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Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

Clustering refinement improved blueberry pixel clustering and NDVI calculation.

Taxon
Blueberryt0
Outcome
clustering accuracye0

Not reportedComparatorValue

Verbatim

e0

“This enhanced clustering accuracy and enabled precise NDVI calculations.”

✓ located verbatim in the source · abstract, characters 909–981
t0

“Blueberry”

✓ located verbatim in the source · title, characters 54–63

Title

Normalized Difference Vegetation Index Prediction for Blueberry Plant Health from RGB Images: A Clustering and Deep Learning Approach

A. G. M. Zaman; Kallol Roy; Jüri Olt AgriEngineering 2024. doi:10.3390/agriengineering6040276

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

Claim · model-written summary

The cluster ensemble process gives better clustering results than all traditional clustering algorithms.

Taxon
chickpeaCicer arietinume1
Outcome
clusteringe0
Direction
bettere0
Comparator
traditional clustering algorithme0

Verbatim

e0

“Cluster Ensemble process (technique) generates clustering which gives better results as compared to all the traditional clustering algorithm”

✓ located verbatim in the source · abstract, characters 991–1131
e1

“RCDA algorithm runs on chickpea germplasm dataset”

✓ located verbatim in the source · abstract, characters 1133–1182

Title

Germplasm evaluation using cluster ensemble

Sangeeta Ahuja; H L Raiger; Abhishek Choubey; et al. 2016

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

Claim · model-written summary

Pooled RAPD, ISSR and SSR clustering resembled RAPD clustering.

Taxon
coconutt0
Outcome
clustering patterne0
Comparator
RAPD clustering patterne0

Verbatim

e0

“The pooled study of RAPD, ISSR and SSR generated clustering pattern appeared to be similar as RAPD clustering pattern.”

✓ located verbatim in the source · abstract, characters 1179–1297
t0

“coconut”

✓ located after whitespace/quote normalisation · title, characters 30–37

Title

Genetic Diversity Analysis of Coconut (Cocos nucifera L.) Genotypes and Hybrids Using Molecular Marker

UK Kandoliya; Ankita K Joshi; Disha S Mori; et al. Indian Journal of Agricultural Biochemistry 2018. doi:10.5958/0974-4479.2018.00004.7

Other claims from this paper (9)
Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

ANN clustering improved soybean genotype clustering patterns compared with the Ward-MLM procedure.

Taxon
soybeanGlycine maxe4
Outcome
clustering patternse4
Direction
improvede4
Comparator
Ward-MLM proceduree4

Verbatim

e4

“ANN analysis improved soybean genotypes clustering patterns compared to Ward-MLM procedure”

✓ located verbatim in the source · abstract, characters 1235–1325

Title

Clustering of soybean genotypes via Ward-MLM and ANNs associated with mixed models

P.E. Teodoro; F.E. Torres; A.M. Corrêa Genetics and Molecular Research 2016. doi:10.4238/gmr.15038384

Other claims from this paper (5)
Associationobservedoriginal resultmeasured

Claim · model-written summary

Marker clustering of accessions corresponded relatively well with phenotypic clustering.

Taxon
bambara groundnutVigna subterraneat0
Outcome
clustering of accessionse0
Comparator
clustering based on phenotypic characterse0

Not reportedDirection

Verbatim

e0

“The clustering of accessions compared relatively well to clustering based on phenotypic characters.”

✓ located verbatim in the source · abstract, characters 1029–1128
t0

“bambara groundnut”

✓ located verbatim in the source · title, characters 33–50

Title

Analysis of genetic diversity in bambara groundnut (Vigna subterranea (L.) Verdc) landraces using amplified fragment length polymorphism (AFLP) markers

Wazael H. Ntundu; Inga C. Bach; J. L. Christiansen; et al. Research at the University of Copenhagen (University of Copenhagen) 2004. doi:10.4314/ajb.v3i4.14947

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

Claim · model-written summary

At 1,280–1,320 nm, systematic clustering outperformed principal-component clustering.

