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EcoSIS Leaf spectra, structural and biochemical leaf traits of eight crop species (reflectance)

ecosis · NIR

EcoSIS Leaf spectra, structural and biochemical leaf traits of eight crop species (reflectance). v2.0 standardized NIRS package: 1 spectral source(s), 46 declared target(s). Auto-generated from dataset_card.json (verify before publication).

nirv2ecosis
184
samples
2,151
wavelengths
1
sources
46
targets
26
metadata
NIR
family

Dataset property explorer

Mean profile risk0.43
Highest axisArtefacts locaux · 1.00
Diagnostics8
Sources profiled1
EcoSIS Leaf spectra, structural and biochemical leaf traits of eight crop species (reflectance) property profile0.250.50.751integritynoiseartefactsbaselinePCA outliersreferencerepeatabilitystructureEcoSIS Leaf spectra, structural and biochemical leaf traits of eight crop species (reflectance) profileintegrity: 0.00noise: 0.00artefacts: 1.00baseline: 0.78PCA outliers: 0.51reference: 0.45repeatability: 0.00structure: 0.69EcoSIS Leaf spe…0 center · 1 outer ring · outward = stronger anomaly / heterogeneity signal

Profile axes

Intégrité0.00
Artefacts locaux1.00
Bruit0.00
Outliers PCA0.51
Distance à la référence0.45
Répétabilité0.00
Baseline / forme0.78
Structure multi-régimes0.69
Diagnostic hypotheses00.250.50.751hypothesis scoreSplice / raccord détecteursSplice / raccord détecteurs: 0.730.73Erreur interpolation / réécha…Erreur interpolation / rééchantillonnage: 0.640.64Erreur calibration / référenc…Erreur calibration / référence blanche: 0.560.56Signature VERA25-likeSignature VERA25-like: 0.560.56Fond différentFond différent: 0.490.49Différence de sonde / géométr…Différence de sonde / géométrie: 0.460.46Dataset multi-régimesDataset multi-régimes: 0.380.38Spectre saturé / clippingSpectre saturé / clipping: 0.380.38
DiagnosticScoreForceSignauxInterprétation probable
Splice / raccord détecteursX0.73forteSpike rate 1.00, Jump rate 1.00, SNR non dégradé 1.00Rupture aux jonctions de détecteurs, calibration locale ou sonde différente.
Erreur interpolation / rééchantillonnageX0.64moyenneSpike rate 1.00, Jump rate 1.00, SNR normal/élevé 1.00Artefacts numériques ou traitement spectral incorrect.
Erreur calibration / référence blancheX0.56moyenneartefacts locaux 1.00, Baseline/mean/area 0.78, PCA Q 0.51Décalage systématique entre campagnes, instruments ou référence blanche.
Signature VERA25-likeX0.56moyenneSpike rate 1.00, Jump rate 1.00, PCA Q 0.51Combinaison possible changement de sonde + splice, amplifiée par géométrie, fond ou calibration.
Fond différentX0.49moyenneBaseline/mean/area 0.78, PCA Q 0.51, RMS/SAM référence 0.45Effet systématique du support, blanc/noir, transflectance ou environnement de mesure.
Différence de sonde / géométrieX0.46moyenneBaseline/mean/area 0.78, PCA Q 0.51, RMS/SAM référence 0.45Modification de l'illumination, collecte, angle ou distance sonde-échantillon.
Dataset multi-régimesX0.38faibleStructure PCA 0.69, PCA Q 0.51, RMS/SAM référence 0.45Mélange de campagnes, opérateurs, lots, setups ou sous-populations spectrales.
Spectre saturé / clippingX0.38faibleJump rate 1.00, Baseline/mean/area 0.78, PCA Q 0.51Détecteur saturé ou dynamique insuffisante.

Spectral sources

BNL_2015glasshouse_SVC_Averaged_Interpolated_Spectra.csv

X · NIR · Spectravista Corporation HR-1024i
BNL_2015glasshouse_SVC_Averaged_Interpolated_Spectra.csv spectra020406001,0002,0003,000q05-q95 envelopeq25-q75 envelopemedian spectrummedianq25–q75q05–q95wavelength / nm350nm — median 7.788 (q25–q75 6.131–9.558)365nm — median 5.791 (q25–q75 4.66–7.2)381nm — median 5.156 (q25–q75 4.042–6.139)396nm — median 4.697 (q25–q75 3.745–5.582)412nm — median 4.321 (q25–q75 3.577–5.107)427nm — median 4.204 (q25–q75 3.549–5.026)443nm — median 4.173 (q25–q75 3.539–5.038)458nm — median 4.366 (q25–q75 3.691–5.286)474nm — median 4.463 (q25–q75 3.731–5.424)489nm — median 4.525 (q25–q75 3.822–5.606)505nm — median 5.343 (q25–q75 4.354–6.607)520nm — median 8.764 (q25–q75 7.056–11.09)536nm — median 13.06 (q25–q75 10.82–16.2)551nm — median 14.13 (q25–q75 11.79–17.52)567nm — median 12.55 (q25–q75 10.22–15.6)582nm — median 9.52 (q25–q75 7.611–12.11)597nm — median 8.326 (q25–q75 6.658–10.52)613nm — median 7.178 (q25–q75 5.8–9.054)628nm — median 6.314 (q25–q75 5.086–7.837)644nm — median 5.33 (q25–q75 4.392–6.607)659nm — median 4.484 (q25–q75 3.796–5.678)675nm — median 4.246 (q25–q75 3.568–5.111)690nm — median 5.686 (q25–q75 4.755–7.005)706nm — median 18.5 (q25–q75 15.87–22.63)721nm — median 32.61 (q25–q75 30.47–36.14)737nm — median 42.78 (q25–q75 40.82–45.12)752nm — median 46.36 (q25–q75 44.38–48.36)768nm — median 47.06 (q25–q75 44.94–49.06)783nm — median 47.15 (q25–q75 45.02–49.03)799nm — median 47.14 (q25–q75 45.02–48.97)814nm — median 47.06 (q25–q75 44.91–48.85)829nm — median 46.99 (q25–q75 44.83–48.76)845nm — median 46.85 (q25–q75 44.75–48.58)860nm — median 46.84 (q25–q75 44.7–48.59)876nm — median 46.62 (q25–q75 44.55–48.38)891nm — median 46.42 (q25–q75 44.39–48.19)907nm — median 46.23 (q25–q75 44.23–48.05)922nm — median 46.01 (q25–q75 44.05–47.81)938nm — median 45.57 (q25–q75 43.67–47.33)953nm — median 44.82 (q25–q75 42.96–46.52)969nm — median 44.21 (q25–q75 42.41–45.87)984nm — median 43.98 (q25–q75 42.06–45.53)1,000nm — median 44.25 (q25–q75 42.44–45.78)1,015nm — median 44.83 (q25–q75 43.1–46.34)1,031nm — median 45.21 (q25–q75 43.4–46.69)1,046nm — median 45.38 (q25–q75 43.51–46.87)1,062nm — median 45.43 (q25–q75 43.54–46.93)1,077nm — median 45.37 (q25–q75 43.49–46.87)1,092nm — median 45.24 (q25–q75 43.4–46.68)1,108nm — median 45.02 (q25–q75 43.21–46.46)1,123nm — median 44.66 (q25–q75 42.9–46.05)1,139nm — median 43.29 (q25–q75 41.66–44.86)1,154nm — median 41.78 (q25–q75 40–43.22)1,170nm — median 41.36 (q25–q75 39.68–42.89)1,185nm — median 41.15 (q25–q75 39.44–42.68)1,201nm — median 41.12 (q25–q75 39.4–42.63)1,216nm — median 41.27 (q25–q75 39.51–42.73)1,232nm — median 41.47 (q25–q75 39.7–42.9)1,247nm — median 41.57 (q25–q75 39.85–43)1,263nm — median 41.56 (q25–q75 39.83–42.99)1,278nm — median 41.34 (q25–q75 39.64–42.79)1,294nm — median 40.83 (q25–q75 39.16–42.3)1,309nm — median 39.89 (q25–q75 38.23–41.38)1,324nm — median 38.45 (q25–q75 36.67–39.96)1,340nm — median 36.37 (q25–q75 34.72–37.98)1,355nm — median 34.58 (q25–q75 32.96–36.35)1,371nm — median 31.89 (q25–q75 30.34–33.96)1,386nm — median 25.75 (q25–q75 24.07–28.05)1,402nm — median 17.38 (q25–q75 15.89–19.62)1,417nm — median 13.45 (q25–q75 12.16–15.47)1,433nm — median 12.19 (q25–q75 10.93–14.23)1,448nm — median 12.1 (q25–q75 10.76–14.1)1,464nm — median 12.64 (q25–q75 11.17–14.57)1,479nm — median 14.06 (q25–q75 12.51–15.99)1,495nm — median 15.98 (q25–q75 14.37–18.07)1,510nm — median 17.87 (q25–q75 16.35–20.25)1,526nm — median 19.97 (q25–q75 18.46–22.33)1,541nm — median 21.84 (q25–q75 20.19–24.15)1,556nm — median 23.49 (q25–q75 21.72–25.78)1,572nm — median 25.02 (q25–q75 23.29–27.22)1,587nm — median 26.24 (q25–q75 24.47–28.33)1,603nm — median 27.31 (q25–q75 25.47–29.38)1,618nm — median 28.07 (q25–q75 26.24–30.18)1,634nm — median 28.69 (q25–q75 26.83–30.81)1,649nm — median 29.16 (q25–q75 27.26–31.28)1,665nm — median 29.4 (q25–q75 27.5–31.53)1,680nm — median 29.25 (q25–q75 27.34–31.39)1,696nm — median 28.88 (q25–q75 26.94–30.99)1,711nm — median 28.43 (q25–q75 26.46–30.51)1,727nm — median 27.8 (q25–q75 25.79–29.79)1,742nm — median 26.87 (q25–q75 24.88–28.92)1,758nm — median 25.68 (q25–q75 23.8–27.8)1,773nm — median 24.75 (q25–q75 22.9–26.91)1,788nm — median 24.26 (q25–q75 22.5–26.47)1,804nm — median 24.17 (q25–q75 22.43–26.38)1,819nm — median 24.07 (q25–q75 22.34–26.3)1,835nm — median 23.53 (q25–q75 21.82–25.79)1,850nm — median 21.78 (q25–q75 20.09–24.09)1,866nm — median 17.1 (q25–q75 15.43–19.15)1,881nm — median 9.891 (q25–q75 8.688–11.55)1,897nm — median 5.494 (q25–q75 5.077–6.332)1,912nm — median 3.581 (q25–q75 3.23–4.204)1,928nm — median 3.118 (q25–q75 2.809–3.653)1,943nm — median 3.146 (q25–q75 2.807–3.66)1,959nm — median 3.396 (q25–q75 3.051–3.983)1,974nm — median 3.803 (q25–q75 3.418–4.538)1,990nm — median 4.481 (q25–q75 3.998–5.439)2,005nm — median 5.27 (q25–q75 4.693–6.38)2,021nm — median 6.176 (q25–q75 5.409–7.444)2,036nm — median 7.146 (q25–q75 6.193–8.523)2,051nm — median 8.054 (q25–q75 7.009–9.581)2,067nm — median 8.969 (q25–q75 7.868–10.67)2,082nm — median 9.947 (q25–q75 8.774–11.67)2,098nm — median 10.96 (q25–q75 9.713–12.85)2,113nm — median 12.02 (q25–q75 10.7–14.03)2,129nm — median 12.98 (q25–q75 11.55–15.03)2,144nm — median 13.53 (q25–q75 12.1–15.7)2,160nm — median 14.14 (q25–q75 12.69–16.34)2,175nm — median 14.48 (q25–q75 13.01–16.75)2,191nm — median 14.72 (q25–q75 13.22–16.96)2,206nm — median 14.95 (q25–q75 13.39–17.21)2,222nm — median 14.98 (q25–q75 13.36–17.24)2,237nm — median 14.74 (q25–q75 13.12–17)2,253nm — median 14.03 (q25–q75 12.49–16.23)2,268nm — median 13.19 (q25–q75 11.7–15.27)2,283nm — median 12.47 (q25–q75 11–14.42)2,299nm — median 11.78 (q25–q75 10.37–13.68)2,314nm — median 11.08 (q25–q75 9.804–12.95)2,330nm — median 10.22 (q25–q75 9.069–12.1)2,345nm — median 9.466 (q25–q75 8.395–11.27)2,361nm — median 9.062 (q25–q75 8.103–10.74)2,376nm — median 8.73 (q25–q75 7.829–10.27)2,392nm — median 7.558 (q25–q75 6.629–8.956)2,407nm — median 6.734 (q25–q75 5.892–8.072)2,423nm — median 6.163 (q25–q75 5.478–7.444)2,438nm — median 5.811 (q25–q75 5.181–7.025)2,454nm — median 5.194 (q25–q75 4.625–6.294)2,469nm — median 4.682 (q25–q75 4.199–5.626)2,485nm — median 4.341 (q25–q75 3.905–5.188)2,500nm — median 4.285 (q25–q75 3.857–5.114)

