cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21429/kkvn-q956
title: The role of landscape characteristics in climate-driven rapid ecological change over the last 21,000 years in the Middle and Southern Rockies, U.S.A.

description: These model objects are the outputs of two Bayesian hierarchical models (one for the Middle Rockies and one for the Southern Rockies) to explore the role of landscape characteristics in climate-driven ecological change and transformation. We used the rate of change for each site at 100-yr time steps as the response variable, and included elevation, CHILI, aspect, slope, and TPI as fixed effects in the models, run separately for each ecoregion. We included a random intercept of site to quantify the magnitude of site-level variation in rate-of-change that may be unaccounted for by our covariates.
DOI: 10.5281/zenodo.6512250
title: Riverscape heterogeneity in estimated Chinook Salmon emergence phenology and implications for size and growth

description: Many salmonid-bearing rivers exhibit thermal and hydrologic heterogeneity at multiple spatial and temporal scales, but how this translates into spatiotemporal patterns of fry emergence is poorly understood. Understanding this variability is important because emergence timing determines the biophysical conditions fish first experience (e.g., temperature, flow, food supply), thereby influencing growth opportunities and survival during this critical life stage. We predicted spring Chinook Salmon (<em>Oncorhynchus tshawytscha</em>) emergence phenology across four NE Oregon subbasins over 5-9 years using empirical spawning and temperature data. We then related inter-annual emergence timing estimates to juvenile salmon size and growth rates at consistent sampling locations. There were clear longitudinal patterns of predicted emergence timing in each subbasin: the shape of these patterns was consistent among years, but not among subbasins. In two subbasins emergence occurred progressively later with distance upstream, whereas in the other two subbasins emergence was earliest at upstream sites. Within each year, median emergence dates among sites within each subbasin ranged between 44 and 58 days. This spatial variation was comparable to inter-annual variation, with median emergence dates for a given location in each subbasin ranging between 47 to 74 days among years. Contrary to our expectations, juvenile salmon were not larger in years with earlier emergence, owing to slower spring and summer growth rates compared to years with later emergence. Despite large inter-annual variation in emergence dates, these results suggest that other factors (e.g., stream flow, temperature, density-dependence) were more important than growth duration in determining juvenile salmon growth rates and size among years. We demonstrated considerable spatial and inter-annual variation in emergence phenology within these subbasins. Understanding how this variation translates to spatiotemporal patterns of juvenile salmon habitat use, growth, and survival has important implications for guiding restoration efforts and understanding how climate change may impact these populations.
description: Please read "Guide to accessing data used to estimate emergence timing.docx" for a description of how to access additional publicly available data.
DOI: 10.5281/zenodo.6512249
title: Riverscape heterogeneity in estimated Chinook Salmon emergence phenology and implications for size and growth

description: Many salmonid-bearing rivers exhibit thermal and hydrologic heterogeneity at multiple spatial and temporal scales, but how this translates into spatiotemporal patterns of fry emergence is poorly understood. Understanding this variability is important because emergence timing determines the biophysical conditions fish first experience (e.g., temperature, flow, food supply), thereby influencing growth opportunities and survival during this critical life stage. We predicted spring Chinook Salmon (<em>Oncorhynchus tshawytscha</em>) emergence phenology across four NE Oregon subbasins over 5-9 years using empirical spawning and temperature data. We then related inter-annual emergence timing estimates to juvenile salmon size and growth rates at consistent sampling locations. There were clear longitudinal patterns of predicted emergence timing in each subbasin: the shape of these patterns was consistent among years, but not among subbasins. In two subbasins emergence occurred progressively later with distance upstream, whereas in the other two subbasins emergence was earliest at upstream sites. Within each year, median emergence dates among sites within each subbasin ranged between 44 and 58 days. This spatial variation was comparable to inter-annual variation, with median emergence dates for a given location in each subbasin ranging between 47 to 74 days among years. Contrary to our expectations, juvenile salmon were not larger in years with earlier emergence, owing to slower spring and summer growth rates compared to years with later emergence. Despite large inter-annual variation in emergence dates, these results suggest that other factors (e.g., stream flow, temperature, density-dependence) were more important than growth duration in determining juvenile salmon growth rates and size among years. We demonstrated considerable spatial and inter-annual variation in emergence phenology within these subbasins. Understanding how this variation translates to spatiotemporal patterns of juvenile salmon habitat use, growth, and survival has important implications for guiding restoration efforts and understanding how climate change may impact these populations.
description: Please read "Guide to accessing data used to estimate emergence timing.docx" for a description of how to access additional publicly available data.
DOI: 10.21429/2aj3-pg02
title: Type and speed of vegetation transformations over the past 21,000 years in the Middle and Southern Rockies, U.S.A.

