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Combining a bioclimatic and a growth model to assess the effect of management practices and building ambiance on growing pig performances at the batch level

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Ludovic Brossard et al.,9 Workshop on Modelling Nutrient Digestion and Utilization in Farm Animals,Ubatuba Itamambuca, Brésil, 14 – 16 septembre 2019, poster

Most pigs in the EU are reared in rooms with controlled ambient conditions. Bioclimatic models represent and predict the energy balance and the direct energy consumption at the room level, based on characteristics of the building, management of the climate control tool and average performance of pigs. Available growth models usually simulate performance of animals, including indirect energy (i.e. feed intake), under thermoneutral conditions.

Document réservé Espace Pro, veuillez vous identifier
2019

Maturité des porcelets : comment l'évaluer par imagerie et ainsi améliorer la survie ?

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Pauline Brenaut, Porc Mag (FRA), 2019, n° 547, novembre, p. 27

Basé sur de l'imagerie, le projet Pic'Let (PICture of pig LET) a pour objectif de développer un capteur capable de détecter précocement les porcelets immatures. Présentation.

2019

Smartpharm, la pharmacie connectée

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Michel Marcon, Réussir Porc/ Tech Porc (FRA), 2019, n° 273, novembre, p. 38

L’Ifip a codéveloppé et testé un outil de numérisation des saisies des traitements vétérinaires qui permet le suivi sanitaire de l’élevage et assure une traçabilité complète.

PDF icon Michel Marcon, Réussir Porc/ Tech Porc (FRA), 2019, n° 273, novembre, p. 38
2019

La station expérimentale de l’Ifip fait peau neuve

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Yvonnick Rousselière, Réussir Porc/ Tech Porc (FRA), 2019, n° 273, novembre, p. 44-45

La station expérimentale de Romillé va connaître entre 2019 et 2020 une évolution ambitieuse. Éric Gault, responsable du site, nous fait entrer dans les coulisses des travaux à venir.

PDF icon Yvonnick Rousselière, Réussir Porc/ Tech Porc (FRA), 2019, n° 273, novembre, p. 44-45
2019
Planning linéaire annuel ifip

Planning linéaire annuel

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Pour gérer la conduite de l’élevage au jour le jour !

Ce calendrier permet de gérer efficacement la conduite des bandes de truies : il permet en premier lieu de connaître exactement la date de mise bas des truies en notant leur date d'insémination. Il sert aussi à noter tous les soins apportés à la bande de truies et à leurs porcelets, jour par jour, sur toute une année. Véritable mémoire pour l'éleveur, il permet de visualiser d’un seul coup d’œil le programme des interventions à réaliser, de contrôler l’efficacité des groupages et la fréquence des retours, d’enregistrer les résultats techniques par bande et les performances de chaque truie... Pour les éleveurs, c'est un outil du quotidien que l'Ifip met à leur service depuis de nombreuses années...

Un support mural est nécessaire pour enrouler la bande d'enregistrement papier (3 mois visibles d'un coup) et nous donnons quelques conseils pour débuter l'utilisation du planning : Notice d’utilisation (pdf 600 ko) 

Édition 2019 utilisable de décembre 2018 jusqu’à janvier 2020 - format 53 x 390 cm

35,00 €
2019

Détection et suivi de la toux

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Yvonnick Rousselière, Réussir Porc/Tech Porc (FRA), 2019, n° 272, octobre, p. 41

L’Ifip a testé sur la station expérimentale de Romillé un dispositif d’enregistrement capable de détecter la présence de toux en élevage puis de suivre l’évolution de cette pathologie respiratoire.

PDF icon Yvonnick Rousselière, Réussir Porc/Tech Porc (FRA), 2019, n° 272, octobre, p. 41
2019

Smart Tracking surveille l'activité des porcs

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Michel Marcon, Réussir Porc/Tech Porc (FRA), 2019, n° 272, octobre, p. 17-18

Savoir comment se comporte chaque porc dans les cases, combien de temps ils passent à manger ou boire… C’est ce que propose le Smart Tracking actuellement testé à la station de l’Ifip à Romillé.

PDF icon Michel Marcon, Réussir Porc/Tech Porc (FRA), 2019, n° 272, octobre, p. 17-18
2019

Mélanger antibiotiques et biocides dans l'eau peut être risqué

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Anne Hémonic, Réussir Porc/Tech Porc (FRA), 2019, n° 272, octobre, p. 34-35

Le chlore et le peroxyde d’hydrogène dégradent certains antibiotiques administrés dans l’eau.
Cela pourrait expliquer des échecs thérapeutiques ou l’apparition d’antibiorésistance dans les élevages.