Sampling

Wavelengths2,151
Axis range350–2,500 nm
Mean spacing1 nm
Griduniform
Observations184

Signal & quality

Value range-6.73 – 54.7
Mean range3.2 – 46.9
Mean level22.57
Area4.855e+04
PTP43.75
Noise RMS0.0020746
SNR1.1e+04
SNR dB8e+01 dB
Dynamic range43.7
Smoothness0.07583
Saturated0.0%
X-outliers79

Integrity & artefacts

NaN ratio0.00%
Inf count0
Zero ratio0.00%
Spike count30,646
Spike rate7.75%
Jump count12,944
Jump rate3.27%
Clip fraction0.00%

Shape & reference

Baseline slope-17.11
Curvature RMS0.070205
D1 RMS0.17553
RMS to mean2.1774
RMS p954.8078
SAM to mean0.052284
SAM p950.094674
Affine offset p953.0155
Affine gain p95 Δ0.13661
Affine residual p952.3791
Xcorr lag p951

Outliers & repeatability

PCA Q p95/median4.1
Hotelling T2 p95/median3
Mahalanobis H p95/median1.7
Repeat groups0

Dimensionality (PCA)

Effective rank2.9
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_ratio0.000253%0.00faibleNormalExport, saturationcount(X == 0) / count(finite X)alert = min(1, zero_ratio / 0.05)
Amplitude globaleMean reflectanceamplitude.mean_reflectance22.5750.78fortValeur 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_curve485520.78fortValeur 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_peak43.7470.00faibleVariabilité forteSaturationmax(mean_spectrum) - min(mean_spectrum)alert increases when dynamic range is abnormally flat
Amplitude globaleVarianceamplitude.variance243.720.00faibleNormal ou hétérogèneMauvais contactvar(X finite)alert increases when variance/dynamic range is abnormally flat
BruitNoise RMSnoise.noise_rms0.00207460.00faibleStableLampe, détecteurmedian MAD(second derivative) * 1.4826 / sqrt(6)alert = noise_rms / signal_scale, saturated at 5%
BruitSNRnoise.snr108820.00faibleBon signalAcquisitionmean(abs(X)) / noise_rmsalert decreases with SNR dB; >=40 dB is treated as low alert
BruitBandwise SNRnoise.bandwise_snr_min17.5710.29faibleZone 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_count30,6461.00fortArtefactsCosmic rays, splicecount robust outliers in second derivativealert follows spike_rate, saturated at 1%
Artefacts locauxSpike rateartefacts.spike_rate7.75%1.00fortSpectre suspectInterpolationspike_count / (n_samples * (n_features - 2))alert = min(1, spike_rate / 0.01)
Artefacts locauxJump countartefacts.jump_count12,9441.00fortRaccord détecteurSplicecount robust outliers in first derivativealert follows jump_rate, saturated at 1%
Artefacts locauxJump rateartefacts.jump_rate3.27%1.00fortProblème spectralCalibrationjump_count / (n_samples * (n_features - 1))alert = min(1, jump_rate / 0.01)
Artefacts locauxClip fractionartefacts.clip_fraction0.000505%0.00faibleNormalDétecteur saturéfraction of finite cells equal to repeated min/max extremaalert = min(1, clip_fraction / 0.01)
Forme spectraleBaseline slopeshape.baseline_slope-17.110.78fortDériveÉclairementlinear slope of mean_spectrum over normalized axisalert = abs(slope / signal_scale), saturated at 0.5
Forme spectraleCurvature RMSshape.curvature_rms0.0702050.16faibleLisseFond, splicemedian RMS(second derivative per spectrum)alert = curvature_rms / signal_scale, saturated at 1%
Forme spectraleD1 RMSshape.d1_rms0.175530.08faiblePlatBiologie ou artefactmedian RMS(first derivative per spectrum)alert = d1_rms / signal_scale, saturated at 5%
Outliers multivariésPCA Q (SPE)outliers.pca_q_ratio4.10140.51moyenSpectre atypiqueArtefact, mélangep95(Q/SPE residual) / median(Q/SPE residual)alert = min(1, pca_q_ratio / 8)
Outliers multivariésHotelling T²outliers.hotelling_t2_ratio3.0280.38faibleCentralVariabilité naturellep95(Hotelling T2) / median(Hotelling T2)alert = min(1, hotelling_t2_ratio / 8)
Outliers multivariésMahalanobis Houtliers.mahalanobis_h_ratio1.74010.44moyenOutlier globalDomaine différentp95(sqrt(T2)) / median(sqrt(T2))alert = min(1, mahalanobis_h_ratio / 4)
Comparaison à référenceRMS to mean spectrumreference.rms_to_mean_spectrum_p954.80780.44moyenSpectre 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_p950.0946740.27faibleSimilaireFond, 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_density0.0277750.69moyenSous-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_p952.07570.54moyenSpectre 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_p950.550210.69moyenSpectre atypiqueDiverses causesp95 IsolationForest anomaly score on PCA scoresalert follows structure complexity; raw score is implementation-dependent