description: This database integrates a list of vegetation transformations that occurred across the Southern and Middle Rockies since 21,000 years ago, the age of occurrence, the type of vegetation switch that occurred, whether the rates of vegetation change peaked at that time, and when applicable, the duration of peak rates of vegetation change.
DOI: 10.15454/x2cxyf/tozzt2
title: datapackage.json

description: ODAM datapackage based on JSON Schema
DOI: 10.15454/x2cxyf/zidxlt
title: FR17PP009.zip

description: Set of data files
DOI: 10.15454/x3ocet/xyvyz6
title: Biological_Operability_of_sheep-cattle_mixed-grazing_01Feb21.py

description: :unav
DOI: 10.15454/x5jnqy/c0gi4s
title: Raw_data.txt
DOI: 10.15454/x6zju0/1ygu5a
title: Appendix_S4_Correlations_PhylogeoPyr_Aalba_final.doc

description: :unav
DOI: 10.15454/x6zju0/awrqm1
title: Appendix_S5_Fossil_PhylogeoPyr_Aalba_final.docx

description: :unav
DOI: 10.15454/x6zju0/dliwsm
title: Appendix_S1_Diversity_PhylogeoPyr_Aalba_final.docx

description: :unav
DOI: 10.15454/x6zju0/hxtgr6
title: Appendix_S4_Correlations_TableS4.2_PhylogeoPyr_Aalba_final.tab

description: :unav
DOI: 10.15454/x6zju0/njdkug
title: Appendix_S3_Demography_PhylogeoPyr_Aalba_final.doc

description: :unav
DOI: 10.15454/x6zju0/nmbzew
title: Appendix_S4_Correlations_Table_S4.3_PhylogeoPyr_Aalba_final.tab

description: :unav
DOI: 10.15454/x6zju0/nu0wmb
title: Appendix_S1_Diversity_TableS1.3_PhylogeoPyr_Aalba_final.tab

description: :unav
DOI: 10.15454/x6zju0/sywoul
title: Appendix_S4_Correlations_TableS4.4_PhylogeoPyr_Aalba_final.tab

description: :unav
DOI: 10.15454/x6zju0/zqf0mz
title: Appendix_S2_Clustering_analysis_PhylogeoPyr_Aalba_final.docx

description: :unav
DOI: 10.15454/x8g2li/4wgrkj
title: Regularb_pollen_ISO-19115.xml
DOI: 10.15454/x8g2li/b6lms0
title: Regularb_pollen_ISO-19110.xml
DOI: 10.15454/x8g2li/s0u3os
title: Regularb_pollen_shp_Data_bees_regularb.zip
DOI: 10.15454/xcqxob/4phylc
title: corg_per_upc.tab

description: Ce fichier décrit pour chaque upc : - SocMulder_GC_vois, la quantité de carbone organique du sol des grandes cultures en kgC/m² entre 0 et 30 cm du sol - SocMulder_pra_vois, la quantité de carbone organique du sol des prairies en kgC/m² entre 0 et 30 cm du sol - SocMulder_100cm_GC_vois, la quantité de carbone organique du sol des grandes cultures en kgC/m² entre 0 et 100 cm du sol - SocMulder_100cm_pra_vois, la quantité de carbone organique du sol des prairies en kgC/m² entre 0 et 100 cm du sol
DOI: 10.15454/xcqxob/4v4cih
title: mergedResultStockingPractice.RDS

description: Résultats des pratiques stockantes issues des simulations PaSim réalisées dans le cadre de l'expertise 4p1000
DOI: 10.15454/xcqxob/6cg2u5
title: mergedResultBaseline.RDS

