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EcoSIS Fresh-leaf CABO spectra from herbarium project (reflectance)

ecosis · NIR

EcoSIS Fresh-leaf CABO spectra from herbarium project (reflectance). v2.0 standardized NIRS package: 1 spectral source(s), 50 declared target(s). Auto-generated from dataset_card.json (verify before publication).

nirv2ecosis
609
samples
2,001
wavelengths
1
sources
50
targets
27
metadata
NIR
family

Dataset property explorer

Mean profile risk0.47
Highest axisArtefacts locaux · 1.00
Diagnostics8
Sources profiled1
EcoSIS Fresh-leaf CABO spectra from herbarium project (reflectance) property profile0.250.50.751integritynoiseartefactsbaselinePCA outliersreferencerepeatabilitystructureEcoSIS Fresh-leaf CABO spectra from herbarium project (reflectance) profileintegrity: 0.00noise: 0.00artefacts: 1.00baseline: 0.55PCA outliers: 0.59reference: 0.62repeatability: 0.00structure: 0.98EcoSIS Fresh-le…0 center · 1 outer ring · outward = stronger anomaly / heterogeneity signal

Profile axes

Intégrité0.00
Artefacts locaux1.00
Bruit0.00
Outliers PCA0.59
Distance à la référence0.62
Répétabilité0.00
Baseline / forme0.55
Structure multi-régimes0.98
Diagnostic hypotheses00.250.50.751hypothesis scoreSplice / raccord détecteursSplice / raccord détecteurs: 0.760.76Erreur interpolation / réécha…Erreur interpolation / rééchantillonnage: 0.630.63Signature VERA25-likeSignature VERA25-like: 0.580.58Erreur calibration / référenc…Erreur calibration / référence blanche: 0.530.53Spectre hors domaine valideSpectre hors domaine valide: 0.500.50Dataset multi-régimesDataset multi-régimes: 0.490.49Différence de sonde / géométr…Différence de sonde / géométrie: 0.470.47Fond différentFond différent: 0.460.46
DiagnosticScoreForceSignauxInterprétation probable
Splice / raccord détecteursX0.76forteSpike rate 1.00, Jump rate 1.00, SNR non dégradé 1.00Rupture aux jonctions de détecteurs, calibration locale ou sonde différente.
Erreur interpolation / rééchantillonnageX0.63moyenneSpike rate 1.00, Jump rate 1.00, SNR normal/élevé 1.00Artefacts numériques ou traitement spectral incorrect.
Signature VERA25-likeX0.58moyenneSpike rate 1.00, Jump rate 1.00, RMS/SAM référence 0.62Combinaison possible changement de sonde + splice, amplifiée par géométrie, fond ou calibration.
Erreur calibration / référence blancheX0.53moyenneartefacts locaux 1.00, RMS/SAM référence 0.62, Mahalanobis / T2 0.59Décalage systématique entre campagnes, instruments ou référence blanche.
Spectre hors domaine valideX0.50moyenneStructure PCA 0.98, RMS/SAM référence 0.62, Mahalanobis / T2 0.59Variété, espèce, lot ou condition différente mais physiquement plausible.
Dataset multi-régimesX0.49moyenneStructure PCA 0.98, RMS/SAM référence 0.62, Mahalanobis / T2 0.59Mélange de campagnes, opérateurs, lots, setups ou sous-populations spectrales.
Différence de sonde / géométrieX0.47moyenneRMS/SAM référence 0.62, Mahalanobis / T2 0.59, Baseline/mean/area 0.55Modification de l'illumination, collecte, angle ou distance sonde-échantillon.
Fond différentX0.46moyenneRMS/SAM référence 0.62, Mahalanobis / T2 0.59, Baseline/mean/area 0.55Effet systématique du support, blanc/noir, transflectance ou environnement de mesure.

Spectral sources

fresh_spec_avg.csv

X · NIR · Spectra Vista Corporation HR-1024i
fresh_spec_avg.csv spectra0.00.20.40.605001,0001,5002,0002,500q05-q95 envelopeq25-q75 envelopemedian spectrummedianq25–q75q05–q95wavelength / nm400nm — median 0.03974 (q25–q75 0.03635–0.04394)414nm — median 0.04031 (q25–q75 0.03664–0.04469)429nm — median 0.04185 (q25–q75 0.03826–0.04748)443nm — median 0.04282 (q25–q75 0.0391–0.05056)458nm — median 0.0438 (q25–q75 0.03986–0.05293)472nm — median 0.04384 (q25–q75 0.03994–0.05353)486nm — median 0.04403 (q25–q75 0.04004–0.05406)501nm — median 0.04676 (q25–q75 0.04212–0.05763)515nm — median 0.06158 (q25–q75 0.05305–0.07472)529nm — median 0.09583 (q25–q75 0.07992–0.1126)544nm — median 0.1122 (q25–q75 0.09358–0.1322)558nm — median 0.1132 (q25–q75 0.09415–0.1346)573nm — median 0.09042 (q25–q75 0.0747–0.1113)587nm — median 0.07493 (q25–q75 0.06143–0.09451)601nm — median 0.06975 (q25–q75 0.0573–0.08802)616nm — median 0.06099 (q25–q75 0.05123–0.07696)630nm — median 0.05701 (q25–q75 0.04857–0.0717)645nm — median 0.05075 (q25–q75 0.04452–0.06425)659nm — median 0.04692 (q25–q75 0.0416–0.05798)673nm — median 0.04594 (q25–q75 0.04134–0.05479)688nm — median 0.05363 (q25–q75 0.04779–0.06319)702nm — median 0.1296 (q25–q75 0.1087–0.1503)717nm — median 0.2755 (q25–q75 0.2541–0.2982)731nm — median 0.3863 (q25–q75 0.3711–0.4035)745nm — median 0.4417 (q25–q75 0.4289–0.4561)760nm — median 0.4594 (q25–q75 0.4447–0.4718)774nm — median 0.4613 (q25–q75 0.4465–0.474)788nm — median 0.4606 (q25–q75 0.4462–0.4738)803nm — median 0.4603 (q25–q75 0.4457–0.4735)817nm — median 0.4606 (q25–q75 0.4457–0.4733)832nm — median 0.461 (q25–q75 0.4459–0.4734)846nm — median 0.4613 (q25–q75 0.4465–0.4741)860nm — median 0.4616 (q25–q75 0.4471–0.4748)875nm — median 0.4617 (q25–q75 0.4473–0.475)889nm — median 0.4615 (q25–q75 0.4471–0.4749)904nm — median 0.4613 (q25–q75 0.4464–0.4744)918nm — median 0.4608 (q25–q75 0.446–0.4739)932nm — median 0.4596 (q25–q75 0.4449–0.4728)947nm — median 0.4571 (q25–q75 0.4425–0.4704)961nm — median 0.4533 (q25–q75 0.4387–0.4668)976nm — median 0.4518 (q25–q75 0.4375–0.4655)990nm — median 0.4512 (q25–q75 0.4374–0.4648)1,004nm — median 0.4506 (q25–q75 0.4368–0.4641)1,019nm — median 0.4526 (q25–q75 0.4388–0.4662)1,033nm — median 0.4545 (q25–q75 0.4412–0.4678)1,047nm — median 0.4556 (q25–q75 0.4426–0.4687)1,062nm — median 0.4563 (q25–q75 0.4434–0.4693)1,076nm — median 0.4563 (q25–q75 0.4434–0.4692)1,091nm — median 0.4558 (q25–q75 0.4431–0.4685)1,105nm — median 0.4547 (q25–q75 0.4421–0.4676)1,119nm — median 0.4534 (q25–q75 0.4411–0.4662)1,134nm — median 0.4492 (q25–q75 0.4367–0.4617)1,148nm — median 0.4403 (q25–q75 0.4263–0.4535)1,163nm — median 0.4338 (q25–q75 0.4193–0.4466)1,177nm — median 0.4316 (q25–q75 0.4168–0.4446)1,191nm — median 0.4301 (q25–q75 0.4152–0.443)1,206nm — median 0.4301 (q25–q75 0.4152–0.4429)1,220nm — median 0.4314 (q25–q75 0.417–0.4443)1,235nm — median 0.4335 (q25–q75 0.4192–0.446)1,249nm — median 0.4343 (q25–q75 0.4205–0.4471)1,263nm — median 0.4343 (q25–q75 0.4206–0.447)1,278nm — median 0.4336 (q25–q75 0.4202–0.4464)1,292nm — median 0.4317 (q25–q75 0.418–0.4444)1,306nm — median 0.4281 (q25–q75 0.4138–0.4406)1,321nm — median 0.4199 (q25–q75 0.4057–0.4334)1,335nm — median 0.4094 (q25–q75 0.3941–0.423)1,350nm — median 0.3967 (q25–q75 0.3806–0.4109)1,364nm — median 0.3847 (q25–q75 0.3681–0.3991)1,378nm — median 0.3624 (q25–q75 0.3437–0.378)1,393nm — median 0.3042 (q25–q75 0.2819–0.3233)1,407nm — median 0.2376 (q25–q75 0.213–0.2583)1,422nm — median 0.2002 (q25–q75 0.1754–0.2221)1,436nm — median 0.1869 (q25–q75 0.1631–0.2091)1,450nm — median 0.186 (q25–q75 0.1622–0.209)1,465nm — median 0.1926 (q25–q75 0.1688–0.216)1,479nm — median 0.205 (q25–q75 0.1807–0.2287)1,494nm — median 0.2231 (q25–q75 0.1981–0.2466)1,508nm — median 0.2411 (q25–q75 0.2166–0.2642)1,522nm — median 0.2579 (q25–q75 0.2337–0.2801)1,537nm — median 0.2744 (q25–q75 0.2498–0.2947)1,551nm — median 0.2865 (q25–q75 0.2633–0.3061)1,565nm — median 0.2969 (q25–q75 0.2752–0.3157)1,580nm — median 0.3065 (q25–q75 0.2856–0.3249)1,594nm — median 0.3139 (q25–q75 0.2932–0.3318)1,609nm — median 0.3206 (q25–q75 0.3003–0.3377)1,623nm — median 0.3258 (q25–q75 0.3062–0.3427)1,637nm — median 0.3289 (q25–q75 0.3104–0.3453)1,652nm — median 0.3302 (q25–q75 0.3122–0.3466)1,666nm — median 0.3297 (q25–q75 0.312–0.3467)1,681nm — median 0.328 (q25–q75 0.3101–0.3443)1,695nm — median 0.324 (q25–q75 0.3063–0.3402)1,709nm — median 0.3186 (q25–q75 0.3009–0.3349)1,724nm — median 0.3128 (q25–q75 0.2946–0.3294)1,738nm — median 0.3076 (q25–q75 0.2884–0.3242)1,753nm — median 0.3015 (q25–q75 0.2827–0.3186)1,767nm — median 0.2953 (q25–q75 0.2766–0.3131)1,781nm — median 0.2914 (q25–q75 0.2721–0.309)1,796nm — median 0.2898 (q25–q75 0.2706–0.3072)1,810nm — median 0.2898 (q25–q75 0.2709–0.3074)1,824nm — median 0.2903 (q25–q75 0.2711–0.3074)1,839nm — median 0.2876 (q25–q75 0.2681–0.3047)1,853nm — median 0.2748 (q25–q75 0.2548–0.2927)1,868nm — median 0.2373 (q25–q75 0.2172–0.257)1,882nm — median 0.174 (q25–q75 0.1516–0.1952)1,896nm — median 0.103 (q25–q75 0.08652–0.1188)1,911nm — median 0.06582 (q25–q75 0.05575–0.07799)1,925nm — median 0.05348 (q25–q75 0.04533–0.06356)1,940nm — median 0.05308 (q25–q75 0.04531–0.06291)1,954nm — median 0.0582 (q25–q75 0.04882–0.06937)1,968nm — median 0.06693 (q25–q75 0.05415–0.079)1,983nm — median 0.07759 (q25–q75 0.0616–0.0915)1,997nm — median 0.08769 (q25–q75 0.0695–0.1033)2,012nm — median 0.09922 (q25–q75 0.07926–0.1166)2,026nm — median 0.1096 (q25–q75 0.08864–0.1278)2,040nm — median 0.1187 (q25–q75 0.09775–0.1378)2,055nm — median 0.1279 (q25–q75 0.1067–0.1471)2,069nm — median 0.1358 (q25–q75 0.1142–0.1552)2,083nm — median 0.1422 (q25–q75 0.1215–0.162)2,098nm — median 0.1484 (q25–q75 0.1292–0.1687)2,112nm — median 0.154 (q25–q75 0.1357–0.1743)2,127nm — median 0.1598 (q25–q75 0.1413–0.1793)2,141nm — median 0.1636 (q25–q75 0.1462–0.1832)2,155nm — median 0.1678 (q25–q75 0.1507–0.1883)2,170nm — median 0.1718 (q25–q75 0.155–0.1929)2,184nm — median 0.1763 (q25–q75 0.159–0.1968)2,199nm — median 0.1796 (q25–q75 0.1629–0.2005)2,213nm — median 0.1818 (q25–q75 0.1649–0.202)2,227nm — median 0.1808 (q25–q75 0.1642–0.2009)2,242nm — median 0.177 (q25–q75 0.1602–0.1962)2,256nm — median 0.1704 (q25–q75 0.1528–0.1888)2,271nm — median 0.1611 (q25–q75 0.1427–0.1794)2,285nm — median 0.1531 (q25–q75 0.133–0.1706)2,299nm — median 0.1442 (q25–q75 0.1245–0.1626)2,314nm — median 0.1375 (q25–q75 0.1172–0.1552)2,328nm — median 0.1299 (q25–q75 0.1106–0.1493)2,342nm — median 0.1246 (q25–q75 0.1049–0.1435)2,357nm — median 0.1186 (q25–q75 0.09848–0.1367)2,371nm — median 0.1131 (q25–q75 0.09263–0.131)2,386nm — median 0.1062 (q25–q75 0.08561–0.1228)2,400nm — median 0.09825 (q25–q75 0.07859–0.1152)

Sampling

Wavelengths2,001
Axis range400–2,400 nm
Mean spacing1 nm
Griduniform
Observations609

Signal & quality

Value range-0.0282 – 0.552
Mean range0.0408 – 0.46
Mean level0.2594
Area519
PTP0.4196
Noise RMS1.2185e-05
SNR2.1e+04
SNR dB9e+01 dB
Dynamic range0.42
Smoothness0.0002445
Saturated0.0%
X-outliers287

Integrity & artefacts

NaN ratio0.00%
Inf count0
Zero ratio0.00%
Spike count35,031
Spike rate2.88%
Jump count50,139
Jump rate4.12%
Clip fraction0.00%

Shape & reference

Baseline slope-0.11639
Curvature RMS0.00023845
D1 RMS0.0016294
RMS to mean0.020573
RMS p950.049852
SAM to mean0.044476
SAM p950.12983
Affine offset p950.040237
Affine gain p95 Δ0.14532
Affine residual p950.031255
Xcorr lag p950

