|Id||Title▲||Authors||Abstract||Picture||Thematic fields||Recommender||Reviewers||Submission date|
15 Dec 2020
Accuracy of predicting chemical body composition of growing pigs using dual-energy X-ray absorptiometryClaudia Kasper, Patrick Schlegel, Isabel Ruiz-Ascacibar, Peter Stoll, Giuseppe Bee https://doi.org/10.1101/2020.09.15.286153
Accurate predictions of chemical composition of pigs for a wide range of body weights: no longer a myth!Recommended by Florence Gondret based on reviews by Mathieu Monziols and 1 anonymous reviewer
Assessing body or carcass composition in growing pigs is essential to refine nutritional models, select for specific traits and evaluate pork products. The gold standard methods are dissection and chemical measurements, which are time-consuming and invasive ways to obtain the data. Different teams have tested dual-energy x-ray absorptiometry (DEXA), especially for determining total and regional body composition of fat, soft lean tissues and bone minerals [1-3]. The DEXA measurements are quick, non-invasive, precise, and operator independent. However, the instruments from different manufacturers are unique in implementation so that it is difficult to obtain and share generalized equations. In addition, the validity and accuracy of the measures when applied to pigs having very different composition have been scarcely addressed.
The present manuscript shows that carcass analysis by DEXA can be used to predict empty body chemical composition, and it provides accuracy values for the content in single nutrients (protein, lipids, Ca, P). The body weight range used to generate differences in body composition is very large (20 to 100 kg), which is important when studying pigs along growth. Moreover, regression equations within weight classes (20, 60 and 100 kg) show no important biases, with the exception for body fat especially at the earliest growth stages. Limitations of the technique are the needs of anesthesia when applied to living pigs, and of standardizing the positions of body, carcass and cuts when applied to living or dissected pigs. Another originality of the manuscript is the comparison of the obtained calibrations with previously published prediction models, showing that the differences do not preclude the possibility to use a single model when built from a meta-analysis of the different data. Taken together, this work offers good perspectives to refine nutritional models by inputs from rapidly analyzed body chemical composition and to monitor body and carcass composition in several pigs for genetics applications.
 Mitchell AD., Scholz AM., Pursel VG., and Evock-Clover CM. (1998). Composition analysis of pork carcasses by dual-energy x-ray absorptiometry. Journal of Animal Science. 76(8), 2104-14. https://doi.org/10.2527/1998.7682104x
 Marcoux M., Bernier JF., and Pomar C. (2003). Estimation of Canadian and European lean yields and composition of pig carcasses by dual-energy X-ray absorptiometry. Meat Science. 63(3), 359-65. https://doi.org/10.1016/S0309-1740(02)00094-3
 Kipper M., Marcoux M., Andretta I., and Pomar C. (2018). Repeatability and reproducibility of measurements obtained by dual-energy X-ray absorptiometry on pig carcasses. Journal of Animal Science, 96(5), 2027-2037. https://doi.org/10.1093/jas/skx046 "
|Accuracy of predicting chemical body composition of growing pigs using dual-energy X-ray absorptiometry||Claudia Kasper, Patrick Schlegel, Isabel Ruiz-Ascacibar, Peter Stoll, Giuseppe Bee||<p>Studies in animal science assessing nutrient and energy efficiency or determining nutrient requirements necessitate gathering exact measurements of body composition or body nutrient contents. Wet chemical analysis methods or standardized dissec...||Agricultural sustainability, Animal nutrition modelling, Monogastrics, Physiology, Pig nutrition||Florence Gondret||2020-09-17 10:44:58||View|
02 Sep 2021
A modelling framework for the prediction of the herd-level probability of infection from longitudinal dataAurélien Madouasse, Mathilde Mercat, Annika van Roon, David Graham, Maria Guelbenzu, Inge Santman Berends, Gerdien van Schaik, Mirjam Nielen, Jenny Frössling, Estelle Ågren, Roger Humphry, Jude Eze, George Gunn, Madeleine Henry, Jörn Gethmann, Simon J. More, Nils Toft, Christine Fourichon https://doi.org/10.1101/2020.07.10.197426
Modelling freedom from disease - how do we compare between countries?Recommended by Rowland Raymond Kao based on reviews by Arata Hidano and 1 anonymous reviewer
In this paper, Madouasse et al. (2021) present a generalisable Bayesian method for calculating the probability that a herd is free from disease, based on its prior disease status, and using data (herd status over time over a sufficient number of herds to inform the model) and reasonable prior estimates of the sensitivity and specificity of tests being used to determine animal infection status. Where available, the modelling approach can also include relevant additional risk factors.