PDF icon Anne Hémonic, Réussir Porc/Tech Porc (FRA), 2019, n° 272, octobre, p. 34-35
2019

L'intelligence artificielle arrive en élevage

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Michel Marcon, Réussir Porc/Tech Porc (FRA), 2019, n° 272, octobre, p. 14-15

L’intelligence artificielle et le numérique promettent de révolutionner le métier de l’éleveur en l’accompagnant 24 heures sur 24 dans le suivi et la traçabilité des animaux.
Des premières solutions ont été dévoilées au Space.

PDF icon Michel Marcon, Réussir Porc/Tech Porc (FRA), 2019, n° 272, octobre, p. 14-15
2019

Toolbox des outils simples et pratiques

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Visuels d'intervention présentés par Michel Marcon et Johan Thomas, Space 2019, 10-13 septembre 2019, Rennes (Matinales de l'Ifip), 5 pages

PDF icon Michel Marcon et Johan Thomas, Space 2019, 10-13 septembre 2019, Rennes (Matinales de l'Ifip), 5 pages
2019

Pourquoi PorcProtect ?

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Visuels d'intervention présentés par Isabelle Corrégé, Space 2019, 10-13 septembre 2019, Rennes (Matinales de l'Ifip), 10 pages

PDF icon Isabelle Corrégé, Space 2019, 10-13 septembre 2019, Rennes (Matinales de l'Ifip), 10 pages
2019

Early disease detection for weaned piglet based on live weight, feeding and drinking behaviour

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Michel Marcon et al., The European Conference on Precision Livestock Farming (ECPLF), 26-29 août 2019, Cork, Irlande, poster

Reduce antibiotic use is a major issue for pigs production because of World Health Organization recommendations and meat consumers concerns.
In order to reduce the needs of medication, one way is the early individual disease detection for isolate and treat only the sick animal. The subclinical
symptoms with the feeding and drinking behaviour can have a diagnostic value. A first automatic warning system has been built based on a statistic model who use data from automatic feeders, connected bowl drinker and connected scale.

PDF icon Michel Marcon et al., The European Conference on Precision Livestock Farming (ECPLF), 26-29 août 2019, Cork, Irlande, poster
2019

Auto-diagnostic de la biosécurité par l'éleveur

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Visuels d'intervention présentés par Anne Hémonic, Space 2019, 10-13 septembre 2019, Rennes (Matinales de l'Ifip), 14 pages

PDF icon Anne Hémonic, Space 2019, 10-13 septembre 2019, Rennes (Matinales de l'Ifip), 14 pages
2019
Couverture du Porc par les chiffres

Le porc par les chiffres 2019-2020

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Les chiffres clés les plus récents des filières porcines dans le monde et l’UE (production, consommation, cheptel...) et de la filière porcine en France ; les données utiles pour se repérer tout au long de l’année et à avoir toujours sous la main : un outil indispensable à tous !

  • les échanges (import/export),
  • les élevages de porcs (cheptel/régions, commerce et signes de qualité),
  • les coûts des bâtiments, le secteur de l’aliment pour porc,
  • la sélection (truies, insémination, évolutions génétiques),
  • l’abattage (entreprises, classement des carcasses, paiement au TMP),
  • le secteur de la charcuterie (entreprises et produits),
  • la consommation des viandes et la distribution des produits du porc

sous forme de tableaux, cartes, graphiques. 

Un fichier powerpoint contenant les principaux graphiques complète la brochure ; les visuels présentant chaque maillon de la filière peuvent directement servir à la préparation d’interventions techniques. Il vous sera envoyé sur simple demande : ifip@ifip.asso.fr

Edition IFIP, 39 pages, 16 X 24

25,00 €
2019

Pig'Insight : données individuelles pour la détection précoce de pathologie

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Visuels d'intervention présentés par Michel Marcon, Journée "Fermes numériques", "êtes-vous technocompatibles" (capteurs, données, robotique, imagerie), jeudi 4 avril 2019, Locminé (France), 8 pages

PDF icon Michel Marcon, Journée "Fermes numériques", 4 avril 2019, 8 pages
2019

Alimentation durable et élevages porcins

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Visuels d'intervention par Sandrine Espagnol, Space 2019, 10-13 septembre 2019, Rennes (Matinales de l'Ifip), 5 pages