Outliers & repeatability

PCA Q p95/median3.7
Hotelling T2 p95/median4.7
Mahalanobis H p95/median2.2
Repeat groups0

Dimensionality (PCA)

Effective rank2.6
PCs → 95% var3
PCs → 99% var6
Top-10 cum. var99.8%
Computed metric scores 29worst 1.00
FamilleMétrique calculéeValeurScoreNiveauInterprétation datasetCauses typiquesCalcul / scoring
Intégrité des donnéesNaN ratiointegrity.nan_ratio0%0.00faibleSpectre completErreur acquisition/exportcount(isnan(X)) / X.sizealert = min(1, nan_ratio / 0.05)
Intégrité des donnéesInf countintegrity.inf_count00.00faibleNormalCalculs invalidescount(isinf(X))alert = min(1, inf_count / 1)
Intégrité des donnéesZero ratiointegrity.zero_ratio0%0.00faibleNormalExport, saturationcount(X == 0) / count(finite X)alert = min(1, zero_ratio / 0.05)
Amplitude globaleMean reflectanceamplitude.mean_reflectance0.259420.55moyenValeur atypique: Trop clair / fond visible ou Trop sombreFond, géométriemean(X finite)alert reuses baseline/shape drift because absolute reflectance ranges are technology-dependent
Amplitude globaleArea under curveamplitude.area_under_curve519.030.55moyenValeur atypique: Différence d'éclairement ou NormalDistance sondetrapezoid(mean_spectrum, spectral_axis)alert reuses baseline/shape drift because area scale depends on axis and units
Amplitude globalePeak-to-peak (PTP)amplitude.peak_to_peak0.41960.00faibleVariabilité forteSaturationmax(mean_spectrum) - min(mean_spectrum)alert increases when dynamic range is abnormally flat
Amplitude globaleVarianceamplitude.variance0.0229990.00faibleNormal ou hétérogèneMauvais contactvar(X finite)alert increases when variance/dynamic range is abnormally flat
BruitNoise RMSnoise.noise_rms1.2185e-050.00faibleStableLampe, détecteurmedian MAD(second derivative) * 1.4826 / sqrt(6)alert = noise_rms / signal_scale, saturated at 5%
BruitSNRnoise.snr212900.00faibleBon signalAcquisitionmean(abs(X)) / noise_rmsalert decreases with SNR dB; >=40 dB is treated as low alert
BruitBandwise SNRnoise.bandwise_snr_min130.790.00faibleZone fiableDétecteurmin(abs(mean_spectrum) / local second-derivative noise)alert decreases with worst-band SNR dB; >=35 dB is treated as low alert
Artefacts locauxSpike countartefacts.spike_count35,0311.00fortArtefactsCosmic rays, splicecount robust outliers in second derivativealert follows spike_rate, saturated at 1%
Artefacts locauxSpike rateartefacts.spike_rate2.88%1.00fortSpectre suspectInterpolationspike_count / (n_samples * (n_features - 2))alert = min(1, spike_rate / 0.01)
Artefacts locauxJump countartefacts.jump_count50,1391.00fortRaccord détecteurSplicecount robust outliers in first derivativealert follows jump_rate, saturated at 1%
Artefacts locauxJump rateartefacts.jump_rate4.12%1.00fortProblème spectralCalibrationjump_count / (n_samples * (n_features - 1))alert = min(1, jump_rate / 0.01)
Artefacts locauxClip fractionartefacts.clip_fraction0.000164%0.00faibleNormalDétecteur saturéfraction of finite cells equal to repeated min/max extremaalert = min(1, clip_fraction / 0.01)
Forme spectraleBaseline slopeshape.baseline_slope-0.116390.55moyenDériveÉclairementlinear slope of mean_spectrum over normalized axisalert = abs(slope / signal_scale), saturated at 0.5
Forme spectraleCurvature RMSshape.curvature_rms0.000238450.06faibleLisseFond, splicemedian RMS(second derivative per spectrum)alert = curvature_rms / signal_scale, saturated at 1%
Forme spectraleD1 RMSshape.d1_rms0.00162940.08faiblePlatBiologie ou artefactmedian RMS(first derivative per spectrum)alert = d1_rms / signal_scale, saturated at 5%
Outliers multivariésPCA Q (SPE)outliers.pca_q_ratio3.72980.47moyenSpectre atypiqueArtefact, mélangep95(Q/SPE residual) / median(Q/SPE residual)alert = min(1, pca_q_ratio / 8)
Outliers multivariésHotelling T²outliers.hotelling_t2_ratio4.71830.59moyenExtrême mais cohérentVariabilité naturellep95(Hotelling T2) / median(Hotelling T2)alert = min(1, hotelling_t2_ratio / 8)
Outliers multivariésMahalanobis Houtliers.mahalanobis_h_ratio2.17220.54moyenOutlier globalDomaine différentp95(sqrt(T2)) / median(sqrt(T2))alert = min(1, mahalanobis_h_ratio / 4)
Comparaison à référenceRMS to mean spectrumreference.rms_to_mean_spectrum_p950.0498520.48moyenSpectre différentDomain shiftp95 RMS distance to dataset mean spectrumalert = RMS_p95 / signal_scale, saturated at 25%
Comparaison à référenceSpectral Angle Mapper (SAM)reference.sam_to_mean_spectrum_p950.129830.37faibleSimilaireFond, géométriep95 spectral angle to dataset mean spectrumalert = min(1, SAM_p95 / 0.35 rad)
RépétabilitéRMS intra-IDrepeatability.rms_intra_id—0.00faibleStablePositionnementmedian RMS distance to repeated-sample centroidalert = RMS_intra_ID / signal_scale, saturated at 10%
RépétabilitéSAM intra-IDrepeatability.sam_intra_id—0.00faibleStableAcquisitionmedian SAM to repeated-sample centroidalert = min(1, SAM_intra_ID / 0.15 rad)
RépétabilitéCV intra-IDrepeatability.cv_intra_id—0.00faibleStableOpérateurmedian within-ID band CValert = min(1, CV_intra_ID / 0.25)
Structure du datasetPCA score densitystructure.pca_score_density5.09870.98fortSous-populationsLots différents1 / median kNN distance in PCA score spacealert follows density_cv/profile structure complexity, not raw density alone
Structure du datasetLocal Outlier Factor (LOF)structure.local_outlier_factor_p952.94410.97fortSpectre isoléCas raresp95 approximate LOF from PCA-score kNN distancesalert = min(1, max(0, LOF_p95 - 1) / 2)
Structure du datasetIsolation Forest scorestructure.isolation_forest_score_p950.586160.98fortSpectre atypiqueDiverses causesp95 IsolationForest anomaly score on PCA scoresalert follows structure complexity; raw score is implementation-dependent
X PCA score plot-4-2024-4-2024PC1 -0.3057 · PC2 -0.02388PC1 0.3307 · PC2 0.3237PC1 0.5743 · PC2 0.3463PC1 0.1858 · PC2 -0.0434PC1 0.7134 · PC2 0.02228PC1 0.9232 · PC2 0.1642PC1 0.9353 · PC2 0.5041PC1 0.1754 · PC2 -0.3213PC1 0.4781 · PC2 0.01593PC1 0.3125 · PC2 -0.1949PC1 0.3821 · PC2 -0.7845PC1 0.1322 · PC2 -0.136PC1 0.9133 · PC2 -0.4588PC1 0.197 · PC2 -0.2539PC1 0.111 · PC2 -0.1754PC1 0.3297 · PC2 -0.7308PC1 0.1385 · PC2 -0.2339PC1 0.2009 · PC2 -0.1141PC1 0.5132 · PC2 -0.6307PC1 0.7251 · PC2 -0.4703PC1 1.05 · PC2 -0.1799PC1 0.2261 · PC2 -0.4818PC1 0.9023 · PC2 -0.1822PC1 0.4351 · PC2 -0.1592PC1 -0.04139 · PC2 -0.3937PC1 -0.2136 · PC2 0.2742PC1 -0.6222 · PC2 -0.1072PC1 -0.5134 · PC2 0.02332PC1 -0.8443 · PC2 -0.226PC1 -0.6522 · PC2 -0.1333PC1 -0.5142 · PC2 -0.07305PC1 -0.6623 · PC2 0.09648PC1 -0.481 · PC2 -0.09427PC1 -0.3825 · PC2 0.002329PC1 -0.4704 · PC2 0.04329PC1 0.4261 · PC2 -0.2242PC1 1.402 · PC2 -0.4643PC1 0.5193 · PC2 -0.134PC1 0.4084 · PC2 -0.3853PC1 0.4475 · PC2 0.1508PC1 1.456 · PC2 -0.1197PC1 1.153 · PC2 -0.02101PC1 0.5672 · PC2 -0.0263PC1 1.202 · PC2 0.02707PC1 0.6941 · PC2 0.2795PC1 1.089 · PC2 0.1246PC1 1.324 · PC2 0.01563PC1 0.1671 · PC2 -0.08397PC1 0.3244 · PC2 -0.2PC1 0.5745 · PC2 -0.236PC1 0.4814 · PC2 -0.03378PC1 0.3648 · PC2 -0.6868PC1 1.176 · PC2 0.131PC1 0.9044 · PC2 0.2971PC1 0.5772 · PC2 0.2346PC1 0.6355 · PC2 0.2041PC1 0.6745 · PC2 0.3553PC1 0.8993 · PC2 0.3983PC1 0.5908 · PC2 0.2543PC1 0.2038 · PC2 -0.1155PC1 0.3195 · PC2 0.3993PC1 -0.3309 · PC2 0.2153PC1 0.5096 · PC2 0.2983PC1 0.8199 · PC2 -0.1616PC1 -0.07587 · PC2 -0.4506PC1 -0.4612 · PC2 -0.4475PC1 -0.716 · PC2 -0.4882PC1 -0.1203 · PC2 0.06324PC1 -0.3256 · PC2 -0.09035PC1 -0.5115 · PC2 0.0879PC1 -0.4547 · PC2 -0.017PC1 -0.5685 · PC2 -0.04289PC1 -0.3083 · PC2 -0.1138PC1 -0.6008 · PC2 -0.1305PC1 0.8212 · PC2 0.1216PC1 0.7467 · PC2 -0.0276PC1 0.8961 · PC2 0.06474PC1 1.427 · PC2 -0.06782PC1 0.7638 · PC2 0.5195PC1 0.644 · PC2 0.3032PC1 0.4879 · PC2 0.2456PC1 0.7931 · PC2 0.2956PC1 1.039 · PC2 -0.09406PC1 0.7294 · PC2 -0.1956PC1 0.8122 · PC2 0.2671PC1 1.02 · PC2 0.01123PC1 0.4622 · PC2 0.182PC1 0.1306 · PC2 0.346PC1 0.615 · PC2 -0.008705PC1 0.7114 · PC2 0.5297PC1 0.02846 · PC2 -0.04086PC1 0.7154 · PC2 0.1192PC1 0.745 · PC2 0.2934PC1 0.6307 · PC2 -0.1596PC1 0.02974 · PC2 -0.02692PC1 -0.6823 · PC2 0.03799PC1 0.3837 · PC2 0.05115PC1 0.2609 · PC2 0.2485PC1 -0.02503 · PC2 -0.006401PC1 -0.4793 · PC2 0.07226PC1 -1.01 · PC2 0.255PC1 -0.3296 · PC2 -0.0456PC1 -0.023 · PC2 0.102PC1 -0.1495 · PC2 0.1315PC1 0.2079 · PC2 -0.4502PC1 1.343 · PC2 0.07976PC1 0.449 · PC2 -0.267PC1 0.913 · PC2 -0.5112PC1 1.145 · PC2 -0.2115PC1 0.7575 · PC2 -0.3556PC1 -0.008328 · PC2 -0.6654PC1 0.9205 · PC2 -0.1827PC1 0.9045 · PC2 -0.1242PC1 1.052 · PC2 -0.1345PC1 0.5988 · PC2 -0.7139PC1 0.5348 · PC2 -0.4974PC1 0.1867 · PC2 -0.4665PC1 0.7047 · PC2 -0.5238PC1 0.9569 · PC2 -0.5585PC1 0.7122 · PC2 -0.4815PC1 0.6769 · PC2 -0.2859PC1 0.7476 · PC2 0.007664PC1 0.7069 · PC2 -0.00924PC1 1.312 · PC2 0.314PC1 1.229 · PC2 -0.2214PC1 0.6724 · PC2 0.1877PC1 0.6133 · PC2 -0.05389PC1 1.336 · PC2 -0.3012PC1 1.307 · PC2 -0.3464PC1 -1.022 · PC2 0.2384PC1 -0.7656 · PC2 0.1509PC1 -0.7311 · PC2 0.3045PC1 -0.5708 · PC2 0.2613PC1 -0.6754 · PC2 0.1901PC1 0.4897 · PC2 0.09039PC1 0.5178 · PC2 0.04182PC1 -0.2383 · PC2 0.2954PC1 0.63 · PC2 -0.06747PC1 0.517 · PC2 0.4937PC1 -0.2349 · PC2 0.04655PC1 0.1733 · PC2 0.06707PC1 0.007979 · PC2 0.2861PC1 0.3586 · PC2 -0.1831PC1 0.09661 · PC2 0.2448PC1 -0.08815 · PC2 -0.6436PC1 0.306 · PC2 -0.5963PC1 -0.1426 · PC2 -0.5433PC1 -0.4098 · PC2 -0.2679PC1 0.4889 · PC2 -0.6269PC1 0.06631 · PC2 -0.4486PC1 0.2992 · PC2 -0.7978PC1 0.4979 · PC2 -0.9755PC1 -0.1135 · PC2 -0.487PC1 -0.1933 · PC2 -0.6914PC1 -0.6109 · PC2 -0.2159PC1 0.6565 · PC2 -0.005819PC1 0.1339 · PC2 0.1189PC1 -0.5981 · PC2 0.3548PC1 0.02499 · PC2 -0.0857PC1 0.2105 · PC2 0.4695PC1 0.2465 · PC2 0.5961PC1 0.2147 · PC2 0.02886PC1 0.1127 · PC2 0.5949PC1 0.2886 · PC2 0.2784PC1 -0.825 · PC2 0.1548PC1 -0.804 · PC2 -0.1001PC1 -0.6246 · PC2 0.07947PC1 -1.13 · PC2 0.1794PC1 -0.8725 · PC2 0.1587PC1 -0.8919 · PC2 0.2092PC1 -0.2682 · PC2 0.2461PC1 -0.5674 · PC2 0.06168PC1 -0.2324 · PC2 0.2825PC1 -0.4541 · PC2 -0.1953PC1 -0.7708 · PC2 -0.7441PC1 -0.5949 · PC2 -0.6793PC1 -0.6245 · PC2 -0.5939PC1 -0.9687 · PC2 -0.4534PC1 -0.475 · PC2 -0.4225PC1 -0.8911 · PC2 -0.3613PC1 -0.3881 · PC2 -0.5514PC1 -0.8497 · PC2 -0.543PC1 -0.2535 · PC2 -0.3227PC1 -0.4715 · PC2 -0.5859PC1 0.2256 · PC2 0.02635PC1 -0.04175 · PC2 0.05995PC1 0.06236 · PC2 0.5141PC1 0.13 · PC2 0.406PC1 -0.05704 · PC2 0.08984PC1 -0.1361 · PC2 0.6298PC1 0.2525 · PC2 0.5341PC1 0.2277 · PC2 0.2313PC1 -0.06676 · PC2 0.4925PC1 -0.02639 · PC2 0.1446PC1 0.4234 · PC2 -0.2834PC1 1.444 · PC2 -0.5691PC1 0.8727 · PC2 -0.1614PC1 1.525 · PC2 -0.5826PC1 0.636 · PC2 -0.3522PC1 0.8888 · PC2 -0.6784PC1 1.12 · PC2 -0.001302PC1 0.7383 · PC2 0.06781PC1 0.5046 · PC2 -0.03586PC1 1.094 · PC2 0.3608PC1 -0.3047 · PC2 -0.09282PC1 -0.1877 · PC2 -0.07406PC1 0.03689 · PC2 0.4209PC1 -0.2269 · PC2 0.05646PC1 0.1039 · PC2 0.06069PC1 -0.08371 · PC2 0.1337PC1 0.1371 · PC2 0.4034PC1 0.1059 · PC2 0.147PC1 0.3903 · PC2 0.2219PC1 