Evaluation of botanical and chemical composition of sheep diet by using faecal near infrared spectroscopy

Sánchez, Nieves Núñez; Carrión, D.; Blanco, Francisco Peña; García, V. Domenech; Sigler, Ana Garzón; Marín, Andrés Luis Martínez

doi:10.1016/j.anifeedsci.2016.09.010

Cited by 18 publications

(9 citation statements)

References 10 publications

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“…Other works provided similar or better results developing fecal NIRS prediction models to estimate plant species diet composition in livestock: cattle (R 2 CAL = 0.94 just for monocots and dicots proportions [ 21 , 25 ]); goat (R 2 CAL = 0.95 to 0.99 depending on the plant taxa hay, Pistacia lentiscus, Phillyrea latifolia and Pinus brutia [ 57 ]; R 2 = 0.85 for herbaceous vegetation as one category; R 2 = 0.89 for Phillyrea latifolia ; R 2 = 0.77 for tannin-rich Pistacia lentiscus [ 58 ]); and sheep (R 2 CAL = 0.96 for Artemisia tridentata [ 59 ]; R 2 CAL = 0.86 to 0.97 depending on the plant taxa species: alfalfa, cereal straw, maize and forage [ 27 ]). The better NIRS prediction power in plant taxa diet composition in the livestock studies may be due to the fact that the reference method was the actual diet intake, since diets were already known and very few species were represented in those diets.…”

Section: Resultsmentioning

confidence: 99%

“…The NIRS technique has already been used to predict nutritional parameters and diet quality in fecal samples (fecal NIRS) of domestic (e.g., sheep [ 15 ], cattle [ 16 ]) and wild animals (e.g., Pyrenean chamois, Rupicapra pyrenaica pyrenaica [ 17 ]; red deer, Cervus elaphus and roe deer, Capreolus capreolus [ 18 ]; white-tailed deer, Odocoileus virginianus [ 19 ]) and other herbivores species [ 15 , 20 , 21 , 22 , 23 , 24 ]. Some studies used fecal NIRS to determine the plant species consumed by domestic animals (cattle [ 25 ], sheep [ 26 , 27 ], cattle and sheep [ 28 ] and pigs [ 29 ]). However, few works have been carried out to achieve a NIRS prediction model for the diet composition of wild ungulates, most likely because the broad dietary niche of these animals is a challenge for NIRS calibration.…”

Section: Introductionmentioning

confidence: 99%

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Near Infrared Reflectance Spectroscopy Analysis to Predict Diet Composition of a Mountain Ungulate Species

Jarque-Bascuñana

Bartolomé

Serrano

et al. 2021

Animals

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The diet composition of ungulates is important to understand not only their impact on vegetation, but also to understand the consequences of natural and human-driven environmental changes on the foraging behavior of these mammals. In this work, we evaluated the use of near infrared reflectance spectroscopy analysis (NIRS), a quick, economic and non-destructive method, to assess the diet composition of the Pyrenean chamois Rupicapra pyrenaica pyrenaica. Fecal samples (n = 192) were collected from two chamois populations in the French and Spanish Pyrenees. Diet composition was initially assessed by fecal cuticle microhistological analysis (CMA) and categorized into four functional groups, namely: woody, herbaceous, graminoid and Fabaceae plants. Regressions of modified partial least squares and several combinations of scattering correction and derivative treatments were tested. The results showed that models based on the second derivative processing obtained the higher determination coefficient for woody, herbaceous and graminoid plants (R2CAL, coefficient of determination in calibration, ranged from 0.86 to 0.91). The Fabaceae group, however, was predicted with lower accuracy (R2CAL = 0.71). Even though an agreement between NIRS and CMA methods was confirmed by a Bland–Altman analysis, confidence limits of agreement differed by up to 25%. Our results support the viability of fecal NIRS analysis to study spatial and temporal variations of the Pyrenean chamois’ diets in summer and winter when differences in the consumption of woody and annual plants are the greatest. This new use for the NIRS technique would be useful to assess the consequences of global change on the feeding behavior of this mountain ungulate and also in other ungulate counterparts.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Near Infrared Reflectance Spectroscopy Analysis to Predict Diet Composition of a Mountain Ungulate Species

Jarque-Bascuñana

Bartolomé

Serrano

et al. 2021

Animals

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“…Wavelength region selections were based on previous studies of sheep faecal analysis with NIR spectroscopy 24–26 and results obtained from the study of H. contortus eggs in water suspension. Wavelength regions with the highest r 2 cv , with the lowest RMSECV and the lowest number of factors, were selected as the best regions for analysis for each specific spectrometer.…”

Section: Methodsmentioning

confidence: 99%

Detection of Haemonchus contortus nematode eggs in sheep faeces using near and mid-infrared spectroscopy