X PCA score plot-400-2000200400-200-1000100200300PC1 -19.15 · PC2 -23.46PC1 -45.44 · PC2 -37.29PC1 -54.88 · PC2 -24.57PC1 8.699 · PC2 -105.8PC1 25.68 · PC2 -87.5PC1 106.4 · PC2 -128.3PC1 22.02 · PC2 -76.76PC1 -34.67 · PC2 -58.12PC1 -27.43 · PC2 -32.1PC1 32.46 · PC2 -16.48PC1 155.7 · PC2 -8.514PC1 -0.1078 · PC2 -46.84PC1 46.86 · PC2 -53.32PC1 -24.58 · PC2 26.1PC1 -94.23 · PC2 37.95PC1 -58.63 · PC2 23.49PC1 -60.86 · PC2 65.74PC1 -92.9 · PC2 6.734PC1 -122.9 · PC2 -42.23PC1 -108.9 · PC2 -44.23PC1 -118 · PC2 -29.32PC1 -6.424 · PC2 5.493PC1 154.4 · PC2 -6.998PC1 77.31 · PC2 -65.51PC1 119.8 · PC2 -86.2PC1 74.86 · PC2 -9.464PC1 -56.85 · PC2 26.06PC1 -10.5 · PC2 -23.09PC1 34.97 · PC2 38.72PC1 -35.63 · PC2 19.3PC1 0.515 · PC2 10.3PC1 -27.78 · PC2 34.7PC1 22.75 · PC2 -1.63PC1 71.39 · PC2 -23.65PC1 -118.6 · PC2 5.485PC1 56.39 · PC2 -44.71PC1 -152.5 · PC2 102.3PC1 -76.34 · PC2 75.7PC1 -34.88 · PC2 77.59PC1 -92.71 · PC2 60.2PC1 -97.93 · PC2 61.49PC1 -151 · PC2 -0.01439PC1 -46.51 · PC2 -9.566PC1 5.189 · PC2 19.72PC1 -106.3 · PC2 -11.93PC1 -65.07 · PC2 -47.57PC1 17.93 · PC2 -19.72PC1 -177.6 · PC2 23.96PC1 -76.13 · PC2 -74.96PC1 -106.5 · PC2 -36.34PC1 48.87 · PC2 -111.6PC1 22.84 · PC2 -80.86PC1 -115.6 · PC2 -39.41PC1 -73.62 · PC2 -52.01PC1 70.75 · PC2 -8.85PC1 54.01 · PC2 -85.51PC1 21.81 · PC2 -51.93PC1 55.54 · PC2 -32.67PC1 -12.21 · PC2 -54.87PC1 -67.01 · PC2 -5.807PC1 -29.01 · PC2 -27.82PC1 -24.87 · PC2 -25.44PC1 -62.14 · PC2 -17.45PC1 -34.76 · PC2 -14.91PC1 34.99 · PC2 -110.1PC1 69.73 · PC2 -94.83PC1 30.42 · PC2 -79.61PC1 15.86 · PC2 -62.08PC1 -8.97 · PC2 -102.6PC1 18.5 · PC2 -69.31PC1 -37.87 · PC2 -18.43PC1 -124.6 · PC2 42.39PC1 22.43 · PC2 -58.91PC1 14.51 · PC2 -1.272PC1 -106.5 · PC2 -38.21PC1 -60.03 · PC2 -50.73PC1 101 · PC2 -83.59PC1 -121.9 · PC2 -6.176PC1 -46.97 · PC2 2.997PC1 -54.07 · PC2 -8.211PC1 -81.03 · PC2 14.76PC1 209.3 · PC2 37.16PC1 41.71 · PC2 -36.93PC1 25.24 · PC2 -70.26PC1 4.048 · PC2 -33.03PC1 109.8 · PC2 72.56PC1 71.67 · PC2 45.37PC1 64.97 · PC2 -38.84PC1 11.09 · PC2 -70.71PC1 49.15 · PC2 150.5PC1 0.6073 · PC2 85.04PC1 103.6 · PC2 21.79PC1 164.6 · PC2 132.7PC1 -79.24 · PC2 -0.2332PC1 -51.67 · PC2 -84.64PC1 151.7 · PC2 19.28PC1 234 · PC2 -3.75PC1 224.8 · PC2 -64.56PC1 227.7 · PC2 -6.565PC1 115.2 · PC2 -35.16PC1 -59.48 · PC2 26.47PC1 -4.188 · PC2 19.18PC1 49.54 · PC2 109.7PC1 101 · PC2 265.5PC1 124.3 · PC2 204.4PC1 282.3 · PC2 -50.95PC1 93.18 · PC2 111.2PC1 -35.06 · PC2 55.36PC1 18.62 · PC2 60.64PC1 85.44 · PC2 115.4PC1 -109 · PC2 17.18PC1 111.3 · PC2 51.08PC1 -24.4 · PC2 39.65PC1 -88.86 · PC2 70.85PC1 -89.07 · PC2 57.54PC1 -21.13 · PC2 89.8PC1 -32.57 · PC2 64.88PC1 -86.14 · PC2 36.97PC1 -71.89 · PC2 46.36PC1 -101 · PC2 49.99PC1 -9.796 · PC2 82.97PC1 -18.31 · PC2 73.49PC1 -10.86 · PC2 43.91PC1 -14.06 · PC2 36.16PC1 -33.28 · PC2 37.16PC1 4.61 · PC2 50.17PC1 -46.59 · PC2 40.53PC1 -54.09 · PC2 26.87PC1 -0.8975 · PC2 37.62PC1 72.77 · PC2 61.95PC1 68.22 · PC2 90.27PC1 -53.17 · PC2 43.49PC1 28.38 · PC2 31.32PC1 46.65 · PC2 0.9363PC1 60.41 · PC2 -26.86PC1 77.77 · PC2 -39.44PC1 67.84 · PC2 -33.26PC1 -45.86 · PC2 -63.13PC1 -16.42 · PC2 -88.64PC1 -19.78 · PC2 -51.33PC1 23.5 · PC2 -48.06PC1 -15.49 · PC2 -63.97PC1 -14.25 · PC2 -21.78PC1 -5.136 · PC2 -6.258PC1 71.96 · PC2 -35.43PC1 146.3 · PC2 7.088PC1 222.4 · PC2 13.47PC1 116.7 · PC2 -21.21PC1 -2.699 · PC2 34.27PC1 200.2 · PC2 -55.26PC1 138.9 · PC2 0.9134PC1 84.72 · PC2 -3.755PC1 158.5 · PC2 1.608PC1 152.7 · PC2 -92.26PC1 150 · PC2 70.82PC1 -113.6 · PC2 -6.741PC1 -128.2 · PC2 -30.77PC1 -2.835 · PC2 -71.91PC1 -223.7 · PC2 -8.294PC1 -62.26 · PC2 -0.8643PC1 -95.25 · PC2 -1.723PC1 -147.2 · PC2 -45.48PC1 -155.5 · PC2 21.57PC1 -147.8 · PC2 0.7767PC1 -196.6 · PC2 -12.56PC1 -215.5 · PC2 -1.418PC1 -149.1 · PC2 -12.77PC1 -150 · PC2 -18.76PC1 109.4 · PC2 20.47PC1 50.15 · PC2 10.15PC1 4.204 · PC2 21.27PC1 176.6 · PC2 14.56PC1 -181 · PC2 -2.206PC1 -147.8 · PC2 -0.4184PC1 -99.6 · PC2 -39.24PC1 46.14 · PC2 -5.144PC1 136.2 · PC2 58.4PC1 144.7 · PC2 48.4PC1 157.5 · PC2 24.85PC1 -32.97 · PC2 45.5PC1 -81.93 · PC2 55.94PC1 -25.75 · PC2 55.49PC1 -58.42 · PC2 48.44PC1 -14.13 · PC2 25.5PC1 (61.7%)PC2 (22.3%)184 scores
PCA explained variance0%25%50%75%100%PC1: 61.7% (cumulative 61.7%)1PC2: 22.3% (cumulative 84.0%)2PC3: 13.3% (cumulative 97.3%)3PC4: 0.9% (cumulative 98.2%)4PC5: 0.6% (cumulative 98.8%)5PC6: 0.4% (cumulative 99.2%)6PC7: 0.2% (cumulative 99.5%)7PC8: 0.1% (cumulative 99.6%)8PC9: 0.1% (cumulative 99.7%)9PC10: 0.1% (cumulative 99.8%)10cumulative explained variancePC variancecumulativeprincipal component · cumulative (dashed)
X-Y spectral correlation 20
X · pot_size spectral correlation-1-0.500.51absolute correlation envelopesigned correlationabsolute correlation01,0002,0003,000|r|signed raxis · Pearson correlation scale
X · C_pc_dry spectral correlation-1-0.500.51absolute correlation envelopesigned correlationabsolute correlation01,0002,0003,000|r|signed raxis · Pearson correlation scale
X · H_pc_dry spectral correlation-1-0.500.51absolute correlation envelopesigned correlationabsolute correlation01,0002,0003,000|r|signed raxis · Pearson correlation scale
Targetmax |r|axis @ maxmean |r||r| ≥ .5
pot_size0.199800.1070.0%
C_pc_dry0.4471,0740.230.0%
H_pc_dry0.312,0140.1630.0%
N_pc_dry0.6617000.21314.9%
C_N_mass0.4581,9130.3340.0%
LMA_g_m20.4512,2810.2130.0%
H20_g_m20.7321,4770.39649.7%
C_N_m20.7946940.28714.0%
DW_FW0.2811,9250.07820.0%
C_g_m20.4992,2810.2410.0%
N_g_m20.717150.3268.6%
cryo_mass_mg0.1137170.02530.0%
protein_ug_extract0.6957220.25911.3%
starch_nmol_Glc_Extract0.5631,3450.41616.9%
glucose_nmol_Glc_extract0.4869690.3050.0%
fructose_nmol_Glc_extract0.2349420.09640.0%
sucrose_nmol_Glc_extract0.6031,1080.32427.9%
amino_acid_nmol_extract0.3387140.10.0%
nitrate_nmol_extract0.291,9300.1310.0%
protein_ug_mg_fr0.77220.26811.6%