0.004764 · PC2 0.07994PC1 -0.5115 · PC2 -0.3186PC1 -0.7753 · PC2 -0.1721PC1 0.2138 · PC2 -0.2482PC1 0.292 · PC2 -0.2186PC1 -0.2748 · PC2 -0.3201PC1 -0.2538 · PC2 -0.2735PC1 0.001584 · PC2 0.02045PC1 -0.3905 · PC2 -0.6565PC1 -0.4638 · PC2 -0.4246PC1 -0.3594 · PC2 -0.6042PC1 0.5059 · PC2 -0.4564PC1 1.277 · PC2 -0.143PC1 1.28 · PC2 -0.02066PC1 1.236 · PC2 0.4122PC1 1.19 · PC2 -0.1908PC1 1.059 · PC2 -0.4282PC1 0.8883 · PC2 -0.4647PC1 1.106 · PC2 -0.2575PC1 1.306 · PC2 -0.3919PC1 1.161 · PC2 -0.1955PC1 -0.8715 · PC2 -0.3305PC1 -0.7123 · PC2 -0.1432PC1 -0.1699 · PC2 0.1108PC1 0.9203 · PC2 -0.0453PC1 -0.721 · PC2 0.3251PC1 0.9668 · PC2 -0.2273PC1 0.6066 · PC2 -0.1177PC1 0.6791 · PC2 -0.1658PC1 1.213 · PC2 -0.2879PC1 0.848 · PC2 -0.2127PC1 0.9371 · PC2 -0.115PC1 1.152 · PC2 -0.03108PC1 1.177 · PC2 0.073PC1 0.7218 · PC2 -0.149PC1 1.622 · PC2 0.5112PC1 -0.2616 · PC2 -0.04366PC1 -0.1675 · PC2 0.1203PC1 -0.6919 · PC2 -0.1768PC1 -0.3448 · PC2 0.1213PC1 0.1947 · PC2 -0.1116PC1 -0.5324 · PC2 -0.1638PC1 0.04199 · PC2 -0.2667PC1 -0.07478 · PC2 -0.05955PC1 0.5918 · PC2 -0.2498PC1 1.545 · PC2 -0.313PC1 0.141 · PC2 -0.2896PC1 -0.1068 · PC2 -0.4891PC1 0.9024 · PC2 -0.3386PC1 -0.02674 · PC2 -0.3983PC1 0.3683 · PC2 -0.3884PC1 1.584 · PC2 -1.153PC1 1.66 · PC2 -0.5219PC1 1.452 · PC2 -0.5807PC1 1.278 · PC2 -0.1675PC1 2.05 · PC2 -1.308PC1 0.6367 · PC2 0.5983PC1 0.8823 · PC2 0.8604PC1 0.6411 · PC2 0.2611PC1 0.9089 · PC2 0.8103PC1 0.4248 · PC2 0.7093PC1 0.575 · PC2 0.9798PC1 0.46 · PC2 0.4636PC1 0.0753 · PC2 0.381PC1 0.4079 · PC2 0.4229PC1 0.1796 · PC2 0.2616PC1 1.593 · PC2 -0.3223PC1 1.656 · PC2 -0.5351PC1 1.27 · PC2 -0.6236PC1 1.8 · PC2 -0.5896PC1 1.656 · PC2 -0.7643PC1 0.2343 · PC2 0.2117PC1 0.4488 · PC2 0.7541PC1 0.1639 · PC2 -0.203PC1 -0.1158 · PC2 0.1095PC1 0.2046 · PC2 0.2474PC1 0.4704 · PC2 -0.03393PC1 0.6261 · PC2 0.3522PC1 0.4651 · PC2 -0.03964PC1 0.4616 · PC2 -0.265PC1 0.4297 · PC2 -0.02564PC1 0.4728 · PC2 1.272PC1 0.801 · PC2 0.3965PC1 1.305 · PC2 0.2327PC1 0.6694 · PC2 0.6783PC1 0.7391 · PC2 0.4169PC1 0.9077 · PC2 0.2284PC1 1.013 · PC2 0.4897PC1 0.9013 · PC2 0.2215PC1 0.6609 · PC2 0.3586PC1 0.7372 · PC2 0.9466PC1 0.2309 · PC2 0.05029PC1 -0.8469 · PC2 0.1231PC1 -0.3124 · PC2 0.03765PC1 -0.2892 · PC2 0.1462PC1 0.3852 · PC2 0.3053PC1 -1.049 · PC2 0.04475PC1 -0.2816 · PC2 0.1238PC1 -0.4929 · PC2 0.3301PC1 -0.8404 · PC2 0.1112PC1 0.318 · PC2 0.3392PC1 0.5504 · PC2 0.2295PC1 0.4743 · PC2 0.2983PC1 0.6748 · PC2 -0.1456PC1 0.635 · PC2 0.2112PC1 0.5801 · PC2 -0.3561PC1 0.8845 · PC2 0.05196PC1 0.9448 · PC2 -0.2785PC1 0.8849 · PC2 0.1381PC1 0.3746 · PC2 0.08644PC1 0.7247 · PC2 -0.06978PC1 -0.6176 · PC2 0.3232PC1 -0.3113 · PC2 0.02514PC1 -0.4611 · PC2 0.2579PC1 -0.1947 · PC2 0.2269PC1 -0.1841 · PC2 0.2218PC1 -0.3861 · PC2 0.1904PC1 -0.5591 · PC2 0.02765PC1 -0.3 · PC2 0.0327PC1 -0.3214 · PC2 0.162PC1 -0.5348 · PC2 0.04338PC1 -0.2943 · PC2 -0.03516PC1 -0.8028 · PC2 0.07512PC1 -0.4301 · PC2 -0.3351PC1 -0.1077 · PC2 0.3363PC1 -0.5576 · PC2 -0.1942PC1 0.3944 · PC2 -0.1193PC1 -0.01714 · PC2 0.373PC1 -0.1868 · PC2 0.1962PC1 -0.9985 · PC2 -0.007326PC1 -0.3422 · PC2 -0.1497PC1 0.977 · PC2 -0.1078PC1 0.9921 · PC2 -0.3487PC1 0.9248 · PC2 0.0436PC1 0.9146 · PC2 -0.4719PC1 1.423 · PC2 0.3063PC1 0.7714 · PC2 -0.4236PC1 1.499 · PC2 -0.7204PC1 1.134 · PC2 -0.7661PC1 1.177 · PC2 -0.8378PC1 1.027 · PC2 -0.456PC1 1.039 · PC2 0.07436PC1 0.7252 · PC2 0.04968PC1 0.4799 · PC2 0.1301PC1 0.8798 · PC2 -0.1902PC1 0.927 · PC2 -0.487PC1 -0.7956 · PC2 -0.05805PC1 -0.8061 · PC2 0.2234PC1 -0.6841 · PC2 -0.02268PC1 -0.1455 · PC2 0.1357PC1 -0.5947 · PC2 0.4031PC1 0.8263 · PC2 -0.6188PC1 1.229 · PC2 -1.503PC1 0.7725 · PC2 -0.2185PC1 0.8889 · PC2 -0.3238PC1 1.087 · PC2 -0.8189PC1 0.4079 · PC2 -0.2051PC1 1.605 · PC2 0.4979PC1 0.9401 · PC2 0.1499PC1 1.393 · PC2 -0.1622PC1 0.9851 · PC2 -0.07278PC1 1.477 · PC2 -0.1889PC1 0.9948 · PC2 0.006161PC1 0.8905 · PC2 0.1421PC1 1.659 · PC2 -0.5284PC1 1.262 · PC2 -0.2797PC1 -0.3981 · PC2 -0.034PC1 -0.362 · PC2 0.08328PC1 -0.3987 · PC2 0.01311PC1 -0.3616 · PC2 0.3069PC1 -0.6572 · PC2 0.2607PC1 1.586 · PC2 -0.03137PC1 1.024 · PC2 0.1162PC1 1.068 · PC2 -0.215PC1 1.582 · PC2 -0.4701PC1 1.186 · PC2 -0.1434PC1 -0.6156 · PC2 0.0943PC1 -0.7236 · PC2 0.2644PC1 -0.6616 · PC2 0.1519PC1 -0.1667 · PC2 0.1681PC1 -0.5315 · PC2 0.4607PC1 -1.172 · PC2 0.1497PC1 1.048 · PC2 1.608PC1 1.811 · PC2 -0.08273PC1 1.984 · PC2 0.3238PC1 0.8963 · PC2 0.7891PC1 -0.7586 · PC2 -0.3398PC1 -0.1022 · PC2 0.8136PC1 -0.5292 · PC2 1.596PC1 -0.7188 · PC2 -0.3932PC1 -0.3047 · PC2 0.9738PC1 0.6873 · PC2 0.7917PC1 0.8763 · PC2 0.4345PC1 2.588 · PC2 0.8938PC1 2.36 · PC2 0.9085PC1 0.03931 · PC2 1.005PC1 -0.4458 · PC2 0.3783PC1 0.444 · PC2 0.4302PC1 1.467 · PC2 1.368PC1 0.2575 · PC2 0.9612PC1 0.4105 · PC2 1.399PC1 -0.5931 · PC2 -0.2076PC1 0.6932 · PC2 2.005PC1 1.22 · PC2 1.837PC1 -0.8385 · PC2 -0.4248PC1 0.3672 · PC2 0.5476PC1 0.7447 · PC2 0.7262PC1 -3.184 · PC2 -1.211PC1 -2.516 · PC2 -0.6248PC1 -1.573 · PC2 -0.3847PC1 -2.301 · PC2 -0.9917PC1 -2.335 · PC2 -0.8434PC1 -2.575 · PC2 -1.028PC1 -2.114 · PC2 -1.725PC1 -1.691 · PC2 -1.392PC1 2.398 · PC2 0.5509PC1 0.1844 · PC2 0.3993PC1 0.5255 · PC2 0.8456PC1 -1.535 · PC2 -1.474PC1 -0.6079 · PC2 -0.4059PC1 0.2316 · PC2 0.7467PC1 0.14 · PC2 1.434PC1 0.3899 · PC2 0.8472PC1 -0.4404 · PC2 0.4437PC1 -0.4337 · PC2 0.5271PC1 -0.0724 · PC2 0.528PC1 0.7108 · PC2 0.5082PC1 0.8821 · PC2 0.5995PC1 2.235 · PC2 0.1783PC1 0.7259 · PC2 1.848PC1 1.326 · PC2 0.7165PC1 2.306 · PC2 0.5367PC1 -1.341 · PC2 -1.159PC1 0.6886 · PC2 0.6907PC1 0.6421 · PC2 0.585PC1 0.08541 · PC2 0.3739PC1 -1.291 · PC2 -1.315PC1 1.78 · PC2 0.103PC1 1.509 · PC2 -0.9523PC1 -0.03429 · PC2 0.5843PC1 -0.1612 · PC2 0.8652PC1 -2.131 · PC2 -1.651PC1 0.02269 · PC2 0.598PC1 -0.2786 · PC2 0.9212PC1 -0.02994 · PC2 0.01271PC1 -0.6151 · PC2 0.6097PC1 0.5007 · PC2 0.2211PC1 -0.0603 · PC2 0.336PC1 0.5266 · PC2 0.3178PC1 0.6566 · PC2 0.4625PC1 -0.4739 · PC2 -0.7751PC1 0.1809 · PC2 0.6919PC1 2.093 · PC2 0.5897PC1 0.1596 · PC2 0.07864PC1 -0.281 · PC2 -0.9798PC1 0.2253 · PC2 -0.4411PC1 -1.277 · PC2 -1.953PC1 -0.6105 · PC2 -0.4375PC1 -0.03046 · PC2 -0.637PC1 -1.991 · PC2 -1.636PC1 -1.689 · PC2 -2.145PC1 0.2558 · PC2 -0.3784PC1 -0.3933 · PC2 -1.7PC1 -1.698 · PC2 -1.844PC1 0.719 · PC2 -0.8798PC1 0.3747 · PC2 -0.3533PC1 -1.29 · PC2 0.02513PC1 -1.375 · PC2 -1.793PC1 -1.066 · PC2 -0.2248PC1 -0.3778 · PC2 0.009834PC1 -2.055 · PC2 -0.6228PC1 0.359 · PC2 0.322PC1 -0.916 · PC2 -0.4938PC1 -0.4583 · PC2 0.2963PC1 -1.641 · PC2 -0.6653PC1 -0.9158 · PC2 -0.5183PC1 -1.369 · PC2 -0.8268PC1 -0.1696 · PC2 -0.02576PC1 -1.141 · PC2 0.3447PC1 0.8405 · PC2 -0.4936PC1 1.442 · PC2 1.294PC1 -1.028 · PC2 -0.7072PC1 -0.5141 · PC2 -1.275PC1 -1.239 · PC2 0.3164PC1 -1.837 · PC2 0.4482PC1 1.615 · PC2 1.4PC1 0.5624 · PC2 0.246PC1 -0.1747 · PC2 -0.5327PC1 0.8881 · PC2 0.9124PC1 -0.4584 · PC2 -0.2839PC1 0.1424 · PC2 -0.4682PC1 1.013 · PC2 -1.077PC1 1.453 · PC2 -1.289PC1 -0.4095 · PC2 -0.649PC1 -0.2966 · PC2 -0.6963PC1 -0.3018 · PC2 -1.136PC1 0.7975 · PC2 -0.6108PC1 -0.6948 · PC2 -0.4801PC1 -1.072 · PC2 0.1777PC1 0.1394 · PC2 0.6246PC1 -1.782 · PC2 -0.3252PC1 -0.3786 · PC2 0.6296PC1 0.04665 · PC2 0.2549PC1 -0.08846 · PC2 0.2368PC1 -0.1238 · PC2 -0.3001PC1 0.1414 · PC2 0.07863PC1 -0.1752 · PC2 0.535PC1 -0.2658 · PC2 -0.4049PC1 1.046 · PC2 -1.168PC1 0.5251 · PC2 -0.3642PC1 0.4594 · PC2 -0.8391PC1 0.3034 · PC2 0.2763PC1 1.102 · PC2 -0.7531PC1 -0.2764 · PC2 -1.412PC1 0.2211 · PC2 -0.5241PC1 -0.3733 · PC2 -0.5846PC1 -1.166 · PC2 -0.5164PC1 0.02483 · PC2 -1.015PC1 -1.392 · PC2 0.3465PC1 -1.995 · PC2 0.3866PC1 -1.269 · PC2 0.4036PC1 -1.836 · PC2 0.2256PC1 -1.182 · PC2 0.3726PC1 -1.266 · PC2 0.205PC1 -2.031 · PC2 0.7558PC1 -0.2491 · PC2 1.151PC1 -1.653 · PC2 -0.02545PC1 -1.436 · PC2 0.09384PC1 -1.825 · PC2 0.6329PC1 -0.9263 · PC2 0.9342PC1 -0.7789 · PC2 1.618PC1 -1.803 · PC2 0.4728PC1 -1.84 · PC2 0.03532PC1 -2.139 · PC2 0.3376PC1 -2.292 · PC2 0.1752PC1 -1.387 · PC2 0.4883PC1 -1.051 · PC2 0.6355PC1 -1.648 · PC2 0.8156PC1 -1.725 · PC2 0.1982PC1 -0.9469 · PC2 0.3858PC1 -1.33 · PC2 0.1749PC1 -1.856 · PC2 0.2541PC1 -1.933 · PC2 0.5794PC1 -2.355 · PC2 0.09007PC1 -2.111 · PC2 0.1906PC1 -1.896 · PC2 0.1045PC1 -1.792 · PC2 -0.1106PC1 -1.042 · PC2 0.9817PC1 -1.637 · PC2 0.3046PC1 -2.087 · PC2 0.0941PC1 -1.457 · PC2 0.3033PC1 -1.537 · PC2 0.6716PC1 -2.058 · PC2 0.2313PC1 -1.411 · PC2 0.8809PC1 -1.969 · PC2 -0.01754PC1 -1.204 · PC2 0.751PC1 -2.192 · PC2 0.258PC1 -2.224 · PC2 0.08189PC1 -2.516 · PC2 0.1485PC1 -2.055 · PC2 0.2788PC1 -1.795 · PC2 0.3409PC1 -1.517 · PC2 0.2273PC1 -1.966 · PC2 -0.1407PC1 -1.919 · PC2 0.1212PC1 -1.939 · PC2 -0.2817PC1 -1.163 · PC2 0.908PC1 -2.287 · PC2 0.3273PC1 -2.913 · PC2 -0.5649PC1 -1.878 · PC2 0.6405PC1 -1.671 · PC2 0.2833PC1 -1.662 · PC2 0.2372PC1 -1.827 · PC2 0.8504PC1 -2.021 · PC2 0.5371PC1 -1.901 · PC2 0.5842PC1 -1.855 · PC2 0.9351PC1 -1.363 · PC2 0.8527PC1 -1.893 · PC2 0.8164PC1 -2.151 · PC2 0.5087PC1 -2.206 · PC2 0.6544PC1 -2.011 · PC2 0.6705PC1 -2.271 · PC2 0.714PC1 -1.5 · PC2 1.053PC1 -2.545 · PC2 0.5077PC1 -1.778 · PC2 1.188PC1 -2.404 · PC2 0.08132PC1 -2.327 · PC2 0.8867PC1 -0.1109 · PC2 0.09533PC1 -0.1592 · PC2 0.03729PC1 0.1581 · PC2 -0.1981PC1 -0.502 · PC2 -0.28PC1 0.269 · PC2 -0.4621PC1 1.966 · PC2 -0.891PC1 1.158 · PC2 -0.655PC1 1.052 · PC2 -0.2468PC1 1.214 · PC2 -0.368PC1 1.232 · PC2 -0.6884PC1 (69.4%)PC2 (20.1%)609 scores
PCA explained variance0%25%50%75%100%PC1: 69.4% (cumulative 69.4%)1PC2: 20.1% (cumulative 89.6%)2PC3: 6.9% (cumulative 96.5%)3PC4: 1.5% (cumulative 97.9%)4PC5: 0.7% (cumulative 98.6%)5PC6: 0.6% (cumulative 99.2%)6PC7: 0.3% (cumulative 99.5%)7PC8: 0.1% (cumulative 99.6%)8PC9: 0.1% (cumulative 99.7%)9PC10: 0.0% (cumulative 99.8%)10cumulative explained variancePC variancecumulativeprincipal component · cumulative (dashed)
X-Y spectral correlation 20
X · Discoloration spectral correlation-1-0.500.51absolute correlation envelopesigned correlationabsolute correlation05001,0001,5002,0002,500|r|signed raxis · Pearson correlation scale
X · SLA spectral correlation-1-0.500.51absolute correlation envelopesigned correlationabsolute correlation05001,0001,5002,0002,500|r|signed raxis · Pearson correlation scale
X · LDMC spectral correlation-1-0.500.51absolute correlation envelopesigned correlationabsolute correlation05001,0001,5002,0002,500|r|signed raxis · Pearson correlation scale
Targetmax |r|axis @ maxmean |r||r| ≥ .5
Discoloration0.2695000.1120.0%
SLA0.7252,3010.3540.9%
LDMC0.3432,2790.1230.0%
LMA0.8132,2700.42347.0%
EWT0.7971,4820.43349.4%
N0.47120.2080.0%
C0.3912,2910.1850.0%
NDF0.3164250.09330.0%
ADF0.2737160.0890.0%
ADL0.3687040.150.0%
solubles0.3164250.09330.0%
hemicellulose0.4314250.1780.0%
cellulose0.2345100.06890.0%
lignin0.3747030.1450.0%
chlA0.5352,2480.31623.8%
chlB0.5222,2600.31113.4%
car0.5712,2530.33131.1%
Al0.235120.1040.0%
Ca0.2534150.08440.0%
Cu0.3764000.140.0%