By bringing all these factors together, it allows for most countries to use the same analytical approach on their data, with differences across datasets expressed in terms of the uncertainty around the central estimates.
Having a single methodology that generates both a central estimate of disease freedom, and uncertainty thus provides the opportunity (given typically available data) to compare the probability of freedom across different systems. This is relevant in terms of the context of trade (since international trade of livestock in many cases depends on disease freedom). It is also important when evaluating, for example, transnational burdens of disease - and with different regulations in place in different countries, this is invaluable and can be used, for example, to assess risks of zoonotic infection including for zoonotic infection emergence. In the BVD example provided, the point is made that, since regular testing would probably pick up infection rapidly, the addition of risk factors is most valuable where testing is infrequent. This emphasizes the advantages of direct incorporation of risk factors into a single modelling framework.
From a technical point of view, the analysis compares two different packages for the Markov Chain Monte Carlo (MCMC) implementation necesary to run the model. They show that, while there are some slight systematic differences, the estimates provided by the two methods are similar to each other; as one method is approximate but substantially more stable and generally much more computationally efficient, this is an important outcome. Both implementations are freely available and with relevant additional software made similarly available by the authors. This is extremely welcome and should encourage its general adoption across different countries.
No single model can of course account for everything. In particular, the reliance on past data means that there is an implicit assumption common to all purely statistical methods that the underlying risks have not changed. Thus projections to altered circumstances (changing underlying risk factors or systematic changes in testing or test performance) cannot so easily be incorporated, since these factors are complicated by the dynamics of infection that lie outside the modelling approach. Of course the well known quote from George Box that "all models are wrong" applies here - the generality of approach, statistical robustness and open source philosophy adopted make this model very useful indeed.
Madouasse A, Mercat M, van Roon A, Graham D, Guelbenzu M, Santman Berends I, van Schaik G, Nielen M, Frössling J, Ågren E, Humphry RW, Eze J, Gunn GJ, Henry MK, Gethmann J, More SJ, Toft N, Fourichon C (2021) A modelling framework for the prediction of the herd-level probability of infection from longitudinal data. bioRxiv, 2020.07.10.197426, ver. 6 peer-reviewed and recommended by PCI Animal Science. https://doi.org/10.1101/2020.07.10.197426
|A modelling framework for the prediction of the herd-level probability of infection from longitudinal data||Aurélien Madouasse, Mathilde Mercat, Annika van Roon, David Graham, Maria Guelbenzu, Inge Santman Berends, Gerdien van Schaik, Mirjam Nielen, Jenny Frössling, Estelle Ågren, Roger Humphry, Jude Eze, George Gunn, Madeleine Henry, Jörn Gethmann, Sim...||<p>The collective control programmes (CPs) that exist for many infectious diseases of farm animals rely on the application of diagnostic testing at regular time intervals for the identification of infected animals or herds. The diversity of these ...||TEST, Veterinary epidemiology||Rowland Raymond Kao||2020-07-23 08:13:18||View|
10 Aug 2022
Decreasing the level of hemicelluloses in sow's lactation diet affects the milk composition and post-weaning performance of low birthweight piglets.Francesco Palumbo, Giuseppe Bee, Paolo Trevisi, Marion Girard https://doi.org/10.31220/agriRxiv.2022.00116
Varying the hemicellulose content in the diet of lactating sows highlights the importance of early-life interventions for improving health and performance of small piglets during the post-weaning periodRecommended by Florence Gondret based on reviews by Hélène Quesnel and Myriam Grundy