description: Résultats de la ligne de base des simulations PaSim réalisées dans le cadre de l'expertise 4p1000
DOI: 10.15454/xcqxob/abocwd
title: general_final.RDS

description: fichier composé des variables suivantes : - upc = numero de l’upc - uts = numero de l’uts (unité de type de sol) - type = « 1 » ou « 4 » selon que la simulation soit de type 1 ou de type 4 - modexp = le mode d’exploitation, compris en 1 et 31 - latitude_rad = la latitude en radian - alti_mean = l’altitude en m - safran = le numéro de la maille safran, utile pour le lien avec le fichier météo - surfaceInUPC = pourcentage de la surface de prairie de ce type au sein de l’UPC (0 si généré dans le cadre des pratiques stockantes) - surfaceInUPCxUTS = pourcentage de la surface de prairie de ce type au sein du couple UPC/UTS (cette surface est supérieur à la surfaceUPC, égal si et seulement si il n’y a qu’un UTS dans l’UPC) (0 si généré dans le cadre des pratiques stockantes) - baseLine = cette simulation apartient à la ligne de base - modexFinal4p1000 = indique le mode d’exploitation auquel est lié cette pratique stockante (cette simulation est donc forcément un départ d’une pratique stockante) - surf_tot_upc = surface totale de l’UPC - surf_rpg_2012 = surface totale de l’UPC au RPG 2012 - commune = code postale de la commune - region = nom de la région, à savoir "Guadeloupe", "Martinique", "Guyane", "La Reunion", "Mayotte", "Ile-de-France", "Champagne-Ardenne", "Picardie", "Haute-Normandie", "Centre", "Basse-Normandie", "Bourgogne", "Nord-Pas-De-Calais", "Lorraine", "Alsace", "Franche-Comte", "Pays de la Loire", "Bretagne", "Poitou-Charentes", "Aquitaine", "Midi-Pyrenees", "Limousin", "Rhone-Alpes", "Auvergne", "Languedoc-Roussillon", "Provence-Alpes-Cote-Azur" et "Corse" - surf_prairie_type1 = Surface de prairie de type 1 sur l’UPC - surf_prairie_type4 = Surface de prairie de type 4 sur l’UPC - surf_simul_prairie_type1 = Surface de prairie simulée de type 1 sur l’UPC - surf_simul_prairie_type4 = Surface de prairie simulée de type 4 sur l’UPC
DOI: 10.15454/xcqxob/diyysy
title: percent_orga_region.RDS

description: fichier composé des variables suivantes : - region = nom de la région, à savoir "Guadeloupe", "Martinique", "Guyane", "La Reunion", "Mayotte", "Ile-de-France", "Champagne-Ardenne", "Picardie", "Haute-Normandie", "Centre", "Basse-Normandie", "Bourgogne", "Nord-Pas-De-Calais", "Lorraine", "Alsace", "Franche-Comte", "Pays de la Loire", "Bretagne", "Poitou-Charentes", "Aquitaine", "Midi-Pyrenees", "Limousin", "Rhone-Alpes", "Auvergne", "Languedoc-Roussillon", "Provence-Alpes-Cote-Azur" et "Corse" - percentOrgaWithAvailable = pourcentage de prairie de la ligne de base susceptible de recevoir de la fertilisation organique qui peut effectivement en recevoir une fois pris en compte la quantité disponible sur la région - percentTargetOrgaWithAvailable = pourcentage de prairie issue de la ligne de base sur laquelle a été appliquée les pratiques stockantes et susceptible de recevoir de la fertilisation organique qui peut effectivement en recevoir une fois pris en compte la quantité disponible sur la région - percentTotWithAvailable = pourcentage de prairie de la ligne de base qui peut effectivement recevoir de la fertilisation organique une fois pris en compte la quantité disponible sur la région - percentTargetTotWithAvailable = pourcentage de prairie de la ligne de base sur laquelle a été appliquée les pratiques stockantes qui peut effectivement recevoir de la fertilisation organique une fois pris en compte la quantité disponible sur la région
DOI: 10.15454/xcqxob/fb2kdh
title: gestion_all.RDS

