Use of Near Infrared Spectroscopy for the Determination of Organic Matter and Total Nitrogen of Soils
Chemical analysis in soils are essential for decision making in agriculture.Currently, the aim is to use non-destructive, fast, and precise techniques that allow for results to be obtaining easily, such as NIRS near infrared spectroscopy. The objective was to generate prediction equations for Organi...
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| Format: | Online |
| Language: | spa |
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Universidad Pedagógica y Tecnológica de Colombia
2023
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| Online Access: | https://revistas.uptc.edu.co/index.php/ciencia_en_desarrollo/article/view/13942 |
| _version_ | 1801706352555327488 |
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| author | Ortega Monsalve, Manuela Cerón-Muñoz, Mario Fernando Medina-Sierra, Marisol |
| author_facet | Ortega Monsalve, Manuela Cerón-Muñoz, Mario Fernando Medina-Sierra, Marisol |
| author_sort | Ortega Monsalve, Manuela |
| collection | OJS |
| description | Chemical analysis in soils are essential for decision making in agriculture.Currently, the aim is to use non-destructive, fast, and precise techniques that allow for results to be obtaining easily, such as NIRS near infrared spectroscopy. The objective was to generate prediction equations for Organic Matter (MO) and total Nitrogen (total N), by using NIRS spectra. 459 soil samples were processed by wet chemistry and by NIRS and various data transformations analyzed by partial least squares were used. In the selection, the values of the coefficient of determination (R2), the root mean square error of prediction (RMSEP) and the predictive residual deviation (RPD). The best model for MO was without transformation with absorbance (R2=0.90, RMSEP=0.29 and RPD=1.3) and for total Nitrogen with transformation of 1a derivative Savitzky-Golay (R2=0.84, RMSEP=0.09 and RPD=2.5). This indicates that the absorbance values of the NIRS spectra can be used to predict the OM and N values of the soil, using partial least squares models. |
| format | Online |
| id | oai:oai.revistas.uptc.edu.co:article-13942 |
| institution | Revista Ciencia en Desarrollo |
| language | spa |
| publishDate | 2023 |
| publisher | Universidad Pedagógica y Tecnológica de Colombia |
| record_format | ojs |
| spelling | oai:oai.revistas.uptc.edu.co:article-139422024-03-25T03:53:58Z Use of Near Infrared Spectroscopy for the Determination of Organic Matter and Total Nitrogen of Soils Espectroscopía de infrarrojo cercano para la determinación de materia orgánica y nitrógeno total del suelo Ortega Monsalve, Manuela Cerón-Muñoz, Mario Fernando Medina-Sierra, Marisol machine learning transformaciones métodos ´ópticos análisis químicos regresiones parciales chemical analysis machine learning optical methods partial regressions transformations Chemical analysis in soils are essential for decision making in agriculture.Currently, the aim is to use non-destructive, fast, and precise techniques that allow for results to be obtaining easily, such as NIRS near infrared spectroscopy. The objective was to generate prediction equations for Organic Matter (MO) and total Nitrogen (total N), by using NIRS spectra. 459 soil samples were processed by wet chemistry and by NIRS and various data transformations analyzed by partial least squares were used. In the selection, the values of the coefficient of determination (R2), the root mean square error of prediction (RMSEP) and the predictive residual deviation (RPD). The best model for MO was without transformation with absorbance (R2=0.90, RMSEP=0.29 and RPD=1.3) and for total Nitrogen with transformation of 1a derivative Savitzky-Golay (R2=0.84, RMSEP=0.09 and RPD=2.5). This indicates that the absorbance values of the NIRS spectra can be used to predict the OM and N values of the soil, using partial least squares models. Los análisis del suelo son fundamentales para la toma de decisiones en agricultura. Estos análisis pueden ser obtenidos por técnicas no destructivas, rápidas y precisas como lo es la espectroscopía de infrarrojo cercano NIRS. El objetivo fue generar ecuaciones de predicción de la Materia Orgánica (MO) y Nitrógeno total (N total), mediante el uso de espectros del NIRS. Se procesaron 459 muestras de suelo por química húmeda y por NIRS y se utilizaron diversas transformaciones de datos analizadas por mínimos cuadrados parciales. En la selección se tuvieron en cuenta los valores del coeficiente de determinación (R2), de la raiz del error cuadrático medio de predicción (RMSEP) y la desviación residual predictiva (RPD). El mejor modelo paraMO correspondió al modelo de aobsorbancia sin transformación (R2=0.90, RMSEP=0.29 y RPD=1.3) y para el nitrógeno total el mejor modelo fue la transformación de la 1a derivada de Savitzky-Golay (R2=0.84, RMSEP=0.09 y RPD=2.5). Lo anterior indica que se pueden utilizar los valores de absorbancia de los espectros del NIRS para predecir los valores de MO y N del suelo, utilizando modelos de mínimos cuadrados parciales. Universidad Pedagógica y Tecnológica de Colombia 2023-03-02 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion texto application/pdf https://revistas.uptc.edu.co/index.php/ciencia_en_desarrollo/article/view/13942 10.19053/01217488.v14.n1.2023.13942 Ciencia En Desarrollo; Vol. 14 No. 1 (2023): Vol 14, Núm.1 (2023): Enero-Junio; 111-118 Ciencia en Desarrollo; Vol. 14 Núm. 1 (2023): Vol 14, Núm.1 (2023): Enero-Junio; 111-118 2462-7658 0121-7488 spa https://revistas.uptc.edu.co/index.php/ciencia_en_desarrollo/article/view/13942/13484 |
| spellingShingle | machine learning transformaciones métodos ´ópticos análisis químicos regresiones parciales chemical analysis machine learning optical methods partial regressions transformations Ortega Monsalve, Manuela Cerón-Muñoz, Mario Fernando Medina-Sierra, Marisol Use of Near Infrared Spectroscopy for the Determination of Organic Matter and Total Nitrogen of Soils |
| title | Use of Near Infrared Spectroscopy for the Determination of Organic Matter and Total Nitrogen of Soils |
| title_alt | Espectroscopía de infrarrojo cercano para la determinación de materia orgánica y nitrógeno total del suelo |
| title_full | Use of Near Infrared Spectroscopy for the Determination of Organic Matter and Total Nitrogen of Soils |
| title_fullStr | Use of Near Infrared Spectroscopy for the Determination of Organic Matter and Total Nitrogen of Soils |
| title_full_unstemmed | Use of Near Infrared Spectroscopy for the Determination of Organic Matter and Total Nitrogen of Soils |
| title_short | Use of Near Infrared Spectroscopy for the Determination of Organic Matter and Total Nitrogen of Soils |
| title_sort | use of near infrared spectroscopy for the determination of organic matter and total nitrogen of soils |
| topic | machine learning transformaciones métodos ´ópticos análisis químicos regresiones parciales chemical analysis machine learning optical methods partial regressions transformations |
| topic_facet | machine learning transformaciones métodos ´ópticos análisis químicos regresiones parciales chemical analysis machine learning optical methods partial regressions transformations |
| url | https://revistas.uptc.edu.co/index.php/ciencia_en_desarrollo/article/view/13942 |
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