Search claims · PlantClaims

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

The best NIR model had a small difference between RMSEC and RMSEP, with an RMSEP of 5.49.

Outcome: RMSEPe1
Value: 5.49e1

Verbatim

e1
“RMSEP (5.49)”
✓ located verbatim in the source · abstract, characters 1190–1202

Title

Measuring the chlorophyll content in leaves by near infrared analysis

Huanyu Jiang; Yingshi Bao; Yibin Ying Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE 2005. doi:10.1117/12.630055

Other claims from this paper (4)

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

RMSEP was lowest at correction factor 0.27, with RMSEP 9.74929.

Taxon: Cannabis sativa L.Cannabis sativat0
Outcome: RMSEPe0
Direction: minimume0
Value: RMSEP=9.74929e0
Qualifier: correction factor (0.27)e0

Verbatim

t0
“Cannabis sativa L.”
✓ located verbatim in the source · title, characters 61–79

e0
“The calculation of the RMSEP parameter confirmed the value of the correction factor (0.27), at which the RMSEP value was the minimum (RMSEP=9.74929).”
✓ located verbatim in the source · abstract, characters 1005–1154

Title

NON-DESTRUCTIVE METHOD TO DETERMINING THE LEAF AREA IN HEMP, Cannabis sativa L.

Florin SALA; Ciprian BUZNA LIFE SCIENCE AND SUSTAINABLE DEVELOPMENT 2022. doi:10.58509/7dpzcw74

Other claims from this paper (9)

Method / resource A correction factor of 0.27 minimized area error at 0.87 cm2.
Method / resource Measured and scanned leaf area fitted linearly with R2 0.952.
Method / resource A cubic equation related scanned leaf area and leaf length with R2 0.932.
Method / resource A cubic equation related scanned leaf area and width with R 0.964.
Method / resource A quadratic equation related scanned area and perimeter with R2 0.995.
Association Measured area correlated with length at r 0.969.
Association Measured area correlated with width at r 0.974.
Association Scanned area correlated with length at r 0.927.
Association Scanned area correlated with width at r 0.957.

Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

Production RMSEP was 50.1633 for B/A80.

Taxon: barleyHordeum vulgaree2
Material: YB/A80e0
Outcome: RMSEPe0
Value: 50.1633e0

Verbatim

e0
“RMSEP=50.1633 for YB/A80, RMSEP=192.3947”
✓ located verbatim in the source · abstract, characters 1218–1258

e1
“for the estimated productions”
✓ located verbatim in the source · abstract, characters 1135–1164

e2
“barley crops”
✓ located verbatim in the source · abstract, characters 52–64

Title

Model for estimating barley production based on satellite images

Florin Sala; Mihai Herbei Journal of Central European Agriculture 2022. doi:10.5513/jcea01/23.3.3515

Other claims from this paper (9)

Method / resource Second-degree polynomial models described temporal variation of MSAVI2 and NDVI with statistical accuracy.
Method / resource Regression estimated production for plot B/A75 with R2=0.998 and P<0.05.
Method / resource Regression estimated production for plot B/A80 with R2=0.999 and P<0.05.
Method / resource Regression estimated production for plot B/A82 with R2=0.997 and P=0.0577.
Method / resource Regression estimated production for plot B/A84 with R2=0.999 and P<0.05.
Method / resource Production RMSEP was 80.8162 for B/A75.
Method / resource Production RMSEP was 192.3947 for B/A82.
Method / resource Production RMSEP was 112.2899 for B/A84.
Method / resource B/A80 had the highest precision production estimate.

Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

External validation gave an RMSEP of 0.18.

Taxon: fructus forsythiaet0
Outcome: RMSEPe0
Value: 0.18e0

Verbatim

e0
“the RMSEP was 0.18”
✓ located verbatim in the source · abstract, characters 728–746

t0
“fructus forsythiae”
✓ located verbatim in the source · title, characters 36–54

Title

[Determination of forsythoside A in fructus forsythiae by NIR].

Xing Wang; Yan Bai; Zhihong Chen; et al. PubMed 2009

Other claims from this paper (4)

Method / resource The calibration model had an RMSECV of 0.221.
Method / resource The calibration model correlation coefficient was 0.969.
Method / resource External validation gave a predicted versus HPLC relative coefficient of 0.961.
Recommendation The authors conclude NIRS can determine forsythoside A content for product-line control.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

BOSS reduced batch-specific model RMSEP by 13%.

