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Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

Relative growth rate based on leaf width was 7.29%.

Taxon
vegetablese1
Outcome
average leaf widthe0
Value
7.29%e0

Verbatim

e0

“average plant height, average leaf length, average leaf width, average stem perimeter and average plant crown are 7.20%, 6.17%, 7.29%, 5.31% and 5.71%, respectively”

✓ located verbatim in the source · abstract, characters 1408–1572
e1

“Experimented on several types of vegetables”

✓ located verbatim in the source · abstract, characters 1143–1186

Title

IoT Based Automatic Water Level and Electrical Conductivity Monitoring System

Soon Jian Yue; Cui Hairu; Marsyita Hanafi; et al. 2020 IEEE 8th Conference on Systems, Process and Control (ICSPC) 2020. doi:10.1109/icspc50992.2020.9305768

Other claims from this paper (7)
Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

An index of total palisade cell width per mm leaf blade discriminated among peanut genotypes better than average cell width or cell number alone.

Outcome
index representing total width (μm) of palisade cells/mm leaf bladee3
Direction
more discriminativee3
Comparator
average of either cell width or cell number alonee3

Verbatim

t0

“Pod Rot Resistance in Peanut”

✓ located verbatim in the source · title, characters 34–62
e3

“An index representing total width (μm) of palisade cells/mm leaf blade was more discriminative in distinguishing among genotypes than average of either cell width or cell number alone”

✓ located verbatim in the source · abstract, characters 739–922

Title

Anatomical Traits Associated With Pod Rot Resistance in Peanut1

R Godoy; O. D Smith; R. A Taber; et al. Peanut Science 1985. doi:10.3146/pnut.12.2.0008

Other claims from this paper (6)
Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

The average leaf length versus average leaf width correlation coefficient was 0.995.

Taxon
Wenzhou orange treese1
Organ / stage
spring leafe1
Outcome
average leaf-length vs.average leaf-widthe0
Value
0.995e0
Setting
orchards of the Yongzhou Vocational and Technical Collegee1

Verbatim

e0

“The adjusting coefficient for the leaf size,correlation coefficients for leaf-length vs.leaf-size and for average leaf-length vs.average leaf-width were determined as 0.6835,0.9962 and 0.995,respectively.”

✓ located verbatim in the source · abstract, characters 536–740
e1

“We determined the spring leaf sizes of the Wenzhou orange trees grown in orchards of the Yongzhou Vocational and Technical College by using coefficient adjusting and one-dimensional regression equation methods.”

✓ located verbatim in the source · abstract, characters 326–536

Title

Approaching the Leaf-size Measurement Schemes

Zhu Xue-zhi 2009

Other claims from this paper (5)
Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

The average leaf length versus leaf width regression model was Y=1.1211+0.6595X.

Taxon
Wenzhou orange treese1
Organ / stage
spring leafe1
Outcome
average leaf-length vs.leaf-widthe0
Value
Y=1.1211+0.6595Xe0
Setting
orchards of the Yongzhou Vocational and Technical Collegee1

Verbatim

e0

“The one-dimensional regression equation model for average leaf-length vs.leaf-width was(Y=1.1211+0.6595X).”

✓ located verbatim in the source · abstract, characters 840–946
e1

“We determined the spring leaf sizes of the Wenzhou orange trees grown in orchards of the Yongzhou Vocational and Technical College by using coefficient adjusting and one-dimensional regression equation methods.”

✓ located verbatim in the source · abstract, characters 326–536

Title

Approaching the Leaf-size Measurement Schemes

Zhu Xue-zhi 2009

Other claims from this paper (5)
Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

Mean prediction error for soybean leaf width was 3.72%.

Taxon
Glycine Max (L) Merrillt0
Outcome
average error of leaf's width predictione0
Value
3.72%e0

Verbatim

e0

“the average error of leaf's width prediction is 3.72%”

✓ located verbatim in the source · abstract, characters 1137–1190
t0

“Glycine Max (L) Merrill”

✓ located verbatim in the source · title, characters 84–107

Title

Machine Learning and Polynomial – L System Algorithm for Modeling and Simulation of Glycine Max (L) Merrill Growth

Rika Rokhana; Wiwiet Herulambang; Rarasmaya Indraswari 2020 International Electronics Symposium (IES) 2020. doi:10.1109/ies50839.2020.9231935

Other claims from this paper (5)
Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

Leaf width measurement had approximately 5.7 percent average relative error compared with manual expert measurement.