PDF icon Sandrine Espagnol, Space 2019, 10-13 septembre 2019, Rennes (Matinales de l'Ifip), 5 pages
2019

Antimicrobial usage evolution between 2010, 2013 and 2016 in a group of French pig farms

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Anne Hémonic et al., 70th Annual Meeting of the European Federation Animal Science (EAAP), 26-30 août 2019, Ghent, Belgique, p. 545

Monitoring antimicrobial usage in pig farms is a key element of a reduction plan. The objective of this study was to analyse the antimicrobial usage evolution in the same farms between 2010-2013-2016 and to identify the factors of variations. The study monitored antimicrobial usage by weight group in 2016 in 33 farrow-to-finish farms in the West of France. The antimicrobial usage had ever been registered twice for 23 of them in 2010 and 2013 and once for 10 of them in 2013. It was quantified by the number of Course Doses per produced pig per year (nCD/pig). Farmers were asked about the factors that could explain the evolution between 2013-2016. On average, antimicrobial usage significantly decreased over six years (-38%). However, a high variability of individual evolutions was observed: among the 23 farms with three annual data, 43% decreased their use between 2010-2013 (-3 nCD/pig on average) but had a stable use between 2013-2016 (-0,2 nCD/pig). 26% decreased their use between 2010-2013 (-4 nCD/pig on average) and also between 2013-2016 (-2 nCD/pig). 9% increased then decreased their use during the two periods (+4 then -7 nCD/pig). One farm had the opposite trajectory (-9 then +2 nCD/pig) and another always increased its use (+2 then +5 nCD/pig). Among the 33 farms with data in 2013-2016, 36% decreased their use (-2 nCD/pig on average), 39% had a stable use and 24% increased their use (+3 nCD/pig). For sows, suckling piglets and fattening pigs, most of the farms had stable usage between 2013-2016. Only antimicrobial usage for weaned piglets was more frequently reduced. Increases were explained by occurrence of sanitary problems (mainly urogenital, digestive and respiratory problems on sows, piglets and fatteners respectively). Decreases were explained by vaccination, stop of preventive treatments and improvement of herd management. This study highlights the variability of individual trajectories in antimicrobial usage, due to sanitary issues that may be different according to each weight group. It usefully complements the monitoring of average evolution at the country level.

PDF icon Anne Hémonic et al., 70th EAAP, 26-30 août 2019, Ghent, Belgique, p. 545
2019

Early disease detection for weaned piglet based on live weight, feeding and drinking behaviour

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Michel Marcon et al., 70th Annual Meeting of the European Federation Animal Science (EAAP), 26-30 août 2019, Ghent, Belgique, p. 547

Early disease detection is one of the key to effective disease control in farms and reducing antibiotics usage. A batch of 153 weaned piglets was used to test a first machine learning algorithm in order to predict the individual health state of each animal. In order to build the early disease detection algorithm, nine boxes of 17 piglets has been set up with automata. In real time within this section we knew the number of times each animal went to the drinker or the feeder, the quantity of water and feed it took and its weight. As the golden standard to know either a piglet seems healthy or not, the clinical signs will be observed by trained operators on each pig every workday and recorded on a standardized grid (diarrhoea, cough, lameness…). Then, data collected from this batch of 153 piglets were used to create an algorithm with the software R, based on bagging and random forest machine-learning method. The database was split into learning (70%) and testing (30%). We obtained a global success of 86% of good prediction. 
In order to validate the accuracy of the model, a second batch of 153 piglets was used. Every day, a list of predicted sick pigs was printed automatically, indicating the individual identification of the animal, and its pen. Then, the results of these predictions were compared with the golden standard (observations of clinical signs by trained operators). Out of 3,437 observations (including predictions that the piglet is not sick), the algorithm correctly predicted the status of the piglets 2,462 times. Artificial intelligence has made 72% of good predictions. Regarding the true positive results, 96 alerts out of 117 were actually associated with observations of animals suffering mainly
from diarrhoea within two days (82% of success). Now, the aim is to improve this algorithm in different ways: to test accelerometers to check the activity of each piglet; to be more accurate on recording cough by a microphone (SOMO, Soundtalks); to test if some trajectories of behavioural change are linked to specific diseases (lameness, digestive or respiratory disease) and not only to generic disease. These studies will be part of the Healthylivestock project (EC funded H2020 research project).

