Method / resource 684,532 claims

684,532 claims

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

Whole-grain NIR estimated rough rice moisture with R 0.99, SEC 0.29%, and SEP 0.34%.

Taxon: rough ricee0
Outcome: rough ricee0
Value: SEP: 0.34%e0
Qualifier: using 2 factors calculated from the second derivative spectra in the wavelength region of 700 nm to 1050 nme0

Verbatim

e0
“The best result for rough rice (R: 0.99, SEC: 0.29%, SEP: 0.34%) could be obtained using 2 factors calculated from the second derivative spectra in the wavelength region of 700 nm to 1050 nm.”
✓ located verbatim in the source · abstract, characters 791–982

Title

Application of Near Infrared Spectroscopy for Determining Protein, Moisture and Water Activity in Rice

BANGWEAK, Charuwan Institutional Repositories DataBase (IRDB) . doi:10.24514/00002816

Other claims from this paper (8)

Method / resource Whole-grain NIR estimated brown rice moisture with R 0.97, SEC 0.39%, and SEP 0.17%.
Method / resource Single-kernel NIR estimated brown rice protein content with SEP 0.58% at long wavelengths.
Method / resource Single-kernel NIR estimated brown rice moisture with SEP 0.39% at short wavelengths.
Method / resource Single-kernel NIR estimated brown rice moisture with SEP 0.36% at long wavelengths.
Observation The single-kernel calibration regression coefficient contained a protein band at 1738 nm.
Observation The single-kernel calibration regression coefficient contained water bands at 966 and 1940 nm.
Method / resource Whole-grain NIR estimated brown rice water activity with SEP 0.02.
Observation The water activity calibration regression coefficient contained a water band at 966 nm.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

Whole-grain NIR estimated brown rice moisture with R 0.97, SEC 0.39%, and SEP 0.17%.

Taxon: brown ricee0
Outcome: moisturee0
Value: SEP: 0.17%e0
Qualifier: R: 0.97, SEC: 0.39%e0

Verbatim

e0
“For moisture equation of brown rice, high accuracy (R: 0.97, SEC: 0.39%, SEP: 0.17%) could be also obtained.”
✓ located verbatim in the source · abstract, characters 982–1090

Title

Application of Near Infrared Spectroscopy for Determining Protein, Moisture and Water Activity in Rice

BANGWEAK, Charuwan Institutional Repositories DataBase (IRDB) . doi:10.24514/00002816

Other claims from this paper (8)

Method / resource Whole-grain NIR estimated rough rice moisture with R 0.99, SEC 0.29%, and SEP 0.34%.
Method / resource Single-kernel NIR estimated brown rice protein content with SEP 0.58% at long wavelengths.
Method / resource Single-kernel NIR estimated brown rice moisture with SEP 0.39% at short wavelengths.
Method / resource Single-kernel NIR estimated brown rice moisture with SEP 0.36% at long wavelengths.
Observation The single-kernel calibration regression coefficient contained a protein band at 1738 nm.
Observation The single-kernel calibration regression coefficient contained water bands at 966 and 1940 nm.
Method / resource Whole-grain NIR estimated brown rice water activity with SEP 0.02.
Observation The water activity calibration regression coefficient contained a water band at 966 nm.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

Single-kernel NIR estimated brown rice protein content with SEP 0.58% at long wavelengths.

