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Method / resourceobservedoriginal resultno effectmeasured

Claim · model-written summary

The 3K array and GBS-based SNPs performed similarly for training population optimization, forward prediction, and univariate and multivariate genomic prediction of forage yield in oat.

Outcome
performancee0
Direction
similare0
Comparator
GBS-based SNPse0

Verbatim

e0

“similar performance of both the 3K array and GBS-based SNPs in terms of training population optimization, forward prediction, and univariate and multivariate genomic prediction of forage yield”

✓ located verbatim in the source · abstract, characters 702–894
t0

“biomass yield in oat”

✓ located verbatim in the source · title, characters 114–134

Title

Effectiveness of low‐density high‐throughput marker platform and easy‐to‐measure traits for genomic prediction of biomass yield in oat ( Avena sativa L.)

Samuel A. Adewale; Md Ali Babar; Diego Jarquin; et al. The Plant Genome 2026. doi:10.1002/tpg2.70179

Other claims from this paper (4)
Method / resourceobservedoriginal resultno effectmeasured

Claim · model-written summary

GBLUP, Bayes-B and random forest models gave similar predictive ability for dry matter yield across harvest-year combinations and both marker platforms.

Outcome
predictive ability for dry matter yield (DMY)e0
Direction
similare0
Comparator
Bayes-Be0

Verbatim

e0

“The genomic best linear unbiased prediction (GBLUP), Bayes-B, and random forest models gave similar predictive ability for dry matter yield (DMY)”

✓ located verbatim in the source · abstract, characters 896–1041
t0

“biomass yield in oat”

✓ located verbatim in the source · title, characters 114–134

Title

Effectiveness of low‐density high‐throughput marker platform and easy‐to‐measure traits for genomic prediction of biomass yield in oat ( Avena sativa L.)

Samuel A. Adewale; Md Ali Babar; Diego Jarquin; et al. The Plant Genome 2026. doi:10.1002/tpg2.70179

Other claims from this paper (4)
Method / resourceobservedoriginal resultno effectmeasured

Claim · model-written summary

The choice of scoring model (linear, non-linear or membership function) had a minimal effect on the final SQI results.

Taxon
MiscanthusMiscanthust0
Outcome
final SQI resultse0
Comparator
scoring modele0

Verbatim

t0

“Miscanthus cultivation enhances soil quality”

✓ located verbatim in the source · title, characters 10–54
e0

“the choice of scoring model had a minimal effect on the final SQI results”

✓ located verbatim in the source · abstract, characters 843–916

Title

Long-term Miscanthus cultivation enhances soil quality in degraded acidic red soils: A multi-indicator assessment

Tiansu Tan; Weiwei Hu; Tongcheng Fu; et al. Industrial Crops and Products 2026. doi:10.1016/j.indcrop.2026.123001

Other claims from this paper (10)
Method / resourceobservedoriginal resultno effectmeasured

Claim · model-written summary

For the linearly interpolated dataset, the predictive performance of the feature-fusion strategy was comparable across the three models.

Outcome
predictive performancee1
Direction
comparablee1
Comparator
the three modelse1

Verbatim

e1

“the predictive performance of the feature-fusion strategy was comparable across the three models”

✓ located verbatim in the source · abstract, characters 2327–2423

Title

Detection of Soluble Solid Content in Xinyu Pears Using Near-Infrared Spectroscopy and Deep Fusion of Multi-Preprocessed Spectral Data

Hengnian Qi; Hao Wang; Quanqing Liao; et al. Applied Sciences 2026. doi:10.3390/app16104732

Other claims from this paper (12)
Method / resourceobservedoriginal resultno effectmeasured

Claim · model-written summary

Across side and front overlap combinations at 60–120 m, reduced overlaps produced RMSE values comparable to full overlaps.

Taxon
corn, cotton, sorghum, and soybeanGossypium hirsutumGlycine maxSorghumZea mays subsp. mayse1
Outcome
RMSE valuese0
Direction
comparablee0
Comparator
full overlapse0

Verbatim

e0

“reduced overlaps produced RMSE values comparable to full overlaps”

✓ located verbatim in the source · abstract, characters 1283–1348
e1

“corn, cotton, sorghum, and soybean”

✓ located verbatim in the source · abstract, characters 710–744

Title

Effects of Flight and Processing Parameters on UAS Image-Based Point Clouds for Plant Height Estimation

Chenghai Yang; Charles P.-C. Suh; Bradley K. Fritz Remote Sensing 2026. doi:10.3390/rs18020360

Other claims from this paper (7)
Method / resourceobservedoriginal resultno effectmeasured

Claim · model-written summary

Canopy height from day and night LiDAR flights differed very little (change in R2 at most 0.01) and was highly replicable.