One of the key questions in pig industry nowadays is how health and performance of piglets can be improved by sow nutrition and milk composition. The levels of dietary fibers in sow’s gestation diet have positive effects observed on the litters. However, the composition of dietary fibers and the organization of polysaccharides within the cell wall in the different plants determine their physicochemical properties and, thereby, their behaviour in the gut of the sows and the subsequent physiological response of the animals. Hemicelluloses are polysaccharides constituents of the cell walls of plants, which are fermented in the gut to produce volatile fatty acids (VFA). These VFA can serve as energy source for milk synthesis and can thereby influence the development of suckling piglets. Palumbo and colleagues (1) proposed an original experimental design to compare diets with similar fiber contents but different hemicellulose levels, thanks to varying the sources of fibers used in the dietary formulations. Effects were studied on performance and health of lactating sows and their piglets during suckling period and until post-weaning. The dietary treatments had no effect on the total number of piglets weaned and, consequently, on litter weight at weaning. Milk yield was not influenced by the dietary treatments, but milk composition (lactose content, copper and threonine proportions) was affected by the level of hemicellulose in the maternal diets. With a decreasing hemicellulose level in sow diet, milk lactose content linearly decreased, whereas the copper and threonine contents linearly increased. There was no effect on piglet performance during the lactation period. During the second week of post-weaning, a quadratic increase in the incidence of diarrhoea and the number of days with diarrhoea for suckling piglets was observed with decreasing hemicellulose level in diet. Interestingly, the observed effects were partly different for piglets born with a low body weight. Indeed, there was a linear decrease in the incidence of diarrhoea and days with diarrhoea with decreased hemicellulose level in the maternal diet for those piglets, together with increased growth performance from birth to two weeks post-weaning. The authors postulated that the improved growth performance and the lower incidence of diarrhoea observed in small piglets during post-weaning period may be related to the increased abundance of threonine and copper and increased concentration of total VFA in milk of sows fed a diet with reduced hemicellulose levels. This study confirms the importance of early-life interventions to improve the post-weaning development and health of this sub-population of piglets.
(1) Palumbo F, Bee G, Trevisi P, and Girard M. (2022). Decreasing the level of hemicelluloses in sow's lactation diet affects the milk composition and post-weaning performance of low birthweight piglets. agriRxiv 2022.00116, ver 4 (R3), peer-reviewed and recommended by PCI Animal Science. https://doi.org/10.31220/agriRxiv.2022.00116
|Decreasing the level of hemicelluloses in sow's lactation diet affects the milk composition and post-weaning performance of low birthweight piglets.||Francesco Palumbo, Giuseppe Bee, Paolo Trevisi, Marion Girard||<p>Hemicelluloses (HC) are polysaccharides constituents of the cell walls of plants. They are fermented in the gut to produce volatile fatty acids (VFA). The present study investigated the effects of decreasing HC level in sow's lactation diet on ...||Pig nutrition||Florence Gondret||2022-01-21 12:00:22||View|
01 Sep 2022
Detecting dairy cows' lying behaviour using noisy 3D ultrawide band positioning dataI. Adriaens, W. Ouweltjes, M. Pastell, E. Ellen, C. Kamphuis https://doi.org/10.5281/zenodo.6627251
A novel method to monitor lying behaviour of dairy cows by combining noisy spatial positioning data, time-series segmentation based on statistical changepoints and machine learning classification algorithmRecommended by Eliel Gonzalez-Garcia based on reviews by Kareemah Chopra and John Fredy Ramirez Agudelo
Using on-farm sensors in dairy farming is known to help decision makings and farmer objectives in the monitoring and potential improvement of animal behaviour, health and production performance. However, in indoor positioning systems, data interpretation is complicated by the inaccuracy and noise in the time series, missing data caused not only by sensor failure or the harsh and changing farm environments in which they operate, but also by the animals' specific physiology itself. Thus, working with spatial data has proven challenging mainly due to their enormous heteroscedasticity, which depends on multiple factors such as the cow, the time of the day, the behaviour, factors interfering with the sensor system, etc., for which we cannot account mathematically. Applying purely black-box approaches generally results in insufficient robustness, interpretability and generalisability.