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 46

species

target · categorical
species classesHEAN3HEAN3: 4040POPULPOPUL: 3131CUSA4CUSA4: 2222SOLYLSOLYL: 2020OCBAOCBA: 2020CUPECUPE: 1818GLMA4GLMA4: 1717PHVUPHVU: 1616
n / missing184 / 0
Classes8
Balance (entropy)0.98
Imbalance ratio2
Top classHEAN3 (40)

pot_size

target · numeric
pot_size distribution0501001 – 1.042: 901.042 – 1.083: 01.083 – 1.125: 01.125 – 1.167: 01.167 – 1.208: 01.208 – 1.25: 01.25 – 1.292: 01.292 – 1.333: 01.333 – 1.375: 01.375 – 1.417: 01.417 – 1.458: 01.458 – 1.5: 01.5 – 1.542: 01.542 – 1.583: 01.583 – 1.625: 01.625 – 1.667: 01.667 – 1.708: 01.708 – 1.75: 01.75 – 1.792: 01.792 – 1.833: 01.833 – 1.875: 01.875 – 1.917: 01.917 – 1.958: 01.958 – 2: 9412510
n / missing184 / 0
Mean ± SD1.511 ± 0.501
Median2
Range1 – 2
CV0.332
Skew / kurtosis-0.044 / -2
Normal?no

C_pc_dry

target · numeric
C_pc_dry distribution010203028.56 – 29.28: 129.28 – 30.01: 030.01 – 30.73: 030.73 – 31.45: 031.45 – 32.18: 132.18 – 32.9: 032.9 – 33.63: 233.63 – 34.35: 034.35 – 35.08: 235.08 – 35.8: 035.8 – 36.52: 236.52 – 37.25: 537.25 – 37.97: 637.97 – 38.7: 738.7 – 39.42: 2239.42 – 40.15: 1940.15 – 40.87: 1740.87 – 41.59: 2141.59 – 42.32: 1742.32 – 43.04: 2743.04 – 43.77: 943.77 – 44.49: 1344.49 – 45.22: 845.22 – 45.94: 4102050100
n / missing184 / 1
Mean ± SD40.89 ± 2.66
Median41.1
Range28.56 – 45.94
CV0.065
Skew / kurtosis-0.98 / 2.5
Normal?no

H_pc_dry

target · numeric
H_pc_dry distribution01020303.165 – 3.311: 13.311 – 3.456: 03.456 – 3.602: 03.602 – 3.748: 03.748 – 3.893: 03.893 – 4.039: 04.039 – 4.184: 04.184 – 4.33: 04.33 – 4.476: 04.476 – 4.621: 24.621 – 4.767: 24.767 – 4.912: 14.912 – 5.058: 35.058 – 5.204: 95.204 – 5.349: 185.349 – 5.495: 155.495 – 5.641: 275.641 – 5.786: 295.786 – 5.932: 215.932 – 6.078: 216.078 – 6.223: 196.223 – 6.369: 86.369 – 6.514: 66.514 – 6.66: 112510
n / missing184 / 1
Mean ± SD5.69 ± 0.438
Median5.715
Range3.165 – 6.66
CV0.077
Skew / kurtosis-1.2 / 5.3
Normal?no

N_pc_dry

target · numeric
N_pc_dry distribution010200.705 – 0.9287: 40.9287 – 1.152: 41.152 – 1.376: 51.376 – 1.6: 91.6 – 1.824: 21.824 – 2.047: 52.047 – 2.271: 82.271 – 2.495: 142.495 – 2.719: 202.719 – 2.942: 112.942 – 3.166: 93.166 – 3.39: 123.39 – 3.614: 103.614 – 3.838: 93.838 – 4.061: 74.061 – 4.285: 54.285 – 4.509: 44.509 – 4.732: 74.732 – 4.956: 104.956 – 5.18: 95.18 – 5.404: 75.404 – 5.628: 55.628 – 5.851: 65.851 – 6.075: 102468
n / missing184 / 1
Mean ± SD3.327 ± 1.32
Median3.17
Range0.705 – 6.075
CV0.397
Skew / kurtosis0.15 / -0.87
Normal?no

C_N_mass

target · numeric
C_N_mass distribution010206.03 – 6.155: 16.155 – 6.279: 56.279 – 6.404: 66.404 – 6.528: 26.528 – 6.653: 126.653 – 6.777: 126.777 – 6.902: 136.902 – 7.027: 187.027 – 7.151: 157.151 – 7.276: 157.276 – 7.4: 187.4 – 7.525: 167.525 – 7.65: 177.65 – 7.774: 137.774 – 7.899: 67.899 – 8.023: 58.023 – 8.148: 28.148 – 8.273: 48.273 – 8.397: 18.397 – 8.522: 08.522 – 8.646: 08.646 – 8.771: 18.771 – 8.895: 08.895 – 9.02: 112510
n / missing184 / 1
Mean ± SD7.21 ± 0.505
Median7.21
Range6.03 – 9.02
CV0.0701
Skew / kurtosis0.26 / 0.32
Normal?yes

LMA_g_m2

target · numeric
LMA_g_m2 distribution010203016.1 – 18.36: 518.36 – 20.63: 320.63 – 22.89: 422.89 – 25.15: 925.15 – 27.42: 1027.42 – 29.68: 2129.68 – 31.94: 1031.94 – 34.21: 1534.21 – 36.47: 2236.47 – 38.73: 1338.73 – 41: 1441 – 43.26: 643.26 – 45.52: 1045.52 – 47.79: 247.79 – 50.05: 850.05 – 52.31: 452.31 – 54.58: 654.58 – 56.84: 556.84 – 59.1: 559.1 – 61.37: 361.37 – 63.63: 463.63 – 65.89: 465.89 – 68.16: 068.16 – 70.42: 1020406080
n / missing184 / 0
Mean ± SD37.94 ± 11.8
Median35.81
Range16.1 – 70.42
CV0.312
Skew / kurtosis0.6 / -0.24
Normal?no

H20_g_m2

target · numeric
H20_g_m2 distribution010203092.31 – 99.4: 199.4 – 106.5: 3106.5 – 113.6: 7113.6 – 120.7: 8120.7 – 127.8: 14127.8 – 134.9: 25134.9 – 142: 10142 – 149.1: 15149.1 – 156.2: 14156.2 – 163.3: 14163.3 – 170.3: 11170.3 – 177.4: 8177.4 – 184.5: 9184.5 – 191.6: 8191.6 – 198.7: 6198.7 – 205.8: 11205.8 – 212.9: 8212.9 – 220: 2220 – 227.1: 4227.1 – 234.2: 2234.2 – 241.3: 1241.3 – 248.4: 2248.4 – 255.5: 0255.5 – 262.6: 11020501002005001,000
n / missing184 / 0
Mean ± SD159.2 ± 34.1
Median153.2
Range92.31 – 262.6
CV0.214
Skew / kurtosis0.56 / -0.35
Normal?no

C_N_m2

target · numeric
C_N_m2 distribution02040607.02 – 9.165: 449.165 – 11.31: 2511.31 – 13.46: 2913.46 – 15.6: 2815.6 – 17.75: 2017.75 – 19.89: 919.89 – 22.04: 722.04 – 24.18: 324.18 – 26.33: 026.33 – 28.47: 528.47 – 30.62: 030.62 – 32.76: 532.76 – 34.91: 334.91 – 37.05: 137.05 – 39.2: 039.2 – 41.34: 041.34 – 43.49: 143.49 – 45.63: 045.63 – 47.78: 147.78 – 49.92: 049.92 – 52.07: 152.07 – 54.21: 054.21 – 56.36: 056.36 – 58.5: 10204060
n / missing184 / 1
Mean ± SD14.94 ± 8.1
Median13.21
Range7.02 – 58.5
CV0.542
Skew / kurtosis2.4 / 7.4
Normal?no

DW_FW

target · numeric
DW_FW distribution010200.07837 – 0.08796: 20.08796 – 0.09754: 10.09754 – 0.1071: 20.1071 – 0.1167: 20.1167 – 0.1263: 60.1263 – 0.1359: 40.1359 – 0.1455: 70.1455 – 0.1551: 130.1551 – 0.1647: 100.1647 – 0.1742: 130.1742 – 0.1838: 150.1838 – 0.1934: 170.1934 – 0.203: 150.203 – 0.2126: 140.2126 – 0.2222: 190.2222 – 0.2318: 130.2318 – 0.2414: 110.2414 – 0.2509: 60.2509 – 0.2605: 50.2605 – 0.2701: 30.2701 – 0.2797: 30.2797 – 0.2893: 10.2893 – 0.2989: 10.2989 – 0.3085: 10.010.020.050.10.20.51
n / missing184 / 0
Mean ± SD0.1923 ± 0.0422
Median0.193
Range0.07837 – 0.3085
CV0.219
Skew / kurtosis-0.095 / -0.082
Normal?yes

