La base documentaire de l'IFIP

La base documentaire de l'IFIP : des centaines de documents à télécharger ou bien à commander.

Résultats 1 à 20 de 33 résultats
Rechercher une documentation
Publication Annéetrier par ordre croissant

Analyse environnementale de stratégies d'alimentation de précision des porcs charcutiers

Consulter le resumé

Florence Garcia-Launay (Inrae) et al., 52e Journées de la Recherche Porcine (FRA), 4 et 5 février 2020, Paris, p. 331-336

2020

Application d’un programme d’alimentation de précision chez le porc en croissance alimenté à volonté : effet sur les performances et l’utilisation des nutriments

Consulter le resumé

Ludovic Brossard (Inrae) et al., 52es Journées de la Recherche Porcine (FRA), 4 et 5 février 2020, Paris, p. 111-112, poster

Poster.

L’alimentation de précision est une technique innovante pour améliorer l’efficacité nutritionnelle en production porcine. Elle consiste à adapter quotidiennement l’apport de nutriments aux besoins de chaque individu au sein d’un groupe de porcs. Dans le cadre du projet européen H2020 Feed-a-Gene, un outil d’aide à la décision (OAD) a été développé pour le porc en croissance pour appliquer l’alimentation de précision (AP) en fermes commerciales. Cet outil repose sur l’analyse des données quotidiennes et individuelles de poids vif (PV) et de consommation alimentaire obtenues les jours précédents afin de prédire les performances du lendemain (PV, gain de PV, consommation alimentaire), les besoins individuels, et donc la composition de l’aliment à distribuer (Brossard et al., 2017 ; Quiniou et al., 2018). L’objectif de l’étude est de tester le fonctionnement de l’OAD en conditions pratiques et ses conséquences sur les  performances et l’utilisation des nutriments chez les porcs en croissance nourris à volonté.

ENG

Poster.

Application of a precision feeding program in growing pigs fed ad libitum: effect on performance and nutrient use

Within the Horizon 2020 EU program Feed-a-Gene, a decision support system (DSS) was developed to implement precision feeding (PF) in commercial pig farms and to help improve feed efficiency. This study aimed to perform PF with the DSS in practical conditions with growing pigs fed ad libitum and to assess consequences on performance and nutrient use. Sixty-four pigs were reared from 77 to 161 days of age (33.5 to 108.8. kg body weight, BW) in a single pen equipped with an automatic weighing-sorting system and eight automatic feeders that register feed intake and deliver a tailored blend of two diets (A and B, respectively 1.0 and 0.4 g SID Lysine (Lys)/MJ net energy (NE), and 9.7 MJ NE/kg) to individual pigs. The control group received a blend providing 0.9 g Lys/MJ NE until the group weighed 65 kg on average (growing phase) and 0.7 g Lys/MJ NE thereafter (finishing phase). For the PF group, the Lys requirement was assessed individually and on a daily basis, based on up to 20 previous records of BW and feed intake, and diets A and B were blended accordingly. Daily feed intake, average daily gain, and feed conversion ratio did not differ between treatments. During the growing period, Lys and nitrogen (N) intake and N excretion were 11%, 9%, and 14% lower in the PF group than those in the control group, respectively (P < 0.05). During the finishing period, these values were only numerically lower (difference <2%; P > 0.66). These results could be explained by the slightly higher feed intake in the PF group (+100 g/d, P = 0.24) and the lower Lys content used during the finishing period of the 2-phase strategy compared to standard diets.

2020

Réduire les rejets azotés des porcs en croissance par un ajustement dynamique des apports en acides aminés au besoin et une diminution de la teneur en matières azotées totales de l'aliment

Consulter le resumé

Nathalie Quiniou et al., 52e Journées de la Recherche Porcine (FRA), 4 et 5 février 2020, Paris, p. 115-116, poster

Poster.

Ajuster quotidiennement les apports en acides aminés au besoin de chaque animal est l’un des objectifs de l’alimentation de précision. Au-delà d’une réduction des coûts alimentaires, il s'agit d'utiliser plus efficacement les ressources et diminuer l'impact environnemental des productions animales. Le système d’alimentation de précision développé pour le porc dans le cadre du projet Feed-a-Gene intègre différents automates (Quiniou et al., 2017) et un outil d'aide à la décision (OAD, Brossard et al., 2017) qui permet à la fois de traiter au niveau individuel et quotidien les données enregistrées par les automates au jour J, de modéliser les besoins nutritionnels et de piloter en conséquence les apports d'aliment au jour J+1. Ce dispositif a été utilisé chez un groupe de porcs en croissance rationnés pour comparer les performances obtenues avec une séquence biphase (2P) ou une alimentation de précision (AP).