PDF icon Mchel Marcon et al., 70th EAAP, 26-30 août 2019, Ghent, Belgique, p. 547
2019

Effect of a beneficial flora colonization of pen surfaces on health and performance of pig weaners

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Eric Royer (ancien Ifip, aujourd'hui Idele) et al., 70th Annual Meeting of the European Federation of Animal Science (EAAP), 26-30 octobre 2019, Ghent, Belgique, p. 566

The objective was to test the effects of a positive biofilm formation on the surfaces of post-weaning piglet facilities.
In total, 494 piglets were used in two experiments using a sanitary challenge. 48 h (d-2) before introduction of piglets, 2 identical rooms of 14 pens were sprayed either with water (Control) or a mix (LP) of selected bacteria strains.
Rooms were exchanged between Exp.1 and Exp.2. In Exp.1 rooms were sprayed again at d 15 and in Exp.2 at d 5, 12, 19, 26 and 33. Environmental challenge for piglets was stronger in Exp.1 than in Exp.2. Wiping samples indicated significantly (P<0.05) higher loads of aerobic bacteria (Lactobacillus spp., Bacillus spp.) in LP pen surfaces in Exp.1 at d 0, 5, and 14 and at d 0, 5, 7 and 35 in Exp.2, suggesting the development of the positive biofilm. Percentage of piglets with regular consistency of faeces was continuously higher in LP rooms in Exp.1 (from d 8 to 21) and Exp.2 (from d 5 to 28). Furthermore, mean scores were significantly improved at d 8 in Exp.1 (3.13 vs 4.50; P<0.01) and in Exp.2 at d 9 (2.19 vs 3.19; P=0.01) and 28 (2.03 vs 2.50; P<0.01). Disease outbreaks occurred two days later in Exp.1 (d 9 vs 7) and five days later in Exp.2 (d 12 vs 7) in LP rooms. However, total numbers of deaths from diarrhoea were similar in both treatments in Exp.1 and 2. In Exp.1, LP piglets had numerically better overall ADFI (794 vs 781 g/d; P>0.10) and ADG (510 vs 499 g/d; P>0.10), and had slightly higher weight at d 42 (29.8 vs 29.4 kg; P>0.10). In Exp.2, ADFI (259 vs 219 g/d; P<0.001) and ADG (211 vs 154 g/d; P<0.001) were significantly increased in the LP treatment in phase 1 (d 0 to 15). Weight was significantly higher for LP piglets at d 15 (11.9 vs 11.0 kg; P<0.001), although it was similar at d 41 (P>0.10). In conclusion, the spraying of a beneficial flora on surfaces may result in a protective positive biofilm that would help the piglets to deal better with the weaning challenges.

PDF icon Eric Royer (ancien IFIP, aujourd'hui Idele) et al., 70th EAAP, 26-30 octobre 2019, Ghent, Belgique, p. 566
2019

Modelling growth performance of pigs and within-room thermal balance in different local conditions

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Nathalie Quiniou et al., 70th Annual Meeting of the European Federation Animal Science (EAAP), 26-30 août 2019, Ghent, Belgique, p. 414, poster

A model has been used to assess both direct and indirect consumption of energy by growing pigs fed ad libitum, housed in fattening rooms with various insulation characteristics, and under different outdoor temperatures. This model combines a growth model and a bioclimatic model. It simulates thermal exchanges at the room level, based on interactions between the insulation of the room, available equipment (fans, heaters…), the parameters of the climate control box, the characteristics of pigs, and the feeding strategy. Heat sources are the animals (sensible heat) and heaters when available. Heat losses are due to insulation characteristics of the room and air renewal. The model has been evaluated from data collected simultaneously on pigs, diets, indoor and outdoor temperature (T) during a trial, and the error of prediction of indoor T was below 0.5 °C on an hourly basis. Thereafter, simulation will be performed, based on the same population of pigs and feeding strategy under different outdoor T, different heater powers in the room combined with different insulation level of wall material. For this purpose, four time series of outdoor T have been collected over 12 months (one in France and three from South to North in Sweden), as well as building characteristics in both countries (heater power: from 0 to 26 Watt/fattening place; 1 or 3 insulated layers).

For each combination of climate and building, indoor T and pig performance will be simulated as well as total energy consumption and its partition between direct and indirect components. This research was part of the Pigsys ERA-Net project, co-funded under European Union’s Horizon 2020 RI program (from SuSan, www.era-susan.eu,Grant Agreement n°696231) by the French ANR (grant n°ANR-16-SUSN-0003-02).

PDF icon Nathalie Quiniou et al., 70th EAAP, 26-30 août 2019, Ghent, Belgique, p. 414, poster
2019

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