition score and live weight of each cow. In first lactation, cows lost TBEC during the initial 8 wk, regained it by wk 22, and continued to build up their reserves until wk 37. Cows started lactations 2 and 3 with considerable reserves from the dry period that they used during the first 13 wk of lactation. Variance components for TBEC were estimated using random regression analysis allowing for heterogeneous residual variance. The genetic variance increased within each lactation, suggesting that the genetic component becomes more important as lactation progresses. The genetic correlations between very early ( wk 1 to 4) and later stages of first lactation were near zero but they increased considerably between later lactation stages. Genetic correlations between TBEC on wk 5 of first lactation and the remainder of this lactation ranged from 0.64 for the more distant weeks to 0.99 for the immediately subsequent weeks. Genetic correlations with TBEC in second lactation were moderately high (0.68 to 0.70) for the early weeks ( 1 to 8) and decreased gradually to 0.56 for weeks at the end of lactation. For third lactation, these estimates ranged from 0.53 to 0.63. Genetic correlation estimates of TBEC in wk 12 of first lactation with subsequent first-lactation weeks varied from 0.79 to 0.99, whereas they ranged from 0.65 to 0.77 and from 0.57 to 0.68 in second and third lactations, respectively. The genetic correlation between TBEC in later weeks of first lactation and the rest of productive life increased as first lactation progressed, but the improvement diminished. Weekly genetic evaluations for first-lactation TBEC were used to predict second- and third-lactation energy content. The accuracy of these predictions increased with progressing weeks in first lactation, but about three-fourths of the improvement occurred by wk 5. Our results suggest that TBEC calculated after a month from the first calving may give useful information about the future energy content of a cow.</p
Eliciting, antimicrobial and film-forming properties of chitosan applied on fresh fruit and vegetables.
No full textBlogForever D5.3: User Questionnaires and Reports
Full text linkThis report presents the feedback gathered from third party users during the BlogForever Case Studies. Therefore, the research framework is defined and the case studies results are presented, followed by a summary of conclusions and remarks
The accuracy of test day model evaluation for the Italian Holstein
No full textGenetic evaluation for production traits in the Holstein breed in Italy has been based on a Random Regression Test Day Model (RRTDM) since November 2004. More specifically, the model is a multiple lactation, multiple trait RRTDM, similar to the model used in Canada for official genetic evaluation. Fixed regression curve effect include time, region, age at calving, parity and season of calving. Last changes in the model included a new definition of the proof scale and of the genetic base. The accuracy of the model was assessed by analyzing residuals and testing Mendelian sampling trends. Residuals were normally distributed for all traits and had zero mean. Residual trends for all the effects included in the model were analyzed also for effects not included in the model like number of milkings per day and number of days pregnant at the test date. Mendelian sampling did not show any significant trend over time both for cows and bulls
Weighting factors of sire daughter information in international genetic evaluations
Full text linkInternational genetic evaluations of dairy bulls are currently based on national genetic evaluation results. Total number of daughters in a country is used to weight national information, but may not optimally reflect the precision of a sire's daughter contribution to international genetic evaluations. This study investigates the impact of alternative weighting factors on international evaluation results. A conventional progeny test scheme was simulated for two dairy cattle populations, with semen exchange at a fixed rate after each generation, True breeding values for both populations were generated as bivariate normal deviates. Each cow had three lactation records in one country only. After 10 generations of selection, all records were used in national breeding value prediction. National breeding values of bulls were used as input to international evaluations. Seven different weighting factors were evaluated: 1) total number of daughters; 2) total number of lactations; 3) as tone) also adjusted for finite contemporary group size; 4) as (three) also adjusted for distribution of daughters over contemporary groups; 5) effective daughter contribution considering finite contemporary group size and correlation between repeated records; 6) as (five) also considering the reliability of the daughter dam evaluation; and 7) as (five) also considering the reliability of the daughter female ancestors' evaluations. Using the last two weighting factors yielded empirically unbiased estimates of sire variance. Using total number of daughters overestimated genetic variance by up to 7%. In general, international breeding values were marginally affected by choice of weighting factor. The effect was larger when different national evaluation models had been applied in the two countries. International reliabilities for the last two weighting factors were close to expectation, whereas using total number of daughters resulted in 1 to 4% negative bias. In practice, different countries apply a wide range of national evaluation models, and genetic ties may be weak between some populations, thereby increasing the potential effect of weighting factors on international comparisons. The weighting factor developed in this study, which considers contemporary group structure, correlation between repeated records, and reliability of dams of daughters, should replace total number of daughters in international genetic evaluations of dairy sires.</p
Bibliographie Hilarion G. Petzold 1958 – 2009 mit Anhang als Einführung
No full textDieses Archiv enthält die Gesamtbibliographie der Werke des Autors nebst einiger Texte „Über H. G. Petzold“ im Schlussteil der Bibliographie sowie einen Anhang mit einer Einführung in die Architektur des Werkes in seinem wissenslogischen Aufbau als Ausarbeitung seines „Tree of Science Modells“ (2007).This archive contains the complete bibliography of the author and some texts about H. G. Petzold, moreover an epilogue with an introduction to the architecture of the works in its epistemological structure and composition and as an elaborations of Petzold’s „Tree of Science Modell (2007).https://www.fpi-publikation.de/polyloge/01-2009-petzold-h-g-gesamtbibliographie-h-g-petzold-1958-2009-updating-november2009/peerReviewedpublishedVersio
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
A Measurement Approach for Characterizing Temperature-Related Emissivity Variability in High-Emissivity Materials
No full textThe effective knowledge of emissivity is pivotal to obtain reliable temperature measurements through non-contact techniques like pyrometry and thermal imaging. This is fundamental in high-temperature applications since material emissivity strongly depends on temperature conditions. Given the recent attention in high-temperature applications, especially for replacing fossil-fuel-dependent heating with greener solutions in energy-intensive processes, renewed interest in characterizing materials radiant properties rose. This work presents a measurement procedure for characterizing the total emissivity of high-emissivity materials exploiting microwaves for heating the test material. The procedure grounds on a sequential approach, using a reference material of known emissivity (e.g., high-emissivity coating, already characterized sample holder, etc.) to derive the target material total emissivity. Uncertainty analysis is performed to provide a metrological characterization of the approach. The procedure is validated on target materials of known emissivity, focusing on high-emissivity materials commonly employed in microwave heating processes. Results are compatible with reference literature and material datasheets, demonstrating the validity of the proposed approach
Technical note: Prediction of liveweight from linear conformation traits in dairy cattle
Full text linkThe objectives of this study were to derive phenotypic and genetic prediction equations of liveweight from linear conformation traits, and estimate genetic and phenotypic parameters for these traits. Data pertained to 2,728 conformation and liveweight records of 613 cows in 1,529 lactations. Cows were raised at the Scottish Agricultural College research station and had calved between 2002 and 2010. Fifteen linear conformation traits were considered as predictors. To validate phenotypic predictions, the data set was randomly split into independent reference and validation subsets. Reference subsets were used to derive prediction equations with the use of a mixed model. Comparisons between predicted and actual liveweight in the validation subsets indicated that stature, chest width, body depth, and angularity could be used to derive phenotypic predictions of liveweight. Accuracy of these predictions was better for first-lactation than for all-lactation liveweight data. Significant genetic correlations between liveweight and the 4 predictor traits ranged from 0.49 to 0.76, and phenotypic correlations were 0.33 to 0.56. Estimated genetic (co)variances were used to develop prediction equations of animal genetic merit for liveweight from routinely calculated genetic evaluations for conformation traits.</p
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