Taxon: brown ricee1
Outcome: proteine0
Value: SEP: 0.58%e0
Qualifier: long wavelengthe0

Verbatim

e0
“accurate determination of protein (SEP: 0.58% for long wavelength) and moisture contents (SEP: 0.39% for short wavelength and SEP: 0.36% for long wavelength)”
✓ located verbatim in the source · abstract, characters 1443–1600

t0
“Rice”
✓ located verbatim in the source · title, characters 98–102

e1
“For moisture equation of brown rice, high accuracy (R: 0.97, SEC: 0.39%, SEP: 0.17%) could be also obtained.”
✓ located verbatim in the source · abstract, characters 982–1090

Title

Application of Near Infrared Spectroscopy for Determining Protein, Moisture and Water Activity in Rice

BANGWEAK, Charuwan Institutional Repositories DataBase (IRDB) . doi:10.24514/00002816

Other claims from this paper (8)

Method / resource Whole-grain NIR estimated rough rice moisture with R 0.99, SEC 0.29%, and SEP 0.34%.
Method / resource Whole-grain NIR estimated brown rice moisture with R 0.97, SEC 0.39%, and SEP 0.17%.
Method / resource Single-kernel NIR estimated brown rice moisture with SEP 0.39% at short wavelengths.
Method / resource Single-kernel NIR estimated brown rice moisture with SEP 0.36% at long wavelengths.
Observation The single-kernel calibration regression coefficient contained a protein band at 1738 nm.
Observation The single-kernel calibration regression coefficient contained water bands at 966 and 1940 nm.
Method / resource Whole-grain NIR estimated brown rice water activity with SEP 0.02.
Observation The water activity calibration regression coefficient contained a water band at 966 nm.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

Single-kernel NIR estimated brown rice moisture with SEP 0.39% at short wavelengths.

Taxon: brown ricee1
Outcome: moisture contentse0
Value: SEP: 0.39%e0
Qualifier: short wavelengthe0

Verbatim

e0
“moisture contents (SEP: 0.39% for short wavelength and SEP: 0.36% for long wavelength)”
✓ located verbatim in the source · abstract, characters 1514–1600

t0
“Rice”
✓ located verbatim in the source · title, characters 98–102

e1
“For moisture equation of brown rice, high accuracy (R: 0.97, SEC: 0.39%, SEP: 0.17%) could be also obtained.”
✓ located verbatim in the source · abstract, characters 982–1090

Title

Application of Near Infrared Spectroscopy for Determining Protein, Moisture and Water Activity in Rice

BANGWEAK, Charuwan Institutional Repositories DataBase (IRDB) . doi:10.24514/00002816

Other claims from this paper (8)

Method / resource Whole-grain NIR estimated rough rice moisture with R 0.99, SEC 0.29%, and SEP 0.34%.
Method / resource Whole-grain NIR estimated brown rice moisture with R 0.97, SEC 0.39%, and SEP 0.17%.
Method / resource Single-kernel NIR estimated brown rice protein content with SEP 0.58% at long wavelengths.
Method / resource Single-kernel NIR estimated brown rice moisture with SEP 0.36% at long wavelengths.
Observation The single-kernel calibration regression coefficient contained a protein band at 1738 nm.
Observation The single-kernel calibration regression coefficient contained water bands at 966 and 1940 nm.
Method / resource Whole-grain NIR estimated brown rice water activity with SEP 0.02.
Observation The water activity calibration regression coefficient contained a water band at 966 nm.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

Single-kernel NIR estimated brown rice moisture with SEP 0.36% at long wavelengths.

Taxon: brown ricee1
Outcome: moisture contentse0
Value: SEP: 0.36%e0
Qualifier: long wavelengthe0

Verbatim

e0
“moisture contents (SEP: 0.39% for short wavelength and SEP: 0.36% for long wavelength)”
✓ located verbatim in the source · abstract, characters 1514–1600

t0
“Rice”
✓ located verbatim in the source · title, characters 98–102

e1
“For moisture equation of brown rice, high accuracy (R: 0.97, SEC: 0.39%, SEP: 0.17%) could be also obtained.”
✓ located verbatim in the source · abstract, characters 982–1090

Title

Application of Near Infrared Spectroscopy for Determining Protein, Moisture and Water Activity in Rice

BANGWEAK, Charuwan Institutional Repositories DataBase (IRDB) . doi:10.24514/00002816

Other claims from this paper (8)