ENG

Reduction of N output through dynamic adjustment of amino acid supplies to requirements and reduced crude protein content in pig diets

Poster.

A test was performed with 96 growing pigs to implement precision feeding (PF) of restricted-fed growing pigs to characterise growth performance and N output using a PF system developed in the Feed-a-Gene project (H2020, no. 633531) compared to a 2-phase strategy (2P). A decision support tool was used to manage data (mainly individual and daily body weight (BW) measured with an automatic scale), to forecast performance on the following day, to assess corresponding amino acid requirements, and to adapt the quality of the diet delivered on the next day through the proportion of two diets used in a blend. Both diets were formulated to 9.75 MJ net energy (NE)/kg, with contrasting concentrations of digestible lysine and crude protein (A: 1.0 g lysine/MJ NE and 16.6% N x 6.25, B: 0.5 g/MJ NE and 10.9% N x 6.25). Forecasting BW and BW gain for PF pigs was interrupted for 2 weeks due to a problem with an electronic device for two consecutive days; it identified a problem of robustness in how forecasting methods were applied. A solution was found and applied to improve the entire system. However, no significant differences were observed between strategies for growth rate (2P: 722 vs PF: 716 g/d, P = 0.62), feed conversion ratio (2.64 vs 2.70, P = 0.063) or carcass leanness (62.0 vs 61.4 units, P = 0.18). The crude protein content of the blend provided to PF during the growing and finishing phases were 15.8% and 13.3%, respectively. With this new 2P diet management, N output can potentially be reduced by 10% compared to a 2P with standard diets (16.0% and 15.0% N x 6.25). Despite the technical problem, which might have minimised the difference in N intake between strategies, the PF contributed an additional decrease of 6%.

2020

Environmental assesment of feeding strategies of precision feeding in growing-finishing pigs (Task 6.2.)

Consulter le resumé

Florence Garcia-Launay (Inrae) et al., colloque final Feed-a-Gene, 22-24 janvier 2020, Rennes, poster

Feed production and excretion of nutrients by the animals are the major sources of the environmental impacts of pig production. The development of communication and information technologies in pig farms allows today the development of precision feeding (PF) in growing-finishing pigs, which appears as a promising technology to decrease environmental impacts of pig production. However, few studies have compared environmental impacts of conventional and PF. Therefore, on objective of Task 6.2. within Feed-a-Gene was to perform life cycle assessment (LCA) of pig production with either conventional or PF applied to growing-finishing pigs.

Document réservé Espace Pro, veuillez vous identifier
2020

Améliorer les performances et le bien être des truies gravides par la mobilisation de nouvelles technologies pour une alimentation de précision et la détection de signaux comportementaux

Consulter le resumé

Michel Marcon et al., Innovations Agronomiques (FRA), 2020, volume 79, janvier, p. 245-256

Depuis la mise en groupe des truies gestantes, les éleveurs observent plus d’hétérogénéité de l’état corporel des truies lors de leur entrée en maternité impliquant plus de pertes de porcelets. Il est également plus difficile d’observer les problèmes d’aplombs dans des grands groupes de truies. La première étape de ce projet avait pour objectif le développement d’un capteur capable d’enregistrer le niveau d’activité individuel des truies logées en groupe conformément à la réglementation bien-être. Cette étude a donc permis la mise au point de l’Acti’Sow. Il s’agit d’un accéléromètre autonome, positionné à l’oreille des truies, qui permet de connaître le temps quotidien passé par les truies à rester couchée, debout ou encore à marcher. Par ailleurs, cette étude offre également une meilleure connaissance du comportement des truies grâce aux nourrisseurs et aux abreuvoirs connectés, à la station de pesée identifiée et aux capteurs d’activité. En moyenne, la consommation d'eau quotidienne d’une truie est de 8,2 l / jour mais ce résultat cache une variabilité conséquente de près de 50% lorsque l'on compare une truie par rapport à une autre et de 38% pour la même truie d'un jour à l'autre. À propos de leur activité, une truie « normale » passe 67% de son temps en position couchée, un peu plus de 28% en position debout sans bouger et moins de 5% en marche. Sachant cela, entre la plus fainéante et la plus active, la dépense énergétique liée à cette activité représente plus de 500 g d’aliment. Le système d'alerte précoce des problèmes de boiterie est l'autre principal objectif de cette étude. En utilisant les comportements alimentaire et hydrique (nombre de visites par jour, heure de chaque visite, quantité d’eau / d’aliments consommée, rang d’accès au nourrisseur / abreuvoirs), le poids individuel et le niveau d’activité, nous avons construit un premier modèle capable de prédire individuellement les boiteries 24 heures avant que l’agriculteur puisse l’observer. La précision est proche de 77%. 