Metric interpretation reference

Metric catalog 29
FamilleMétriqueCe qu’elle détecteForte valeur =Faible valeur =Causes typiquesCalcul / score
Intégrité des donnéesNaN ratioDonnées manquantesSpectre corrompuSpectre completErreur acquisition/exportcount(isnan(X)) / X.sizealert = min(1, nan_ratio / 0.05)
Intégrité des donnéesInf countValeurs infiniesCorruptionNormalCalculs invalidescount(isinf(X))alert = min(1, inf_count / 1)
Intégrité des donnéesZero ratioColonnes ou cellules nullesSpectre tronquéNormalExport, saturationcount(X == 0) / count(finite X)alert = min(1, zero_ratio / 0.05)
Amplitude globaleMean reflectanceNiveau moyenTrop clair / fond visibleTrop sombreFond, géométriemean(X finite)alert reuses baseline/shape drift because absolute reflectance ranges are technology-dependent
Amplitude globaleArea under curveIntensité globaleDifférence d'éclairementNormalDistance sondetrapezoid(mean_spectrum, spectral_axis)alert reuses baseline/shape drift because area scale depends on axis and units
Amplitude globalePeak-to-peak (PTP)DynamiqueVariabilité forteSpectre platSaturationmax(mean_spectrum) - min(mean_spectrum)alert increases when dynamic range is abnormally flat
Amplitude globaleVarianceVariabilité spectraleNormal ou hétérogèneSpectre platMauvais contactvar(X finite)alert increases when variance/dynamic range is abnormally flat
BruitNoise RMSBruit haute fréquenceBruitéStableLampe, détecteurmedian MAD(second derivative) * 1.4826 / sqrt(6)alert = noise_rms / signal_scale, saturated at 5%
BruitSNRQualité signalBon signalMauvais signalAcquisitionmean(abs(X)) / noise_rmsalert decreases with SNR dB; >=40 dB is treated as low alert
BruitBandwise SNRBruit localiséZone fiableZone problématiqueDétecteurmin(abs(mean_spectrum) / local second-derivative noise)alert decreases with worst-band SNR dB; >=35 dB is treated as low alert
Artefacts locauxSpike countPics étroitsArtefactsSpectre propreCosmic rays, splicecount robust outliers in second derivativealert follows spike_rate, saturated at 1%
Artefacts locauxSpike rateDensité de picsSpectre suspectNormalInterpolationspike_count / (n_samples * (n_features - 2))alert = min(1, spike_rate / 0.01)
Artefacts locauxJump countDiscontinuitésRaccord détecteurContinuSplicecount robust outliers in first derivativealert follows jump_rate, saturated at 1%
Artefacts locauxJump rateFréquence de sautsProblème spectralNormalCalibrationjump_count / (n_samples * (n_features - 1))alert = min(1, jump_rate / 0.01)
Artefacts locauxClip fractionSaturationClippingNormalDétecteur saturéfraction of finite cells equal to repeated min/max extremaalert = min(1, clip_fraction / 0.01)
Forme spectraleBaseline slopePente globaleDériveStableÉclairementlinear slope of mean_spectrum over normalized axisalert = abs(slope / signal_scale), saturated at 0.5
Forme spectraleCurvature RMSCourbureForme inhabituelleLisseFond, splicemedian RMS(second derivative per spectrum)alert = curvature_rms / signal_scale, saturated at 1%
Forme spectraleD1 RMSVariabilité localeSpectre structuréPlatBiologie ou artefactmedian RMS(first derivative per spectrum)alert = d1_rms / signal_scale, saturated at 5%
Outliers multivariésPCA Q (SPE)Non expliqué par PCASpectre atypiqueConformeArtefact, mélangep95(Q/SPE residual) / median(Q/SPE residual)alert = min(1, pca_q_ratio / 8)
Outliers multivariésHotelling T²Extrême dans PCAExtrême mais cohérentCentralVariabilité naturellep95(Hotelling T2) / median(Hotelling T2)alert = min(1, hotelling_t2_ratio / 8)
Outliers multivariésMahalanobis HDistance au nuageOutlier globalPopulation normaleDomaine différentp95(sqrt(T2)) / median(sqrt(T2))alert = min(1, mahalanobis_h_ratio / 4)
Comparaison à référenceRMS to mean spectrumDistance moyenneSpectre différentTypiqueDomain shiftp95 RMS distance to dataset mean spectrumalert = RMS_p95 / signal_scale, saturated at 25%
Comparaison à référenceSpectral Angle Mapper (SAM)Différence de formeForme différenteSimilaireFond, géométriep95 spectral angle to dataset mean spectrumalert = min(1, SAM_p95 / 0.35 rad)
RépétabilitéRMS intra-IDReproductibilitéMauvaise répétabilitéStablePositionnementmedian RMS distance to repeated-sample centroidalert = RMS_intra_ID / signal_scale, saturated at 10%
RépétabilitéSAM intra-IDVariation de formeInstableStableAcquisitionmedian SAM to repeated-sample centroidalert = min(1, SAM_intra_ID / 0.15 rad)
RépétabilitéCV intra-IDVariabilité interneMauvais contrôleStableOpérateurmedian within-ID band CValert = min(1, CV_intra_ID / 0.25)
Structure du datasetPCA score densityClustersSous-populationsHomogèneLots différents1 / median kNN distance in PCA score spacealert follows density_cv/profile structure complexity, not raw density alone
Structure du datasetLocal Outlier Factor (LOF)Anomalie localeSpectre isoléPopulation normaleCas raresp95 approximate LOF from PCA-score kNN distancesalert = min(1, max(0, LOF_p95 - 1) / 2)
Structure du datasetIsolation Forest scoreAnomalie globaleSpectre atypiqueNormalDiverses causesp95 IsolationForest anomaly score on PCA scoresalert follows structure complexity; raw score is implementation-dependent
Technology-specific extensions
TechnologieAdaptations / métriquesAnomalies cibléesCommentaire pratique
UV-Vis 300-1000 nmBaseline, pente globale, dérive aux bords 300-350 et 900-1000; métriques par zonesLumière parasite, mauvais blanc, saturation, faible signal aux extrémitésLes bords sont souvent instables; calculer aussi des scores edge/middle.
UV-Vis 300-1000 nmSaturation / clipping proche absorbance max ou réflectance maxSignal écrêtéTrès important si absorption forte.
UV-Vis 300-1000 nmRed-edge, position de maximum, ratios de bandes si végétalDécalage biologique ou artefact optiqueAide à distinguer changement réel et problème d'acquisition.
UV-Vis 300-1000 nmSmoothness / roughness indexBruit haute fréquenceSouvent plus informatif que le SNR seul.
MIR / ATR-FTIRATR contact quality index: intensité globale, aire totale, profondeur des bandes clésMauvais contact cristal-échantillonCrucial: beaucoup d'anomalies viennent du contact ATR.
MIR / ATR-FTIRCO2 / H2O atmospheric bandsMauvaise correction atmosphériquePics parasites fréquents.
MIR / ATR-FTIRBaseline curvature / rubber-band residualDiffusion, contact, dérive baselineTrès utile avant PCA.
MIR / ATR-FTIRPeak position shiftMauvais alignement spectral / calibrationImportant en FTIR car de petits shifts comptent.
MIR / ATR-FTIRBand area ratios sur bandes connuesSpectre chimiquement incohérentÀ adapter par matrice: polysaccharides, protéines, lipides, etc.
HS-MSTotal Ion Current (TIC), Base Peak Intensity (BPI)Injection faible, ionisation instableÉquivalent MS du niveau global spectral.
HS-MSNombre de pics détectésSpectre pauvre ou trop bruitéTrop peu = mauvais signal; trop = bruit/contamination.
HS-MSMass accuracy / m/z driftProblème calibration masseFondamental en HRMS.
HS-MSRetention time drift si LC/GC-MSDérive chromatographiqueÀ suivre sur standards/QC pools.
HS-MSBlank contamination scoreContaminants / carry-overComparer échantillons vs blancs.
HS-MSInternal standard CVVariabilité instrumentaleTrès robuste si standards disponibles.
HS-MSMissingness par featureInstabilité de détectionCrucial pour filtrer les variables.
Avec répétitionsRMS intra-échantillonRépétabilité globaleApplicable à toutes les technologies.
Avec répétitionsSAM / corrélation intra-échantillonRépétabilité de formeTrès utile pour spectres.
Avec répétitionsCV intra-échantillon par bande / featureRépétabilité localeDétecte les zones instables.
Avec répétitionsICC ou variance componentsPart variance échantillon vs techniqueTrès utile si plusieurs répétitions par sample.
Avec répétitionsDistance au centroïde intra-IDRépétition aberrantePermet de flagger la mauvaise répétition plutôt que le sample entier.
Bug-hunting / supervised audits
Famille de bug potentielMéthodes à ajouterCe que ça détecteÉtat dans l’explorateur
Shift spectral globalCorrélation spectre moyen inter-dataset, DTW, cross-correlation, comparaison positions de picsDécalage en longueur d'onde, mauvais alignement, interpolation différentePartiellement calculé: cross-correlation lag et dispersion des positions de pics vs spectre moyen.
Baseline / offset / gainRégression chaque spectre vs spectre moyen: x = a + b ref + residual; suivi de a, b, RMS résiduelOffset additif, effet multiplicatif, dérive de baselineCalculé dans reference.affine_*.
Mélange de lignes / mauvais appariement X-M-YVérification index, hash des lignes, duplication ID, distance spectrale intra-ID, labels incohérentsLignes mélangées, metadata mal alignées, Y attribué au mauvais spectrePartiellement couvert par répétabilité intra-ID; checks index/hash à ajouter au pipeline canonical.
Fuite d'information / répétitions mal splitéesGroupKFold par sample_id vs StratifiedKFold random; audit des partitions par sample_idPerformance artificiellement bonne due aux répétitionsNécessite splits et benchmark modèle; non calculé par la carte descriptive.
Label bugsÉchantillons proches en X mais Y différents, confident learning, erreurs systématiques FP/FNY inversés, erreurs de saisie, classes ambiguësNécessite Y et/ou modèle; recommandé pour l'explorateur supervisé.
Sous-domaines cachésPCA/UMAP/t-SNE + clustering non supervisé + association avec dataset/Y/date/operatorLots, campagnes, sondes, backgrounds non renseignésPartiellement calculé par structure PCA/LOF; UMAP/t-SNE hors carte statique.
Artefacts localisés inconnusCarte wavelength x dataset: différence moyenne, différence variance, KS par longueur d'ondeRégions spectrales anormales non anticipéesÀ calculer au niveau banque quand plusieurs datasets partagent un axe spectral.
Ruptures instrumentalesDiscontinuités dans dérivées, changepoint detectionSplice, raccord détecteur, saut local non prévuCalculé par jump/spike rates; changepoint plus avancé à ajouter.
Mélange / contamination spectraleNMF / unmixing / reconstruction par convex hullComposante externe: fond, plastique, solNon calculé automatiquement; nécessite hypothèses de composants ou grande bibliothèque.
Features instables mais prédictivesImportance modèle vs instabilité QC par variableModèle qui apprend un artefact plutôt qu'un signal biologiqueNécessite modèle supervisé; recommandé pour rapports de benchmark.