With this work, Adriaens et al. (2022) developed a relatively simple and new methodology to monitor the lying behaviour of dairy cows by using noisy spatial positioning data, while combining time-series segmentation based on statistical changepoints and a machine learning classification algorithm. The two-step methodology identifies lying behaviour using an ultra-wide band indoor positioning system. Getting-up or lying-down events were indicated by the accelerometers. Overall classification and lying behaviour prediction performance was above 91% in independent test sets, with a very high consistency across cow-days. The robustness of the algorithm was demonstrated by the fact that both the cow identity-based split and the time-based split performed equally well.
The article represents an original contribution for advancing the state of the art in the automated quantification of lying behaviour in dairy cows, aiming to monitor health or animal welfare issues. Future research must be considered however to validate the performance of the model when using different position-measuring technologies, in other farm settings and over a longer period of time.
Adriaens I, Ouweltjes W, Pastell M, Ellen E, Kamphuis C. 2022. Detecting dairy cows' lying behaviour using noisy 3D ultra-wide band positioning data. Zenodo, 6627251, ver. 3 peer-reviewed and recommended by Peer Community in Animal Science. https://doi.org/10.5281/zenodo.6627251
|Detecting dairy cows' lying behaviour using noisy 3D ultrawide band positioning data||I. Adriaens, W. Ouweltjes, M. Pastell, E. Ellen, C. Kamphuis||<p>In precision livestock farming, technology-based solutions are used to monitor and manage<br>livestock and support decisions based on on-farm available data. In this study, we developed<br>a methodology to monitor the lying behaviour of dairy c...||Animal behaviour , Mathematical modelling, Precision livestock farming||Eliel Gonzalez-Garcia||2022-02-28 18:19:37||View|
14 Oct 2020
Determining insulin sensitivity from glucose tolerance tests in Iberian and Landrace pigsJ. M. Rodríguez-López, M. Lachica, L. González-Valero, I. Fernández-Fígares https://doi.org/10.1101/2019.12.20.884056
Iberian pigs: more than excellent ham!Recommended by Jordi Estellé based on reviews by 2 anonymous reviewers
Iberian pigs represent a treasured resource that allows the maintenance of their “montanera” traditional breeding system and, thus, contributes to the socioeconomic sustainability of the rural areas in the south-western regions of Iberian Peninsula. While the excellence of Iberian meat products is widely recognized, the idea of using Iberian pigs as biomedical models is currently emerging. Interestingly, due to the particular fatty acid metabolism of this porcine breed, Iberian pigs have been proposed as models for type 2 diabetes (Torres-Rovira et al. 2012) or obesity-related renal disease (Rodríguez et a. 2020).
In the present manuscript, Rodríguez-López et al. provide further insights on the particularities of “obese” Iberian pigs by comparing their insulin sensitivity in a glucose tolerance test with that of commercial “lean” Landrace pigs. The authors compared four Iberian pigs with five Landrace pigs in an intense time-series following an intra-arterial glucose tolerance test and measuring insulin, glucose, lactate, triglycerides, cholesterol, creatinine, albumin and urea plasma levels. Several of these parameters showed significant differences between both breeds, with some of them being compatible with an early stage of insulin resistance in Iberian pigs. These results are relevant from an animal production perspective, but provide also further evidence for considering the Iberian pigs as a suitable biomedical model for obesity-related disorders.
 Torres-Rovira, L., Astiz, S., Caro, A., Lopez-Bote, C., Ovilo, C., Pallares, P., Perez-Solana, M. L., Sanchez-Sanchez, R., & Gonzalez-Bulnes, A. (2012). Diet-induced swine model with obesity/leptin resistance for the study of metabolic syndrome and type 2 diabetes. The Scientific World Journal, 510149. https://doi.org/10.1100/2012/510149
|Determining insulin sensitivity from glucose tolerance tests in Iberian and Landrace pigs||J. M. Rodríguez-López, M. Lachica, L. González-Valero, I. Fernández-Fígares||<p>As insulin sensitivity may help to explain divergences in growth and body composition between native and modern breeds, metabolic responses to glucose infusion were measured using an intra-arterial glucose tolerance test (IAGTT). Iberian (n = 4...||Monogastrics, Physiology, Pig nutrition||Jordi Estellé||2019-12-28 10:51:03||View|
05 Dec 2019
Effects of feeding treatment on growth rate and performance of primiparous Holstein dairy heifersYannick Le Cozler, Julien Jurquet, Nicolas Bedere https://doi.org/10.1101/760082
Optimizing growth rate of dairy heifers through nutrition to maximize reproduction and productionRecommended by Luis Tedeschi based on reviews by Emilio Mauricio Ungerfeld and 2 anonymous reviewers
The idea of altering the growth rate of replacement heifers to improve reproductive and productive indicators of dairy cattle is not new. In the late 1970s, Gill and Allaire  indicated that the first parturition between 22.5 to 23.5 months of age yielded the optimum lifetime performance as long as the heifers had adequate body size . Since 1980s, many studies have been conducted to understand the partitioning of energy between growth and lactation, including the impact of growth rates on the heifer puberty  as well as growth and development of the mammary gland [4,5]. The senior author of the recommended study has written previously about this research topic .