C_g_m2

target · numeric
C_g_m2 distribution010206.612 – 7.482: 47.482 – 8.353: 58.353 – 9.223: 39.223 – 10.09: 710.09 – 10.96: 1010.96 – 11.83: 1511.83 – 12.7: 1612.7 – 13.57: 1013.57 – 14.44: 1214.44 – 15.31: 1915.31 – 16.19: 1316.19 – 17.06: 1017.06 – 17.93: 1417.93 – 18.8: 318.8 – 19.67: 619.67 – 20.54: 620.54 – 21.41: 721.41 – 22.28: 522.28 – 23.15: 423.15 – 24.02: 424.02 – 24.89: 524.89 – 25.76: 225.76 – 26.63: 226.63 – 27.5: 1125102050100
n / missing184 / 1
Mean ± SD15.42 ± 4.57
Median14.78
Range6.612 – 27.5
CV0.297
Skew / kurtosis0.46 / -0.36
Normal?no

N_g_m2

target · numeric
N_g_m2 distribution010200.2453 – 0.3519: 30.3519 – 0.4586: 90.4586 – 0.5652: 60.5652 – 0.6719: 150.6719 – 0.7786: 110.7786 – 0.8852: 70.8852 – 0.9919: 100.9919 – 1.099: 131.099 – 1.205: 181.205 – 1.312: 161.312 – 1.419: 131.419 – 1.525: 171.525 – 1.632: 101.632 – 1.738: 111.738 – 1.845: 51.845 – 1.952: 51.952 – 2.058: 32.058 – 2.165: 42.165 – 2.272: 12.272 – 2.378: 12.378 – 2.485: 32.485 – 2.592: 12.592 – 2.698: 02.698 – 2.805: 10123
n / missing184 / 1
Mean ± SD1.211 ± 0.507
Median1.196
Range0.2453 – 2.805
CV0.419
Skew / kurtosis0.39 / -0.051
Normal?yes

cryo_mass_mg

target · numeric
cryo_mass_mg distribution0102022.9 – 23.15: 123.15 – 23.4: 123.4 – 23.65: 223.65 – 23.9: 023.9 – 24.15: 124.15 – 24.4: 024.4 – 24.65: 924.65 – 24.9: 524.9 – 25.15: 1925.15 – 25.4: 1125.4 – 25.65: 1525.65 – 25.9: 1025.9 – 26.15: 1326.15 – 26.4: 1026.4 – 26.65: 1826.65 – 26.9: 926.9 – 27.15: 2027.15 – 27.4: 527.4 – 27.65: 1527.65 – 27.9: 927.9 – 28.15: 328.15 – 28.4: 328.4 – 28.65: 328.65 – 28.9: 22224262830
n / missing184 / 0
Mean ± SD26.22 ± 1.16
Median26.25
Range22.9 – 28.9
CV0.0444
Skew / kurtosis-0.092 / -0.35
Normal?yes

protein_ug_extract

target · numeric
protein_ug_extract distribution0102030165 – 218.2: 2218.2 – 271.5: 4271.5 – 324.8: 3324.8 – 378: 6378 – 431.2: 13431.2 – 484.5: 7484.5 – 537.8: 9537.8 – 591: 7591 – 644.2: 10644.2 – 697.5: 14697.5 – 750.8: 12750.8 – 804: 22804 – 857.2: 15857.2 – 910.5: 5910.5 – 963.8: 13963.8 – 1,017: 61,017 – 1070: 71070 – 1124: 61124 – 1177: 61177 – 1,230: 61,230 – 1283: 41283 – 1336: 31336 – 1390: 31390 – 1,443: 105001,0001,500
n / missing184 / 0
Mean ± SD763.7 ± 279
Median763
Range165 – 1,443
CV0.366
Skew / kurtosis0.15 / -0.56
Normal?yes

starch_nmol_Glc_Extract

target · numeric
starch_nmol_Glc_Extract distribution0102014 – 364.9: 12364.9 – 715.8: 7715.8 – 1067: 171067 – 1418: 171418 – 1768: 101768 – 2119: 142119 – 2470: 112470 – 2,821: 112,821 – 3172: 143172 – 3523: 93523 – 3874: 93874 – 4224: 144224 – 4575: 64575 – 4926: 44926 – 5277: 45277 – 5,628: 105,628 – 5979: 65979 – 6330: 46330 – 6681: 06681 – 7032: 17032 – 7382: 17382 – 7733: 07733 – 8084: 08084 – 8,435: 102,5005,0007,50010,000
n / missing184 / 2
Mean ± SD2763 ± 1.78e+03
Median2534
Range14 – 8,435
CV0.645
Skew / kurtosis0.5 / -0.42
Normal?no

glucose_nmol_Glc_extract

target · numeric
glucose_nmol_Glc_extract distribution010203068 – 146.9: 17146.9 – 225.8: 23225.8 – 304.6: 25304.6 – 383.5: 24383.5 – 462.4: 10462.4 – 541.2: 12541.2 – 620.1: 16620.1 – 699: 10699 – 777.9: 6777.9 – 856.8: 8856.8 – 935.6: 9935.6 – 1014: 71014 – 1093: 61093 – 1172: 11172 – 1251: 21251 – 1,330: 11,330 – 1409: 11409 – 1488: 31488 – 1567: 21567 – 1646: 01646 – 1724: 01724 – 1803: 01803 – 1882: 01882 – 1,961: 105001,0001,5002,000
n / missing184 / 0
Mean ± SD516.4 ± 354
Median409
Range68 – 1,961
CV0.685
Skew / kurtosis1.2 / 1.3
Normal?no

fructose_nmol_Glc_extract

target · numeric
fructose_nmol_Glc_extract distribution0102030-3 – 35.25: 1835.25 – 73.5: 2473.5 – 111.8: 24111.8 – 150: 15150 – 188.2: 21188.2 – 226.5: 22226.5 – 264.8: 9264.8 – 303: 10303 – 341.2: 8341.2 – 379.5: 5379.5 – 417.8: 8417.8 – 456: 1456 – 494.2: 3494.2 – 532.5: 3532.5 – 570.8: 2570.8 – 609: 2609 – 647.2: 1647.2 – 685.5: 2685.5 – 723.8: 1723.8 – 762: 1762 – 800.2: 1800.2 – 838.5: 0838.5 – 876.8: 0876.8 – 915: 3-25002505007501,000
n / missing184 / 0
Mean ± SD212.5 ± 185
Median168.5
Range-3 – 915
CV0.871
Skew / kurtosis1.6 / 2.9
Normal?no

sucrose_nmol_Glc_extract

target · numeric
sucrose_nmol_Glc_extract distribution010203014 – 129.8: 4129.8 – 245.7: 16245.7 – 361.5: 28361.5 – 477.3: 15477.3 – 593.2: 13593.2 – 709: 23709 – 824.8: 13824.8 – 940.7: 8940.7 – 1056: 211056 – 1172: 41172 – 1288: 41288 – 1,404: 31,404 – 1520: 11520 – 1636: 11636 – 1752: 41752 – 1867: 41867 – 1983: 41983 – 2,099: 32,099 – 2215: 22215 – 2331: 32331 – 2446: 32446 – 2562: 02562 – 2678: 42678 – 2,794: 301,0002,0003,000
n / missing184 / 0
Mean ± SD866.1 ± 668
Median666
Range14 – 2,794
CV0.772
Skew / kurtosis1.3 / 0.85
Normal?no

amino_acid_nmol_extract

target · numeric
amino_acid_nmol_extract distribution010203024 – 82.62: 1582.62 – 141.2: 22141.2 – 199.9: 18199.9 – 258.5: 18258.5 – 317.1: 21317.1 – 375.8: 12375.8 – 434.4: 17434.4 – 493: 13493 – 551.6: 8551.6 – 610.2: 3610.2 – 668.9: 5668.9 – 727.5: 3727.5 – 786.1: 6786.1 – 844.8: 2844.8 – 903.4: 5903.4 – 962: 0962 – 1021: 11021 – 1079: 21079 – 1138: 11138 – 1196: 61196 – 1255: 01255 – 1314: 11314 – 1372: 01372 – 1,431: 105001,0001,500
n / missing184 / 4
Mean ± SD385 ± 292
Median306.5
Range24 – 1,431
CV0.759
Skew / kurtosis1.3 / 1.4
Normal?no

nitrate_nmol_extract

target · numeric
nitrate_nmol_extract distribution050100150-7 – 52.21: 10852.21 – 111.4: 14111.4 – 170.6: 12170.6 – 229.8: 5229.8 – 289: 4289 – 348.2: 10348.2 – 407.5: 6407.5 – 466.7: 0466.7 – 525.9: 5525.9 – 585.1: 4585.1 – 644.3: 1644.3 – 703.5: 2703.5 – 762.7: 1762.7 – 821.9: 1821.9 – 881.1: 1881.1 – 940.3: 5940.3 – 999.5: 1999.5 – 1059: 11059 – 1118: 01118 – 1177: 01177 – 1236: 21236 – 1296: 01296 – 1355: 01355 – 1,414: 1-50005001,0001,500
n / missing184 / 0
Mean ± SD175.1 ± 275
Median42.5
Range-7 – 1,414
CV1.57
Skew / kurtosis2.2 / 4.9
Normal?no

