Search claims · PlantClaims

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

CPD-YOLO generalization showed a 0.55 % mAP decrease.

Taxon: cottonGossypium hirsutumt0
Outcome: mAPe0
Direction: decreasee0
Value: 0.55 %e0

Not reportedComparator

Verbatim

e0
“the CPD-YOLO model had superior generalization capability, with a 1.30 % decrease in F1-score and a 0.55 % decrease in mAP.”
✓ located verbatim in the source · abstract, characters 1287–1410

t0
“cotton pests and diseases”
✓ located verbatim in the source · title, characters 48–73

Title

CPD-YOLO: A cross-platform detection method for cotton pests and diseases using UAV and smartphone imaging

Guowei Yu; Benxue Ma; Ruoyu Zhang; et al. Industrial Crops and Products 2025. doi:10.1016/j.indcrop.2025.121515

Other claims from this paper (7)

Method / resource The improvement strategy improved multi-scale object detection accuracy in cross-platform scenarios.
Method / resource CPD-YOLO increased F1-score by 7.44 % versus the original model.
Method / resource CPD-YOLO increased mAP by 7.08 % versus the original model.
Method / resource CPD-YOLO outperformed typical detectors with an F1-score of 88.86 %.
Method / resource CPD-YOLO outperformed typical detectors with mAP of 90.42 %.
Method / resource CPD-YOLO generalization showed a 1.30 % F1-score decrease.
Method / resource A mobile application named Doctor Cotton using CPD-YOLO was developed.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

YOLOv8n-RML shows a 34.5% decrease in GFLOPS for strawberry ripeness detection.

Taxon: strawberryFragaria ×ananassae0
Outcome: GFLOPSe2
Direction: decreasee2
Value: 34.5%e2

Verbatim

e0
“specifically tailored for strawberry harvesting”
✓ located verbatim in the source · abstract, characters 79–126

e2
“The YOLOv8n-RML model demonstrates a 48.6% reduction in parameters and a 34.5% decrease in GFLOPS”
✓ located verbatim in the source · abstract, characters 1002–1099

Title

A Lightweight Detection Algorithm for Strawberry Ripeness

Gaofeng Xu; Zhengcai Wang IEEE Access 2025. doi:10.1109/access.2025.3627896

Other claims from this paper (2)

Method / resource YOLOv8n-RML has a higher mAP than the baseline YOLOv8 model for strawberry ripeness detection, at 91.3%.
Method / resource YOLOv8n-RML shows a 48.6% reduction in parameters for strawberry ripeness detection.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

CPD-YOLO generalization showed a 1.30 % F1-score decrease.

Taxon: cottonGossypium hirsutumt0
Outcome: F1-scoree0
Direction: decreasee0
Value: 1.30 %e0

Not reportedComparator

Verbatim

e0
“the CPD-YOLO model had superior generalization capability, with a 1.30 % decrease in F1-score and a 0.55 % decrease in mAP.”
✓ located verbatim in the source · abstract, characters 1287–1410

t0
“cotton pests and diseases”
✓ located verbatim in the source · title, characters 48–73

Title

CPD-YOLO: A cross-platform detection method for cotton pests and diseases using UAV and smartphone imaging

Guowei Yu; Benxue Ma; Ruoyu Zhang; et al. Industrial Crops and Products 2025. doi:10.1016/j.indcrop.2025.121515

Other claims from this paper (7)

Method / resource The improvement strategy improved multi-scale object detection accuracy in cross-platform scenarios.
Method / resource CPD-YOLO increased F1-score by 7.44 % versus the original model.
Method / resource CPD-YOLO increased mAP by 7.08 % versus the original model.
Method / resource CPD-YOLO outperformed typical detectors with an F1-score of 88.86 %.
Method / resource CPD-YOLO outperformed typical detectors with mAP of 90.42 %.
Method / resource CPD-YOLO generalization showed a 0.55 % mAP decrease.
Method / resource A mobile application named Doctor Cotton using CPD-YOLO was developed.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

The two approaches gave a higher decrease rate with fewer samples.