https://www6.inrae.fr/ciag/content/download/6832/49647/file/Vol79-16-Marcon%20et%20al.pdf

ENG

Use of new technologies to improve welfare and technical results of pregnant sows through precision feeding and early abnormal behavioural signals detection 

Since the new welfare regulation, farmers have to breed pregnant sows penned in the group. Thus, breeders observed more heterogeneity in the backfat thickness of sows when they are entering the farrowing units, implying more losses of piglets. It is also more difficult to observe lameness issues in large groups of sows. The objectives of this project are (i) to develop an activity sensor to feed each sow according to the energy it spends and (ii) to create an early detection system for lameness problems. The first step of this project was to develop a sensor able to record the individual activity level of sows penned in a group. As a result, Acti’Sow has been created. It is an ear tag accelerometer offering to know the daily time spent lying, standing and walking by a sow with a global accuracy close to 85 %. This project offers a better knowledge about sow behavior thanks to automatic feeders, connected drinkers, weighing scale and activity sensors. On average, the daily water consumption is 8.2 l/day/sow, but this result hides a huge variability close to 50 % when comparing a sow to another and 38 % for the same sow from a day to the next one. About their activity, an average sow spends 67 % of its time lying down, a bit more than 28 % standing up without moving and less than 5% walking. According to that, between the laziest one and the more active one, energy expenditure represent more than 500 g of feed. It means, with the same fixed objective of backfat thickness with these two sows, a farmer will need to give 500 g more feed/day for the very active sow. Early warning system for lameness issues was the other main result of this study. Through the use of watering and feeding behavior (number of visits per day, time of each visit, quantity of water/feed consumed, access rank to the feeder), individual weight and activity level, we built a first model able to individually predict lameness issue 24 hours before the farmer can observe it. The accuracy is close to 77 %. It means, that a cell phone app can alert farmers when a sow needs to be checked. 

https://www6.inrae.fr/ciag/content/download/6832/49647/file/Vol79-16-Marcon%20et%20al.pdf

2020

Alimentation à la demande en maternité

Consulter le resumé

Yvonnick Rousselière, Réussir Porc/ Tech Porc (FRA), 2020, n° 275, janvier, p. 41

L’Ifip a testé sur la station de Romillé un système d’alimentation en maternité permettant de distribuer des petites doses d’aliment frais tout au long de la journée selon la demande de la truie.

PDF icon Yvonnick Rousselière, Réussir Porc/ Tech Porc (FRA), 2020, n° 275, janvier, p. 41
2020

Application of a precision feeding program in growing pigs: effect on performance and nutrient use

Consulter le resumé

Ludovic Brossard (INRA) et al., 70th Annual meeting of the European Federation of Animal science (EAAP), 26-30 août 2019, Ghent, Belgique, visuels d'intervention

Improvement of feed efficiency in growing pigs is a key issue for the economic and environmental sustainability of livestock production. This can be achieved with novel techniques such as precision feeding (PF). Within the Horizon 2020 EU Feed-a-Gene program (grant agreement n°633531), a decision support system (DSS) was developed to implement precision feeding in commercial pig farms. This study aimed to test the functioning of the DSS in practical conditions and the consequences on performance and nutrient use of growing pigs fed ad libitum. Sixty-four pigs were reared from 77 to 161 days of age (34 to 109 kg body weight, BW) in a single pen equipped with an automatic weighing-sorting system and eight automatic feeders allowing to register feed intake and deliver a tailored blend of two diets (A and B with respectively 1.0 and 0.4 g SID Lysine (Lys)/MJ NE, and 9.7 MJ NE/kg) to individual pigs.