Outcome
CHe0
Value
Δ R 2 ≤0.01e0
Qualifier
highly replicablee0
Comparator
day and night flightse0

Verbatim

e0

“When comparing between LiDAR data collected during day and night flights, CH showed very little difference (Δ R 2 ≤0.01) and were found to be highly replicable”

✓ located verbatim in the source · abstract, characters 1143–1302
e1

“multi-planting date (seven dates) corn experiments conducted in Temple, Texas”

✓ located verbatim in the source · abstract, characters 887–964

Title

Assessing day and night UAV-based estimates of crop characterization using LiDAR

K. Colton Flynn; Gurjinder S. Baath; Bala Ram Sapkota; et al. Smart Agricultural Technology 2026. doi:10.1016/j.atech.2026.101805

Other claims from this paper (4)
Method / resourceobservedoriginal resultno effectmeasured

Claim · model-written summary

For selection, differences among second-stage models were minor.

Taxon
sweetpotatoIpomoea batatast0
Outcome
differences among second-stage modelse1
Value
minore1

Verbatim

e1

“For selection, differences among second-stage models were minor”

✓ located verbatim in the source · abstract, characters 1404–1467
t0

“sweetpotato”

✓ located verbatim in the source · title, characters 10–21

Title

Towards a sweetpotato genomic-enabled breeding: optimizing two-stage analysis of multi-environment augmented trials

Saulo Chaves; Reuben Ssali; José Tiago B. Chagas; et al. Theoretical and Applied Genetics 2026. doi:10.1007/s00122-026-05204-x

Other claims from this paper (6)
Method / resourceobservedoriginal resultno effectmeasured

Claim · model-written summary

Using the complete dataset, differences between entries in prediction were marginal.

Taxon
sweetpotatoIpomoea batatast0
Outcome
differences between entriese1
Value
marginale1

Verbatim

e1

“Using the complete dataset, differences between entries were marginal”

✓ located verbatim in the source · abstract, characters 1685–1754
t0

“sweetpotato”

✓ located verbatim in the source · title, characters 10–21

Title

Towards a sweetpotato genomic-enabled breeding: optimizing two-stage analysis of multi-environment augmented trials

Saulo Chaves; Reuben Ssali; José Tiago B. Chagas; et al. Theoretical and Applied Genetics 2026. doi:10.1007/s00122-026-05204-x

Other claims from this paper (6)
Method / resourceobservedoriginal resultno effectnot significant (as stated)measured

Claim · model-written summary

DBH showed no significant difference between P2U MLS and RTC360 TLS.

Taxon
Urban Street Treest0
Outcome
DBHe1
Direction
no significant differencee1
Value
p=0.6078e1
Comparator
RTC360e0

Verbatim

t0

“Inter-Sensor Error Analysis between TLS and MLS for Urban Street Trees toward Digital Twin Development”

✓ located verbatim in the source · title, characters 0–102
e0

“P2U tended to underestimate TreeHeight and crown-related metrics compared with RTC360 (Δ TreeHeight=−1.02m; ΔCrownVolume=−103.38m³ )”

✓ located verbatim in the source · abstract, characters 753–885
e1

“while DBH showed no significant difference (Wilcoxon p=0.6078)”

✓ located verbatim in the source · abstract, characters 887–949

Title

Inter-Sensor Error Analysis between TLS and MLS for Urban Street Trees toward Digital Twin Development

Yongbum Park; Gunwon Lee KIEAE Journal 2026. doi:10.12813/kieae.2026.26.1.055

Other claims from this paper (6)
Method / resourceobservedoriginal resultno effectmeasured

Claim · model-written summary

The machine learning model maintained a heritability for blackleg resistance similar to that of expert raters.

Outcome
heritabilitye2
Direction
similare2
Qualifier
blackleg resistance traite2
Comparator
expert raterse2

Verbatim

e1

“infected canola ( Brassica napus L., Brassica rapa L ., Brassica juncea L .)”

✓ located verbatim in the source · abstract, characters 99–175
e2

“while maintaining a similar heritability as expert raters for the blackleg resistance trait”

✓ located verbatim in the source · abstract, characters 1081–1172

Title

Phenotypic scoring of canola blackleg severity using machine learning image analysis

Qiao Hu; Sarah Anderson; Stuart Gardner; et al. The Plant Phenome Journal 2026. doi:10.1002/ppj2.70063

Other claims from this paper (3)

Lexical search (BM25). All words must match; if nothing does, any word. Organism names also match every spelling of the same organism. No semantic search yet.