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 | Acceso al texto completo restringido a Biblioteca INIA La Estanzuela. Por información adicional contacte bib_le@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela. |
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Fecha actual : |
21/02/2014 |
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Actualizado : |
30/09/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
B - 1 |
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Autor : |
MORON, A.; COZZOLINO, D. |
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Afiliación : |
DAVID ALEJANDRO MORON YACOEL, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; DANIEL COZZOLINO GÓMEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Determination of potentially mineralizable nitrogen and nitrogen in particulate organic matter fractions in soil by visible and near-infrared reflectance spectroscopy. |
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Fecha de publicación : |
2004 |
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Fuente / Imprenta : |
Journal of Agricultural Science, June 2004, Volume 142, Issue 3, Pages 335-343. |
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DOI : |
10.1017/S0021859604004290 |
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Idioma : |
Inglés |
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Notas : |
Article history:Revised MS received 2 July 2004 |
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Contenido : |
SUMMARY:
Visible (VIS) and near-infrared reflectance spectroscopy (NIRS) combined with multivariate data analysis was used to predict potentially mineralizable nitrogen (PMN) and nitrogen in particulate organic matter fractions (PSOM-N). Soil samples from a long-term experiment (n=24) as well as
soils under commercial management (n=160) in Uruguay (South America) were analysed. Samples were scanned in a NIRS 6500 monochromator instrument by reflectance (400?2500 nm). Modified partial least square regression (MPLS) and cross validation were used to develop the calibration
models between NIRS data and reference values. NIRS calibration models gave a coefficient of determination for the calibration (R2 CAL)>0.80 and the standard deviation of reference data to standard error in cross validation (RPD) ratio ranging from 2 to 5. 5 for the variables evaluated. The
results obtained in the study showed that NIRS could have the potential to determine PMN and PSOM-N fractions in soils under different agronomic conditions. However, the relatively limited number of samples led us to be cautious in terms of conclusions and to extend the results of this work
to similar conditions. |
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Palabras claves : |
AGRICULTURAL SOILS; MINERALIZATION; MULTIVARIATE ANALYSIS; NITROGEN CONTNET; ORGANIC SOILS; SOIL ORGANIC MATTER(SOM). |
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Thesagro : |
NIRS. |
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Asunto categoría : |
-- |
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Marc : |
LEADER 02043naa a2200241 a 4500
001 1035241
005 2019-09-30
008 2004 bl uuuu u00u1 u #d
024 7 $a10.1017/S0021859604004290$2DOI
100 1 $aMORON, A.
245 $aDetermination of potentially mineralizable nitrogen and nitrogen in particulate organic matter fractions in soil by visible and near-infrared reflectance spectroscopy.$h[electronic resource]
260 $c2004
500 $aArticle history:Revised MS received 2 July 2004
520 $aSUMMARY: Visible (VIS) and near-infrared reflectance spectroscopy (NIRS) combined with multivariate data analysis was used to predict potentially mineralizable nitrogen (PMN) and nitrogen in particulate organic matter fractions (PSOM-N). Soil samples from a long-term experiment (n=24) as well as soils under commercial management (n=160) in Uruguay (South America) were analysed. Samples were scanned in a NIRS 6500 monochromator instrument by reflectance (400?2500 nm). Modified partial least square regression (MPLS) and cross validation were used to develop the calibration models between NIRS data and reference values. NIRS calibration models gave a coefficient of determination for the calibration (R2 CAL)>0.80 and the standard deviation of reference data to standard error in cross validation (RPD) ratio ranging from 2 to 5. 5 for the variables evaluated. The results obtained in the study showed that NIRS could have the potential to determine PMN and PSOM-N fractions in soils under different agronomic conditions. However, the relatively limited number of samples led us to be cautious in terms of conclusions and to extend the results of this work to similar conditions.
650 $aNIRS
653 $aAGRICULTURAL SOILS
653 $aMINERALIZATION
653 $aMULTIVARIATE ANALYSIS
653 $aNITROGEN CONTNET
653 $aORGANIC SOILS
653 $aSOIL ORGANIC MATTER(SOM)
700 1 $aCOZZOLINO, D.
773 $tJournal of Agricultural Science, June 2004, Volume 142, Issue 3, Pages 335-343.
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