Method / resource Whole-grain NIR estimated rough rice moisture with R 0.99, SEC 0.29%, and SEP 0.34%.
Method / resource Whole-grain NIR estimated brown rice moisture with R 0.97, SEC 0.39%, and SEP 0.17%.
Method / resource Single-kernel NIR estimated brown rice protein content with SEP 0.58% at long wavelengths.
Method / resource Single-kernel NIR estimated brown rice moisture with SEP 0.39% at short wavelengths.
Observation The single-kernel calibration regression coefficient contained a protein band at 1738 nm.
Observation The single-kernel calibration regression coefficient contained water bands at 966 and 1940 nm.
Method / resource Whole-grain NIR estimated brown rice water activity with SEP 0.02.
Observation The water activity calibration regression coefficient contained a water band at 966 nm.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

Whole-grain NIR estimated brown rice water activity with SEP 0.02.

Taxon: RiceOryza sativat0
Outcome: calibration equatione0
Value: 0.02e0

Verbatim

e0
“From second derivative spectra, accurate calibration equation with low SEP, 0.02 could be obtained.”
✓ located verbatim in the source · abstract, characters 2084–2183

t0
“Rice”
✓ located verbatim in the source · title, characters 98–102

Title

Application of Near Infrared Spectroscopy for Determining Protein, Moisture and Water Activity in Rice

BANGWEAK, Charuwan Institutional Repositories DataBase (IRDB) . doi:10.24514/00002816

Other claims from this paper (8)

Method / resource Whole-grain NIR estimated rough rice moisture with R 0.99, SEC 0.29%, and SEP 0.34%.
Method / resource Whole-grain NIR estimated brown rice moisture with R 0.97, SEC 0.39%, and SEP 0.17%.
Method / resource Single-kernel NIR estimated brown rice protein content with SEP 0.58% at long wavelengths.
Method / resource Single-kernel NIR estimated brown rice moisture with SEP 0.39% at short wavelengths.
Method / resource Single-kernel NIR estimated brown rice moisture with SEP 0.36% at long wavelengths.
Observation The single-kernel calibration regression coefficient contained a protein band at 1738 nm.
Observation The single-kernel calibration regression coefficient contained water bands at 966 and 1940 nm.
Observation The water activity calibration regression coefficient contained a water band at 966 nm.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

Images from 10 m altitude gave satisfactory planter assessment results.

Taxon: cornZea mays subsp. mayse1
Outcome: satisfactory resultse0
Value: 4.5 mm pixel -1e0
Setting: 10 m altitudee0

Verbatim

e0
“Images captured from10 m altitude (4.5 mm pixel -1 ) could give satisfactory results in relation to our objectives.”
✓ located verbatim in the source · abstract, characters 800–915

t0
“Drone Imagery for Monitoring Performance of a Modified Drill”
✓ located verbatim in the source · title, characters 15–75

e1
“no-till corn planter”
✓ located verbatim in the source · abstract, characters 32–52

Title

Feasibility of Drone Imagery for Monitoring Performance of a Modified Drill in a Conservation Farming System\n\t\t\t\tدوره10 شماره1 سال1399

Kavoosi, Z; Raoufat, M. H Māshīn/hā-yi kishāvarzī/Māshīn/hā-yi kishāvarzī 1397 (?). doi:10.22067/jam.v10i1.71498

Other claims from this paper (4)

Method / resource Aerial and terrestrial seedling spacing measurements correlated with R between 0.94 and 0.98.
Method / resource Aerial imagery underestimated quality of feed and precision indices.
Method / resource Aerial imagery overestimated miss index.
Method / resource Aerial imagery could not supply the data range needed to compute multiple index.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

Aerial and terrestrial seedling spacing measurements correlated with R between 0.94 and 0.98.

