Near-infrared spectroscopy and wet chemistry dataset for forage nutritional quality assessment in Urochloa humidicola
Assessing the nutritional quality traits of pastures is crucial for germplasm and breeding evaluations, enabling the selection of high-quality forages to enhance livestock productivity. However, traditional laboratory analytical methods are logistically demanding and costly, particularly in large-sc...
| Main Authors: | , , , , |
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| Format: | Data Paper |
| Language: | Inglés |
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Elsevier
2025
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| Online Access: | https://hdl.handle.net/10568/174967 |
| _version_ | 1855515058586517504 |
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| author | Camelo, Rodrigo Andres Mazabel, Johanna Espitia-Buitrago, Paula Jauregui, Rosa Noemi Cardoso, Juan Andres |
| author_browse | Camelo, Rodrigo Andres Cardoso, Juan Andres Espitia-Buitrago, Paula Jauregui, Rosa Noemi Mazabel, Johanna |
| author_facet | Camelo, Rodrigo Andres Mazabel, Johanna Espitia-Buitrago, Paula Jauregui, Rosa Noemi Cardoso, Juan Andres |
| author_sort | Camelo, Rodrigo Andres |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Assessing the nutritional quality traits of pastures is crucial for germplasm and breeding evaluations, enabling the selection of high-quality forages to enhance livestock productivity. However, traditional laboratory analytical methods are logistically demanding and costly, particularly in large-scale trials, underscoring the need for rapid, precise, and high-throughput evaluation methods. Near-Infrared Spectroscopy (NIRS) optimizes the estimation of forage nutritional quality parameters by developing chemometric models that predict these parameters with high accuracy and precision, based on the association between NIRS data and wet chemistry analyses. This dataset, collected over ten years by the Tropical Forages Program at the International Center for Tropical Agriculture (CIAT) in Colombia, comprises 1112 samples. It includes 995 measurements of Neutral Detergent Fiber (NDF), 996 of Acid Detergent Fiber (ADF), 995 of In Vitro Dry Matter (IVDMD), and 469 of Crude Protein (CP), all obtained through wet chemistry methodologies. Additionally, the 1112 samples contain absorbance data spanning 400 to 2498 nanometers (nm) in 2 nm intervals, generating 1050 spectral data points per sample. Finally, this dataset is a valuable resource for predicting forage nutritional quality beyond conventional parameters, incorporating plant reflectance attributes to enhance selection strategies for optimized forage selection. |
| format | Data Paper |
| id | CGSpace174967 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | CGSpace1749672025-12-08T10:29:22Z Near-infrared spectroscopy and wet chemistry dataset for forage nutritional quality assessment in Urochloa humidicola Camelo, Rodrigo Andres Mazabel, Johanna Espitia-Buitrago, Paula Jauregui, Rosa Noemi Cardoso, Juan Andres high-throughput phenotyping fenotipado de alto rendimiento forage yield nutritive value-nutritional assessment of feeds infrared spectrophotometry-near infrared spectroscopy valor nutritivo-evaluación nutricional piensos calidad del cultivo espectroscopia infrarroja-espectroscopia infrarrojo cercano Assessing the nutritional quality traits of pastures is crucial for germplasm and breeding evaluations, enabling the selection of high-quality forages to enhance livestock productivity. However, traditional laboratory analytical methods are logistically demanding and costly, particularly in large-scale trials, underscoring the need for rapid, precise, and high-throughput evaluation methods. Near-Infrared Spectroscopy (NIRS) optimizes the estimation of forage nutritional quality parameters by developing chemometric models that predict these parameters with high accuracy and precision, based on the association between NIRS data and wet chemistry analyses. This dataset, collected over ten years by the Tropical Forages Program at the International Center for Tropical Agriculture (CIAT) in Colombia, comprises 1112 samples. It includes 995 measurements of Neutral Detergent Fiber (NDF), 996 of Acid Detergent Fiber (ADF), 995 of In Vitro Dry Matter (IVDMD), and 469 of Crude Protein (CP), all obtained through wet chemistry methodologies. Additionally, the 1112 samples contain absorbance data spanning 400 to 2498 nanometers (nm) in 2 nm intervals, generating 1050 spectral data points per sample. Finally, this dataset is a valuable resource for predicting forage nutritional quality beyond conventional parameters, incorporating plant reflectance attributes to enhance selection strategies for optimized forage selection. 2025-05-13 2025-06-04T13:02:14Z 2025-06-04T13:02:14Z Data Paper https://hdl.handle.net/10568/174967 en Open Access application/pdf Elsevier Camelo, R.A.; Mazabel, J.; Espitia-Buitrago, P.; Jauregui, R.N.; Cardoso, J.A. (2025) Near-infrared spectroscopy and wet chemistry dataset for forage nutritional quality assessment in Urochloa humidicola. Data in Brief 60: 111651. ISSN: 2352-3409 |
| spellingShingle | high-throughput phenotyping fenotipado de alto rendimiento forage yield nutritive value-nutritional assessment of feeds infrared spectrophotometry-near infrared spectroscopy valor nutritivo-evaluación nutricional piensos calidad del cultivo espectroscopia infrarroja-espectroscopia infrarrojo cercano Camelo, Rodrigo Andres Mazabel, Johanna Espitia-Buitrago, Paula Jauregui, Rosa Noemi Cardoso, Juan Andres Near-infrared spectroscopy and wet chemistry dataset for forage nutritional quality assessment in Urochloa humidicola |
| title | Near-infrared spectroscopy and wet chemistry dataset for forage nutritional quality assessment in Urochloa humidicola |
| title_full | Near-infrared spectroscopy and wet chemistry dataset for forage nutritional quality assessment in Urochloa humidicola |
| title_fullStr | Near-infrared spectroscopy and wet chemistry dataset for forage nutritional quality assessment in Urochloa humidicola |
| title_full_unstemmed | Near-infrared spectroscopy and wet chemistry dataset for forage nutritional quality assessment in Urochloa humidicola |
| title_short | Near-infrared spectroscopy and wet chemistry dataset for forage nutritional quality assessment in Urochloa humidicola |
| title_sort | near infrared spectroscopy and wet chemistry dataset for forage nutritional quality assessment in urochloa humidicola |
| topic | high-throughput phenotyping fenotipado de alto rendimiento forage yield nutritive value-nutritional assessment of feeds infrared spectrophotometry-near infrared spectroscopy valor nutritivo-evaluación nutricional piensos calidad del cultivo espectroscopia infrarroja-espectroscopia infrarrojo cercano |
| url | https://hdl.handle.net/10568/174967 |
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