In the present manuscript, Le Cozler et al. studied the effect of feeding programs to increase the growth rate of late-born heifers to catch up with the growth of those born earlier in the calving season on their reproductive and productive performance. The authors analyzed 217 heifers for three consecutive years, split into three dietary treatments: control (C), accelerated growth rate from birth to 6 months of age (ID1), or accelerated growth rate from birth to 12 months of age (ID2). In this study, the late-born heifers receiving the ID2 treatment were able to partially reach the bodyweight of the early-born heifers at 24 months of age. In part, the incomplete understanding of the prioritization of the use of energy (and other nutrients) for different physiological stages (e.g., maintenance, growth, lactation, and pregnancy) of the dairy animal  undercuts the development of more robust feeding strategies to improve the reproductive and productive performance of the animal. In the recommended study by Le Cozler et al., although there was no impact on reproductive performance among groups, heifers in the group ID2 produced less milk (about 400 kg for the whole first lactation) than heifers in the groups C and ID1, apparently suggesting that energy allocation for growth had priority over that needed for lactation. The question then becomes what would have happened with energy partitioning if energy intake was restricted. Studies like this one are important to shed some light on the prioritization of the use of energy and other nutrients in support of growth, pregnancy, and lactation of dairy animals, and how compensatory growth differs between meat versus dairy growing animals, both physiologically and energetically.
 Gill, G. S., & Allaire, F. R. (1976). Relationship of Age at First Calving, Days Open, Days Dry, and Herdlife to a Profit function for Dairy Cattle1. Journal of Dairy Science, 59(6), 1131–1139. doi: 10.3168/jds.S0022-0302(76)84333-0
|Effects of feeding treatment on growth rate and performance of primiparous Holstein dairy heifers||Yannick Le Cozler, Julien Jurquet, Nicolas Bedere||<p>The objective of this study was to investigate effects of feeding-rearing programs that aim for first calving at 20-27 months (mo) of age on growth, reproduction and production performance of Holstein cows at nulliparous and primiparous stages....||Cattle production, Reproduction, Ruminant nutrition||Luis Tedeschi||2019-09-09 09:22:36||View|
14 Dec 2022
Feed efficiency of lactating Holstein cows was not as repeatable across diets as within diet over subsequent lactation stagesAmelie Fischer, Philippe Gasnier, philippe faverdin https://doi.org/10.1101/2021.02.10.430560
A focus on feed efficiency reproducibility and repeatability of dairy cows fed different diets over the lactation stage.Recommended by Alberto Atzori based on reviews by Ioannis Kaimakamis, Angela Schwarm and 2 anonymous reviewers
The topic of feed efficiency is under discussion in the scientific community and several studies pointed out that lactation stage has to be accounted for when estimates of feed efficiency are carried out, especially for genetic ranking of animals and their performances, as highlighted by Li et al. (2017). Other researchers applied a latin square design to test dietary effects across lactation (Ipharraguerre et al. 2002) but this approach cannot be followed out of experimental conditions and particularly does not allow, nowadays, to valorize precision livestock farm data to get phenotypic information from individual animals at farm level.