Taxon: mangoMangifera indicat0
Treatment: BOSSe0
Outcome: RMSEPe0
Direction: reductione0
Value: 13%e0

Verbatim

e0
“a 13% reduction in RMSEP when BOSS was applied”
✓ located verbatim in the source · abstract, characters 1000–1046

t0
“mango”
✓ located verbatim in the source · title, characters 22–27

Title

Assessing firmness in mango comparing broadband and miniature spectrophotometers

Nur Fauzana Mohd Kasim; Puneet Mishra; Rob E. Schouten; et al. Infrared Physics & Technology 2021. doi:10.1016/j.infrared.2021.103733

Other claims from this paper (6)

Method / resource SCiO and laboratory instrument had similar prediction R2 for firmness.
Method / resource The laboratory instrument had slightly lower RMSEP than SCiO.
Method / resource BOSS improved batch-specific model R2 by up to 8%.
Method / resource Global models predicted firmness with R2 of 0.74–0.93 depending on batch.
Method / resource Global models predicted firmness with RMSEP of 4.8 – 8.2 Hz2g2/3 depending on batch.
Recommendation The authors judge SCiO a potential inexpensive nondestructive mango firmness tool.

Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

Ciprian leaf-area RMSEP was 1.32042.

Taxon: WHEATTriticum aestivumt0
Material: Cipriane0
Outcome: RMSEPe0
Value: 1.32042e0

Verbatim

t0
“WHEAT”
✓ located verbatim in the source · title, characters 73–78

e0
“RMSEP=1.32042 for Ciprian cultivar”
✓ located verbatim in the source · abstract, characters 892–926

Title

LEAF AREA IN GRASS CEREALS IN RELATION TO LEAF PARAMETERS; CASE STUDY IN WHEAT

Alina Laura AGAPIE; Florin SALA LIFE SCIENCE AND SUSTAINABLE DEVELOPMENT 2023. doi:10.58509/f58ex328

Other claims from this paper (14)

Method / resource Ciprian correction factor was 0.79.
Method / resource Dacic correction factor was 0.80.
Method / resource Glosa correction factor was 0.78.
Method / resource Padureni correction factor was 0.79.
Method / resource Dacic leaf-area RMSEP was 2.41317.
Method / resource Glosa leaf-area RMSEP was 2.21665.
Method / resource Padureni leaf-area RMSEP was 1.30141.
Method / resource Padureni showed the highest measured-to-scanned leaf-area fit, R2 0.933.
Association Length/width and width/length ratios had a strong negative correlation, r −0.977.
Association Measured and scanned leaf area were strongly positively correlated, r 0.920.
Observation Ciprian measured leaf area had high variability, CV 19.61861.
Observation Padureni measured leaf area had high variability, CV 27.07106.
Observation Dacic scanned leaf area had high variability, CV 22.72838.
Observation Glosa scanned leaf area had high variability, CV 18.52030.

Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

Dacic leaf-area RMSEP was 2.41317.

Taxon: WHEATTriticum aestivumt0
Material: Dacice0
Outcome: RMSEPe0
Value: 2.41317e0

Verbatim

t0
“WHEAT”
✓ located verbatim in the source · title, characters 73–78

e0
“RMSEP=2.41317 for Dacic cultivar”
✓ located verbatim in the source · abstract, characters 928–960

Title

LEAF AREA IN GRASS CEREALS IN RELATION TO LEAF PARAMETERS; CASE STUDY IN WHEAT

Alina Laura AGAPIE; Florin SALA LIFE SCIENCE AND SUSTAINABLE DEVELOPMENT 2023. doi:10.58509/f58ex328

Other claims from this paper (14)

Method / resource Ciprian correction factor was 0.79.
Method / resource Dacic correction factor was 0.80.
Method / resource Glosa correction factor was 0.78.
Method / resource Padureni correction factor was 0.79.
Method / resource Ciprian leaf-area RMSEP was 1.32042.
Method / resource Glosa leaf-area RMSEP was 2.21665.
Method / resource Padureni leaf-area RMSEP was 1.30141.
Method / resource Padureni showed the highest measured-to-scanned leaf-area fit, R2 0.933.
Association Length/width and width/length ratios had a strong negative correlation, r −0.977.
Association Measured and scanned leaf area were strongly positively correlated, r 0.920.
Observation Ciprian measured leaf area had high variability, CV 19.61861.
Observation Padureni measured leaf area had high variability, CV 27.07106.
Observation Dacic scanned leaf area had high variability, CV 22.72838.
Observation Glosa scanned leaf area had high variability, CV 18.52030.

Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

Glosa leaf-area RMSEP was 2.21665.

