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Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

The detection and diagnosis system processed images at around 3 seconds per image.

Taxon: CucumberCucumis sativust0
Outcome: seconds/imagee0
Value: around 3 seconds/imagee0
Setting: on-site imagese0

Verbatim

t0
“Cucumber Images”
✓ located verbatim in the source · title, characters 70–85

e0
“at around 3 seconds/image on 500 wide-angle on-site images”
✓ located verbatim in the source · abstract, characters 780–838

Title

An End-To-End Practical Plant Disease Diagnosis System For Wide-Angle Cucumber Images

CAP, Quan Huu; IYATOMI, Hitoshi Institutional Repositories DataBase (IRDB) . doi:10.15002/00022037

Other claims from this paper (3)

Method / resource The system detected leaves in wide-angle on-site cucumber images with an F1 score of 73.9%.
Method / resource Overall detection and diagnosis recall was 68.1% on wide-angle on-site cucumber images.
Method / resource Overall detection and diagnosis precision was 65.8% on wide-angle on-site cucumber images.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

Automatically collected sugar beet harvester data enabled a complete detailed work study.

Taxon: Sugar BeetBeta vulgaris subsp. vulgarist0
Outcome: complete detailed work studye0

Not reportedComparatorValue

Verbatim

e0
“The analysis of automatically collected data made a complete detailed work study possible.”
✓ located verbatim in the source · abstract, characters 173–263

t0
“Sugar Beet Harvester”
✓ located verbatim in the source · title, characters 80–100

Title

Georeferenced Data Collection and Yield Measurement on a Self Propelled Six Row Sugar Beet Harvester

Markus Demmel; Hermann Auernhammer; Josef Rottmeier mediaTUM (Technical University of Munich)

Other claims from this paper (2)

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

The collected harvester data allowed field length and field size effects to be ascertained.

Taxon: Sugar BeetBeta vulgaris subsp. vulgarist0
Outcome: direct affects of field length and field sizee0

Not reportedComparatorValue

Verbatim

e0
“The direct affects of field length and field size could be ascertained.”
✓ located verbatim in the source · abstract, characters 264–335

t0
“Sugar Beet Harvester”
✓ located verbatim in the source · title, characters 80–100

Title

Georeferenced Data Collection and Yield Measurement on a Self Propelled Six Row Sugar Beet Harvester

Markus Demmel; Hermann Auernhammer; Josef Rottmeier mediaTUM (Technical University of Munich)

Other claims from this paper (2)

Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

GWAS found 74 marker associations using GLM and FarmCPU.

Taxon: maizeZea mayse1
Outcome: marker associationse0
Value: 74 marker associationse0

Verbatim

e0
“The results from GWAS identified 74 marker associations from GLM and FarmCPU models.”
✓ located verbatim in the source · abstract, characters 903–987

e1
“336 maize inbred lines”
✓ located verbatim in the source · abstract, characters 366–388

Title

Genome-Wide Association Study Reveals Novel QTNs and Candidate Genes Implicated in Resistance to Northern Corn Leaf Blight in Maize (Zea mays L.)

Udaya, S.; Muntagodu Shreekanth, S.; Hirenallur Chandappa, L.; et al. MyPrints@UOM (Mysore University Library)

Other claims from this paper (7)

Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

KELM had the highest performance estimating chlorophyll a content, with a root mean square error of 1.95 0.36 g cm -2.

Taxon: Teat0
Outcome: chlorophyll ae0
Value: 1.95 0.36 g cm -2e0
Comparator: highest performancee0

Verbatim

e0
“KELM had the highest performance with a root mean square error of 1.95 0.36 g cm -2 , 1.08 0.11 g cm -2 and 0.68 0.10 g cm -2 for estimating chlorophyll a, b and carotenoid contents, respectively”
✓ located verbatim in the source · abstract, characters 726–921

t0
“Tea”
✓ located verbatim in the source · title, characters 50–53

Title

Monitoring Photosynthetic Pigments of Shade-Grown Tea from Hyperspectral Reflectance

SANO, Tomohito; HORIE, Hideki Institutional Repositories DataBase (IRDB)

Other claims from this paper (2)

Method / resource KELM estimated chlorophyll b with a root mean square error of 1.08 0.11 g cm -2.
Method / resource KELM estimated carotenoids with a root mean square error of 0.68 0.10 g cm -2.

Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

KELM estimated chlorophyll b with a root mean square error of 1.08 0.11 g cm -2.

Taxon: Teat0
Outcome: be0
Value: 1.08 0.11 g cm -2e0

Verbatim

e0
“1.08 0.11 g cm -2 and 0.68 0.10 g cm -2 for estimating chlorophyll a, b and carotenoid contents, respectively”
✓ located verbatim in the source · abstract, characters 812–921

t0
“Tea”
✓ located verbatim in the source · title, characters 50–53

Title

Monitoring Photosynthetic Pigments of Shade-Grown Tea from Hyperspectral Reflectance

SANO, Tomohito; HORIE, Hideki Institutional Repositories DataBase (IRDB)

Other claims from this paper (2)

Method / resource KELM had the highest performance estimating chlorophyll a content, with a root mean square error of 1.95 0.36 g cm -2.
Method / resource KELM estimated carotenoids with a root mean square error of 0.68 0.10 g cm -2.

Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

KELM estimated carotenoids with a root mean square error of 0.68 0.10 g cm -2.

Taxon: Teat0
Outcome: carotenoid contentse0
Value: 0.68 0.10 g cm -2e0

Verbatim

e0
“0.68 0.10 g cm -2 for estimating chlorophyll a, b and carotenoid contents, respectively”
✓ located verbatim in the source · abstract, characters 834–921

t0
“Tea”
✓ located verbatim in the source · title, characters 50–53

Title

Monitoring Photosynthetic Pigments of Shade-Grown Tea from Hyperspectral Reflectance

SANO, Tomohito; HORIE, Hideki Institutional Repositories DataBase (IRDB)

Other claims from this paper (2)

Method / resource KELM had the highest performance estimating chlorophyll a content, with a root mean square error of 1.95 0.36 g cm -2.
Method / resource KELM estimated chlorophyll b with a root mean square error of 1.08 0.11 g cm -2.

Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

FFT processing extracted the wrinkle part of black soybean images.

Taxon: black soybeane0
Outcome: wrinkle part of the black soybean was extractede0

Not reportedComparatorValue

Verbatim

e0
“The wrinkle part of the black soybean was extracted by the two dimensional Fast Fourier Transform (FFT) method”
✓ located verbatim in the source · abstract, characters 411–521

Title

Recognition of wrinkle black soybean by machine vision

Ito, Hiromichi; Yamashita, Ritsuya Institutional Repositories DataBase (IRDB)

Other claims from this paper (2)

Method / resource Processed wrinkle and whole soybean images differed markedly.
Method / resource The algorithm had 35 % judgment error across 30 samples.

Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

Processed wrinkle and whole soybean images differed markedly.

Taxon: black soybeane1
Outcome: remarkable differencee0
Comparator: whole soybeanse0

Verbatim

e0
“There was a remarkable difference between the processed image of the wrinkle and whole soybeans”
✓ located verbatim in the source · abstract, characters 818–913

e1
“the black soybean and objective is to develop an algorithm”
✓ located verbatim in the source · abstract, characters 187–245

Title

Recognition of wrinkle black soybean by machine vision

Ito, Hiromichi; Yamashita, Ritsuya Institutional Repositories DataBase (IRDB)

Other claims from this paper (2)

Method / resource FFT processing extracted the wrinkle part of black soybean images.
Method / resource The algorithm had 35 % judgment error across 30 samples.

Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

The algorithm had 35 % judgment error across 30 samples.

Taxon: black soybeane0
Outcome: percentage of judgment errore0
Value: 35 %e0
Qualifier: 30 samplese0

Verbatim

e0
“A percentage of judgment error of the developed algorithm for the wrinkle black soybean was 35 % in 30 samples”
✓ located verbatim in the source · abstract, characters 914–1024

Title

Recognition of wrinkle black soybean by machine vision

Ito, Hiromichi; Yamashita, Ritsuya Institutional Repositories DataBase (IRDB)

Other claims from this paper (2)

Method / resource FFT processing extracted the wrinkle part of black soybean images.
Method / resource Processed wrinkle and whole soybean images differed markedly.

Method / resource 684,532 claims

684,532 claims