Pigs of the control group received a blend providing 0.9 g SID Lysine (Lys)/MJ NE until the average group BW was 65 kg (growing phase) and 0.7 g SID Lys/MJ NE thereafter (finishing phase). For the PF group, the assessment of the SID Lys requirement was performed individually and on a daily basis, based on up to 20 previous records of BW and feed intake. Feed composition was changed accordingly by blending diets A and B in appropriate proportions. Daily feed intake, average daily gain, and feed conversion ratio did not differ between treatments for the overall period or per period. During the growing period, the SID Lys intake and the nitrogen intake and excretion were respectively  10.8, 8.8, and 14.4% lower in the PF group compared to the control group (P<0.05). During the finishing period, these values were only numerically lower (difference <2%; P>0.68). This could result from a slightly higher feed intake (+100 g/d, P=0.24) in PF group combined with a SID Lys supply already low in control group. A second experiment will be performed in the same conditions to confirm the potential of the PF using the developed DSS.

Document réservé Espace Pro, veuillez vous identifier
2019

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

Consulter le resumé

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

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
2019

Adapter le rationnement des truies à leur activité : quelle précision d'un accéléromètre fixé à l'oreille

Consulter le resumé

Nathalie Quiniou et Michel Marcon, Bilan 2018, éditions IFIP, avril 2019, p. 80

Des progrès dans l’alimentation des truies gestantes sont attendus par la prise en compte de leur activité. En effet, cette activité consomme de l’énergie et elle est en outre très variable d’un individu à l’autre, plus encore si les animaux sont élevés dans des grandes cases. Des études démontrent la possibilité d’utiliser l’accélérométrie pour quantifier en continu l’activité des truies. Pour passer du niveau expérimental au développement en élevage, il est nécessaire de disposer d’un outil fiable, robuste, peu coûteux et pouvant équiper la truie pendant toute sa carrière. Dans le cadre du projet CASDAR BEALIM, un prototype a été développé par la société RF-Track en partenariat avec l’IFIP. Fixé à l’oreille, le boîtier émet toutes les heures une synthèse, après traitement par un algorithme embarqué dans la boucle, des données recueillies par l’accéléromètre. Un travail a été réalisé afin d’en évaluer la fiabilité.

PDF icon Nathalie Quiniou et Michel Marcon, Bilan 2018, éditions IFIP, avril 2019, p. 80
2019

Vers une distribution multiphase en soupe

Consulter le resumé

Didier Gaudré, Bilan 2018, éditions IFIP, avril 2019, p. 81

La distribution multiphase consiste à mélanger en cours d’engraissement 2 aliments de composition différente selon des proportions variables au cours du temps, de façon à suivre au plus près les besoins nutritionnels des animaux, de manière à maintenir leurs performances en réduisant leurs rejets. En distribution d’aliment liquide (machine à soupe), système très représenté en France, ce type de plan d’alimentation est difficile à réaliser car il suppose la préparation de petites quantités de soupe et leur acheminement jusqu’à la case de destination. Dans le cadre du programme SOS Protein conduit par les régions Bretagne et Pays de la Loire, des travaux expérimentaux et d’enquêtes ont été entrepris afin d’évaluer les possibilités d’amélioration du mode de distribution en soupe sur ce point.

PDF icon Didier Gaudré, Bilan 2018, éditions IFIP, avril 2019, p. 82
2019

Prédiction en temps réel du poids vif des porcs en croissance logés en groupe à partir des pesées quotidiennes réalisées avec une bascule automatique

Consulter le resumé

51es Journées de la Recherche Porcine, 5 et 6 février 2019, Paris, p. 153-154, par Nathalie Quiniou et al., poster

Poster. 

