<?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>2026-04-14T05:22:13Z</responseDate><request verb="GetRecord" identifier="oai:www.recercat.cat:20.500.12327/2325" metadataPrefix="marc">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><record xmlns="http://www.loc.gov/MARC21/slim" 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://www.loc.gov/MARC21/slim http://www.loc.gov/standards/marcxml/schema/MARC21slim.xsd">
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      <subfield code="a">Lobos, I.</subfield>
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      <subfield code="a">Gou, Pere</subfield>
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      <subfield code="a">Hube, S.</subfield>
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      <subfield code="a">Saldaña, R.</subfield>
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      <subfield code="a">Alfaro, M.</subfield>
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      <subfield code="c">2013-05-22</subfield>
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      <subfield code="a">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.</subfield>
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      <subfield code="a">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.</subfield>
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      <subfield code="a">0718-9508</subfield>
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      <subfield code="a">http://hdl.handle.net/20.500.12327/2325</subfield>
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      <subfield code="a">http://dx.doi.org/10.4067/S0718-95162013005000036</subfield>
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      <subfield code="a">Evaluation of potential nirs to predict pastures nutritive value</subfield>
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