The current manuscript by Fischer, et al. (2022a) describes an experimental trial in which cows were first fed a high starch diet-low fibre then switched over to a low starch diet-high fibre and individually monitored over time. Data were analyzed with the objective to investigate effects within diets and across diets. Since all cows went through the same sequence at the same time it was not possible to completely separate the confounding effect of lactation stage and diet as stated by the authors. However, this manuscript adds methodological discussions and opens research questions especially to the matter of repeatability and reproducibility of feed efficiency of individual animals over the lactation stage. These variables are fundamental to evaluate nutritional traits and phenotypic performances of dairy cows at farm level, as highlighted by a paper of the same first author (Fischer, et al. 2022b) dealing to reproducibility and repeatability with a similar approach. My opinion is that this manuscript gives the opportunity to enlarge the scientific discussions on the calculation of repeatability and reproducibility of feed efficiency of individual animals over time. In particular, as in this study, specific mathematical approaches need to be carried out with the final goal to analyze and valorize precision livestock farm data for cow phenotyping and to propose new methods of feed efficiency evaluations. It also needs complete databases carried out under experimental conditions. In fact it has to be considered that this manuscript makes available to the scientific community all the data and the R code developed for data analysis giving the opportunity to replicate the calculations and propose new advancements in the feed efficiency evaluations of dairy cows.
Fischer A, Gasnier P, Faverdin P (2022a) Feed efficiency of lactating Holstein cows was not as repeatable across diets as within diet over subsequent lactation stages. bioRxiv, 2021.02.10.430560, ver. 3 peer-reviewed and recommended by Peer Community in Animal Science. https://doi.org/10.1101/2021.02.10.430560
Fischer A, Dai X, Kalscheur KF (2022b) Feed efficiency of lactating Holstein cows is repeatable within diet but less reproducible when changing dietary starch and forage concentrations. animal, 16, 100599. https://doi.org/10.1016/J.ANIMAL.2022.100599
Ipharraguerre IR, Ipharraguerre RR, Clark JH (2002) Performance of Lactating Dairy Cows Fed Varying Amounts of Soyhulls as a Replacement for Corn Grain. Journal of Dairy Science, 85, 2905–2912. https://doi.org/10.3168/JDS.S0022-0302(02)74378-6
Li B, Berglund B, Fikse WF, Lassen J, Lidauer MH, Mäntysaari P, Løvendahl P (2017) Neglect of lactation stage leads to naive assessment of residual feed intake in dairy cattle. Journal of Dairy Science, 100, 9076–9084. https://doi.org/10.3168/JDS.2017-12775
|Feed efficiency of lactating Holstein cows was not as repeatable across diets as within diet over subsequent lactation stages||Amelie Fischer, Philippe Gasnier, philippe faverdin||<p> Background: Improving feed efficiency has become a common target for dairy farmers to<br>meet the requirement of producing more milk with fewer resources. To improve feed<br>efficiency, a prerequisite is to ensure that the cows identified...||Cattle production, Ruminant nutrition||Alberto Atzori||Anonymous, Ioannis Kaimakamis, Giuseppe Conte, Angela Schwarm||2021-02-11 08:43:59||View|
24 May 2022
Identifying cattle with superior growth feed efficiency through their natural 15N abundance and plasma urea concentration: a meta-analysis.Gonzalo Cantalapiedra-Hijar, Isabelle Morel, Bernard Sepchat, Céline Chantelauze, Gemma A. Miller, Carol-Anne Duthie, Isabelle Ortigues-Marty, Richard J. Dewhurst https://doi.org/10.5281/zenodo.5783960
15N as a marker for feed efficiency in beef cattleRecommended by Marcos Marcondes based on reviews by Emilio Mauricio Ungerfeld and 1 anonymous reviewer
Identifying individuals with a more remarkable feed efficiency may positively affect the profitability and sustainability of the beef industry (Cruz et al., 2010; Basarab et al., 2013). However, although most international nutrient requirements systems predict animal feed efficiency, intake data is usually unavailable at the farm level, and ranking animals based on efficiency might be challenging. In this sense, using differences in the occurrence of isotopic N between animal and diet (Δ15Nanimal-diet) might become a natural biomarker to determine feed efficiency at the farm level. This methodology was firstly demonstrated by Guarnido-Lopez et al. (2021). In the present study by Cantalapiedra-Hijar et al. (2022), the authors evaluated the extent to which Δ15Nanimal-diet can be used as a marker for feed efficiency in beef animals. For this, a meta-analysis was conducted using a database including 759 individual records for performance and N isotopic discrimination measured in plasma or muscle (Δ15Nanimal-diet; n = 749) and plasma urea concentration (n = 659). The database was composed of 37% Charolais, 15% Simmental, and 40% of beef crossbreds. The results confirmed that Δ15Nanimal-diet could discriminate animals with at least 0.10 kg/kg difference in feed efficiency. Furthermore, the Δ15Nanimal-diet marker also successfully discriminated the feed efficiency of two animals from the same contemporary group if they differ by at least 0.06 kg/kg of FCE. However, when trying to predict feed efficiency, using the two candidate biomarkers did not improve estimates. Lastly, when data from biomarkers were combined with performance data, improvement in the predictions was observed. Nonetheless, the present results warrant more studies to evaluate the use of Δ15Nanimal-diet as a biomarker for feed efficiency since it could be used not only for feed efficiency discrimination but also in genetic selections.