Variables

Targets 50

Species

target · categorical
Species classesPopulus tremuloides MichauxPopulus tremuloides Michaux: 102102Betula populifolia MarshallBetula populifolia Marshall: 8484Acer rubrum LinnaeusAcer rubrum Linnaeus: 7272Agonis flexuosa (Willd.) SweetAgonis flexuosa (Willd.) Sweet: 6868Acer saccharum MarshallAcer saccharum Marshall: 4141Fagus grandifolia EhrhartFagus grandifolia Ehrhart: 2626Quercus rubra LinnaeusQuercus rubra Linnaeus: 2626Populus grandidentata MichauxPopulus grandidentata Michaux: 2121Acer saccharinum LinnaeusAcer saccharinum Linnaeus: 2121Betula papyrifera MarshallBetula papyrifera Marshall: 2020+10 more+10 more: 6868
n / missing609 / 0
Classes66
Balance (entropy)0.71
Imbalance ratio102
Top classPopulus tremuloides Michaux (102)

LatinGenus

target · categorical
LatinGenus classesAcerAcer: 137137PopulusPopulus: 126126BetulaBetula: 105105AgonisAgonis: 6868FagusFagus: 2626QuercusQuercus: 2626SolidagoSolidago: 1313RubusRubus: 1010CornusCornus: 1010PhragmitesPhragmites: 1010+10 more+10 more: 5151
n / missing609 / 0
Classes43
Balance (entropy)0.65
Imbalance ratio137
Top classAcer (137)

LatinSpecies

target · categorical
LatinSpecies classestremuloidestremuloides: 102102populifoliapopulifolia: 8484rubrumrubrum: 7272flexuosaflexuosa: 6868saccharumsaccharum: 4141grandifoliagrandifolia: 2626rubrarubra: 2626grandidentatagrandidentata: 2121saccharinumsaccharinum: 2121papyriferapapyrifera: 2020+10 more+10 more: 7171
n / missing609 / 0
Classes60
Balance (entropy)0.72
Imbalance ratio102
Top classtremuloides (102)

Discoloration

target · numeric
Discoloration distribution02004000 – 0.1667: 3910.1667 – 0.3333: 00.3333 – 0.5: 00.5 – 0.6667: 00.6667 – 0.8333: 00.8333 – 1: 01 – 1.167: 1471.167 – 1.333: 01.333 – 1.5: 01.5 – 1.667: 01.667 – 1.833: 01.833 – 2: 02 – 2.167: 522.167 – 2.333: 02.333 – 2.5: 02.5 – 2.667: 02.667 – 2.833: 02.833 – 3: 03 – 3.167: 143.167 – 3.333: 03.333 – 3.5: 03.5 – 3.667: 03.667 – 3.833: 03.833 – 4: 501234
n / missing609 / 0
Mean ± SD0.514 ± 0.811
Median0
Range0 – 4
CV1.58
Skew / kurtosis1.7 / 3
Normal?no

GrowthForm

target · categorical
GrowthForm classesbroadleafbroadleaf: 500500herbherb: 5757shrubshrub: 4646vinevine: 66
n / missing609 / 0
Classes4
Balance (entropy)0.45
Imbalance ratio8e+01
Top classbroadleaf (500)

SLA

target · numeric
SLA distribution0501001504.589 – 6.179: 446.179 – 7.769: 217.769 – 9.358: 59.358 – 10.95: 1510.95 – 12.54: 7612.54 – 14.13: 8214.13 – 15.72: 11815.72 – 17.31: 8617.31 – 18.9: 6318.9 – 20.49: 3220.49 – 22.08: 2222.08 – 23.67: 1323.67 – 25.26: 725.26 – 26.85: 526.85 – 28.44: 428.44 – 30.03: 030.03 – 31.62: 231.62 – 33.21: 133.21 – 34.8: 034.8 – 36.39: 236.39 – 37.98: 137.98 – 39.57: 239.57 – 41.16: 141.16 – 42.75: 201020304050
n / missing609 / 5
Mean ± SD15.04 ± 5.37
Median14.9
Range4.589 – 42.75
CV0.357
Skew / kurtosis1.1 / 4.7
Normal?no

LDMC

target · numeric
LDMC distribution050100154.8 – 172.2: 2172.2 – 189.6: 3189.6 – 207: 3207 – 224.5: 6224.5 – 241.9: 3241.9 – 259.3: 2259.3 – 276.7: 6276.7 – 294.2: 7294.2 – 311.6: 19311.6 – 329: 14329 – 346.4: 27346.4 – 363.9: 24363.9 – 381.3: 59381.3 – 398.7: 79398.7 – 416.1: 83416.1 – 433.6: 70433.6 – 451: 76451 – 468.4: 42468.4 – 485.8: 22485.8 – 503.3: 33503.3 – 520.7: 11520.7 – 538.1: 8538.1 – 555.5: 2555.5 – 573: 11002005001,000
n / missing609 / 7
Mean ± SD403.6 ± 64
Median407
Range154.8 – 573
CV0.159
Skew / kurtosis-0.86 / 1.7
Normal?no

LMA

target · numeric
LMA distribution0501001500.02339 – 0.0315: 90.0315 – 0.0396: 110.0396 – 0.04771: 320.04771 – 0.05582: 770.05582 – 0.06392: 1190.06392 – 0.07203: 1290.07203 – 0.08013: 720.08013 – 0.08824: 540.08824 – 0.09634: 240.09634 – 0.1044: 50.1044 – 0.1126: 30.1126 – 0.1207: 30.1207 – 0.1288: 10.1288 – 0.1369: 20.1369 – 0.145: 70.145 – 0.1531: 60.1531 – 0.1612: 60.1612 – 0.1693: 70.1693 – 0.1774: 100.1774 – 0.1855: 70.1855 – 0.1936: 90.1936 – 0.2017: 60.2017 – 0.2098: 20.2098 – 0.2179: 30.000.050.100.150.200.25
n / missing609 / 5
Mean ± SD0.07725 ± 0.0367
Median0.06709
Range0.02339 – 0.2179
CV0.474
Skew / kurtosis2 / 3.7
Normal?no

EWT

target · numeric
EWT distribution0501000.04878 – 0.05848: 70.05848 – 0.06818: 200.06818 – 0.07788: 450.07788 – 0.08758: 890.08758 – 0.09728: 840.09728 – 0.107: 930.107 – 0.1167: 940.1167 – 0.1264: 320.1264 – 0.1361: 210.1361 – 0.1458: 190.1458 – 0.1555: 200.1555 – 0.1652: 200.1652 – 0.1749: 200.1749 – 0.1846: 120.1846 – 0.1943: 50.1943 – 0.204: 70.204 – 0.2137: 40.2137 – 0.2234: 10.2234 – 0.2331: 30.2331 – 0.2428: 00.2428 – 0.2524: 10.2524 – 0.2621: 20.2621 – 0.2718: 00.2718 – 0.2815: 30.00.10.20.3
n / missing609 / 7
Mean ± SD0.1111 ± 0.0364
Median0.1043
Range0.04878 – 0.2815
CV0.328
Skew / kurtosis1.5 / 3.1
Normal?no

N

target · numeric
N distribution0501001500.8833 – 1.081: 141.081 – 1.278: 411.278 – 1.475: 281.475 – 1.672: 451.672 – 1.87: 601.87 – 2.067: 712.067 – 2.264: 1162.264 – 2.461: 842.461 – 2.659: 772.659 – 2.856: 382.856 – 3.053: 103.053 – 3.25: 33.25 – 3.448: 43.448 – 3.645: 63.645 – 3.842: 43.842 – 4.04: 34.04 – 4.237: 24.237 – 4.434: 04.434 – 4.631: 14.631 – 4.829: 04.829 – 5.026: 15.026 – 5.223: 05.223 – 5.42: 05.42 – 5.618: 10246
n / missing609 / 0
Mean ± SD2.119 ± 0.591
Median2.135
Range0.8833 – 5.618
CV0.279
Skew / kurtosis0.86 / 3.4
Normal?no

C

target · numeric
C distribution05010039.54 – 40.13: 140.13 – 40.71: 040.71 – 41.3: 141.3 – 41.88: 341.88 – 42.47: 442.47 – 43.05: 1043.05 – 43.64: 543.64 – 44.23: 1044.23 – 44.81: 944.81 – 45.4: 2445.4 – 45.98: 3345.98 – 46.57: 2546.57 – 47.16: 3147.16 – 47.74: 4847.74 – 48.33: 8948.33 – 48.91: 8848.91 – 49.5: 7649.5 – 50.09: 5550.09 – 50.67: 3550.67 – 51.26: 2251.26 – 51.84: 2551.84 – 52.43: 1152.43 – 53.01: 353.01 – 53.6: 1102050100
n / missing609 / 0
Mean ± SD48.15 ± 2.16
Median48.38
Range39.54 – 53.6
CV0.045
Skew / kurtosis-0.66 / 0.75
Normal?no

NDF

target · numeric
NDF distribution05010015011.05 – 13.16: 313.16 – 15.26: 815.26 – 17.36: 1117.36 – 19.46: 1919.46 – 21.56: 3121.56 – 23.66: 4023.66 – 25.76: 6225.76 – 27.86: 8427.86 – 29.96: 10429.96 – 32.06: 6832.06 – 34.16: 3234.16 – 36.26: 3936.26 – 38.36: 2438.36 – 40.47: 1040.47 – 42.57: 1542.57 – 44.67: 1744.67 – 46.77: 1046.77 – 48.87: 248.87 – 50.97: 550.97 – 53.07: 753.07 – 55.17: 355.17 – 57.27: 257.27 – 59.37: 359.37 – 61.47: 2020406080
n / missing609 / 8
Mean ± SD29.85 ± 8.12
Median28.7
Range11.05 – 61.47
CV0.272
Skew / kurtosis1 / 1.8
Normal?no

ADF

target · numeric
ADF distribution0501007.972 – 9.084: 59.084 – 10.2: 710.2 – 11.31: 611.31 – 12.42: 812.42 – 13.53: 2113.53 – 14.64: 2014.64 – 15.76: 3615.76 – 16.87: 6116.87 – 17.98: 6817.98 – 19.09: 8319.09 – 20.2: 5420.2 – 21.32: 5021.32 – 22.43: 4822.43 – 23.54: 2423.54 – 24.65: 3024.65 – 25.76: 2325.76 – 26.88: 1726.88 – 27.99: 927.99 – 29.1: 1429.1 – 30.21: 630.21 – 31.32: 231.32 – 32.44: 032.44 – 33.55: 233.55 – 34.66: 3010203040
n / missing609 / 12
Mean ± SD19.4 ± 4.44
Median18.76
Range7.972 – 34.66
CV0.229
Skew / kurtosis0.38 / 0.45
Normal?no

