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 | Acceso al texto completo restringido a Biblioteca INIA Las Brujas. Por información adicional contacte bibliolb@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas; INIA Treinta y Tres. |
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Fecha : |
25/01/2019 |
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Actualizado : |
22/12/2020 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
PRAVIA, V.; KEMANIAN, A. R.; TERRA, J.A.; SHI, Y.; MACEDO, I.; GOSLEE, S. |
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Afiliación : |
MARIA VIRGINIA PRAVIA NIN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ARMEN R. KEMANIAN, Department of Plant Science, The Pennsylvania State University, USA.; JOSÉ ALFREDO TERRA FERNÁNDEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; YUNING SHI, Department of Ecosystem Science and Management, The Pennsylvania State University, USA.; IGNACIO MACEDO YAPOR, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; SARAH GOSLEE, Pasture Systems and Watershed Management Research Unit, USDA-ARS, USA. |
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Título : |
Soil carbon saturation, productivity, and carbon and nitrogen cycling in crop-pasture rotations. |
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Fecha de publicación : |
2019 |
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Fuente / Imprenta : |
Agricultural Systems, May 2019, volume 171, pages 13-22. |
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ISSN : |
0308-521X |
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DOI : |
10.1016/j.agsy.2018.11.001 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 30 December 2017 // Received in revised form 2 November 2018 // Accepted 2 November 2018.
Funding for this work was provided by the Instituto Nacional de Investigación Agropecuaria (INIA-Uruguay) and the USDA-ARS Research Agreement Contract #58-1902-1-165 (Modeling of multispecies pasture growth and management). Appendices. |
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Contenido : |
ABSTRACT.
Agricultural systems integrating perennial grass-legume pastures in rotation with grain crops sustain high crop yields while preserving soil organic carbon (Cs) with low nitrogen (N) fertilizer inputs. We hypothesize that Cs saturation in the topsoil may explain the favorable C and N cycling in these systems. We tested this hypothesis by evaluating and simulating three contrasting crop and pasture rotational systems from a 20-year no-till experiment in Treinta y Tres, Uruguay. The systems were: 1) Continuous annual cropping (CC); 2) crop-pasture rotation with two years of crops and four years of pastures (CP); and 3) perennial pasture (PP). Using the Cycles agroecosystems model, we evaluated the inclusion or exclusion of a Cs saturation algorithm. The model simulated forage, soybean, and sorghum grain yields correctly, with low root mean square error (RMSE) of 1.5, 0.7 and 1.0 Mg ha−1, respectively. Measurements show Cs accretion and Cs decline for the first and second half of the experiment, respectively. The Cs accretion rate was highest for PP, while the Cs decline was highest for CC (1.3 vs −0.6 Mg ha−1 y−1 of C). The model captured this Cs dynamics and performed better when using the Cs saturation algorithm than when excluding it (RMSE 4.7 vs 6.8 Mg C ha−1 and relative RMSE of 14% and 21% for the top 15-cm). The model with saturation simulated subsoil Cs distribution with depth well, and simulated faster N turnover and greater N availability for the subsequent grain crop in CP vs CC. The results suggest that Cs saturation, and by extension soil organic N saturation, underpin the sustainability of crop-pasture rotations, and that modeling Cs saturation dynamics can be critical to reliably simulate complex crop-pasture rotational systems.
© 2018 Elsevier Ltd MenosABSTRACT.