Cantalapiedra-Hijar G, Morel I, Sepchat B, Chantelauze C, Miller GA, Duthie CA, Ortigues-Marty I, Dewhurst RJ (2022). Identifying cattle with superior growth feed efficiency through their natural 15N abundance and plasma urea concentration: A meta-analysis. Zenodo, 5783960, ver. 3 peer-reviewed and recommended by Peer community in Animal Science. https://doi.org/10.5281/zenodo.5783960.
Cruz GD, Rodríguez-Sánchez JA, Oltjen JW, Sainz RD (2010). Performance, residual feed intake, digestibility, carcass traits, and profitability of Angus-Hereford steers housed in individual or group pens. J. Anim. Sci. 88:324-329. https://doi.org/10.2527/jas.2009-1932.
Basarab JA, Beauchemin KA, Baron VS, Ominski KH, Guan LL, Miller SP, Crowley JJ (2013). Reducing GHG emissions through genetic improvement for feed efficiency: effects on economically important traits and enteric methane production. Animal 7:303-315. https://doi.org/10.1017/S1751731113000888.
Guarnido-Lopez P, Ortigues-Marty I, Taussat S, Fossaert C, Renand G, Cantalapiedra-Hijar G (2021). Plasma proteins Δ15N vs. plasma urea as candidate biomarkers of between-animal variations of feed efficiency in beef cattle: Phenotypic and genetic evaluation. Animal 15:100318. https://doi.org/10.1016/j.animal.2021.100318.
|Identifying cattle with superior growth feed efficiency through their natural 15N abundance and plasma urea concentration: a meta-analysis.||Gonzalo Cantalapiedra-Hijar, Isabelle Morel, Bernard Sepchat, Céline Chantelauze, Gemma A. Miller, Carol-Anne Duthie, Isabelle Ortigues-Marty, Richard J. Dewhurst||<p>The objective of this study was to test two candidate biomarkers of feed efficiency in growing cattle. A database was built using performance data from 13 trials conducted with growing heifers, steers and young bulls and testing 34 dietary trea...||Physiology, Ruminant nutrition||Marcos Marcondes||2021-12-07 15:24:15||View|
05 Jul 2022
Impact of pre-breeding feeding practices on rabbit mammary gland development at mid-pregnancy.Cathy Hue-Beauvais, Karine Bebin, Raphael Robert, Delphine Gardan-Salmon, Mickael Maupin, Nicolas Brun, Etienne Aujean, Florence Jaffrezic, Steve Simon, Madia Charlier, Fabienne Le Provost https://doi.org/10.1101/2022.01.17.476562
Managing the feeding of rabbits to improve metabolic efficiencyRecommended by Giuseppe Conte based on reviews by Marion Boutinaud, Davi Savietto and 1 anonymous reviewer
A correct execution of feeding plan for growing rabbit decreases the possibility of post-weaning digestive disorders, thus enhancing the feed efficiency in the animals. However, a limitation of feed daily quantity is required between 10 weeks of age and the first artificial insemination. This limitation causes energy deficiency with a consequent reduction in fertility. Beauvais et al. (2022) studied the impact of feed restriction strategies in female rabbits. Four feed restriction strategies were applied in two distinct periods (post-weaning and puberty) and evaluated by different physiological parameters (growth rate, metabolic profiles, reproductive parameters and mammary gland development). In the first part of the paper, the authors evaluated the association between weight slopes and feeding strategies in the late post-weaning and peripartum period in the four groups. As revealed by the authors, a significant difference was observed during the late post-weaning period, which remained significant between the pubertal and fattening phases. Probably these differences are related to the restriction feeding pattern. The results indicated that restrictive feeding changes in the first step of post-weaning period is associated with a significant difference in body weight. This difference occurs from the third week of diet, highlighting the high sensitivity of growing rabbit to nutrition during the post-weaning period.