description: fichier composé des variables suivantes : - upc = numero de l’upc - uts = numero de l’uts (unité de type de sol) - type = « 1 » ou « 4 » selon que la simulation soit de type 1 ou de type 4 - modexp = le mode d’exploitation, compris en 1 et 31 - an = année (entre 1 et 35) - type_vache = type de vache (1 laitière, 2 allaitante) - cut1 à cut4 = les dates des 4 fauches, le cas échéant - tfert1 à tfert6 = les dates des 6 fertilisations, le cas échéant - az1 à az6 = les quantités des apports des 6 fertilisants minéraux, le cas échéant - tanimal1 à tanimal10 = les dates des 10 périodes de 10 jours de pâturages, le cas échéant - nanimal = chargement instantanée sur chacune des périodes de pâturage
DOI: 10.15454/xcqxob/oiudeu
title: 4p1000_PaSim_Simulation.pdf

description: Document principal détaillant le processus des simulations PaSim dans le cadre de 4p1000
DOI: 10.15454/xcqxob/uyqi6k
title: pasim_metadata.tab

description: Métadonnées des fichiers RDS d'agrégations des sorties de PaSim
DOI: 10.15454/xcqxob/whdigs
title: surface_region.RDS

description: fichier composé des variables suivantes : - region = nom de la région, à savoir "Guadeloupe", "Martinique", "Guyane", "La Reunion", "Mayotte", "Ile-de-France", "Champagne-Ardenne", "Picardie", "Haute-Normandie", "Centre", "Basse-Normandie", "Bourgogne", "Nord-Pas-De-Calais", "Lorraine", "Alsace", "Franche-Comte", "Pays de la Loire", "Bretagne", "Poitou-Charentes", "Aquitaine", "Midi-Pyrenees", "Limousin", "Rhone-Alpes", "Auvergne", "Languedoc-Roussillon", "Provence-Alpes-Cote-Azur" et "Corse" - surf_tot_upc = somme des surfaces des upc appartenant à la région - surf_rpg_2012 = somme des surfaces déclarées à la RPG 2012 appartenant à la région - surf_prairie_type1 = somme des surfaces de prairie type 1 appartenant à la région - surf_prairie_type4 = somme des surfaces de prairie type 4 appartenant à la région - surf_simul_prairie_type1 = somme des surfaces de prairie simulée de type 1 appartenant à la région - surf_simul_prairie_type4 = somme des surfaces de prairie simulée de type 4 appartenant à la région
DOI: 10.15454/xcqxob/wixrxd
title: sol_final.RDS

description: Fichier composé des variables suivantes : - upc = numero de l’upc - uts = numero de l’uts (unité de type de sol) - pH = le pH - p1 à p4 = la profondeur des différentes horizons avec p1
DOI: 10.15454/xdmksa/avqzq1
title: rpg_complete_2018_d36.zip

description: :unav
DOI: 10.15454/xemdld/ijvgxs
title: File_04_91genotypes_94ssr_structure.txt

description: Input file for Structure software: 91 unique genotypes of the INRAE chestnut germplasm collection characterized with 94 SSRs
DOI: 10.15454/xemdld/kw6chv
title: File_01_Sequences_CASTA_343SNP.tab

description: List of 343 tested SNPs, 237 validated ones and final selection of 79 SNPs for species or cultivar identification.
DOI: 10.15454/xemdld/mcjhmv
title: 91genotypes_94ssr_structure.txt

description: Input file for Structure software: 91 unique genotypes of the INRAE chestnut germplasm collection characterized with 94 SSRs.
DOI: 10.15454/xemdld/mvk79s
title: File_02_MassARRAY_Multiplexes_CASTA_W1W2_79SNP.tab

description: Information about the 79 SNPs from the two final multiplexes for the MassARRAY platform.
DOI: 10.15454/xemdld/qqgd72
title: MassARRAY_Multiplexes_CASTA_W1W2_79SNP.tab

description: Information about the 79 SNPs from the two final multiplexes for the MassARRAY platform.
DOI: 10.15454/xemdld/trid3m
title: Sequences_CASTA_343SNP.tab