protein_ug_mg_fr

target · numeric
protein_ug_mg_fr distribution010206 – 8: 18 – 10: 210 – 12: 512 – 14: 214 – 16: 1216 – 18: 818 – 20: 720 – 22: 1122 – 24: 724 – 26: 1026 – 28: 1728 – 30: 1030 – 32: 1932 – 34: 1434 – 36: 1036 – 38: 838 – 40: 1040 – 42: 542 – 44: 644 – 46: 946 – 48: 648 – 50: 250 – 52: 052 – 54: 30204060
n / missing184 / 0
Mean ± SD29.08 ± 10.4
Median29.5
Range6 – 54
CV0.357
Skew / kurtosis0.069 / -0.58
Normal?yes

starch_nmol_Glc_mg_fr

target · numeric
starch_nmol_Glc_mg_fr distribution010201 – 14.79: 1314.79 – 28.58: 928.58 – 42.38: 1542.38 – 56.17: 1656.17 – 69.96: 1469.96 – 83.75: 1283.75 – 97.54: 1197.54 – 111.3: 14111.3 – 125.1: 14125.1 – 138.9: 9138.9 – 152.7: 12152.7 – 166.5: 8166.5 – 180.3: 7180.3 – 194.1: 2194.1 – 207.9: 7207.9 – 221.7: 8221.7 – 235.5: 4235.5 – 249.2: 3249.2 – 263: 2263 – 276.8: 0276.8 – 290.6: 0290.6 – 304.4: 1304.4 – 318.2: 0318.2 – 332: 10100200300400
n / missing184 / 2
Mean ± SD105.5 ± 68.6
Median99
Range1 – 332
CV0.65
Skew / kurtosis0.58 / -0.19
Normal?no

glucose_nmol_Glc_mg_fr

target · numeric
glucose_nmol_Glc_mg_fr distribution01020303 – 5.917: 165.917 – 8.833: 248.833 – 11.75: 2311.75 – 14.67: 2014.67 – 17.58: 1717.58 – 20.5: 1120.5 – 23.42: 1523.42 – 26.33: 626.33 – 29.25: 1429.25 – 32.17: 632.17 – 35.08: 635.08 – 38: 738 – 40.92: 740.92 – 43.83: 243.83 – 46.75: 146.75 – 49.67: 149.67 – 52.58: 252.58 – 55.5: 255.5 – 58.42: 258.42 – 61.33: 161.33 – 64.25: 064.25 – 67.17: 067.17 – 70.08: 070.08 – 73: 1020406080
n / missing184 / 0
Mean ± SD19.7 ± 13.5
Median16
Range3 – 73
CV0.683
Skew / kurtosis1.2 / 1.3
Normal?no

fructose_nmol_Glc_mg_fr

target · numeric
fructose_nmol_Glc_mg_fr distribution020400 – 1.458: 191.458 – 2.917: 162.917 – 4.375: 324.375 – 5.833: 125.833 – 7.292: 267.292 – 8.75: 178.75 – 10.21: 1510.21 – 11.67: 511.67 – 13.12: 1213.12 – 14.58: 214.58 – 16.04: 916.04 – 17.5: 017.5 – 18.96: 118.96 – 20.42: 720.42 – 21.88: 021.88 – 23.33: 223.33 – 24.79: 124.79 – 26.25: 226.25 – 27.71: 027.71 – 29.17: 229.17 – 30.62: 130.62 – 32.08: 032.08 – 33.54: 133.54 – 35: 2010203040
n / missing184 / 0
Mean ± SD8.12 ± 7.07
Median6
Range0 – 35
CV0.87
Skew / kurtosis1.6 / 2.9
Normal?no

sucrose_nmol_Glc_mg_fr

target · numeric
sucrose_nmol_Glc_mg_fr distribution01020301 – 5.333: 65.333 – 9.667: 169.667 – 14: 2214 – 18.33: 2018.33 – 22.67: 1422.67 – 27: 1827 – 31.33: 1531.33 – 35.67: 1135.67 – 40: 1740 – 44.33: 844.33 – 48.67: 248.67 – 53: 253 – 57.33: 257.33 – 61.67: 061.67 – 66: 366 – 70.33: 570.33 – 74.67: 474.67 – 79: 379 – 83.33: 283.33 – 87.67: 087.67 – 92: 592 – 96.33: 396.33 – 100.7: 1100.7 – 105: 5050100150
n / missing184 / 0
Mean ± SD33.12 ± 25.6
Median26
Range1 – 105
CV0.774
Skew / kurtosis1.3 / 0.79
Normal?no

aa_nmol_mg_fr

target · numeric
aa_nmol_mg_fr distribution01020301 – 3.375: 163.375 – 5.75: 195.75 – 8.125: 298.125 – 10.5: 1410.5 – 12.88: 1912.88 – 15.25: 1815.25 – 17.62: 1417.62 – 20: 820 – 22.38: 1022.38 – 24.75: 324.75 – 27.12: 727.12 – 29.5: 229.5 – 31.88: 431.88 – 34.25: 434.25 – 36.62: 136.62 – 39: 139 – 41.38: 341.38 – 43.75: 443.75 – 46.12: 146.12 – 48.5: 148.5 – 50.88: 150.88 – 53.25: 053.25 – 55.62: 055.62 – 58: 10204060
n / missing184 / 4
Mean ± SD14.67 ± 11.1
Median12
Range1 – 58
CV0.754
Skew / kurtosis1.4 / 1.7
Normal?no

nitrate_nmol_mg_fr

target · numeric
nitrate_nmol_mg_fr distribution0501001500 – 2.167: 1112.167 – 4.333: 124.333 – 6.5: 116.5 – 8.667: 58.667 – 10.83: 310.83 – 13: 713 – 15.17: 815.17 – 17.33: 217.33 – 19.5: 319.5 – 21.67: 421.67 – 23.83: 223.83 – 26: 126 – 28.17: 428.17 – 30.33: 030.33 – 32.5: 332.5 – 34.67: 134.67 – 36.83: 236.83 – 39: 239 – 41.17: 041.17 – 43.33: 043.33 – 45.5: 145.5 – 47.67: 147.67 – 49.83: 049.83 – 52: 10204060
n / missing184 / 0
Mean ± SD6.679 ± 10.3
Median2
Range0 – 52
CV1.54
Skew / kurtosis2.2 / 4.5
Normal?no

protein_ug_mg_DW

target · numeric
protein_ug_mg_DW distribution0102045 – 54.67: 654.67 – 64.33: 564.33 – 74: 574 – 83.67: 683.67 – 93.33: 393.33 – 103: 4103 – 112.7: 8112.7 – 122.3: 7122.3 – 132: 15132 – 141.7: 16141.7 – 151.3: 15151.3 – 161: 9161 – 170.7: 16170.7 – 180.3: 11180.3 – 190: 10190 – 199.7: 7199.7 – 209.3: 16209.3 – 219: 5219 – 228.7: 6228.7 – 238.3: 3238.3 – 248: 2248 – 257.7: 6257.7 – 267.3: 0267.3 – 277: 30100200300
n / missing184 / 0
Mean ± SD154.4 ± 52.6
Median154.5
Range45 – 277
CV0.341
Skew / kurtosis-0.033 / -0.42
Normal?yes

starch_nmol_Glc_mg_DW

target · numeric
starch_nmol_Glc_mg_DW distribution0510153 – 60.83: 1160.83 – 118.7: 6118.7 – 176.5: 12176.5 – 234.3: 6234.3 – 292.2: 14292.2 – 350: 11350 – 407.8: 10407.8 – 465.7: 9465.7 – 523.5: 13523.5 – 581.3: 10581.3 – 639.2: 13639.2 – 697: 7697 – 754.8: 9754.8 – 812.7: 4812.7 – 870.5: 7870.5 – 928.3: 10928.3 – 986.2: 6986.2 – 1,044: 81,044 – 1102: 51102 – 1160: 51160 – 1218: 21218 – 1275: 11275 – 1333: 11333 – 1,391: 205001,0001,500
n / missing184 / 2
Mean ± SD552.1 ± 338
Median519.5
Range3 – 1,391
CV0.612
Skew / kurtosis0.32 / -0.77
Normal?no

glucose_nmol_Glc_mg_DW

target · numeric
glucose_nmol_Glc_mg_DW distribution010203011 – 27.08: 1427.08 – 43.17: 1943.17 – 59.25: 2559.25 – 75.33: 2175.33 – 91.42: 1691.42 – 107.5: 11107.5 – 123.6: 20123.6 – 139.7: 16139.7 – 155.8: 10155.8 – 171.8: 9171.8 – 187.9: 7187.9 – 204: 2204 – 220.1: 2220.1 – 236.2: 2236.2 – 252.2: 2252.2 – 268.3: 4268.3 – 284.4: 1284.4 – 300.5: 0300.5 – 316.6: 0316.6 – 332.7: 1332.7 – 348.8: 1348.8 – 364.8: 0364.8 – 380.9: 0380.9 – 397: 10100200300400
n / missing184 / 0
Mean ± SD102.6 ± 66.8
Median88.5
Range11 – 397
CV0.651
Skew / kurtosis1.3 / 2.5
Normal?no