In the second part of the paper, the authors evaluated the expression of genes involved in the lipid metabolism. During the mid-pregnancy, was revealed a significant higher expression of lipogenic genes, which may be considered as useful markers for the mammary epithelial development in less restrictive strategies during early life period.
The results proposed by Beauvais et al. (2022) enlighten the important role played by the feeding conditions of young female rabbits in the early life rearing. In particular, this activity provides specific recommendations for optimizing lactation and thus preventing neonatal mortality of the offspring. Moreover, the authors provide indications about the effect of feeding strategies on the mammary development and gene expression with absolute consequences on the development of offspring. Mammary lipid metabolism affects the milk profile and therefore the growth performance of the young animals.
Hue-Beauvais C, Bebin K, Robert R, Gardan-Salmon D, Maupin M, Brun N, Aujean E, Jaffrezic F, Simon S, Charlier M, Le Provost F (2022). Impact of pre-breeding feeding practices on rabbit mammary gland development at mid-pregnancy. biorXiv, 2022.01.17.476562, ver. 3 peer-reviewed and recommended by Peer Community in Animal Science. https://doi.org/10.1101/2022.01.17.476562
|Impact of pre-breeding feeding practices on rabbit mammary gland development at mid-pregnancy.||Cathy Hue-Beauvais, Karine Bebin, Raphael Robert, Delphine Gardan-Salmon, Mickael Maupin, Nicolas Brun, Etienne Aujean, Florence Jaffrezic, Steve Simon, Madia Charlier, Fabienne Le Provost||<p>Optimizing rabbit does preparation during early life to improve reproductive potential is a major challenge for breeders. Does selected for reproduction have specific nutritional needs, which may not be supplied with the common practice of feed...||Animal nutrition modelling||Giuseppe Conte||2022-01-19 14:44:30||View|
06 Sep 2019
Lactation curve model with explicit representation of perturbations as a phenotyping tool for dairy livestock precision farming.Ben Abdelkrim Ahmed, Puillet Laurence, Gomes Pierre, Martin Olivier https://doi.org/10.1101/661249
Developing smart fitting algorithms to identify random perturbations in time-series dataRecommended by Luis Tedeschi based on reviews by Alberto Atzori, Jennifer Spencer and 1 anonymous reviewer
The ability to adequately characterize the lactation curve of livestock is important not only to ensure proper nutrition of the lactating animal but, among many other benefits, it can assist in diagnosing the incidence of diseases, predicting the quantity of milk production, and comparing animals within the herd for managerial strategies such as culling. Eventually, such smart fitting algorithms can lead to improved genetic selection of more productive animals after genetic-unrelated noises are removed from the data, systematically.
 Johansson, I. (1961). Genetic Aspects of Dairy Cattle Breeding. University of Illinois Press, Urbana, IL.
 Nelder, J. A. (1966). Inverse polynomials, a useful group of multi-factor response functions. Biometrics. 22 (1):128-141. doi: 10.2307/2528220
|Lactation curve model with explicit representation of perturbations as a phenotyping tool for dairy livestock precision farming.||Ben Abdelkrim Ahmed, Puillet Laurence, Gomes Pierre, Martin Olivier||<p>Background Understanding the effects of environment on livestock provides valuable information on how farm animals express their production potential, and on their welfare. Ruminants are often confronted with perturbations that affect their per...||Lactation biology , Mathematical modelling, Precision livestock farming||Luis Tedeschi||2019-06-07 09:38:26||View|
Luis O. Tedeschi