Agricultural systems integrating perennial grass-legume pastures in rotation with grain crops sustain high crop yields while preserving soil organic carbon (Cs) with low nitrogen (N) fertilizer inputs. We hypothesize that Cs saturation in the topsoil may explain the favorable C and N cycling in these systems. We tested this hypothesis by evaluating and simulating three contrasting crop and pasture rotational systems from a 20-year no-till experiment in Treinta y Tres, Uruguay. The systems were: 1) Continuous annual cropping (CC); 2) crop-pasture rotation with two years of crops and four years of pastures (CP); and 3) perennial pasture (PP). Using the Cycles agroecosystems model, we evaluated the inclusion or exclusion of a Cs saturation algorithm. The model simulated forage, soybean, and sorghum grain yields correctly, with low root mean square error (RMSE) of 1.5, 0.7 and 1.0 Mg ha−1, respectively. Measurements show Cs accretion and Cs decline for the first and second half of the experiment, respectively. The Cs accretion rate was highest for PP, while the Cs decline was highest for CC (1.3 vs −0.6 Mg ha−1 y−1 of C). The model captured this Cs dynamics and performed better when using the Cs saturation algorithm than when excluding it (RMSE 4.7 vs 6.8 Mg C ha−1 and relative RMSE of 14% and 21% for the top 15-cm). The model with saturation simulated subsoil Cs distribution with depth well, and simulated faster N turnover and greater N a... Presentar Todo |
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Palabras claves : |
AGROECOSYSTEM MODELING; CROP PASTURE INTERSEEDNG; LONG-TERM EXPERIMENTS; SOIL ORGANIC MATTER. |
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Thesagro : |
CARBONO ORGANICO DEL SUELO. |
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Asunto categoría : |
--
P34 Biología del suelo |
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Marc : |
LEADER 03007naa a2200277 a 4500
001 1059451
005 2020-12-22
008 2019 bl uuuu u00u1 u #d
022 $a0308-521X
024 7 $a10.1016/j.agsy.2018.11.001$2DOI
100 1 $aPRAVIA, V.
245 $aSoil carbon saturation, productivity, and carbon and nitrogen cycling in crop-pasture rotations.$h[electronic resource]
260 $c2019
500 $aArticle history: Received 30 December 2017 // Received in revised form 2 November 2018 // Accepted 2 November 2018. Funding for this work was provided by the Instituto Nacional de Investigación Agropecuaria (INIA-Uruguay) and the USDA-ARS Research Agreement Contract #58-1902-1-165 (Modeling of multispecies pasture growth and management). Appendices.
520 $aABSTRACT. Agricultural systems integrating perennial grass-legume pastures in rotation with grain crops sustain high crop yields while preserving soil organic carbon (Cs) with low nitrogen (N) fertilizer inputs. We hypothesize that Cs saturation in the topsoil may explain the favorable C and N cycling in these systems. We tested this hypothesis by evaluating and simulating three contrasting crop and pasture rotational systems from a 20-year no-till experiment in Treinta y Tres, Uruguay. The systems were: 1) Continuous annual cropping (CC); 2) crop-pasture rotation with two years of crops and four years of pastures (CP); and 3) perennial pasture (PP). Using the Cycles agroecosystems model, we evaluated the inclusion or exclusion of a Cs saturation algorithm. The model simulated forage, soybean, and sorghum grain yields correctly, with low root mean square error (RMSE) of 1.5, 0.7 and 1.0 Mg ha−1, respectively. Measurements show Cs accretion and Cs decline for the first and second half of the experiment, respectively. The Cs accretion rate was highest for PP, while the Cs decline was highest for CC (1.3 vs −0.6 Mg ha−1 y−1 of C). The model captured this Cs dynamics and performed better when using the Cs saturation algorithm than when excluding it (RMSE 4.7 vs 6.8 Mg C ha−1 and relative RMSE of 14% and 21% for the top 15-cm). The model with saturation simulated subsoil Cs distribution with depth well, and simulated faster N turnover and greater N availability for the subsequent grain crop in CP vs CC. The results suggest that Cs saturation, and by extension soil organic N saturation, underpin the sustainability of crop-pasture rotations, and that modeling Cs saturation dynamics can be critical to reliably simulate complex crop-pasture rotational systems. © 2018 Elsevier Ltd
650 $aCARBONO ORGANICO DEL SUELO
653 $aAGROECOSYSTEM MODELING
653 $aCROP PASTURE INTERSEEDNG
653 $aLONG-TERM EXPERIMENTS
653 $aSOIL ORGANIC MATTER
700 1 $aKEMANIAN, A. R.
700 1 $aTERRA, J.A.
700 1 $aSHI, Y.
700 1 $aMACEDO, I.
700 1 $aGOSLEE, S.
773 $tAgricultural Systems, May 2019, volume 171, pages 13-22.