fructose_nmol_Glc_mg_DW

target · numeric
fructose_nmol_Glc_mg_DW distribution0204060-1 – 12.71: 3412.71 – 26.42: 4126.42 – 40.12: 4040.12 – 53.83: 2253.83 – 67.54: 1567.54 – 81.25: 681.25 – 94.96: 494.96 – 108.7: 4108.7 – 122.4: 7122.4 – 136.1: 2136.1 – 149.8: 2149.8 – 163.5: 0163.5 – 177.2: 2177.2 – 190.9: 0190.9 – 204.6: 1204.6 – 218.3: 2218.3 – 232: 0232 – 245.8: 1245.8 – 259.5: 0259.5 – 273.2: 0273.2 – 286.9: 0286.9 – 300.6: 0300.6 – 314.3: 0314.3 – 328: 1-1000100200300400
n / missing184 / 0
Mean ± SD45.49 ± 47.8
Median31.5
Range-1 – 328
CV1.05
Skew / kurtosis2.6 / 9.1
Normal?no

sucrose_nmol_Glc_mg_DW

target · numeric
sucrose_nmol_Glc_mg_DW distribution01020304 – 24.83: 424.83 – 45.67: 845.67 – 66.5: 1866.5 – 87.33: 2187.33 – 108.2: 16108.2 – 129: 19129 – 149.8: 16149.8 – 170.7: 20170.7 – 191.5: 15191.5 – 212.3: 5212.3 – 233.2: 6233.2 – 254: 1254 – 274.8: 1274.8 – 295.7: 4295.7 – 316.5: 3316.5 – 337.3: 4337.3 – 358.2: 3358.2 – 379: 5379 – 399.8: 5399.8 – 420.7: 3420.7 – 441.5: 1441.5 – 462.3: 1462.3 – 483.2: 3483.2 – 504: 20200400600
n / missing184 / 0
Mean ± SD166.3 ± 114
Median136
Range4 – 504
CV0.686
Skew / kurtosis1.2 / 0.6
Normal?no

aa_nmol_mg_DW

target · numeric
aa_nmol_mg_DW distribution010206 – 16.17: 1616.17 – 26.33: 1726.33 – 36.5: 1336.5 – 46.67: 1746.67 – 56.83: 1356.83 – 67: 1867 – 77.17: 1277.17 – 87.33: 1187.33 – 97.5: 997.5 – 107.7: 14107.7 – 117.8: 6117.8 – 128: 5128 – 138.2: 4138.2 – 148.3: 2148.3 – 158.5: 5158.5 – 168.7: 4168.7 – 178.8: 0178.8 – 189: 3189 – 199.2: 1199.2 – 209.3: 1209.3 – 219.5: 3219.5 – 229.7: 2229.7 – 239.8: 2239.8 – 250: 20100200300
n / missing184 / 4
Mean ± SD78.03 ± 56.2
Median64
Range6 – 250
CV0.721
Skew / kurtosis1.1 / 0.83
Normal?no

nitrate_nmol_mg_DW

target · numeric
nitrate_nmol_mg_DW distribution050100150-1 – 16.12: 12016.12 – 33.25: 1433.25 – 50.38: 1050.38 – 67.5: 767.5 – 84.62: 384.62 – 101.8: 6101.8 – 118.9: 3118.9 – 136: 2136 – 153.1: 1153.1 – 170.2: 1170.2 – 187.4: 3187.4 – 204.5: 2204.5 – 221.6: 3221.6 – 238.8: 1238.8 – 255.9: 3255.9 – 273: 1273 – 290.1: 0290.1 – 307.2: 1307.2 – 324.4: 2324.4 – 341.5: 0341.5 – 358.6: 0358.6 – 375.8: 0375.8 – 392.9: 0392.9 – 410: 1-2000200400600
n / missing184 / 0
Mean ± SD41.55 ± 73.1
Median8
Range-1 – 410
CV1.76
Skew / kurtosis2.5 / 6.3
Normal?no

protein_mg_m2

target · numeric
protein_mg_m2 distribution010201.31 – 1.758: 21.758 – 2.207: 62.207 – 2.655: 102.655 – 3.103: 93.103 – 3.552: 93.552 – 4: 84 – 4.448: 154.448 – 4.897: 114.897 – 5.345: 175.345 – 5.793: 105.793 – 6.242: 116.242 – 6.69: 136.69 – 7.138: 117.138 – 7.587: 137.587 – 8.035: 88.035 – 8.483: 108.483 – 8.932: 68.932 – 9.38: 109.38 – 9.828: 19.828 – 10.28: 210.28 – 10.72: 010.72 – 11.17: 011.17 – 11.62: 111.62 – 12.07: 1051015
n / missing184 / 0
Mean ± SD5.678 ± 2.2
Median5.56
Range1.31 – 12.07
CV0.387
Skew / kurtosis0.18 / -0.6
Normal?no

starch_umol_Glc_m2

target · numeric
starch_umol_Glc_m2 distribution0510150.09 – 2.45: 132.45 – 4.81: 84.81 – 7.17: 97.17 – 9.53: 139.53 – 11.89: 1311.89 – 14.25: 1314.25 – 16.61: 1216.61 – 18.97: 1218.97 – 21.33: 1021.33 – 23.69: 923.69 – 26.05: 1126.05 – 28.41: 1328.41 – 30.77: 730.77 – 33.13: 633.13 – 35.49: 735.49 – 37.85: 437.85 – 40.21: 540.21 – 42.57: 642.57 – 44.93: 344.93 – 47.29: 247.29 – 49.65: 049.65 – 52.01: 252.01 – 54.37: 254.37 – 56.73: 20204060
n / missing184 / 2
Mean ± SD20.43 ± 13.2
Median18.46
Range0.09 – 56.73
CV0.648
Skew / kurtosis0.57 / -0.25
Normal?no

glucose_umol_Glc_m2

target · numeric
glucose_umol_Glc_m2 distribution01020300.38 – 0.8829: 90.8829 – 1.386: 251.386 – 1.889: 211.889 – 2.392: 232.392 – 2.895: 122.895 – 3.397: 153.397 – 3.9: 93.9 – 4.403: 104.403 – 4.906: 64.906 – 5.409: 75.409 – 5.912: 65.912 – 6.415: 26.415 – 6.918: 76.918 – 7.421: 67.421 – 7.924: 37.924 – 8.427: 18.427 – 8.93: 28.93 – 9.432: 69.432 – 9.935: 49.935 – 10.44: 410.44 – 10.94: 210.94 – 11.44: 211.44 – 11.95: 011.95 – 12.45: 2051015
n / missing184 / 0
Mean ± SD3.945 ± 2.92
Median2.985
Range0.38 – 12.45
CV0.739
Skew / kurtosis1.1 / 0.17
Normal?no

fructose_umol_Glc_m2

target · numeric
fructose_umol_Glc_m2 distribution02040-0.02 – 0.3312: 220.3312 – 0.6825: 360.6825 – 1.034: 171.034 – 1.385: 171.385 – 1.736: 251.736 – 2.087: 252.087 – 2.439: 122.439 – 2.79: 62.79 – 3.141: 63.141 – 3.493: 63.493 – 3.844: 33.844 – 4.195: 14.195 – 4.546: 24.546 – 4.898: 14.898 – 5.249: 15.249 – 5.6: 15.6 – 5.951: 05.951 – 6.303: 06.303 – 6.654: 06.654 – 7.005: 17.005 – 7.356: 07.356 – 7.708: 17.708 – 8.059: 08.059 – 8.41: 1-2.50.02.55.07.510.0
n / missing184 / 0
Mean ± SD1.547 ± 1.34
Median1.37
Range-0.02 – 8.41
CV0.865
Skew / kurtosis2.1 / 6.4
Normal?no

sucrose_umol_Glc_m2

target · numeric
sucrose_umol_Glc_m2 distribution010200.11 – 0.8342: 30.8342 – 1.558: 151.558 – 2.282: 192.282 – 3.007: 173.007 – 3.731: 193.731 – 4.455: 124.455 – 5.179: 85.179 – 5.903: 85.903 – 6.628: 96.628 – 7.352: 107.352 – 8.076: 78.076 – 8.8: 88.8 – 9.524: 69.524 – 10.25: 1010.25 – 10.97: 210.97 – 11.7: 311.7 – 12.42: 312.42 – 13.14: 313.14 – 13.87: 413.87 – 14.59: 314.59 – 15.32: 415.32 – 16.04: 516.04 – 16.77: 216.77 – 17.49: 405101520
n / missing184 / 0
Mean ± SD6.329 ± 4.48
Median5.125
Range0.11 – 17.49
CV0.708
Skew / kurtosis0.81 / -0.37
Normal?no

