<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-04-14T06:53:34Z</responseDate><request verb="GetRecord" identifier="oai:www.recercat.cat:20.500.12327/2325" metadataPrefix="qdc">https://recercat.cat/oai/request</request><GetRecord><record><header><identifier>oai:recercat.cat:20.500.12327/2325</identifier><datestamp>2025-10-22T11:15:23Z</datestamp><setSpec>com_2072_4428</setSpec><setSpec>com_2072_4427</setSpec><setSpec>col_2072_487898</setSpec></header><metadata><qdc:qualifieddc xmlns:qdc="http://dspace.org/qualifieddc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://purl.org/dc/elements/1.1/ http://dublincore.org/schemas/xmls/qdc/2006/01/06/dc.xsd http://purl.org/dc/terms/ http://dublincore.org/schemas/xmls/qdc/2006/01/06/dcterms.xsd http://dspace.org/qualifieddc/ http://www.ukoln.ac.uk/metadata/dcmi/xmlschema/qualifieddc.xsd">
   <dc:title>Evaluation of potential nirs to predict pastures nutritive value</dc:title>
   <dc:creator>Lobos, I.</dc:creator>
   <dc:creator>Gou, Pere</dc:creator>
   <dc:creator>Hube, S.</dc:creator>
   <dc:creator>Saldaña, R.</dc:creator>
   <dc:creator>Alfaro, M.</dc:creator>
   <dc:contributor>Indústries Alimentàries</dc:contributor>
   <dc:contributor>Qualitat i Tecnologia Alimentària</dc:contributor>
   <dcterms:abstract>This paper describes the capability of near infra-reflectance (NIRS) to predict the nutritional quality of pastures&#xd;
from southern Chile (39°-40°S). A Fourier transformed near-infrared (FT-NIR) method for rapid determination&#xd;
of dry matter (DM), crude protein (CP), in vitro digestibility (IVD) and metabolizable energy (ME) was used.&#xd;
Calibration models were developed between chemical and NIRS spectral data using partial least squares (PLS)&#xd;
regression and external validation. The coefficients of determination in calibration (R2c) were high varying between&#xd;
0.89-0.99 and the root mean square errors of calibration (RMSEC) were low, ranging between 0.46-2.55 for the&#xd;
parameters analysed. The Residual Prediction Deviation (RPD) was higher than 2.5. Our results confirmed the&#xd;
convenience of using a wide range of samples applicability in the calibration set. Data also showed that the use of&#xd;
an independent set of samples for external validation increases the robustness of the models to predict unknown&#xd;
samples. Our results indicated RPD values higher than 2.5 which is the minimum recommended for this type of&#xd;
prediction. Thus, the result showed that NIRS was useful to estimate the nutritional quality of permanent pastures,&#xd;
and has a great potential to be used as a rapid decision tool for the studied analysis.</dcterms:abstract>
   <dcterms:dateAccepted>2025-10-22T11:15:23Z</dcterms:dateAccepted>
   <dcterms:available>2025-10-22T11:15:23Z</dcterms:available>
   <dcterms:created>2025-10-22T11:15:23Z</dcterms:created>
   <dcterms:issued>2013-05-22</dcterms:issued>
   <dc:type>info:eu-repo/semantics/article</dc:type>
   <dc:identifier>Lobos, I., P. Gou, S. Hube, R. Saldaña, and M. Alfaro. 2013 “Evaluation of potential nirs to predict pastures nutritive value”. Journal of Soil Science and Plant Nutrition 13 (2): 463-468. doi: 10.4067/S0718-95162013005000036.</dc:identifier>
   <dc:identifier>0718-9508</dc:identifier>
   <dc:identifier>http://hdl.handle.net/20.500.12327/2325</dc:identifier>
   <dc:identifier>http://dx.doi.org/10.4067/S0718-95162013005000036</dc:identifier>
   <dc:language>eng</dc:language>
   <dc:relation>Journal of Soil Science and Plant Nutrition</dc:relation>
   <dc:rights>http://creativecommons.org/licenses/by-nc/4.0/</dc:rights>
   <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
   <dc:rights>Attribution-NonCommercial 4.0 International</dc:rights>
   <dc:publisher>Springer</dc:publisher>
</qdc:qualifieddc></metadata></record></GetRecord></OAI-PMH>