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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela; INIA Las Brujas; INIA Tacuarembó. |
Fecha : |
21/02/2014 |
Actualizado : |
22/02/2014 |
Autor : |
Arboleya, J.Gilsanz, J.C.Villamil, J.M.Gómez, R. |
Título : |
Control de malezas postrasplante en el cultivo de la cebolla |
Fecha de publicación : |
1997 |
Fuente / Imprenta : |
Las Brujas, Canelones (Uruguay): INIA, 1997. |
Páginas : |
p. 28-35 |
Serie : |
(INIA Serie Actividades de Difusión ; 128) |
Idioma : |
Español |
Notas : |
INIA Las Brujas |
Thesagro : |
ALLIUM CEPA; CEBOLLA; ESCARDA; MALEZAS. |
Asunto categoría : |
-- |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/262/1/18429200808102311.pdf
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Marc : |
LEADER 00564naa a2200193 a 4500 001 1006872 005 2014-02-22 008 1997 bl uuuu u00u1 u #d 100 1 $aARBOLEYA, J.GILSANZ, J.C.VILLAMIL, J.M.GÓMEZ, R. 245 $aControl de malezas postrasplante en el cultivo de la cebolla 260 $c1997 300 $ap. 28-35 490 $a(INIA Serie Actividades de Difusión ; 128) 500 $aINIA Las Brujas 650 $aALLIUM CEPA 650 $aCEBOLLA 650 $aESCARDA 650 $aMALEZAS 773 $tLas Brujas, Canelones (Uruguay): INIA, 1997.
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INIA Las Brujas (LB) |
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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela. |
Fecha actual : |
21/02/2014 |
Actualizado : |
28/10/2019 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Circulación / Nivel : |
A - 2 |
Autor : |
FASSIO, A.; COZZOLINO, D. |
Afiliación : |
ALBERTO SANTIAGO FASSIO ARAUJO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; DANIEL COZZOLINO GÓMEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
Non-destructive prediction of chemical composition in sunflower seeds by near infrared spectroscopy. |
Fecha de publicación : |
2004 |
Fuente / Imprenta : |
Industrial Crops and Products, 2004, 20 (3): 321-329. |
DOI : |
10.1016/j.indcrop.2003.11.004 |
Idioma : |
Inglés |
Notas : |
Article history: Received 25 April 2003 / Accepted 14 November 2003. |
Contenido : |
Abstract:
Near infrared reflectance spectroscopy (NIRS) was explored as a technique to predict moisture (M), oil and crude protein
(CP) content on intact sunflower seeds (Helianthus annuus L.). Three hundred samples were scanned intact in a monochromator
instrument NIRS 6500 (NIRSystems, Silver Spring, MD, USA). Calibration equations were developed using modified partial
least square regression (MPLS) with internal cross validation. Samples were split in two sets, one set used as calibration
(n = 250) where the remaining samples (n = 50) were used as validation set. Two mathematical treatments (first and second
derivative), none (log 1/R) and standard normal variate and detrend (SNVD) as scatter corrections were explored. The coefficient
of determination in calibration (R2
cal) and the standard error in cross validation (SECV) were 0.95 (SECV: 3.3) for M; 0.96
(SECV: 13.1) for CP and 0.90 (SECV: 22.3) for oil in g kg?1 on a dry weight basis (second derivative, 400?2500 nm). Prediction
models accounted for less than 65, 70 and 72% of the total variation for oil, M and CP, respectively. However, it was concluded
that NIRS is a suitable technique to be used as a tool for rapid pre-screening of quality characteristics on breeding programs. |
Palabras claves : |
CRUDE PROTEIN; MOISTURE; NEAR INFRARED REFLECTANCE SPECTROSCOPY; OIL; SEEDS. |
Thesagro : |
GIRASOL; HELIANTHUS ANNUUS L; NIRS; PROTEINA CRUDA; SEMILLAS. |
Asunto categoría : |
-- |
Marc : |
LEADER 02084naa a2200277 a 4500 001 1049578 005 2019-10-28 008 2004 bl uuuu u00u1 u #d 024 7 $a10.1016/j.indcrop.2003.11.004$2DOI 100 1 $aFASSIO, A. 245 $aNon-destructive prediction of chemical composition in sunflower seeds by near infrared spectroscopy. 260 $c2004 500 $aArticle history: Received 25 April 2003 / Accepted 14 November 2003. 520 $aAbstract: Near infrared reflectance spectroscopy (NIRS) was explored as a technique to predict moisture (M), oil and crude protein (CP) content on intact sunflower seeds (Helianthus annuus L.). Three hundred samples were scanned intact in a monochromator instrument NIRS 6500 (NIRSystems, Silver Spring, MD, USA). Calibration equations were developed using modified partial least square regression (MPLS) with internal cross validation. Samples were split in two sets, one set used as calibration (n = 250) where the remaining samples (n = 50) were used as validation set. Two mathematical treatments (first and second derivative), none (log 1/R) and standard normal variate and detrend (SNVD) as scatter corrections were explored. The coefficient of determination in calibration (R2 cal) and the standard error in cross validation (SECV) were 0.95 (SECV: 3.3) for M; 0.96 (SECV: 13.1) for CP and 0.90 (SECV: 22.3) for oil in g kg?1 on a dry weight basis (second derivative, 400?2500 nm). Prediction models accounted for less than 65, 70 and 72% of the total variation for oil, M and CP, respectively. However, it was concluded that NIRS is a suitable technique to be used as a tool for rapid pre-screening of quality characteristics on breeding programs. 650 $aGIRASOL 650 $aHELIANTHUS ANNUUS L 650 $aNIRS 650 $aPROTEINA CRUDA 650 $aSEMILLAS 653 $aCRUDE PROTEIN 653 $aMOISTURE 653 $aNEAR INFRARED REFLECTANCE SPECTROSCOPY 653 $aOIL 653 $aSEEDS 700 1 $aCOZZOLINO, D. 773 $tIndustrial Crops and Products, 2004, 20 (3): 321-329.
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