Evidence map›Paper›PMID 28453544›Full record

ArticlePloS one2017

Predicting herbivore faecal nitrogen using a multispecies near-infrared reflectance spectroscopy calibration.

Miriam Villamuelas, Emmanuel Serrano, Johan Espunyes, Néstor Fernández, Jorge R López-Olvera, Mathieu Garel, João Santos, María Ángeles Parra-Aguado, Maurizio Ramanzin, Xavier Fernández-Aguilar and 5 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.5field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 35 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 5 institutions in 4 countries.

Miriam VillamuelasServei d'Ecopatologia de Fauna Salvatge, Departament de Medicina i Cirurgia Animals, Facultat de Veterinária, Universitat Autònoma de Barcelona (UAB), Bellaterra, Barcelona, Spain.
Emmanuel SerranoServei d'Ecopatologia de Fauna Salvatge, Departament de Medicina i Cirurgia Animals, Facultat de Veterinária, Universitat Autònoma de Barcelona (UAB), Bellaterra, Barcelona, Spain.
Johan EspunyesServei d'Ecopatologia de Fauna Salvatge, Departament de Medicina i Cirurgia Animals, Facultat de Veterinária, Universitat Autònoma de Barcelona (UAB), Bellaterra, Barcelona, Spain.
Néstor FernándezDepartment of Conservation Biology, Estación Biológica de Doñana, Consejo Superior de Investigaciones Científicas EBD-CSIC, Sevilla, Spain.
Jorge R López-OlveraServei d'Ecopatologia de Fauna Salvatge, Departament de Medicina i Cirurgia Animals, Facultat de Veterinária, Universitat Autònoma de Barcelona (UAB), Bellaterra, Barcelona, Spain.
Mathieu GarelOffice National de la Chasse et de la Faune Sauvage (ONCFS - Unité Faune de Montagne), Gières, France.
João SantosDepartamento de Biologia & CESAM, Universidade de Aveiro (UA), Aveiro, Portugal.
María Ángeles Parra-AguadoSanidad y Biotecnología (SaBio), Instituto de Investigación en Recursos Cinegéticos, IREC (CSIC-UCLM-JCCM), Ciudad Real, Spain.
Maurizio RamanzinDepartment of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova (UNIPD), Agripolis, Legnaro, Italy.
Xavier Fernández-AguilarServei d'Ecopatologia de Fauna Salvatge, Departament de Medicina i Cirurgia Animals, Facultat de Veterinária, Universitat Autònoma de Barcelona (UAB), Bellaterra, Barcelona, Spain.
Andreu Colom-CadenaServei d'Ecopatologia de Fauna Salvatge, Departament de Medicina i Cirurgia Animals, Facultat de Veterinária, Universitat Autònoma de Barcelona (UAB), Bellaterra, Barcelona, Spain.
Ignasi MarcoServei d'Ecopatologia de Fauna Salvatge, Departament de Medicina i Cirurgia Animals, Facultat de Veterinária, Universitat Autònoma de Barcelona (UAB), Bellaterra, Barcelona, Spain.
Santiago LavínServei d'Ecopatologia de Fauna Salvatge, Departament de Medicina i Cirurgia Animals, Facultat de Veterinária, Universitat Autònoma de Barcelona (UAB), Bellaterra, Barcelona, Spain.
Jordi BartoloméRuminant Research Group, Departament de Ciència Animal i dels Aliments, Universitat Autònoma de Barcelona (UAB), Bellaterra, Barcelona, Spain.
Elena AlbanellRuminant Research Group, Departament de Ciència Animal i dels Aliments, Universitat Autònoma de Barcelona (UAB), Bellaterra, Barcelona, Spain.ORCID http://orcid.org/0000-0002-6158-7736
Universitat Autònoma de Barcelona · ESInstituto de Investigación en Recursos Cinegéticos · ESConsejo Superior de Investigaciones Científicas · ESOffice National de la Chasse et de la Faune Sauvage · FRUniversity of Padua · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Optimal management of free-ranging herbivores requires the accurate assessment of an animal's nutritional status. For this purpose 'near-infrared reflectance spectroscopy' (NIRS) is very useful, especially when nutritional assessment is done through faecal indicators such as faecal nitrogen (FN). In order to perform an NIRS calibration, the default protocol recommends starting by generating an initial equation based on at least 50-75 samples from the given species. Although this protocol optimises prediction accuracy, it limits the use of NIRS with rare or endangered species where sample sizes are often small. To overcome this limitation we tested a single NIRS equation (i.e., multispecies calibration) to predict FN in herbivores. Firstly, we used five herbivore species with highly contrasting digestive physiologies to build monospecies and multispecies calibrations, namely horse, sheep, Pyrenean chamois, red deer and European rabbit. Secondly, the equation accuracy was evaluated by two procedures using: (1) an external validation with samples from the same species, which were not used in the calibration process; and (2) samples from different ungulate species, specifically Alpine ibex, domestic goat, European mouflon, roe deer and cattle. The multispecies equation was highly accurate in terms of the coefficient of determination for calibration R2 = 0.98, standard error of validation SECV = 0.10, standard error of external validation SEP = 0.12, ratio of performance to deviation RPD = 5.3, and range error of prediction RER = 28.4. The accuracy of the multispecies equation to predict other herbivore species was also satisfactory (R2 > 0.86, SEP < 0.27, RPD > 2.6, and RER > 8.1). Lastly, the agreement between multi- and monospecies calibrations was also confirmed by the Bland-Altman method. In conclusion, our single multispecies equation can be used as a reliable, cost-effective, easy and powerful analytical method to assess FN in a wide range of herbivore species.

Indexed as

HerbivoryAnimalsCalibrationFecesNitrogenSpectroscopy, Near-InfraredNitrogen

Identifiers

PMID28453544
PMCPMC5409079
OpenAlexW2609732913

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.