aa_umol_m2

target · numeric
aa_umol_m2 distribution020400.14 – 0.7442: 210.7442 – 1.348: 291.348 – 1.953: 321.953 – 2.557: 222.557 – 3.161: 93.161 – 3.765: 153.765 – 4.369: 184.369 – 4.973: 64.973 – 5.577: 55.577 – 6.182: 66.182 – 6.786: 66.786 – 7.39: 07.39 – 7.994: 47.994 – 8.598: 08.598 – 9.203: 39.203 – 9.807: 09.807 – 10.41: 110.41 – 11.02: 011.02 – 11.62: 111.62 – 12.22: 112.22 – 12.83: 012.83 – 13.43: 013.43 – 14.04: 014.04 – 14.64: 1051015
n / missing184 / 4
Mean ± SD2.923 ± 2.39
Median2.2
Range0.14 – 14.64
CV0.818
Skew / kurtosis1.7 / 4.2
Normal?no

nitrate_umol_m2

target · numeric
nitrate_umol_m2 distribution050100-0.05 – 0.3458: 970.3458 – 0.7417: 210.7417 – 1.137: 171.137 – 1.533: 71.533 – 1.929: 21.929 – 2.325: 62.325 – 2.721: 32.721 – 3.117: 13.117 – 3.513: 43.513 – 3.908: 23.908 – 4.304: 54.304 – 4.7: 24.7 – 5.096: 15.096 – 5.492: 45.492 – 5.888: 05.888 – 6.283: 26.283 – 6.679: 26.679 – 7.075: 17.075 – 7.471: 07.471 – 7.867: 17.867 – 8.262: 08.262 – 8.658: 48.658 – 9.054: 19.054 – 9.45: 1-2.50.02.55.07.510.0
n / missing184 / 0
Mean ± SD1.329 ± 2.12
Median0.3
Range-0.05 – 9.45
CV1.59
Skew / kurtosis2.2 / 4
Normal?no

H2O_pc

target · numeric
H2O_pc distribution0102069.15 – 70.11: 170.11 – 71.07: 171.07 – 72.03: 172.03 – 72.99: 372.99 – 73.95: 373.95 – 74.91: 574.91 – 75.86: 675.86 – 76.82: 1176.82 – 77.78: 1377.78 – 78.74: 1978.74 – 79.7: 1479.7 – 80.66: 1580.66 – 81.62: 1781.62 – 82.58: 1582.58 – 83.54: 1383.54 – 84.49: 1084.49 – 85.45: 1385.45 – 86.41: 786.41 – 87.37: 487.37 – 88.33: 688.33 – 89.29: 389.29 – 90.25: 190.25 – 91.21: 191.21 – 92.16: 2102050100
n / missing184 / 0
Mean ± SD80.77 ± 4.22
Median80.7
Range69.15 – 92.16
CV0.0522
Skew / kurtosis0.095 / -0.082
Normal?yes

TNC_nmol_Glc_mg

target · numeric
TNC_nmol_Glc_mg distribution01020134 – 205.2: 3205.2 – 276.3: 2276.3 – 347.5: 5347.5 – 418.7: 4418.7 – 489.8: 9489.8 – 561: 9561 – 632.2: 10632.2 – 703.3: 18703.3 – 774.5: 12774.5 – 845.7: 17845.7 – 916.8: 12916.8 – 988: 11988 – 1059: 171059 – 1130: 171130 – 1202: 111202 – 1273: 121273 – 1344: 51344 – 1,415: 21,415 – 1486: 11486 – 1557: 11557 – 1628: 21628 – 1700: 11700 – 1771: 01771 – 1,842: 105001,0001,5002,000
n / missing184 / 2
Mean ± SD865.6 ± 315
Median852.5
Range134 – 1,842
CV0.364
Skew / kurtosis0.081 / -0.069
Normal?yes

all_sugar_nmol_Glc_mg

target · numeric
all_sugar_nmol_Glc_mg distribution0102048 – 77.58: 877.58 – 107.2: 8107.2 – 136.8: 9136.8 – 166.3: 11166.3 – 195.9: 13195.9 – 225.5: 15225.5 – 255.1: 13255.1 – 284.7: 10284.7 – 314.2: 12314.2 – 343.8: 20343.8 – 373.4: 12373.4 – 403: 2403 – 432.6: 9432.6 – 462.2: 7462.2 – 491.8: 5491.8 – 521.3: 7521.3 – 550.9: 3550.9 – 580.5: 4580.5 – 610.1: 2610.1 – 639.7: 3639.7 – 669.2: 5669.2 – 698.8: 4698.8 – 728.4: 0728.4 – 758: 20200400600800
n / missing184 / 0
Mean ± SD314.4 ± 165
Median295
Range48 – 758
CV0.526
Skew / kurtosis0.61 / -0.26
Normal?no

TNC_umol_Glc_m2

target · numeric
TNC_umol_Glc_m2 distribution010202.77 – 5.773: 45.773 – 8.776: 38.776 – 11.78: 411.78 – 14.78: 814.78 – 17.78: 517.78 – 20.79: 1820.79 – 23.79: 1123.79 – 26.79: 1226.79 – 29.8: 1429.8 – 32.8: 1532.8 – 35.8: 1835.8 – 38.81: 1338.81 – 41.81: 1541.81 – 44.81: 1344.81 – 47.81: 547.81 – 50.82: 1050.82 – 53.82: 553.82 – 56.82: 356.82 – 59.83: 359.83 – 62.83: 162.83 – 65.83: 065.83 – 68.83: 068.83 – 71.84: 171.84 – 74.84: 1020406080
n / missing184 / 2
Mean ± SD32.2 ± 13.3
Median32.14
Range2.77 – 74.84
CV0.414
Skew / kurtosis0.21 / -0.004
Normal?yes

all_sug_umol_Glc_m2

target · numeric
all_sug_umol_Glc_m2 distribution010201.4 – 2.523: 72.523 – 3.647: 133.647 – 4.77: 124.77 – 5.893: 125.893 – 7.017: 127.017 – 8.14: 168.14 – 9.263: 89.263 – 10.39: 810.39 – 11.51: 911.51 – 12.63: 912.63 – 13.76: 813.76 – 14.88: 514.88 – 16: 916 – 17.13: 517.13 – 18.25: 918.25 – 19.37: 1219.37 – 20.5: 520.5 – 21.62: 721.62 – 22.74: 922.74 – 23.87: 223.87 – 24.99: 424.99 – 26.11: 126.11 – 27.24: 027.24 – 28.36: 20102030
n / missing184 / 0
Mean ± SD11.82 ± 6.69
Median10.94
Range1.4 – 28.36
CV0.566
Skew / kurtosis0.35 / -0.98
Normal?no
Constant metadata 19
  • ecosis_resource_id8d4fa096-d8cd-4ba2-91b4-fe18c6877794
  • locationUpton, NY, USA
  • coordinate_precision_notessource-provided coordinates when available
  • year2,018
  • plant_partLeaf
  • canopy_or_leafleaf
  • instrumentSpectravista Corporation HR-1024i
  • acquisition_modeContact
  • signal_typereflectance
  • axis_unitnm
  • axis_min350
  • axis_max2,500
  • n_points_original2,151
  • publication_doi10.1093/jxb/erz061 | 10.21232/C2GM2Z | 10.21232/c2gm2z
  • citationEly K.S. Serbin S.P. Lieberman-Cribbin W. Rogers A.. 2018. Leaf spectra, structural and biochemical leaf traits of eight crop species. Data set. Available on-line [http://ecosis.org] from the Ecological Spectral Information System (EcoSIS). doi:10.21232/C2GM2Z
  • licenseOpen Data Commons Attribution License
  • rights_statusexplicit_open
  • usage_scopepublic_reuse_possible
  • notesEcoSIS package leaf-spectra--structural-and-biochemical-leaf-traits-of-eight-crop-species, no interpolation applied by project.

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

Alignment

Alignment levelobservation
Sample id availableyes
Samples184
Observations (total)184
Reps per samplemin 1 · mean 1 · max 1

Provenance & citation

ContributorLeaf spectra, structural and biochemical leaf traits of eight crop species
Origin · url [open]https://data.ecosis.org/dataset/leaf-spectra--structural-and-biochemical-leaf-traits-of-eight-crop-species
Origin · script [manual]source_to_standard.py — standardization script (maintainer-only)
Publication10.1093/jxb/erz061 — Kim S Ely, Angela C Burnett, Wil Lieberman-Cribbin, Shawn P Serbin, Alistair Rogers, Spectroscopy can predict key leaf traits associated with source–sink balance and carbon–nitrogen status, Journal of Experimental Botany, Volume 70, Issue 6, 1 March 2019, Pages 1789–1799
Publication10.21232/C2GM2Z — Leaf spectra, structural and biochemical leaf traits of eight crop species
Publication10.21232/c2gm2z

Governance & integrity

Tierpublic
LicenseODC-By-1.0
Permitted useResearch and benchmarking.
Access policyOpen per source license.
RedistributionEcoSIS CKAN metadata exposes an open license.
Content version1.0.0
Schema / protocol2.0
Content hash0881ee48eaeb5fc6…
Processing hashb6e7262b0164612b…
Metadata hashd88cc5ca98535cb2…

Load this dataset

# pip install nirs4all-datasets
from nirs4all_datasets import get

ds = get("ecosis_leaf_spectra_structural_and_biochemical_leaf_traits_of_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.