La mise en oeuvre de l’alimentation de précision chez le porc consiste à adapter quotidiennement l’apport de nutriments en fonction des besoins nutritionnels de chaque animal au sein du groupe. Dans un contexte où les animaux sont rationnés, la quantité d’aliment distribuée dépend étroitement des spécificités du plan de rationnement, qui peut intégrer certaines caractéristiques individuelles, par exemple le poids de chaque porc à l’entrée en engraissement pour fixer la ration initiale ou le sexe pour fixer le plafond d’alimentation.
Dans le même temps, la qualité de l’aliment apporté peut être modulée de façon dynamique, par exemple au regard de la teneur en acides aminés, selon le poids atteint chaque jour par le porc (qui détermine le besoin d’entretien) et la variation de poids quotidienne (qui détermine le besoin de croissance). Le système d’alimentation de précision développé dans le cadre du projet européen H2020 Feed-a-Gene intègre à la fois des distributeurs de granulés, une bascule automatique et un logiciel de pilotage (OAD) qui s’appuie sur les données historiques de chaque porc pour prédire ses caractéristiques pondérales le lendemain et modéliser les besoins en acides aminés associés.
L’objectif de l’étude est d’évaluer la pertinence des prédictions de poids réalisées par cet outil tout au long de l’engraissement selon le porc, voire selon la séquence alimentaire appliquée à chaque animal qui est susceptible d’influencer son gain de poids.

Real-time prediction of individual body weight of group-housed growing pigs from daily measurements with an automatic weighing scale

Precision feeding is a promising strategy to improve the efficiency of resource use by improving the adequacy between nutrient supplies and animal requirements. Technologies that identify each pig within a group (RFID ear tags), weighs it automatically and mixes different diets to adapt the quality of the feed ration on an individual and daily basis (precision feeders) were combined in a decision support system developed in the H2020 Feed-a-Gene project. It also includes a conceptual model to estimate nutritional requirements that relies on prediction of body weight (BW) and BW gain. These day D+1 criteria must be predicted from daily and individual measurements of BW performed up to day D on growing pigs group-housed in a pen equipped with an automatic weighing scale. The BW predicted with the Holt-Winters’ double exponential smoothing model (HWα, with the smoothing parameter α set at 0.6) were compared to measurements performed over at least 97 days on two groups of 96 pigs. From the 85 and 83 individual growth curves available, the slope of the regression between mean measured and predicted BW averaged 0.98 (R² = 0.99). Based on 9080 and 7662 measured BW available (respectively in each group), mean daily RMSEP regularly varies over time around 4-5% (without any particular event during the trial). Consequently, the accuracy of the prediction method was considered to meet expectations.

PDF icon Nathalie Quiniou et al., 51es JRP, 5 et 6 février 2019, Paris, p. 153-154, poster
2019

ActiSow mesure l’activité des truies

Consulter le resumé

Yvonnick Rousselière, Réussir Porc-Tech Porc (FRA), 2019, n° 265, janvier, p. 39

L’ActiSow est un accéléromètre positionné à l’oreille permettant de mesurer le niveau d’activité des porcs. Ce capteur embarqué a été codéveloppé par l’Ifip et la société RF Track.

PDF icon Yvonnick Rousselière, Réussir Porc-Tech Porc (FRA), 2019, n° 265, janvier, p. 39
2019

L’intelligence artificielle entre dans les élevages

Consulter le resumé

Michel Marcon, Réussir Porc-Tech Porc (FRA), 2018, n° 261, septembre, p. 64-65

De nouvelles solutions capables d’améliorer la gestion quotidienne de l’élevage font appel à l’intelligence artificielle. Parmi elles, un système de détection précoce de pathologies est testé actuellement par l’Ifip.

PDF icon Michel Marcon, Réussir Porc-Tech Porc (FRA), 2018, n° 261, septembre, p. 64-65
2018

Precision feeding with a decision support tool dealing with daily and individual pigs’ body weight

Consulter le resumé

Nathalie Quiniou (IFIP) Michel Marcon (IFIP) et Ludovic Brossard (INRA), 69h Annual meeting of the european federation of animal science (EAAP), Dubrovnik, Croatie, 27-31 août 2018 