Taxon: WHEATTriticum aestivumt0
Material: Glosae0
Outcome: RMSEPe0
Value: 2.21665e0

Verbatim

t0
“WHEAT”
✓ located verbatim in the source · title, characters 73–78

e0
“RMSEP=2.21665 for Glosa cultivar”
✓ located verbatim in the source · abstract, characters 962–994

Title

LEAF AREA IN GRASS CEREALS IN RELATION TO LEAF PARAMETERS; CASE STUDY IN WHEAT

Alina Laura AGAPIE; Florin SALA LIFE SCIENCE AND SUSTAINABLE DEVELOPMENT 2023. doi:10.58509/f58ex328

Other claims from this paper (14)

Method / resource Ciprian correction factor was 0.79.
Method / resource Dacic correction factor was 0.80.
Method / resource Glosa correction factor was 0.78.
Method / resource Padureni correction factor was 0.79.
Method / resource Ciprian leaf-area RMSEP was 1.32042.
Method / resource Dacic leaf-area RMSEP was 2.41317.
Method / resource Padureni leaf-area RMSEP was 1.30141.
Method / resource Padureni showed the highest measured-to-scanned leaf-area fit, R2 0.933.
Association Length/width and width/length ratios had a strong negative correlation, r −0.977.
Association Measured and scanned leaf area were strongly positively correlated, r 0.920.
Observation Ciprian measured leaf area had high variability, CV 19.61861.
Observation Padureni measured leaf area had high variability, CV 27.07106.
Observation Dacic scanned leaf area had high variability, CV 22.72838.
Observation Glosa scanned leaf area had high variability, CV 18.52030.

Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

Padureni leaf-area RMSEP was 1.30141.

Taxon: WHEATTriticum aestivumt0
Material: Padurenie0
Outcome: RMSEPe0
Value: 1.30141e0

Verbatim

t0
“WHEAT”
✓ located verbatim in the source · title, characters 73–78

e0
“RMSEP=1.30141 for Padureni cultivar”
✓ located verbatim in the source · abstract, characters 996–1031

Title

LEAF AREA IN GRASS CEREALS IN RELATION TO LEAF PARAMETERS; CASE STUDY IN WHEAT

Alina Laura AGAPIE; Florin SALA LIFE SCIENCE AND SUSTAINABLE DEVELOPMENT 2023. doi:10.58509/f58ex328

Other claims from this paper (14)

Method / resource Ciprian correction factor was 0.79.
Method / resource Dacic correction factor was 0.80.
Method / resource Glosa correction factor was 0.78.
Method / resource Padureni correction factor was 0.79.
Method / resource Ciprian leaf-area RMSEP was 1.32042.
Method / resource Dacic leaf-area RMSEP was 2.41317.
Method / resource Glosa leaf-area RMSEP was 2.21665.
Method / resource Padureni showed the highest measured-to-scanned leaf-area fit, R2 0.933.
Association Length/width and width/length ratios had a strong negative correlation, r −0.977.
Association Measured and scanned leaf area were strongly positively correlated, r 0.920.
Observation Ciprian measured leaf area had high variability, CV 19.61861.
Observation Padureni measured leaf area had high variability, CV 27.07106.
Observation Dacic scanned leaf area had high variability, CV 22.72838.
Observation Glosa scanned leaf area had high variability, CV 18.52030.

Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

At correction factor 0.27, RMSEP reached its minimum of 9.74929.

Taxon: Cannabis sativa L.Cannabis sativat0
Outcome: RMSEPe0
Direction: minimume0
Value: RMSEP=9.74929e0
Qualifier: correction factor (0.27)e0

Verbatim

e0
“The calculation of the RMSEP parameter confirmed the value of the correction factor (0.27), at which the RMSEP value was the minimum (RMSEP=9.74929)”
✓ located verbatim in the source · abstract, characters 1005–1153

t0
“Cannabis sativa L.”
✓ located verbatim in the source · title, characters 61–79

Title

NON-DESTRUCTIVE METHOD TO DETERMINING THE LEAF AREA IN HEMP, Cannabis sativa L.

Ciprian BUZNA; Florin SALA LIFE SCIENCE AND SUSTAINABLE DEVELOPMENT 2022. doi:10.58509/lssd.v3i2.203

Other claims from this paper (6)

Method / resource A correction factor of 0.27 minimized the measured versus scanned leaf-area error at 0.87 cm2.
Method / resource Measured and scanned leaf area had a linear fit with R2=0.952.
Method / resource Scanned leaf area and leaf length had a third-degree polynomial relation with R2=0.932.
Method / resource Scanned leaf area and leaf width had a third-degree polynomial relation with R=0.964.
Method / resource Scanned leaf area and perimeter had a second-degree polynomial relation with R2=0.995.
Method / resource Measured leaf area correlated more strongly with leaf dimensions than scanned area did.

“RMSEP”

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