description: List of 343 tested SNPs, 237 validated ones and final selection of 79 SNPs for species or cultivar identification.
DOI: 10.15454/xemdld/wdilhv
title: File_03_91genotypes_68snp_strucure.txt

description: Input file for Structure software: 91 unique genotypes of the INRAE chestnut germplasm collection characterized with 68 SNPs.
DOI: 10.15454/xemdld/wrmogi
title: 91genotypes_68snp_strucure.txt

description: Input file for Structure software: 91 unique genotypes of the INRAE chestnut germplasm collection characterized with 68 SNPs.
DOI: 10.15454/xetxqu/2h28g0
title: 4_HFD1_47C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/5hqyms
title: 4_HFD1_54C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/5vbqtd
title: 5_HFD2_79C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/adazlh
title: 6_HFD4_42C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/bqcqe4
title: 6_HFD4_76C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/bsnqpk
title: 1_HFD0_51C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/e8yvkw
title: 5_HFD2_70C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/fbijxn
title: 5_HFD2_62C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/fpjyl4
title: 4_HFD1-46C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/fu1blu
title: 5_HFD2_49C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/gyaelm
title: 5_HFD2_64C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/iri5vn
title: 1_HFD0_61C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/kgutxy
title: 4_HFD1_43C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/khoqhd
title: 4_HFD1_52C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/ly0voe
title: 6_HFD4_69C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/mcz7f4
title: 6_HFD4_45C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/mdzwht
title: 1_HFD0_55C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/mjy49k
title: 3_HF2H_57C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/mwoxuv
title: Caecal_Metabolomic_DataMatrix.txt

description: :unav
DOI: 10.15454/xetxqu/nquvxr
title: Hypothalamic_data.tab

description: :unav
DOI: 10.15454/xetxqu/nsn6ly
title: 3_HF2H_58C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/oyvtwe
title: 5_HFD2_48C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/paysuk
title: 3_HF2H_56C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/pkn2mv
title: 1_HFD0_72C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/pxlo31
title: 6_HFD4_63C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/qi1d09
title: 6_HFD4_53C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/qpyzal
title: 1_HFD0_44C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/rajttu
title: 4_HFD1_75C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/tu6q7o
title: 4_HFD1_73C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/vogmea
title: 3_HF2H_65C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/wu6l5a
title: 3_HF2H_66C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/x58kd7
title: 6_HFD4_77C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/xqmmwm
title: 3_HF2H_67C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/ye544n
title: 1_HFD0_81C.fastq.gz

description: :unav
DOI: 10.15454/xetxqu/yyqjbx
title: 5_HFD2_80C.fastq.gz

description: :unav
DOI: 10.15454/xfopl1/8dkdot
title: WOOD BASIC DENSITY FOR 125 TREE FOREST SPECIES FROM THE FRENCH FORESTS-2016-2017-data for BK PhD-Plant Ecology.tab

description: :unav
DOI: 10.15454/xftlv4/0vdtft
title: Buchi-NIRFlexN500_cm-1_reflectance_spectra_transfer_validation_set.tabular

description: BUCHI N500 spectrometer gave reflectance spectra in wave numbers, with a range of 4000 to 10000 cm-1 and a resolution of 4 cm-1. Each spectrum was an average of 96 spectral readings of the same cup or vial. Samples were poured either into 10 cm diameter cups (about 30g) or into 1.3 cm diameter vials (about 3g) and spectra were acquired in triplicate and then averaged.
DOI: 10.15454/xftlv4/5p9sif
title: Buchi-NIRFlexN500_cm-1_reflectance_spectra_transfer_set.tabular

description: BUCHI N500 spectrometer gave reflectance spectra in wave numbers, with a range of 4000 to 10000 cm-1 and a resolution of 4 cm-1. Each spectrum was an average of 96 spectral readings of the same cup or vial. Samples were poured either into 10 cm diameter cups (about 30g) or into 1.3 cm diameter vials (about 3g) and spectra were acquired in triplicate and then averaged.
DOI: 10.15454/xftlv4/89ftmc
title: Appendix_3_list_of_organic_sample_names_of_spectra_transfer_validation_set.tab