Nutritionists, feed companies and equipment manufacturers look for solutions that help farmers to improve sustainability of pig production. Based on experimental results obtained in silico or in vivo, a better adequacy between amino acid supplies and requirements increases feed efficiency and farmer’s income and reduces the environmental impact of growing pigs, highlighting the interest for precision feeding. Data are collected to characterize daily animal traits (e.g. body weight, BW) and their variation from one day to another (e.g. growth rate, &‘6;BW). They are used to determine the requirement for maintenance and growth on the next day, respectively. Therefore, adequacy between requirements and supplies depends on these predicted BW and &‘6;BW. The double exponential smoothing (Holt-Winters) method with a smoothing parameter &”5;=0.6 (HW0.6), presents a low sensitivity to the number of latest values used to forecast BW. It seems to allow for a secured prediction of BW soon after the beginning of the growing phase (at least after 4 days). A group of pigs was used in restricted feeding conditions to compare results obtained either with a 2-phase feeding strategy, considered as the control treatment, or a precision feeding strategy based on BW forecasting with the HW0.6 method. Pigs allocated to both treatments were group-housed in the same pen, equipped with the decision support system built in the Feed-a-Gene project to manage the data, to determine in real-time the corresponding nutritional requirements, and to adapt the feed characteristics provided to each pig through the blend of two diets (9.75 MJ net energy/kg, 0.5 or 1.0 g of digestible lysine per MJ). Available results from 24 pigs per treatment indicate that overall average growth performance were not influenced by the feeding strategy (P>0.58 for both average daily gain and feed conversion ratio) but digestible lysine intake was reduced by 6% (1,774 vs 1,879 g, P<0.01) and N output by 7% (P<0.01) with precision feeding. Results will be completed by a second group using the same treatments. This study is part of the Feed-a-Gene project and received funding from the European Union’s H2020 program under grant agreement no. 633531.

PDF icon Nathalie Quiniou et al., 69th EAAP, Dubrovnik, Croatie, 27-31 août 2018
2018

Prédire le poids du porc en temps réel pour mettre en œuvre une alimentation de précision

Consulter le resumé

Nathalie Quiniou et Michel Marcon, bilan 2017, éditions IFIP, mai 2018, p. 45

L’alimentation de précision consiste à adapter l’apport de nutriments chaque jour en fonction des besoins nutritionnels de chaque porc au sein du groupe.
La qualité de l’aliment apportée au jour J dépend des besoins estimés ce jour-là. Or, ces derniers dépendent à la fois du poids du porc et de sa croissance, qui doivent donc être prédits à partir des caractéristiques connues du porc. La bascule automatique permet de peser chaque porc chaque jour et de décrire la forme de sa courbe de croissance de façon satisfaisante sur l’ensemble de l’engraissement. Mais l’utilisation de ces données en temps réel est plus compliquée du fait des variations soudaines enregistrées d’un jour à l’autre. Des méthodes de lissage doivent alors être mise en œuvre.

PDF icon Nathalie Quiniou et Michel Marcon, bilan 2017, éditions IFIP, mai 2018, p. 45, fiche n° 17
2018

L’Ifip affine les plafonds d’aliment

Consulter le resumé

Nathalie Quiniou, Réussir Porc - Tech Porc (FRA), 2018, n° 258, mai, p. 32-33

Un suivi précis des porcs en engraissement avec un système d’alimentation individualisé démontre qu’un plafond de 2,7 kg rationne les mâles, mais pas les femelles.

PDF icon Nathalie Quiniou, Réussir Porc - Tech Porc (FRA), 2018, n° 258, mai, p. 32-33
2018

Accelerometer technology to perform precision feeding of pregnant sows and follow their health status

Consulter le resumé

8e European Conference on Precision Livestock Farming (ECPLF), le 12-14 septembre 2017, Nantes, in : Precision Livestock Farming 17, 2017, p. 666-673, par Michel Marcon et al.

Two trials were conducted at experimental stations of IFIP, located in Romillé (France, Trial 1), and INRA, located in Saint Gilles (France, Trial 2), on pregnant sows equipped with individual ear tag accelerometers to record their activity level: duration of lying, standing and moving sequences. The first trial involved 72 sows penned on a slatted floor in a dynamic group with connected drinkers and automatic feeders, whereas the second trial was carried out on 4 small groups of 6 sows penned on a concrete floor with straw and fed in individual stalls. Firstly, an algorithm was built from video recordings of 24 sows on the slatted floor (2 x 2 h sequences per sow, 96 h). Secondly, the accuracy of the algorithm was assessed by recording and sequencing 96 h and 109 h, respectively, on the slatted floor and concrete floor with straw. The respective sensitivities of the lying, standing and moving behaviours on the slatted floor were 94.4%, 66.9% and 68.4%. With straw, lower sensitivity values were found: 93.65% for lying, 68.35% for standing and 38.83% for moving, linked to more investigative behaviours using the head. The final step was to use these data to improve the feeding practices of pregnant sows, taking their activity level into account. The strong inter- and intra-individual variability shown in the physical activity is a limiting factor for detection of health problems, such as lameness, through the accelerometers. Thus we need additional information, especially the behaviour data generated by identified drinkers and automatic feeders.

