32 research outputs found

    Valeur agronomique et alimentaire du Sainfoin

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    National audienceSainfoin is a legume rich in condensed tannins. In spite of the fact it has a low yield and is not as persistent as alfalfa, Sainfoin offers undeniable nutritional qualities for ruminants and helps limit nitrogen leaching and methane emissions from cattle in the environment. Production of Sainfoin is dependant on the agronomic factors (cultivation conditions, varieties, end use, yield, diseases) described below. Depending on their levels and structure, condensed tannins can have a beneficial or negative effect on the nutritional value of Sainfoin for ruminants, but does not affect ingested quantity and digestibility. However, a reduced degradation of proteins in the rumen and a reduced digestibility in the intestine is observed, but does not affect nitrogen capture by the ruminant.Le sainfoin est une légumineuse en tannins condensés. Bien que moins productif et moins pérenne que la luzerne, il possède des qualités nutritionnelles indéniables pour les ruminants et présente un intérêt pour limiter les rejets d'azote lessivable et de méthane émis par les animaux dans l'environnement. La production du sainfoin en climat tempéré dépend de facteurs agronomiques (conditions de culture, variétés, mode d'utilisation, rendement, maladies) ici présentés. Selon leur teneur et leur structure, les tannins condensés ont un effet bénéfique ou négatif sur la valeur alimentaire de ce fourrage pour les ruminants, sans en modifier la quantité ingérée ni la digestibilité. En revanche, une diminution de la dégradation des protéines dans le rumen et de leur digestibilité dans l'intestin est mesurée, mais sans modification de la rétention d'azote par le ruminant. Le sainfoin offre des perspectives pour limiter les rejets d'azote urinaire et de méthane dans l'environnement

    Fecal near-infrared reflectance spectroscopy prediction of the feed value of temperate forages for ruminants and some parameters of the chemical composition of feces: efficiency of four calibration strategies

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    Epub 2017 Jan 01The forage feed value determined by organic matter digestibility (OMD) and voluntary intake (VI) is hard and expensive. Thus, several indirect methods such as near infrared reflectance (NIR) spectroscopy have been developed for predicting the feed value of forages. In this study, NIR spectra of 1040 samples of feces from sheep fed fresh temperate forages were used to develop calibration models for the prediction of fecal crude ash (CA), fecal crude protein (CP), fresh forage OMD, and VI. Another 136 samples of feces were used to assess these models. Four calibration strategies were compared: (1) species-specific calibration; (2) family-specific calibration; (3) a global procedure; and (4) a LOCAL approach. The first three strategies were based on classical regression models developed on different sample populations, whereas the LOCAL approach is based on the development models from selected samples spectrally similar to the sample to be predicted. The first two strategies use feces-samples grouping based on the species or the family of the forage ingested. Forage calibration data sets gave value ranges of 79-327g/kg dry matter (DM) for CA, 65-243g/kg DM for CP, 0.52-0.85g/g for OMD, and 34.7-100.5g DM/kg metabolic body weight (BW0.75) for VI. The prediction of CA and CP content in feces by species-specific fecal NIR (FNIR) spectroscopy models showed lower standard error of prediction (SEP) (CA 15.03 and CP 7.48g/kg DM) than family-specific (CA 21.93 and CP 7.69g/kg DM), global (CA 19.83 and CP 7.98g/kg DM), or LOCAL (CA 30.85 and CP 8.10g/kg DM) models. For OMD, the LOCAL procedure led to a lower SEP (0.018g/g) than the other approaches (0.023, 0.024, and 0.023g/g for species-specific, family-specific, and global models, respectively). For VI, the LOCAL approach again led to a lower SEP (6.15g/kg BW0.75) than the other approaches (7.35, 8.00, and 8.13g/kg BW0.75 for the species-specific, family-specific, and global models, respectively). LOCAL approach performed on FNIR spectroscopy samples gives more precise models for predicting OMD and VI than species-specific, family-specific, or global approaches
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