Taxon
citrusCitrust0
Outcome
performed bettere0
Value
1,280–1,320 nme0
Comparator
principal component clusteringe0

Verbatim

e0

“In 1,280–1,320 nm, systematic clustering performed better than principal component clustering”

✓ located verbatim in the source · abstract, characters 745–838
t0

“citrus”

✓ located verbatim in the source · title, characters 20–26

Title

Cluster analysis of citrus genotypes using near-infrared spectroscopy

Qiuhong Liao; Yanbo Huang; Shaolan He; et al. Intelligent Automation & Soft Computing 2013. doi:10.1080/10798587.2013.824719

Other claims from this paper (4)
Associationobservedoriginal resultmeasured

Claim · model-written summary

Genetic clustering agreed relatively well with phenotypic clustering.

Taxon
bambara groundnutVigna subterraneat0
Outcome
clustering of accessionse0
Comparator
clustering based on phenotypic characterse0

Not reportedDirection

Verbatim

e0

“The clustering of accessions compared relatively well to clustering based on phenotypic characters”

✓ located verbatim in the source · abstract, characters 1029–1127
t0

“bambara groundnut”

✓ located verbatim in the source · title, characters 62–79

Title

Full Length Research Paper - Analysis of genetic diversity in bambara groundnut [Vigna subterranea (L.) Verdc] landraces using amplified fragment length polymorphism (AFLP) markers

Wazael H. Ntundu; Inga C. Bach; J. L. Christiansen; et al. TSpace 2004

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

Claim · model-written summary

Average linkage clustering achieved 87% accuracy on herb leaves.

Taxon
Herbs Leavest0
Treatment
Average Linkage Clusteringe0
Outcome
clustering accuracye0
Value
87%e0

Verbatim

e0

“the use of Average Linkage Clustering method obtained clustering accuracy of 87%”

✓ located verbatim in the source · abstract, characters 1185–1265
t0

“Herbs Leaves”

✓ located verbatim in the source · title, characters 73–85

Title

Comparative Analysis of Hierarchical Clustering with Improve Feature for Herbs Leaves

Febri Liantoni; Nurcahya Pradana Taufik Prakisya; Yusfia Hafid Aristyagama; et al. Journal of Physics Conference Series 2021. doi:10.1088/1742-6596/1808/1/012025

Other claims from this paper (1)
Observationobservedoriginal resultmixedmeasured

Claim · model-written summary

Clustering based on yield traits differed from clustering based on molecular variation.

Outcome
clustering patterne0
Comparator
yield related traits and molecular variatione0

Not reportedTaxon

Verbatim

e0

“The clustering pattern basedon yield related traits and molecular variation wasdifferent”

✓ located verbatim in the source · abstract, characters 496–584

Title

Multivariate analysis of the genetic diversity of bittergourd (Momordica charantia L.)

J. Resmi; I. Sreelathakumary Vegetable Science 2012

Other claims from this paper (2)
Associationobservedoriginal resultmeasured

Claim · model-written summary

Clustering of kabuli genotypes based on quantitative traits was similar to molecular clustering for most genotypes.

Taxon
kabuli genotypese0
Outcome
clustering patterne0
Direction
similare0
Comparator
molecular clusteringe0

Verbatim

e0

“Quantitative traits based clustering pattern was found to be similar to molecular clustering for most of the kabuli genotypes”

✓ located verbatim in the source · abstract, characters 436–561

Title

Genetic Diversity Analysis In Kabuli Chickpea (Cicer Arietinum L.) Genotypes Based On Quantitative Traits And Molecular Markers

Ravindra Singh Solanki; Anita Babbar; Niraj Tripathi Bangladesh Journal of Botany 2022. doi:10.3329/bjb.v51i3.62005

Other claims from this paper (2)

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