description: A set of 11 sorghums and 24 miscanthus samples, listed in Appendix 3, was selected to validate transfer models and estimate the quality of these transfers. A : available NA : non available
DOI: 10.15454/xftlv4/bzz8ds
title: ChemFlow_history_spectra_transfer_model_from_FOSS_to_BUCHI.tar.gz

description: This folder contains all files from the ChemFlow history of the transfer function creation from FOSS to BUCHI spectra: • Raw spectra of model set and validation set, named by “Raw...”. • Other files corresponding to output files from the transfer model workflow: sorting samples, unit conversion, absorbance/reflectance conversion. • PDF output files corresponding to spectra plots of raw or transferred BUCHI and FOSS spectra.
DOI: 10.15454/xftlv4/eyis74
title: ChemFlow_history_spectra_transfer_model_from_BUCHI_to_FOSS.tar.gz

description: This folder contains all files from the ChemFlow history of the transfer function creation from BUCHI to FOSS spectra: • Raw spectra of model set and validation set, named by “Raw...”. • Other files corresponding to output files from the transfer model workflow: sorting samples, unit conversion, absorbance/reflectance conversion. • PDF output files corresponding to spectra plots of raw or transferred BUCHI and FOSS spectra.
DOI: 10.15454/xftlv4/gcn0yx
title: ChemFlow_history_spectra_transfer_model_from_BUCHI_to_ANTARIS.tar.gz

description: These folders contain all files from the ChemFlow histories of the transfer function creations: • Raw spectra of model set and validation set, named by “Raw...”. • Other files corresponding to output files from the transfer model workflow: sorting samples, unit conversion, absorbance/reflectance conversion. • PDF output files corresponding to spectra plots of raw or transferred spectra.
DOI: 10.15454/xftlv4/gcpq0z
title: Appendix_1_list_of_organic_sample_names_of_spectra_transfer_set.tab

description: A set of 92 organic samples was selected to cover a large range of variation for cell wall composition to promote a wide range of spectra, in order to create spectra transfer models. A : available NA : non available
DOI: 10.15454/xftlv4/gtai4h
title: ThermoScientific-ANTARIS-II_cm-1_absorbance_spectra_transfer_set.tabular

description: ThermoScientific ANTARIS II spectrometer gave absorbance spectra in wave numbers with a range of 4000 to 10001 cm-1 and a resolution of 3.86 cm-1. Samples were divided into 10 subsamples (aliquots) and poured into 0.8 cm diameter vials (about 2ml) which was scanned once. For each subsample, an average (spectrum) of 64 spectra were recorded.
DOI: 10.15454/xftlv4/i6rpty
title: ChemFlow_history_spectra_transfer_model_from_FOSS_to_ANTARIS.tar.gz

description: These folders contain all files from the ChemFlow histories of the transfer function creations: • Raw spectra of model set and validation set, named by “Raw...”. • Other files corresponding to output files from the transfer model workflow: sorting samples, unit conversion, absorbance/reflectance conversion. • PDF output files corresponding to spectra plots of raw or transferred spectra.
DOI: 10.15454/xftlv4/jjg1c5
title: FOSS-NIRSystem5000_nm_absorbance_spectra_transfer_set.tabular

description: FOSS spectrometer NIRSystem5000 gave absorbance spectra in wavelength with a range of 1100 to 2498 nm and a resolution of 2 nm. Each spectrum was an average of 32 spectral readings of the same cup. Samples were poured into 3.5 cm diameter cups (about 4g) and spectra were acquired in duplicate and automatically averaged.
DOI: 10.15454/xftlv4/rodxbv
title: ChemFlow_history_spectra_transfer_model_from_ANTARIS_to_BUCHI.tar.gz

description: These folders contain all files from the ChemFlow histories of the transfer function creations: • Raw spectra of model set and validation set, named by “Raw...”. • Other files corresponding to output files from the transfer model workflow: sorting samples, unit conversion, absorbance/reflectance conversion. • PDF output files corresponding to spectra plots of raw or transferred spectra.