Taxon
leaves from different plant familiese1
Outcome
leaf widthe0
Value
approximately 5.7 percente0
Comparator
manual measurements by expert ecologists and botanistse0

Not reportedDirection

Verbatim

e0

“Measured leaves of comparable size have an average relative error of about 4.6 percent for leaf length and approximately 5.7 percent for leaf width when compared to manual measurements by expert ecologists and botanists”

✓ located verbatim in the source · abstract, characters 781–1000
e1

“leaves from different plant families”

✓ located verbatim in the source · abstract, characters 743–779

Title

Detecting Leaf Diseases Using Centralized CNN'S with Efficient R-CNN and Mask R-CNN

Pongiannan R K; Samudra Banerjee; Poornima P U; et al. 2024 International Conference on System, Computation, Automation and Networking (ICSCAN) 2024. doi:10.1109/icscan62807.2024.10894455

Other claims from this paper (2)
Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

Width to length ratio and leaf jaggedness caused the fractal value of white oak, red oak and sugar maple leaves to depart from the average.

Taxon
white oak, red oak, and sugar mapleQuercus rubraQuercus albaAcer saccharume4
Outcome
fractal valuee4
Qualifier
width to length ratio and the degree of jaggednesse4
Comparator
averagee4

Verbatim

e4

“Similar sensitivity to shape change was observed among the leaves of white oak, red oak, and sugar maple where such variables as width to length ratio and the degree of jaggedness of the leaf caused a departure of the fractal value from the average”

✓ located verbatim in the source · abstract, characters 862–1110

Title

Fractal analysis of leaf shapes

J. Vlcek; E. Cheung Canadian Journal of Forest Research 1986. doi:10.1139/x86-020

Other claims from this paper (2)
Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

Pak Choy leaf width detection was most accurate at the 2nd week of growth, with an average accuracy of 99%.

Taxon
Pak Choye0
Outcome
accuracye3
Value
99%e3
Qualifier
2 nd weeke3

Verbatim

e0

“Pak Choy plant is a vegetable plant that can grow with soil and hydroponic media”

✓ located verbatim in the source · abstract, characters 0–80
e3

“the best accuracy was obtained at 2 nd week with an average accuracy of 99%”

✓ located verbatim in the source · abstract, characters 573–648

Title

Pak Choy Leaf Width Detection using Image Processing with Canny Edge Detection Extraction Method

Brenda; Budhi Irawan; Casi Setianingsih 2021 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT) 2021. doi:10.1109/iaict52856.2021.9532575

Other claims from this paper (1)
Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

In apple and peach orchards the system measured tree width and extension with under 10 percent average error and high precision.

Organ / stage
different stages of leaf developmente1
Outcome
tree width and extensione1
Value
<10% average errore1
Qualifier
high precisione1
Setting
apple and peach orchardse1

Verbatim

e1

“Field tests in apple and peach orchards at different stages of leaf development found the system to measure tree width and extension with <10% average error and high precision”

✓ located verbatim in the source · abstract, characters 370–545

Title

Electronic Measurement of Tree Canopy Volume

Authors Paste Over This Text Transactions of the ASAE 1988. doi:10.13031/2013.30698

Other claims from this paper (2)
Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

The leaf area model using total midrib length times average leaflet width achieved R2 = 0.9932.

Outcome
Total leaf blade areae0
Value
R2 = 0.9932e0
Qualifier
0-intercept linear modele0

Verbatim

t0

“Konjac”

✓ located verbatim in the source · title, characters 93–99
e0

“Total leaf blade area (LA) of the irregular konjac compound leaf can be accurately (R2 = 0.9932) and consistently estimated using the 0-intercept linear model and the multiplication product of total midrib length and average width of all leaflets (TLM×AWL) is used as predictor.”

✓ located verbatim in the source · abstract, characters 964–1242

Title

Planting Materials, Shading Effects, and Non-Destructive Estimation of Compound Leaf Area in Konjac (Amorphophallus Muelleri)

Dora Fatma Nurshanti; Benyamin Lakitan; Mery Hasmeda; et al. Trends in Sciences 2022. doi:10.48048/tis.2022.3973

Other claims from this paper (9)

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