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Registro original : |
INIA Las Brujas (LB) |
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| Acceso al texto completo restringido a Biblioteca INIA Las Brujas. Por información adicional contacte bibliolb@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela; INIA Las Brujas. |
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Fecha actual : |
21/02/2014 |
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Actualizado : |
09/10/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
C - 0 |
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Autor : |
COZZOLINO, D.; RESTAINO, E.; FASSIO, A. |
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Afiliación : |
D. COZZOLINO, The Australian Wine Research Institute, Waite Campus, Adelaide, Australia; ERNESTO ANGEL RESTAINO GALUP, Instituto Nacional de Investigación Agropecuaria (INIA), Uruguay; ALBERTO SANTIAGO FASSIO ARAUJO, Instituto Nacional de Investigación Agropecuaria (INIA), Uruguay. |
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Título : |
Discrimination of yerba mate (Ilex paraguayensis St. Hil.) samples according to their geographical origin by means of near infrared spectroscopy and multivariate analysis. |
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Fecha de publicación : |
2010 |
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Fuente / Imprenta : |
Sensing and Instrumentation for Food Quality and Safety, 2010, v.4, no.2, p.67-72. |
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DOI : |
10.1007/s11694-010-9096-y |
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Idioma : |
Inglés |
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Notas : |
Article history: Received: 13 December 2009 / Accepted: 17 April 2010 / Published online: 29 April 2010. |
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Contenido : |
ABSTRACT.
Near infrared reflectance (NIR) spectroscopy combined with multivariate data analysis was used to discriminate between the geographical origins of yerba mate (Ilex paraguayensis St. Hil.) samples. Samples were purchased from the local market and scanned in the NIR region (1100-2500 nm) in a monochromator instrument in reflectance. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and linear discriminant analysis (LDA) were used to classify the samples based on their NIR spectra according to their geographical origin. Full cross validation was used as validation method when classification models were developed. The overall classification rates obtained were 76 and 100% using PLS-DA and LDA, respectively. The results demonstrated the usefulness of NIR spectra combined with multivariate data analysis as an objective and rapid method to classify yerba mate samples according to their geographical origin. Nevertheless, NIR spectroscopic might provide initial screening in the food chain and enable costly methods to be used more productively on suspect specimens.
© 2010 Springer Science+Business Media, LLC. |
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Palabras claves : |
ANÁLISIS MULTIVARIANTE; ESPECTROSCOPÍA DE REFLECTANCIA EN EL INFRARROJO CERCANO; NIRS; ORIGEN GEOGRÁFICO; YERBA MATE. |
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Thesagro : |
ESPECTROSCOPÍA DEL INFRARROJO CERCANO; ILEX PARAGUARIENSIS; YERBA MATE. |
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Asunto categoría : |
F01 Cultivo
Q01 Ciencia y tecnología de los alimentos |
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Marc : |
LEADER 02183naa a2200265 a 4500
001 1012847
005 2019-10-09
008 2010 bl uuuu u00u1 u #d
024 7 $a10.1007/s11694-010-9096-y$2DOI
100 1 $aCOZZOLINO, D.
245 $aDiscrimination of yerba mate (Ilex paraguayensis St. Hil.) samples according to their geographical origin by means of near infrared spectroscopy and multivariate analysis.
260 $c2010
500 $aArticle history: Received: 13 December 2009 / Accepted: 17 April 2010 / Published online: 29 April 2010.
520 $aABSTRACT. Near infrared reflectance (NIR) spectroscopy combined with multivariate data analysis was used to discriminate between the geographical origins of yerba mate (Ilex paraguayensis St. Hil.) samples. Samples were purchased from the local market and scanned in the NIR region (1100-2500 nm) in a monochromator instrument in reflectance. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and linear discriminant analysis (LDA) were used to classify the samples based on their NIR spectra according to their geographical origin. Full cross validation was used as validation method when classification models were developed. The overall classification rates obtained were 76 and 100% using PLS-DA and LDA, respectively. The results demonstrated the usefulness of NIR spectra combined with multivariate data analysis as an objective and rapid method to classify yerba mate samples according to their geographical origin. Nevertheless, NIR spectroscopic might provide initial screening in the food chain and enable costly methods to be used more productively on suspect specimens. © 2010 Springer Science+Business Media, LLC.
650 $aESPECTROSCOPÍA DEL INFRARROJO CERCANO
650 $aILEX PARAGUARIENSIS
650 $aYERBA MATE
653 $aANÁLISIS MULTIVARIANTE
653 $aESPECTROSCOPÍA DE REFLECTANCIA EN EL INFRARROJO CERCANO
653 $aNIRS
653 $aORIGEN GEOGRÁFICO
653 $aYERBA MATE
700 1 $aRESTAINO, E.
700 1 $aFASSIO, A.
773 $tSensing and Instrumentation for Food Quality and Safety, 2010$gv.4, no.2, p.67-72.
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