PDF icon Michel Marcon et al., 8e ECPLF, 12-14 septembre 2017, Nantes
2017

Assessment of the dynamic growth of the fattening pigs from body weight measured daily and automatically to elaborate precision feeding strategies

Consulter le resumé

8e European Conference on Precision Livestock Farming (ECPLF), le 12-14 septembre 2017, Nantes, in : Precision Livestock Farming 17, 2017, p. 593-602, par Nathalie Quiniou et al.

Growing pigs are often fed below ad libitum to increase their feed efficiency and carcass leanness. When energy supply is under control, precision feeding is implemented through the amino acids (AA). As the AA requirement depends on the body weight (BW) for the maintenance part and on its daily variation (ΔBW) for the growth part, the adequacy between requirements and supplies on day D+1 depends on the adequacy of predicted BWD+1 and ΔBWD+1. Data sets from four trials were used to forecast BW from time series analyses based either on multivariate adaptive regression splines (MARS) or double exponential smoothing (HWα) methods using the k latest data (8, 14 or 20). Pigs (n = 117) were group-housed and restrictively fed, and their BW was recorded daily and individually with an automatic scale (n = 11 736). With HW0.6, the RMSEP of BWD+1 was the smallest one (1.21 kg) and not influenced by k. Linear regression on the l latest forecasted BW was used to assess ΔBWD+1. At the beginning of the trial, ΔBWD+1 was more difficult to predict from BW forecasted with MARS than with HW0.6. Descriptive statistics of individual variation of ΔBWD+1 based on MARS and HW0.6 were comparable with k = l = 20 only after removal of the first 19 days. Compared to other methods studied, the method HW0.6 seems to be the best compromise to forecast BWD+1 and ΔBWD+1 of restrictively fed pigs.

PDF icon Nathalie Quiniou et al., 8e ECPLF, 12-14 septembre 2017, Nantes
2017

Reduction of the amino acids supplied in excess to the growing pig using a precision feeding device

Consulter le resumé

Nathalie Quiniou et al. 68th Annual Meeting of the European Federation of Animal Science, Tallin, Estonie, 28–31 août 2017, session 43, p. 389, abstract

PDF icon Nathalie Quiniou et al. 68th Annual Meeting of the EAAP, Tallin, Estonie, 28–31 août 2017, session 43, abstract
2017

Development of a precision support system for precision feeding application in pigs and poultry

Consulter le resumé

Ludovic Brossard et al. 68th Annual Meeting of the European Federation of Animal Science, Tallin, Estonie, 28–31 août 2017, session 33, p. 319, abstract

Precision feeding is a promising way to improve feed efficiency and thus economic and environmental sustainability of livestock production. A decision support system (DSS) was built to determine in real-time the nutritional requirements of animals and feed characteristics (composition, amount). This tool will be associated with a controlling module to be part of an automatic feeding system and exchange data with different devices for an application of precision feeding in pig and poultry commercial farms (Figure 1). This DSS tool, dedicated to animals managed individually or in group, is designed with a modular structure for adaptation to different feeder devices, species and production stage (growing pigs, gestating and lactating sows, broilers, laying hens) (Figure 2). The modules are built to perform specialized tasks in a cooperative way. It includes a data management module with a proper characterization of data by meta-data definition for precision feeding. It ensures standard encoding to allow data interoperability from any platform. Other modules are dedicated to data checking and correction for database filling, prediction of most probable body weight (BW) gain and feed intake (ad libitum or restricted feeding) and calculation of nutritional requirements. The BW and feed intake prediction is based on dynamic data analyses. For that, specific methods have been studied and selected depending on the number of available data, their type (BW or feed intake) and recording frequency. The calculation of nutritional requirements is performed using nutritional models specific to a species or a production stage. These two last modules are currently designed for healthy animals and will be refined to extent prediction to a larger range of field situations (e.g. health problems, climatic conditions) with nutritional models in development/refinement in other workpackages of the project. The general specifications of this DSS and dynamic data analyses will be illustrated for growing pigs.

Document réservé Espace Pro, veuillez vous identifier
2017

Pages