ADL

target · numeric
ADL distribution02550751.145 – 2.006: 52.006 – 2.866: 162.866 – 3.727: 233.727 – 4.587: 154.587 – 5.448: 275.448 – 6.309: 406.309 – 7.169: 467.169 – 8.03: 708.03 – 8.89: 578.89 – 9.751: 619.751 – 10.61: 5810.61 – 11.47: 5011.47 – 12.33: 3712.33 – 13.19: 2913.19 – 14.05: 2114.05 – 14.91: 1314.91 – 15.78: 1115.78 – 16.64: 216.64 – 17.5: 617.5 – 18.36: 218.36 – 19.22: 419.22 – 20.08: 020.08 – 20.94: 320.94 – 21.8: 10102030
n / missing609 / 12
Mean ± SD8.998 ± 3.45
Median8.887
Range1.145 – 21.8
CV0.383
Skew / kurtosis0.41 / 0.52
Normal?no

solubles

target · numeric
solubles distribution05010015038.53 – 40.63: 240.63 – 42.73: 342.73 – 44.83: 244.83 – 46.93: 346.93 – 49.03: 749.03 – 51.13: 551.13 – 53.23: 253.23 – 55.33: 1055.33 – 57.43: 1757.43 – 59.53: 1559.53 – 61.64: 1061.64 – 63.74: 2463.74 – 65.84: 3965.84 – 67.94: 3267.94 – 70.04: 6870.04 – 72.14: 10472.14 – 74.24: 8474.24 – 76.34: 6176.34 – 78.44: 4178.44 – 80.54: 3180.54 – 82.64: 1982.64 – 84.74: 1184.74 – 86.84: 886.84 – 88.95: 3102050100
n / missing609 / 8
Mean ± SD70.15 ± 8.12
Median71.3
Range38.53 – 88.95
CV0.116
Skew / kurtosis-1 / 1.8
Normal?no

hemicellulose

target · numeric
hemicellulose distribution0501001502.773 – 4.078: 64.078 – 5.384: 135.384 – 6.689: 626.689 – 7.994: 1097.994 – 9.299: 1229.299 – 10.6: 7310.6 – 11.91: 6011.91 – 13.21: 5113.21 – 14.52: 1614.52 – 15.82: 1515.82 – 17.13: 1517.13 – 18.44: 1718.44 – 19.74: 519.74 – 21.05: 721.05 – 22.35: 722.35 – 23.66: 123.66 – 24.96: 024.96 – 26.27: 426.27 – 27.57: 627.57 – 28.88: 128.88 – 30.18: 230.18 – 31.49: 131.49 – 32.79: 132.79 – 34.1: 3010203040
n / missing609 / 12
Mean ± SD10.49 ± 4.81
Median9.127
Range2.773 – 34.1
CV0.458
Skew / kurtosis2 / 5.3
Normal?no

cellulose

target · numeric
cellulose distribution0501005.19 – 6.048: 56.048 – 6.905: 176.905 – 7.763: 577.763 – 8.62: 948.62 – 9.477: 909.477 – 10.33: 9310.33 – 11.19: 7911.19 – 12.05: 4612.05 – 12.91: 3812.91 – 13.76: 2213.76 – 14.62: 1614.62 – 15.48: 915.48 – 16.34: 716.34 – 17.19: 417.19 – 18.05: 218.05 – 18.91: 118.91 – 19.77: 019.77 – 20.62: 120.62 – 21.48: 021.48 – 22.34: 122.34 – 23.2: 423.2 – 24.05: 424.05 – 24.91: 524.91 – 25.77: 20102030
n / missing609 / 12
Mean ± SD10.4 ± 3.14
Median9.78
Range5.19 – 25.77
CV0.302
Skew / kurtosis2.3 / 7.3
Normal?no

lignin

target · numeric
lignin distribution02550750.918 – 1.775: 61.775 – 2.631: 142.631 – 3.488: 203.488 – 4.344: 184.344 – 5.201: 295.201 – 6.057: 386.057 – 6.914: 506.914 – 7.77: 757.77 – 8.626: 528.626 – 9.483: 649.483 – 10.34: 5910.34 – 11.2: 5211.2 – 12.05: 3412.05 – 12.91: 2612.91 – 13.77: 2213.77 – 14.62: 1214.62 – 15.48: 815.48 – 16.33: 216.33 – 17.19: 517.19 – 18.05: 318.05 – 18.9: 418.9 – 19.76: 019.76 – 20.62: 320.62 – 21.47: 10102030
n / missing609 / 12
Mean ± SD8.681 ± 3.41
Median8.593
Range0.918 – 21.47
CV0.392
Skew / kurtosis0.4 / 0.68
Normal?no

chlA

target · numeric
chlA distribution02550751.242 – 1.836: 101.836 – 2.43: 302.43 – 3.025: 233.025 – 3.619: 233.619 – 4.213: 324.213 – 4.807: 364.807 – 5.401: 515.401 – 5.996: 735.996 – 6.59: 666.59 – 7.184: 657.184 – 7.778: 557.778 – 8.373: 348.373 – 8.967: 298.967 – 9.561: 149.561 – 10.16: 710.16 – 10.75: 510.75 – 11.34: 011.34 – 11.94: 111.94 – 12.53: 412.53 – 13.13: 413.13 – 13.72: 113.72 – 14.31: 014.31 – 14.91: 014.91 – 15.5: 105101520
n / missing609 / 45
Mean ± SD5.986 ± 2.19
Median6.043
Range1.242 – 15.5
CV0.367
Skew / kurtosis0.3 / 0.79
Normal?no

chlB

target · numeric
chlB distribution02550750.486 – 0.6863: 160.6863 – 0.8866: 270.8866 – 1.087: 281.087 – 1.287: 251.287 – 1.487: 361.487 – 1.688: 431.688 – 1.888: 541.888 – 2.088: 672.088 – 2.289: 702.289 – 2.489: 622.489 – 2.689: 382.689 – 2.89: 392.89 – 3.09: 193.09 – 3.29: 143.29 – 3.49: 93.49 – 3.691: 33.691 – 3.891: 33.891 – 4.091: 04.091 – 4.292: 34.292 – 4.492: 34.492 – 4.692: 24.692 – 4.892: 24.892 – 5.093: 05.093 – 5.293: 10246
n / missing609 / 45
Mean ± SD2.034 ± 0.766
Median2.032
Range0.486 – 5.293
CV0.376
Skew / kurtosis0.53 / 1.2
Normal?no

car

target · numeric
car distribution0501000.193 – 0.312: 50.312 – 0.4309: 300.4309 – 0.5499: 290.5499 – 0.6688: 50.6688 – 0.7878: 130.7878 – 0.9067: 180.9067 – 1.026: 431.026 – 1.145: 531.145 – 1.264: 761.264 – 1.383: 721.383 – 1.501: 711.501 – 1.62: 541.62 – 1.739: 391.739 – 1.858: 231.858 – 1.977: 121.977 – 2.096: 82.096 – 2.215: 32.215 – 2.334: 32.334 – 2.453: 02.453 – 2.572: 62.572 – 2.691: 02.691 – 2.81: 02.81 – 2.929: 02.929 – 3.048: 101234
n / missing609 / 45
Mean ± SD1.25 ± 0.439
Median1.276
Range0.193 – 3.048
CV0.351
Skew / kurtosis-0.068 / 0.62
Normal?no

Al

target · numeric
Al distribution0501001500 – 0.01579: 620.01579 – 0.03158: 1250.03158 – 0.04738: 1310.04738 – 0.06317: 1130.06317 – 0.07896: 600.07896 – 0.09475: 400.09475 – 0.1105: 280.1105 – 0.1263: 110.1263 – 0.1421: 60.1421 – 0.1579: 60.1579 – 0.1737: 70.1737 – 0.1895: 70.1895 – 0.2053: 50.2053 – 0.2211: 00.2211 – 0.2369: 30.2369 – 0.2527: 00.2527 – 0.2685: 10.2685 – 0.2843: 00.2843 – 0.3: 10.3 – 0.3158: 00.3158 – 0.3316: 00.3316 – 0.3474: 10.3474 – 0.3632: 00.3632 – 0.379: 10.00.10.20.30.4
n / missing609 / 1
Mean ± SD0.05587 ± 0.0445
Median0.046
Range0 – 0.379
CV0.797
Skew / kurtosis2.5 / 9.8
Normal?no

Ca

target · numeric
Ca distribution0501001.639 – 3.093: 83.093 – 4.547: 224.547 – 6.001: 696.001 – 7.455: 687.455 – 8.91: 908.91 – 10.36: 7410.36 – 11.82: 7111.82 – 13.27: 4413.27 – 14.73: 2814.73 – 16.18: 2416.18 – 17.63: 2317.63 – 19.09: 1919.09 – 20.54: 2220.54 – 22: 1022 – 23.45: 723.45 – 24.9: 724.9 – 26.36: 526.36 – 27.81: 027.81 – 29.27: 529.27 – 30.72: 430.72 – 32.18: 332.18 – 33.63: 533.63 – 35.08: 035.08 – 36.54: 1010203040
n / missing609 / 0
Mean ± SD11.29 ± 6.03
Median9.88
Range1.639 – 36.54
CV0.534
Skew / kurtosis1.4 / 2.1
Normal?no

Cu

target · numeric
Cu distribution01002003000 – 0.002167: 900.002167 – 0.004333: 580.004333 – 0.0065: 1100.0065 – 0.008667: 830.008667 – 0.01083: 2010.01083 – 0.013: 200.013 – 0.01517: 100.01517 – 0.01733: 80.01733 – 0.0195: 50.0195 – 0.02167: 60.02167 – 0.02383: 10.02383 – 0.026: 40.026 – 0.02817: 30.02817 – 0.03033: 20.03033 – 0.0325: 10.0325 – 0.03467: 10.03467 – 0.03683: 10.03683 – 0.039: 00.039 – 0.04117: 00.04117 – 0.04333: 00.04333 – 0.0455: 10.0455 – 0.04767: 10.04767 – 0.04983: 10.04983 – 0.052: 10.000.020.040.06
n / missing609 / 1
Mean ± SD0.007842 ± 0.00594
Median0.008
Range0 – 0.052
CV0.757
Skew / kurtosis2.9 / 15
Normal?no

Fe

target · numeric
Fe distribution0501000.01497 – 0.02526: 280.02526 – 0.03555: 400.03555 – 0.04585: 470.04585 – 0.05614: 820.05614 – 0.06643: 980.06643 – 0.07673: 730.07673 – 0.08702: 620.08702 – 0.09731: 430.09731 – 0.1076: 410.1076 – 0.1179: 160.1179 – 0.1282: 190.1282 – 0.1385: 130.1385 – 0.1488: 120.1488 – 0.1591: 140.1591 – 0.1694: 40.1694 – 0.1797: 20.1797 – 0.1899: 20.1899 – 0.2002: 00.2002 – 0.2105: 40.2105 – 0.2208: 10.2208 – 0.2311: 40.2311 – 0.2414: 10.2414 – 0.2517: 10.2517 – 0.262: 10.00.10.20.3
n / missing609 / 1
Mean ± SD0.07533 ± 0.0388
Median0.068
Range0.01497 – 0.262
CV0.515
Skew / kurtosis1.5 / 3.2
Normal?no

K

target · numeric
K distribution0501001501.058 – 2.522: 362.522 – 3.985: 653.985 – 5.449: 1355.449 – 6.912: 1466.912 – 8.375: 908.375 – 9.839: 399.839 – 11.3: 3711.3 – 12.77: 1112.77 – 14.23: 714.23 – 15.69: 1015.69 – 17.16: 917.16 – 18.62: 718.62 – 20.08: 420.08 – 21.55: 421.55 – 23.01: 023.01 – 24.47: 124.47 – 25.94: 125.94 – 27.4: 127.4 – 28.86: 028.86 – 30.33: 030.33 – 31.79: 031.79 – 33.25: 233.25 – 34.72: 134.72 – 36.18: 2010203040
n / missing609 / 1
Mean ± SD7.09 ± 4.45
Median6.152
Range1.058 – 36.18
CV0.627
Skew / kurtosis2.8 / 12
Normal?no

Mg

target · numeric
Mg distribution0501001500.482 – 0.7895: 50.7895 – 1.097: 81.097 – 1.405: 291.405 – 1.712: 571.712 – 2.019: 932.019 – 2.327: 1022.327 – 2.635: 962.635 – 2.942: 722.942 – 3.25: 563.25 – 3.557: 303.557 – 3.864: 213.864 – 4.172: 114.172 – 4.479: 94.479 – 4.787: 54.787 – 5.095: 65.095 – 5.402: 25.402 – 5.71: 25.71 – 6.017: 16.017 – 6.325: 16.325 – 6.632: 06.632 – 6.939: 16.939 – 7.247: 07.247 – 7.554: 07.554 – 7.862: 202468
n / missing609 / 0
Mean ± SD2.484 ± 0.913
Median2.362
Range0.482 – 7.862
CV0.367
Skew / kurtosis1.5 / 5
Normal?no

Mn

target · numeric
Mn distribution0501001500 – 0.04262: 1490.04262 – 0.08525: 1330.08525 – 0.1279: 820.1279 – 0.1705: 410.1705 – 0.2131: 380.2131 – 0.2557: 180.2557 – 0.2984: 230.2984 – 0.341: 250.341 – 0.3836: 160.3836 – 0.4262: 140.4262 – 0.4689: 150.4689 – 0.5115: 120.5115 – 0.5541: 90.5541 – 0.5967: 100.5967 – 0.6394: 30.6394 – 0.682: 20.682 – 0.7246: 30.7246 – 0.7672: 30.7672 – 0.8099: 40.8099 – 0.8525: 50.8525 – 0.8951: 00.8951 – 0.9377: 20.9377 – 0.9804: 10.9804 – 1.023: 10.00.51.01.5
n / missing609 / 0
Mean ± SD0.1734 ± 0.19
Median0.094
Range0 – 1.023
CV1.09
Skew / kurtosis1.8 / 3.1
Normal?no

Na

target · numeric
Na distribution0501001500 – 0.203: 870.203 – 0.406: 630.406 – 0.609: 850.609 – 0.812: 1100.812 – 1.015: 971.015 – 1.218: 601.218 – 1.421: 281.421 – 1.624: 161.624 – 1.827: 131.827 – 2.03: 132.03 – 2.233: 32.233 – 2.436: 92.436 – 2.639: 42.639 – 2.842: 52.842 – 3.045: 33.045 – 3.248: 23.248 – 3.451: 13.451 – 3.654: 03.654 – 3.857: 43.857 – 4.06: 24.06 – 4.263: 14.263 – 4.466: 14.466 – 4.669: 04.669 – 4.872: 10246
n / missing609 / 1
Mean ± SD0.8504 ± 0.707
Median0.7315
Range0 – 4.872
CV0.832
Skew / kurtosis2 / 6.2
Normal?no

P

target · numeric
P distribution01002000.2228 – 0.5126: 210.5126 – 0.8024: 100.8024 – 1.092: 671.092 – 1.382: 1681.382 – 1.672: 1411.672 – 1.962: 561.962 – 2.251: 272.251 – 2.541: 272.541 – 2.831: 192.831 – 3.121: 143.121 – 3.411: 83.411 – 3.7: 163.7 – 3.99: 63.99 – 4.28: 84.28 – 4.57: 14.57 – 4.86: 54.86 – 5.149: 35.149 – 5.439: 25.439 – 5.729: 35.729 – 6.019: 26.019 – 6.309: 26.309 – 6.598: 16.598 – 6.888: 06.888 – 7.178: 202468
n / missing609 / 0
Mean ± SD1.762 ± 1.03
Median1.455
Range0.2228 – 7.178
CV0.583
Skew / kurtosis2.2 / 5.8
Normal?no

