02d. IVDMD.tab

This file is part of "Near-Infrared Spectroscopy and Wet Chemistry Dataset for Forage Nutritional Quality Assessment in Urochloa humidicola".

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File Citation
Camelo Munevar, Rodrigo Andres; Cardoso Arango, Juan Andres; Jauregui, Rosa Noemi; Espitia Buitrago, Paula Andrea; Mazabel Parra, Lady Johanna, 2024, "Near-Infrared Spectroscopy and Wet Chemistry Dataset for Forage Nutritional Quality Assessment in Urochloa humidicola", https://doi.org/10.7910/DVN/XPNIQY, Harvard Dataverse, V3; 02d. IVDMD.tab [fileName], UNF:6:3wNKaAVs6A3i8DezuJQr0w== [fileUNF]
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Dataset Citation
Camelo Munevar, Rodrigo Andres; Cardoso Arango, Juan Andres; Jauregui, Rosa Noemi; Espitia Buitrago, Paula Andrea; Mazabel Parra, Lady Johanna, 2024, "Near-Infrared Spectroscopy and Wet Chemistry Dataset for Forage Nutritional Quality Assessment in Urochloa humidicola", https://doi.org/10.7910/DVN/XPNIQY, Harvard Dataverse, V3, UNF:6:6nNxExBTq2TOHSSzwqMApA== [fileUNF]
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Our Community Norms as well as good scientific practices expect that proper credit is given via citation. Please use the data citation shown on the dataset page.

Custom Dataset Terms - the following Custom Dataset Terms have been defined for this dataset.

Creative Commons License
These data and documents are licensed under a Creative Commons Attribution 4.0 International license. You may copy, distribute and transmit the data as long as you acknowledge the source through proper data citation.

The Alliance of Bioversity International and CIAT (hereinafter "the Alliance"), its partners, and the data authors have exercised utmost care in collecting and compiling the data. However, the data is provided "as is" without any express or implied warranty. Neither the Alliance, its partners, the data authors, nor any relevant funding agencies shall be held liable for any actual, incidental, or consequential damages arising from the use of this data.

By utilizing the Alliance Dataverse, users explicitly acknowledge that the data may contain nonconformities, defects, or errors. No warranty is provided that the data will meet users' needs or expectations, nor that all nonconformities, defects, or errors can or will be corrected.

Users are responsible for verifying the accuracy and suitability of the data for their intended use. It is strongly recommended that users refer to related publications as a baseline for their analysis whenever possible. This practice serves as an additional safeguard against misinterpretation of the data. Related publications are listed in the metadata section of the respective Dataverse study.

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