Taxon: cornZea mays subsp. mayse1
Outcome: correlationse0
Value: 0.94<R<0.98e0
Comparator: terrestrial and aerial seedlings spacing data setse0

Not reportedDirection

Verbatim

e0
“acceptable correlations existed between terrestrial and aerial seedlings spacing data sets (0.94<R<0.98)”
✓ located verbatim in the source · abstract, characters 937–1041

t0
“Drone Imagery for Monitoring Performance of a Modified Drill”
✓ located verbatim in the source · title, characters 15–75

e1
“no-till corn planter”
✓ located verbatim in the source · abstract, characters 32–52

Title

Feasibility of Drone Imagery for Monitoring Performance of a Modified Drill in a Conservation Farming System\n\t\t\t\tدوره10 شماره1 سال1399

Kavoosi, Z; Raoufat, M. H Māshīn/hā-yi kishāvarzī/Māshīn/hā-yi kishāvarzī 1397 (?). doi:10.22067/jam.v10i1.71498

Other claims from this paper (4)

Method / resource Images from 10 m altitude gave satisfactory planter assessment results.
Method / resource Aerial imagery underestimated quality of feed and precision indices.
Method / resource Aerial imagery overestimated miss index.
Method / resource Aerial imagery could not supply the data range needed to compute multiple index.

Method / resourceobservedoriginal resultnegativemeasured

Claim · model-written summary

Aerial imagery underestimated quality of feed and precision indices.

Taxon: cornZea mays subsp. mayse1
Outcome: quality of feed and precision indicese0
Direction: underestimatede0
Comparator: Aerial imagery data sourcee0

Verbatim

e0
“Aerial imagery data source underestimated quality of feed and precision indices”
✓ located verbatim in the source · abstract, characters 1146–1225

t0
“Drone Imagery for Monitoring Performance of a Modified Drill”
✓ located verbatim in the source · title, characters 15–75

e1
“no-till corn planter”
✓ located verbatim in the source · abstract, characters 32–52

Title

Feasibility of Drone Imagery for Monitoring Performance of a Modified Drill in a Conservation Farming System\n\t\t\t\tدوره10 شماره1 سال1399

Kavoosi, Z; Raoufat, M. H Māshīn/hā-yi kishāvarzī/Māshīn/hā-yi kishāvarzī 1397 (?). doi:10.22067/jam.v10i1.71498

Other claims from this paper (4)

Method / resource Images from 10 m altitude gave satisfactory planter assessment results.
Method / resource Aerial and terrestrial seedling spacing measurements correlated with R between 0.94 and 0.98.
Method / resource Aerial imagery overestimated miss index.
Method / resource Aerial imagery could not supply the data range needed to compute multiple index.

Method / resourceobservedoriginal resultnegativemeasured

Claim · model-written summary

Aerial imagery overestimated miss index.

Taxon: cornZea mays subsp. mayse1
Outcome: miss indexe0
Direction: overestimatede0
Comparator: Aerial imagery data sourcee0

Verbatim

e0
“Aerial imagery data source underestimated quality of feed and precision indices, overestimated miss index”
✓ located verbatim in the source · abstract, characters 1146–1251

t0
“Drone Imagery for Monitoring Performance of a Modified Drill”
✓ located verbatim in the source · title, characters 15–75

e1
“no-till corn planter”
✓ located verbatim in the source · abstract, characters 32–52

Title

Feasibility of Drone Imagery for Monitoring Performance of a Modified Drill in a Conservation Farming System\n\t\t\t\tدوره10 شماره1 سال1399

Kavoosi, Z; Raoufat, M. H Māshīn/hā-yi kishāvarzī/Māshīn/hā-yi kishāvarzī 1397 (?). doi:10.22067/jam.v10i1.71498

Other claims from this paper (4)

Method / resource Images from 10 m altitude gave satisfactory planter assessment results.
Method / resource Aerial and terrestrial seedling spacing measurements correlated with R between 0.94 and 0.98.
Method / resource Aerial imagery underestimated quality of feed and precision indices.
Method / resource Aerial imagery could not supply the data range needed to compute multiple index.