179 research outputs found

    Overview of possibilities and challenges of the use of infrared spectrometry in cattle breeding

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    peer reviewedNear or mid-infrared (NIR or MIR) spectrometry is a versatile and cost-efficient technology used in cattle production to trace the chemical composition of gases, liquids and solid matters. Recent research showed the potential of MIR spectrometry in milk to predict many different milk components but also status and well-being of the cows, quality of their products, their efficiency and their environmental impact. Under changing socio-economic circumstances, novels traits could help to select for enlarged breeding objectives. But the following challenges need to be overcome: (1) access to and harmonization of MIR data; (2) availability of reference values representing the variability to be described, also highlighting the importance of international collaborations; (3) difficulties to obtain, but also to transfer prediction equations between instruments; (4) modeling of the massive longitudinal data generated; (5) estimation of parameters to assess phenotypic and genetic variability and links with other traits leading to the; (6) assessment of the position of novel traits in breeding objectives. Recent research reported how to address these issues for traits close to routine use including fatty acids and methane. Expected future developments include direct use of MIR data and multivariate modeling of novel traits. Similarly, genomic prediction for novel traits, which are limited by the availability of phenotyped reference populations, will also benefit from the use of correlated, MIR predicted, traits. Currently, MIR instruments can only be used in the frame of milk recording and not on-farm. But recent research showed that NIR is closing the gap thereby allowing advances in precise on-farm phenotyping and giving new opportunities for breeding, but also management. Possibilities for the use of infrared technologies for other trait groups such as meat composition and quality should allow cross-fostering of developments

    Potential use of mid-infrared spectrometry to predict cheese yield from milk and to study its genetic variability

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    peer reviewedFournir une indication rapide, fiable et bon marché du rendement fromager pour un lait donné, sans devoir appliquer des formules (empiriques ou théoriques) à partir des concentrations préalablement déterminées pour différents constituants du lait, serait un outil utile et économiquement intéressant tant pour les éleveurs que pour l’industrie laitière. En vue d’étudier la variabilité génétique du rendement fromager à l’échelle du cheptel bovin wallon, des méthodes chimiométriques ont été utilisées afin de développer des équations de prédictions basées sur des spectres moyen infrarouge (MIR) pour les rendements fromagers déterminés en laboratoire et exprimés en frais (RdFF) ou en sec (RdFS). Ceux-ci ont été déterminés sur 258 échantillons de lait analysés en spectrométrie MIR. Les équations de prédiction à partir du spectre MIR du lait ont été développées en utilisant la régression des moindres carrés partiels (PLS) avec une validation croisée interne appliquée sur la dérivée première des spectres MIR. Les coefficients de détermination de validation croisée (R²cv) des équations étaient de 0,81 pour les prédictions du RdFF et de 0,82 pour les celles du RdFS. Les rapports des performances sur les variabilités (RPD) étaient égaux à 2,3. Ces résultats peuvent permettre d’envisager une bonne utilité pratique pour leur prédiction respective, notamment dans le cadre de recherches génétiques. Ces équations ont été appliquées sur la base de données spectrales générée dans le cadre du contrôle laitier wallon. Les composantes de la variance ont été estimées séparément pour le RdFF et le RdFS basées sur un modèle animal « contrôles élémentaires » utilisant des régressions aléatoires. Le jeu de données utilisé comportait 51 537 prédictions pour 7 870 vaches primipares Holstein. Les héritabilités journalières moyennes variaient entre 0,31 (au 5ème jour de lactation (JDL)) et 0,59 (au 279ème JDL) pour le RdFF et entre 0,31 (au 5ème JDL) et 0,57 (au 299ème JDL) pour le RdFS. Ces héritabilités journalières modérées à élevées ont indiqué le potentiel de sélection génétique pour ces deux caractères.ProFARMilk, BlueSe

    Impact of high-wheat bran diet on sows’ microbiota, performances and progeny’s growth and health

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    Finding alternatives to antimicrobial growth promoters is part of the goal of improving sustainability in pig production. Dietary fibres are considered as health-promoting substances acting on pigs’ microbiota. This study aimed to investigate whether the enrichment of sows’ diet with high levels of wheat bran (WB) could impact the performances of sows and piglets’ health. Seven sows were fed a control diet (CON) and 8 sows a WB diet from day 43 of gestation (WB 240 g/kg DM) until the end of the lactation period (WB 140 g/kg DM). Diets were formulated to be iso-energetic and iso-nitrogenous by changing the proportions of some ingredients. Faeces were sampled at different time points (before treatment, during treatment: in gestation and lactation) to determine microbiota composition (sequencing with Illumina MiSeq). Milk was sampled weekly to determine lactose, fat and protein concentration by mid-infrared technology and IgA and IgG contents by ELISA. Before weaning (d26-27), piglets were euthanized, intestinal contents and tissues sampled for further analyses. Zootechnical performances of sows and piglets were recorded. Statistical analyses were performed using the SAS MIXED procedure and repeated measurements. Treatment never impacted piglets’ weight (P=0.51). Sows’ ingestion during the lactation period was comparable between both treatments until the last 4 days of lactation where the percentage of target ingestion was significantly (P<0.001) lower for the WB (66%) compared to the CON group (89%). No effect on sows’ backfat and weight changes was observed. An increased abundance of Lactobacillus spp. in feces of the WB group was observed in gestation before and after diet change (8.8% vs 15.1% of total bacteria). However, for the overall genera changes between treatments, it only seems to occur for minor groups of bacteria. Milk protein, fat, IgG and IgA were not affected by treatment, but a time-effect (P<0.001) was observed while treatment impacted (P<0.05) lactose content. In conclusion, sows’ performances were not affected by the high WB diet and more research on the piglets’ samples is foreseen

    Prediction of the individual enteric methane emission of dairy cows from milk mid-infrared spectra

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    peer reviewedThe livestock sector is considered the largest producer of methane (CH4) from anthropogenic sources, world wide contributing 37% of emissions (FAO, 2006). An important step to study and develop mitigation methods for livestock emissions is to be able to measure them on a large scale. However, it is difficult to obtain a large number of individual CH4 measurements with the currently available techniques (chambers or SF6). The aim of this study was to develop a high throughput tool for determination of CH4 emissions from dairy cows. Anaerobic fermentation of food in the reticulorumen is the basis of enteric CH4 production. End-products of that enteric fermentation can be found in the milk (e.g., volatile fatty acids). Therefore individual enteric CH4 emissions could be quantified from whole milk mid-infrared (MIR) spectra which reflect milk composition and can be obtained at low cost (e.g., national milk recording). Prediction equations of individual CH4 emissions (determined using the SF6 method) from milk MIR spectra have been established (Dehareng et al., 2012; Soyeurt et al., 2013). The results presented here are the improvement of this methodology by using a multiple breed and country approach
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