Zn

target · numeric
Zn distribution01002003000.001424 – 0.02832: 2770.02832 – 0.05522: 880.05522 – 0.08212: 340.08212 – 0.109: 410.109 – 0.1359: 540.1359 – 0.1628: 370.1628 – 0.1897: 250.1897 – 0.2166: 150.2166 – 0.2435: 140.2435 – 0.2704: 60.2704 – 0.2973: 70.2973 – 0.3242: 20.3242 – 0.3511: 30.3511 – 0.378: 20.378 – 0.4049: 10.4049 – 0.4318: 00.4318 – 0.4587: 00.4587 – 0.4856: 00.4856 – 0.5125: 00.5125 – 0.5394: 00.5394 – 0.5663: 20.5663 – 0.5932: 00.5932 – 0.6201: 00.6201 – 0.647: 10.00.20.40.60.8
n / missing609 / 0
Mean ± SD0.07226 ± 0.0839
Median0.03
Range0.001424 – 0.647
CV1.16
Skew / kurtosis2.1 / 7.4
Normal?no

N_area

target · numeric
N_area distribution02040605.15e-05 – 6.102e-05: 36.102e-05 – 7.055e-05: 87.055e-05 – 8.007e-05: 88.007e-05 – 8.96e-05: 168.96e-05 – 9.912e-05: 319.912e-05 – 0.0001086: 330.0001086 – 0.0001182: 600.0001182 – 0.0001277: 450.0001277 – 0.0001372: 460.0001372 – 0.0001467: 370.0001467 – 0.0001563: 440.0001563 – 0.0001658: 580.0001658 – 0.0001753: 440.0001753 – 0.0001848: 350.0001848 – 0.0001944: 270.0001944 – 0.0002039: 330.0002039 – 0.0002134: 170.0002134 – 0.0002229: 220.0002229 – 0.0002325: 120.0002325 – 0.000242: 130.000242 – 0.0002515: 60.0002515 – 0.000261: 10.000261 – 0.0002706: 30.0002706 – 0.0002801: 20.00000.00010.00020.0003
n / missing609 / 5
Mean ± SD0.0001513 ± 4.33e-05
Median0.0001505
Range5.15e-05 – 0.0002801
CV0.286
Skew / kurtosis0.3 / -0.44
Normal?no

C_area

target · numeric
C_area distribution0501001500.00109 – 0.001504: 100.001504 – 0.001917: 150.001917 – 0.002331: 380.002331 – 0.002745: 950.002745 – 0.003159: 1070.003159 – 0.003573: 1340.003573 – 0.003987: 730.003987 – 0.004401: 470.004401 – 0.004815: 130.004815 – 0.005228: 30.005228 – 0.005642: 10.005642 – 0.006056: 20.006056 – 0.00647: 10.00647 – 0.006884: 10.006884 – 0.007298: 60.007298 – 0.007712: 50.007712 – 0.008126: 50.008126 – 0.008539: 90.008539 – 0.008953: 80.008953 – 0.009367: 90.009367 – 0.009781: 70.009781 – 0.01019: 90.01019 – 0.01061: 30.01061 – 0.01102: 30.00000.00250.00500.00750.01000.0125
n / missing609 / 5
Mean ± SD0.00376 ± 0.00193
Median0.00325
Range0.00109 – 0.01102
CV0.514
Skew / kurtosis2.1 / 3.8
Normal?no

solubles_area

target · numeric
solubles_area distribution0501001500.001542 – 0.00214: 70.00214 – 0.002738: 200.002738 – 0.003336: 400.003336 – 0.003934: 740.003934 – 0.004532: 1180.004532 – 0.00513: 1100.00513 – 0.005727: 900.005727 – 0.006325: 370.006325 – 0.006923: 190.006923 – 0.007521: 70.007521 – 0.008119: 40.008119 – 0.008717: 20.008717 – 0.009315: 60.009315 – 0.009913: 40.009913 – 0.01051: 90.01051 – 0.01111: 50.01111 – 0.01171: 80.01171 – 0.0123: 90.0123 – 0.0129: 70.0129 – 0.0135: 40.0135 – 0.0141: 70.0141 – 0.0147: 40.0147 – 0.01529: 30.01529 – 0.01589: 20.0000.0050.0100.0150.020
n / missing609 / 13
Mean ± SD0.005426 ± 0.00262
Median0.004747
Range0.001542 – 0.01589
CV0.483
Skew / kurtosis2 / 3.6
Normal?no

hemicellulose_area

target · numeric
hemicellulose_area distribution0501001500.000118 – 0.0002366: 100.0002366 – 0.0003552: 320.0003552 – 0.0004738: 920.0004738 – 0.0005924: 960.0005924 – 0.000711: 1180.000711 – 0.0008296: 620.0008296 – 0.0009482: 430.0009482 – 0.001067: 230.001067 – 0.001185: 210.001185 – 0.001304: 150.001304 – 0.001423: 130.001423 – 0.001541: 110.001541 – 0.00166: 140.00166 – 0.001778: 90.001778 – 0.001897: 110.001897 – 0.002016: 50.002016 – 0.002134: 40.002134 – 0.002253: 50.002253 – 0.002371: 10.002371 – 0.00249: 10.00249 – 0.002609: 40.002609 – 0.002727: 00.002727 – 0.002846: 00.002846 – 0.002964: 20.0000.0010.0020.003
n / missing609 / 17
Mean ± SD0.0007963 ± 0.000466
Median0.0006587
Range0.000118 – 0.002964
CV0.586
Skew / kurtosis1.7 / 3
Normal?no

cellulose_area

target · numeric
cellulose_area distribution0501000.000199 – 0.0002915: 100.0002915 – 0.0003841: 230.0003841 – 0.0004766: 700.0004766 – 0.0005691: 990.0005691 – 0.0006616: 840.0006616 – 0.0007541: 730.0007541 – 0.0008467: 560.0008467 – 0.0009392: 420.0009392 – 0.001032: 250.001032 – 0.001124: 130.001124 – 0.001217: 110.001217 – 0.001309: 50.001309 – 0.001402: 60.001402 – 0.001494: 120.001494 – 0.001587: 80.001587 – 0.001679: 120.001679 – 0.001772: 120.001772 – 0.001864: 70.001864 – 0.001957: 90.001957 – 0.002049: 60.002049 – 0.002142: 40.002142 – 0.002234: 00.002234 – 0.002327: 30.002327 – 0.002419: 20.0000.0010.0020.003
n / missing609 / 17
Mean ± SD0.000804 ± 0.000428
Median0.0006809
Range0.000199 – 0.002419
CV0.532
Skew / kurtosis1.5 / 1.8
Normal?no

lignin_area

target · numeric
lignin_area distribution0501005.55e-05 – 0.0001585: 250.0001585 – 0.0002615: 380.0002615 – 0.0003645: 600.0003645 – 0.0004675: 870.0004675 – 0.0005705: 990.0005705 – 0.0006735: 780.0006735 – 0.0007765: 630.0007765 – 0.0008796: 220.0008796 – 0.0009826: 200.0009826 – 0.001086: 80.001086 – 0.001189: 110.001189 – 0.001292: 50.001292 – 0.001395: 90.001395 – 0.001498: 40.001498 – 0.001601: 50.001601 – 0.001704: 40.001704 – 0.001807: 40.001807 – 0.00191: 90.00191 – 0.002013: 110.002013 – 0.002116: 70.002116 – 0.002219: 110.002219 – 0.002322: 40.002322 – 0.002425: 40.002425 – 0.002528: 40.0000.0010.0020.003
n / missing609 / 17
Mean ± SD0.0007092 ± 0.000523
Median0.0005596
Range5.55e-05 – 0.002528
CV0.738
Skew / kurtosis1.7 / 2.3
Normal?no

chlA_area

target · numeric
chlA_area distribution0501001.2e-05 – 1.669e-05: 11.669e-05 – 2.139e-05: 152.139e-05 – 2.608e-05: 232.608e-05 – 3.077e-05: 533.077e-05 – 3.547e-05: 753.547e-05 – 4.016e-05: 844.016e-05 – 4.485e-05: 944.485e-05 – 4.954e-05: 894.954e-05 – 5.424e-05: 465.424e-05 – 5.893e-05: 405.893e-05 – 6.362e-05: 196.362e-05 – 6.832e-05: 86.832e-05 – 7.301e-05: 67.301e-05 – 7.77e-05: 37.77e-05 – 8.24e-05: 18.24e-05 – 8.709e-05: 08.709e-05 – 9.178e-05: 29.178e-05 – 9.648e-05: 09.648e-05 – 0.0001012: 00.0001012 – 0.0001059: 00.0001059 – 0.0001106: 00.0001106 – 0.0001152: 00.0001152 – 0.0001199: 00.0001199 – 0.0001246: 10.000000.000050.000100.00015
n / missing609 / 49
Mean ± SD4.21e-05 ± 1.2e-05
Median4.175e-05
Range1.2e-05 – 0.0001246
CV0.285
Skew / kurtosis1 / 4.3
Normal?no

chlB_area

target · numeric
chlB_area distribution0501003.99e-06 – 5.599e-06: 25.599e-06 – 7.208e-06: 137.208e-06 – 8.816e-06: 228.816e-06 – 1.042e-05: 531.042e-05 – 1.203e-05: 811.203e-05 – 1.364e-05: 811.364e-05 – 1.525e-05: 951.525e-05 – 1.686e-05: 831.686e-05 – 1.847e-05: 571.847e-05 – 2.008e-05: 262.008e-05 – 2.169e-05: 222.169e-05 – 2.329e-05: 112.329e-05 – 2.49e-05: 52.49e-05 – 2.651e-05: 42.651e-05 – 2.812e-05: 22.812e-05 – 2.973e-05: 22.973e-05 – 3.134e-05: 03.134e-05 – 3.295e-05: 03.295e-05 – 3.456e-05: 03.456e-05 – 3.616e-05: 03.616e-05 – 3.777e-05: 03.777e-05 – 3.938e-05: 03.938e-05 – 4.099e-05: 04.099e-05 – 4.26e-05: 10.000000.000010.000020.000030.000040.00005
n / missing609 / 49
Mean ± SD1.432e-05 ± 4.13e-06
Median1.4e-05
Range3.99e-06 – 4.26e-05
CV0.289
Skew / kurtosis0.99 / 4.1
Normal?no

car_area

target · numeric
car_area distribution0501002.92e-06 – 3.819e-06: 43.819e-06 – 4.718e-06: 104.718e-06 – 5.618e-06: 255.618e-06 – 6.517e-06: 436.517e-06 – 7.416e-06: 837.416e-06 – 8.315e-06: 978.315e-06 – 9.214e-06: 809.214e-06 – 1.011e-05: 901.011e-05 – 1.101e-05: 501.101e-05 – 1.191e-05: 331.191e-05 – 1.281e-05: 171.281e-05 – 1.371e-05: 131.371e-05 – 1.461e-05: 81.461e-05 – 1.551e-05: 11.551e-05 – 1.641e-05: 31.641e-05 – 1.731e-05: 01.731e-05 – 1.821e-05: 11.821e-05 – 1.911e-05: 11.911e-05 – 2e-05: 02e-05 – 2.09e-05: 02.09e-05 – 2.18e-05: 02.18e-05 – 2.27e-05: 02.27e-05 – 2.36e-05: 02.36e-05 – 2.45e-05: 10.000000.000010.000020.00003
n / missing609 / 49
Mean ± SD8.73e-06 ± 2.36e-06
Median8.58e-06
Range2.92e-06 – 2.45e-05
CV0.271
Skew / kurtosis0.99 / 3.9
Normal?no

Al_area

target · numeric
Al_area distribution01002003000 – 1.683e-07: 1081.683e-07 – 3.367e-07: 2133.367e-07 – 5.05e-07: 1255.05e-07 – 6.733e-07: 806.733e-07 – 8.417e-07: 338.417e-07 – 1.01e-06: 191.01e-06 – 1.178e-06: 71.178e-06 – 1.347e-06: 51.347e-06 – 1.515e-06: 41.515e-06 – 1.683e-06: 41.683e-06 – 1.852e-06: 21.852e-06 – 2.02e-06: 12.02e-06 – 2.188e-06: 12.188e-06 – 2.357e-06: 02.357e-06 – 2.525e-06: 02.525e-06 – 2.693e-06: 02.693e-06 – 2.862e-06: 02.862e-06 – 3.03e-06: 03.03e-06 – 3.198e-06: 03.198e-06 – 3.367e-06: 03.367e-06 – 3.535e-06: 03.535e-06 – 3.703e-06: 03.703e-06 – 3.872e-06: 03.872e-06 – 4.04e-06: 10.0000000.0000020.0000040.000006
n / missing609 / 6
Mean ± SD3.98e-07 ± 3.33e-07
Median3.19e-07
Range0 – 4.04e-06
CV0.836
Skew / kurtosis3.6 / 27
Normal?no

Ca_area

target · numeric
Ca_area distribution0501001503.83e-06 – 1.942e-05: 61.942e-05 – 3.5e-05: 653.5e-05 – 5.059e-05: 1035.059e-05 – 6.617e-05: 1146.617e-05 – 8.176e-05: 898.176e-05 – 9.734e-05: 489.734e-05 – 0.0001129: 410.0001129 – 0.0001285: 350.0001285 – 0.0001441: 280.0001441 – 0.0001597: 180.0001597 – 0.0001753: 80.0001753 – 0.0001909: 90.0001909 – 0.0002064: 110.0002064 – 0.000222: 60.000222 – 0.0002376: 60.0002376 – 0.0002532: 40.0002532 – 0.0002688: 50.0002688 – 0.0002844: 50.0002844 – 0.0003: 10.0003 – 0.0003155: 10.0003155 – 0.0003311: 00.0003311 – 0.0003467: 00.0003467 – 0.0003623: 00.0003623 – 0.0003779: 10.00000.00010.00020.00030.0004
n / missing609 / 5
Mean ± SD8.497e-05 ± 5.55e-05
Median6.855e-05
Range3.83e-06 – 0.0003779
CV0.654
Skew / kurtosis1.7 / 3.1
Normal?no

Cu_area

target · numeric
Cu_area distribution01002000 – 1.821e-08: 521.821e-08 – 3.642e-08: 1723.642e-08 – 5.463e-08: 1295.463e-08 – 7.283e-08: 1497.283e-08 – 9.104e-08: 669.104e-08 – 1.093e-07: 161.093e-07 – 1.275e-07: 31.275e-07 – 1.457e-07: 51.457e-07 – 1.639e-07: 41.639e-07 – 1.821e-07: 01.821e-07 – 2.003e-07: 12.003e-07 – 2.185e-07: 12.185e-07 – 2.367e-07: 22.367e-07 – 2.549e-07: 22.549e-07 – 2.731e-07: 02.731e-07 – 2.913e-07: 02.913e-07 – 3.095e-07: 03.095e-07 – 3.278e-07: 03.278e-07 – 3.46e-07: 03.46e-07 – 3.642e-07: 03.642e-07 – 3.824e-07: 03.824e-07 – 4.006e-07: 04.006e-07 – 4.188e-07: 04.188e-07 – 4.37e-07: 10.00000000.00000020.00000040.0000006
n / missing609 / 6
Mean ± SD5.147e-08 ± 3.55e-08
Median4.76e-08
Range0 – 4.37e-07
CV0.689
Skew / kurtosis3.5 / 28
Normal?no