Kho

Fernandes

Kotze

et al. 2020

Journal of Near Infrared Spectroscopy

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This paper reports the use of near infrared and mid-infrared spectroscopy to detect the presence and quantity of eggs of the gastrointestinal nematode Haemonchus contortus in sheep faeces. Haemonchus contortus eggs were quantified in dried, finely ground sheep faeces and in moist, coarsely ground faeces using near infrared and mid-infrared bench top spectrometers and a portable near infrared spectrometer. When Haemonchus contortus eggs were presented without faecal medium, it was found that the wavelength region of 1880–2100 nm was most important for detection. Broad classes of chemical properties found in the near infrared region were identified for dried Haemonchus contortus eggs using a mid-infrared spectrometer. However, when Haemonchus contortus eggs were mixed into the complex matrix of sheep faeces, the development of a robust calibration model for egg detection proved to be challenging (R2 < 0.47). The reliability of this method, if used for the detection of Haemonchus contortus eggs in the field, may be further limited by variations in egg species, faecal moisture content, faecal composition and particle size. Nevertheless, this is the first report identifying near infrared bands for Haemonchus contortus eggs and provides valuable information for future studies towards a spectroscopy-based method for detection of gastrointestinal nematodes.

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“…De nombreux travaux rapportent la capacité de la SPIR fécale à prédire la composition botanique de l'ingéré. Ces différentes approches peuvent consister à prédire les proportions de différentes espèces végétales dans un mélange ou le pourcentage de concentré (Landau et al, 2008 ;Núñez-Sánchez et al, 2016) ou encore les proportions entre différentes classes de végétaux (Coates et Dixon, 2008). La constitution d'étalonnages pour la prédiction qualitative de l'ingéré pose toutefois un problème méthodologique, car les essais sont en général réalisés avec des animaux confinés, alimentés avec un régime ne correspondant pas forcément aux choix alimentaires qu'auraient réalisé les animaux sur parcours (Landau et al, 2006).…”

Section: Prédiction à Partir D'échantillons De Fèces Chez Les Ruminantsunclassified

“…La constitution d'étalonnages pour la prédiction qualitative de l'ingéré pose toutefois un problème méthodologique, car les essais sont en général réalisés avec des animaux confinés, alimentés avec un régime ne correspondant pas forcément aux choix alimentaires qu'auraient réalisé les animaux sur parcours (Landau et al, 2006). De fait, même si les précisions des modèles de prédiction sont bonnes dans la phase d'étalonnage, ils ne sont généralement pas assez robustes pour prédire la diversité des espèces végétales des parcours lorsqu'ils sont testés en validation externe (Landau et al, 2006 ;Glasser et al, 2008 ;Núñez-Sánchez et al, 2016).…”

Section: Prédiction à Partir D'échantillons De Fèces Chez Les Ruminantsunclassified

La spectrométrie dans le proche infrarouge pour la caractérisation des ressources alimentaires

et al. 2019

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Le pilotage des systèmes d’élevage en vue d’une optimisation technique, économique et environnementale passe par une formulation des rations de plus en plus précise et nécessite donc une connaissance fine des aliments consommés par les animaux. La spectrométrie dans le proche infrarouge (SPIR), utilisée de façon croissante depuis les années 60, est une technique analytique permettant de caractériser rapidement des échantillons d’aliments ou de fourrages. Les premières applications concernaient la composition chimique des fourrages, mais il est également possible de développer des étalonnages pour une estimation de la valeur nutritive et de l’ingestion. Au-delà de ces mesures directes sur l’aliment, la SPIR peut être appliquée sur les fèces afin de caractériser l’alimentation d’animaux sur parcours. Le traitement conjoint des spectres des aliments et des fèces peut donner une vision de l’utilisation réellement faite des aliments par les animaux. D’autres utilisations possibles de la SPIR comme la traçabilité ou la classification des aliments ainsi que la reconnaissance botanique des végétaux dans les prairies sont aussi décrites. Les développements techniques actuels, et notamment la miniaturisation des spectromètres, permettent d’amener les instruments sur le terrain pour produire l’information au plus près de son utilisation. D’autres techniques spectroscopiques alternatives ou complémentaires à la SPIR comme la spectroscopie dans le moyen infrarouge, la spectroscopie Raman ou l’imagerie hyperspectrale permettront d’autres conditions de mesures et d’autres applications.

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Evaluation of botanical and chemical composition of sheep diet by using faecal near infrared spectroscopy

Cited by 18 publications

References 10 publications

Near Infrared Reflectance Spectroscopy Analysis to Predict Diet Composition of a Mountain Ungulate Species

Near Infrared Reflectance Spectroscopy Analysis to Predict Diet Composition of a Mountain Ungulate Species

Detection of Haemonchus contortus nematode eggs in sheep faeces using near and mid-infrared spectroscopy

La spectrométrie dans le proche infrarouge pour la caractérisation des ressources alimentaires

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