Fe_area

target · numeric
Fe_area distribution0501001501.46e-07 – 2.112e-07: 122.112e-07 – 2.763e-07: 362.763e-07 – 3.415e-07: 573.415e-07 – 4.067e-07: 1224.067e-07 – 4.718e-07: 1064.718e-07 – 5.37e-07: 625.37e-07 – 6.022e-07: 546.022e-07 – 6.673e-07: 366.673e-07 – 7.325e-07: 297.325e-07 – 7.977e-07: 187.977e-07 – 8.628e-07: 178.628e-07 – 9.28e-07: 169.28e-07 – 9.932e-07: 99.932e-07 – 1.058e-06: 91.058e-06 – 1.123e-06: 61.123e-06 – 1.189e-06: 21.189e-06 – 1.254e-06: 11.254e-06 – 1.319e-06: 21.319e-06 – 1.384e-06: 31.384e-06 – 1.449e-06: 11.449e-06 – 1.514e-06: 01.514e-06 – 1.58e-06: 11.58e-06 – 1.645e-06: 21.645e-06 – 1.71e-06: 20.00000000.00000050.00000100.00000150.0000020
n / missing609 / 6
Mean ± SD5.173e-07 ± 2.37e-07
Median4.5e-07
Range1.46e-07 – 1.71e-06
CV0.459
Skew / kurtosis1.7 / 4.2
Normal?no

K_area

target · numeric
K_area distribution01002001.48e-05 – 2.347e-05: 252.347e-05 – 3.213e-05: 1233.213e-05 – 4.08e-05: 1514.08e-05 – 4.946e-05: 1044.946e-05 – 5.813e-05: 675.813e-05 – 6.679e-05: 456.679e-05 – 7.546e-05: 207.546e-05 – 8.412e-05: 148.412e-05 – 9.279e-05: 129.279e-05 – 0.0001015: 80.0001015 – 0.0001101: 70.0001101 – 0.0001188: 40.0001188 – 0.0001274: 40.0001274 – 0.0001361: 80.0001361 – 0.0001448: 20.0001448 – 0.0001534: 40.0001534 – 0.0001621: 40.0001621 – 0.0001708: 00.0001708 – 0.0001794: 00.0001794 – 0.0001881: 00.0001881 – 0.0001968: 00.0001968 – 0.0002054: 00.0002054 – 0.0002141: 00.0002141 – 0.0002228: 10.00000.00010.00020.0003
n / missing609 / 6
Mean ± SD4.867e-05 ± 2.63e-05
Median4.1e-05
Range1.48e-05 – 0.0002228
CV0.54
Skew / kurtosis2.3 / 6.8
Normal?no

Mg_area

target · numeric
Mg_area distribution0501001503.18e-06 – 6.456e-06: 136.456e-06 – 9.732e-06: 569.732e-06 – 1.301e-05: 1221.301e-05 – 1.628e-05: 1131.628e-05 – 1.956e-05: 901.956e-05 – 2.284e-05: 752.284e-05 – 2.611e-05: 482.611e-05 – 2.939e-05: 192.939e-05 – 3.266e-05: 193.266e-05 – 3.594e-05: 93.594e-05 – 3.921e-05: 73.921e-05 – 4.249e-05: 104.249e-05 – 4.577e-05: 54.577e-05 – 4.904e-05: 44.904e-05 – 5.232e-05: 25.232e-05 – 5.559e-05: 55.559e-05 – 5.887e-05: 35.887e-05 – 6.214e-05: 26.214e-05 – 6.542e-05: 06.542e-05 – 6.87e-05: 16.87e-05 – 7.197e-05: 07.197e-05 – 7.525e-05: 07.525e-05 – 7.852e-05: 07.852e-05 – 8.18e-05: 10.000000.000020.000040.000060.000080.00010
n / missing609 / 5
Mean ± SD1.867e-05 ± 1.01e-05
Median1.62e-05
Range3.18e-06 – 8.18e-05
CV0.542
Skew / kurtosis2 / 5.8
Normal?no

Mn_area

target · numeric
Mn_area distribution02004000 – 6.75e-07: 3086.75e-07 – 1.35e-06: 1171.35e-06 – 2.025e-06: 552.025e-06 – 2.7e-06: 452.7e-06 – 3.375e-06: 183.375e-06 – 4.05e-06: 234.05e-06 – 4.725e-06: 94.725e-06 – 5.4e-06: 65.4e-06 – 6.075e-06: 76.075e-06 – 6.75e-06: 46.75e-06 – 7.425e-06: 47.425e-06 – 8.1e-06: 08.1e-06 – 8.775e-06: 28.775e-06 – 9.45e-06: 09.45e-06 – 1.013e-05: 21.013e-05 – 1.08e-05: 11.08e-05 – 1.147e-05: 11.147e-05 – 1.215e-05: 01.215e-05 – 1.283e-05: 01.283e-05 – 1.35e-05: 01.35e-05 – 1.418e-05: 11.418e-05 – 1.485e-05: 01.485e-05 – 1.553e-05: 01.553e-05 – 1.62e-05: 10.0000000.0000050.0000100.0000150.000020
n / missing609 / 5
Mean ± SD1.322e-06 ± 1.78e-06
Median6.63e-07
Range0 – 1.62e-05
CV1.35
Skew / kurtosis3.4 / 17
Normal?no

Na_area

target · numeric
Na_area distribution01002000 – 2.9e-06: 1692.9e-06 – 5.8e-06: 1935.8e-06 – 8.7e-06: 1218.7e-06 – 1.16e-05: 451.16e-05 – 1.45e-05: 111.45e-05 – 1.74e-05: 41.74e-05 – 2.03e-05: 52.03e-05 – 2.32e-05: 32.32e-05 – 2.61e-05: 52.61e-05 – 2.9e-05: 42.9e-05 – 3.19e-05: 53.19e-05 – 3.48e-05: 53.48e-05 – 3.77e-05: 93.77e-05 – 4.06e-05: 44.06e-05 – 4.35e-05: 74.35e-05 – 4.64e-05: 24.64e-05 – 4.93e-05: 24.93e-05 – 5.22e-05: 25.22e-05 – 5.51e-05: 45.51e-05 – 5.8e-05: 15.8e-05 – 6.09e-05: 06.09e-05 – 6.38e-05: 06.38e-05 – 6.67e-05: 06.67e-05 – 6.96e-05: 20.000000.000020.000040.000060.00008
n / missing609 / 6
Mean ± SD7.822e-06 ± 1.06e-05
Median4.73e-06
Range0 – 6.96e-05
CV1.36
Skew / kurtosis2.9 / 8.8
Normal?no

P_area

target · numeric
P_area distribution01002003.09e-06 – 5.995e-06: 385.995e-06 – 8.899e-06: 1888.899e-06 – 1.18e-05: 1641.18e-05 – 1.471e-05: 811.471e-05 – 1.761e-05: 321.761e-05 – 2.052e-05: 282.052e-05 – 2.342e-05: 232.342e-05 – 2.633e-05: 102.633e-05 – 2.923e-05: 112.923e-05 – 3.214e-05: 53.214e-05 – 3.504e-05: 63.504e-05 – 3.794e-05: 43.794e-05 – 4.085e-05: 54.085e-05 – 4.375e-05: 44.375e-05 – 4.666e-05: 04.666e-05 – 4.956e-05: 14.956e-05 – 5.247e-05: 05.247e-05 – 5.537e-05: 15.537e-05 – 5.828e-05: 05.828e-05 – 6.118e-05: 16.118e-05 – 6.409e-05: 16.409e-05 – 6.699e-05: 06.699e-05 – 6.99e-05: 06.99e-05 – 7.28e-05: 10.000000.000020.000040.000060.00008
n / missing609 / 5
Mean ± SD1.263e-05 ± 8.24e-06
Median1.01e-05
Range3.09e-06 – 7.28e-05
CV0.653
Skew / kurtosis2.8 / 11
Normal?no

Zn_area

target · numeric
Zn_area distribution02004002.3e-08 – 2.4e-07: 3172.4e-07 – 4.569e-07: 684.569e-07 – 6.739e-07: 466.739e-07 – 8.908e-07: 548.908e-07 – 1.108e-06: 321.108e-06 – 1.325e-06: 191.325e-06 – 1.542e-06: 211.542e-06 – 1.759e-06: 131.759e-06 – 1.976e-06: 81.976e-06 – 2.193e-06: 82.193e-06 – 2.41e-06: 92.41e-06 – 2.627e-06: 42.627e-06 – 2.843e-06: 12.843e-06 – 3.06e-06: 23.06e-06 – 3.277e-06: 03.277e-06 – 3.494e-06: 03.494e-06 – 3.711e-06: 03.711e-06 – 3.928e-06: 13.928e-06 – 4.145e-06: 04.145e-06 – 4.362e-06: 04.362e-06 – 4.579e-06: 04.579e-06 – 4.796e-06: 04.796e-06 – 5.013e-06: 05.013e-06 – 5.23e-06: 10.0000000.0000020.0000040.000006
n / missing609 / 5
Mean ± SD5.131e-07 ± 6.32e-07
Median2.01e-07
Range2.3e-08 – 5.23e-06
CV1.23
Skew / kurtosis2.2 / 7.3
Normal?no

Metadata 3

latitude

metadata · numeric
latitude distribution0200400600-34.81 – -31.44: 68-31.44 – -28.08: 0-28.08 – -24.71: 0-24.71 – -21.34: 0-21.34 – -17.98: 0-17.98 – -14.61: 0-14.61 – -11.24: 0-11.24 – -7.876: 0-7.876 – -4.509: 0-4.509 – -1.143: 0-1.143 – 2.224: 02.224 – 5.59: 05.59 – 8.957: 08.957 – 12.32: 012.32 – 15.69: 015.69 – 19.06: 019.06 – 22.42: 022.42 – 25.79: 025.79 – 29.16: 029.16 – 32.52: 032.52 – 35.89: 035.89 – 39.26: 039.26 – 42.62: 042.62 – 45.99: 541-50-2502550
n / missing609 / 0
Mean ± SD36.64 ± 25.3
Median45.55
Range-34.81 – 45.99
CV0.69
Skew / kurtosis-2.5 / 4.1
Normal?no

longitude

metadata · numeric
longitude distribution0200400600-75.52 – -67.54: 541-67.54 – -59.55: 0-59.55 – -51.57: 0-51.57 – -43.59: 0-43.59 – -35.61: 0-35.61 – -27.62: 0-27.62 – -19.64: 0-19.64 – -11.66: 0-11.66 – -3.674: 0-3.674 – 4.309: 04.309 – 12.29: 012.29 – 20.27: 020.27 – 28.26: 028.26 – 36.24: 036.24 – 44.22: 044.22 – 52.21: 052.21 – 60.19: 060.19 – 68.17: 068.17 – 76.15: 076.15 – 84.14: 084.14 – 92.12: 092.12 – 100.1: 0100.1 – 108.1: 0108.1 – 116.1: 68-100-50050100150
n / missing609 / 0
Mean ± SD-52.65 ± 59.8
Median-73.47
Range-75.52 – 116.1
CV1.14
Skew / kurtosis2.5 / 4.1
Normal?no

species

metadata · categorical
species classesPopulus tremuloides MichauxPopulus tremuloides Michaux: 102102Betula populifolia MarshallBetula populifolia Marshall: 8484Acer rubrum LinnaeusAcer rubrum Linnaeus: 7272Agonis flexuosa (Willd.) SweetAgonis flexuosa (Willd.) Sweet: 6868Acer saccharum MarshallAcer saccharum Marshall: 4141Fagus grandifolia EhrhartFagus grandifolia Ehrhart: 2626Quercus rubra LinnaeusQuercus rubra Linnaeus: 2626Populus grandidentata MichauxPopulus grandidentata Michaux: 2121Acer saccharinum LinnaeusAcer saccharinum Linnaeus: 2121Betula papyrifera MarshallBetula papyrifera Marshall: 2020+10 more+10 more: 6868
n / missing609 / 0
Classes66
Balance (entropy)0.71
Imbalance ratio102
Top classPopulus tremuloides Michaux (102)
Constant metadata 18
  • ecosis_resource_idac6e3625-80ad-462a-8f07-6b72cf604d41
  • coordinate_precision_notessource-provided coordinates when available
  • year2,022
  • plant_partLeaf
  • canopy_or_leafleaf
  • instrumentSpectra Vista Corporation HR-1024i
  • acquisition_modeContact
  • signal_typereflectance
  • axis_unitnm
  • axis_min400
  • axis_max2,400
  • n_points_original2,001
  • publication_doi10.1101/2021.04.21.440856v5.full | 10.21232/44vxHorW | 10.21232/44vxhorw | 10.21232/VYJzNBEy | 10.21232/deP7jVyq
  • citationShan Kothari, Rosalie Beauchamp-Rioux, Etienne Lalibert and Jeannine Cavender-Bares. 2022. Fresh-leaf CABO spectra from herbarium project. Data set. Available on-line [http://ecosis.org] from the Ecological Spectral Information System (EcoSIS). 10.21232/deP7jVyq
  • licenseCreative Commons Attribution Share-Alike
  • rights_statusexplicit_open
  • usage_scopepublic_reuse_possible
  • notesEcoSIS package fresh-leaf-cabo-spectra-from-herbarium-project, no interpolation applied by project.

6 variable(s) omitted (no recorded values).

Alignment

Alignment levelobservation
Sample id availableyes
Samples609
Observations (total)609
Reps per samplemin 1 · mean 1 · max 1

Provenance & citation

ContributorFresh-leaf CABO spectra from herbarium project
Origin · url [open]https://data.ecosis.org/dataset/fresh-leaf-cabo-spectra-from-herbarium-project
Origin · script [manual]source_to_standard.py — standardization script (maintainer-only)
Publication10.1101/2021.04.21.440856v5.full — Reflectance spectroscopy allows rapid, accurate, and non-destructive estimates of functional traits from pressed leaves
Publication10.21232/deP7jVyq — Fresh-leaf CABO spectra from herbarium project
Publication10.21232/44vxHorW
Publication10.21232/44vxhorw
Publication10.21232/VYJzNBEy

Governance & integrity

Tierpublic
LicenseCC-BY-SA-4.0
Permitted useResearch and benchmarking.
Access policyOpen per source license.
RedistributionEcoSIS CKAN metadata exposes an open license.
Content version1.0.0
Schema / protocol2.0
Content hash0962914a9d2a16e9…
Processing hash8189752588b8b6ce…
Metadata hashc5b1180edd000463…

Load this dataset

# pip install nirs4all-datasets
from nirs4all_datasets import get

ds = get("ecosis_fresh_leaf_cabo_spectra_from_herbarium_project_reflectance_nirs")            # DOI-pinned, checksum-verified, cached
X, y = ds.x(), ds.y()
print(X.shape, y.shape)
card.jsoncroissant.jsonIdentity metadata only — the dataset bytes live at the origin / DOI.