Taxon: WatermelonCitrullus lanatust0
Outcome: decrease ratee0
Direction: highere0
Comparator: smaller quantitiese0

Verbatim

e0
“Testing different amount of samples, the two approaches can provide higher decrease rate in smaller quantities”
✓ located verbatim in the source · abstract, characters 810–920

t0
“Watermelon”
✓ located verbatim in the source · title, characters 36–46

Title

An Efficient Recognition Method for Watermelon using Faster R-CNN with Post-Processing

Ming-Jui Ho; Yu-Chin Lin; Hsin-Chuan Hsu; et al. 2019 8th International Conference on Innovation, Communication and Engineering (ICICE) 2019. doi:10.1109/icice49024.2019.9117374

Other claims from this paper (3)

Method / resource Cross scanning reduced missed watermelons from 30% to 18%.
Method / resource HSV color filtering reduced the recognition error rate from 6.1% to 1.4%.
Method / resource Aerial watermelon recognition and yield estimation saved time versus manual labeling.

Method / resourceauthor interpretationoriginal resultpositivemeasured

Claim · model-written summary

Feature importance suggests one camera may suffice without a significant accuracy decrease.

Taxon: CornZea mays subsp. mayst0
Outcome: accuracye0
Direction: without significant decreasee0
Comparator: one camerae0

Verbatim

e0
“Feature weight importance suggests that one camera may be sufficient for prediction without significant decrease in accuracy”
✓ located verbatim in the source · abstract, characters 991–1115

t0
“Corn Ear Height Prediction”
✓ located verbatim in the source · title, characters 10–36

Title

Automated Corn Ear Height Prediction Using Video-Based Deep Learning

Johnson Wong; Hao Sha; Mohammad Al Hasan; et al. 2020 IEEE International Conference on Big Data (Big Data) 2020. doi:10.1109/bigdata50022.2020.9378115

Other claims from this paper (3)

Method / resource The video model predicted average plot ear height with 0.772 concordance against hand measurements.
Method / resource The model had 2.989 inches root mean squared error against hand measured ear height.
Method / resource The model had 2.263 inches mean absolute error against hand measured ear height.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

Increasing replications from five to six gave only a small decrease in L.S.D.

Taxon: CornZea mays subsp. mayst0
Outcome: L.S.D.e0
Direction: decreasee0
Value: 5 to 6e0

Verbatim

e0
“There was only a small decrease in L.S.D. by increasing the replications from 5 to 6.”
✓ located verbatim in the source · abstract, characters 391–476

t0
“Hybrid Corn”
✓ located verbatim in the source · title, characters 26–37

Title

Field Plot Technique With Hybrid Corn Under Alabama Conditions¹

A. A. Fleming; T. Hayden Rogers; T. A. Bancroft Agronomy Journal 1957. doi:10.2134/agronj1957.00021962004900010001x

Other claims from this paper (4)

Method / resource Plots one to three rows wide and 10 to 15 hills long were most efficient.
Recommendation Two-row plots 10 to 15 hills long were considered optimal for general use.
Recommendation A basic unit larger than five plants may be advantageous.
Recommendation The precision gain did not justify using simple lattice over randomized blocks.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

Model parameters fell from 9,413,574 to 2,297,334, a 75.6% decrease.

Outcome: number of model parameterse0
Direction: reducede0
Value: 2,297,334e0
Qualifier: a decrease of 75.6%e0
Comparator: YOLOv11se0

Not reportedTaxon

Verbatim

e0
“number of model parameters has been substantially reduced from 9,413,574 in YOLOv11s to 2,297,334 (a decrease of 75.6%)”
✓ located verbatim in the source · abstract, characters 1931–2050

Title

YOLO-MECD: Citrus Detection Algorithm Based on YOLOv11

Yue Liao; Lerong Li; Huiqiang Xiao; et al. Agronomy 2025. doi:10.3390/agronomy15030687

Other claims from this paper (15)

Method / resource Replacing C2PSA with EMA improved citrus detection accuracy and reduced model parameters.
Method / resource CSPPC reduced parameter count and computational complexity while maintaining mAP.
Method / resource MPDIoU improved bounding-box accuracy and convergence.
Method / resource Reducing backbone convolutions improved small-object detection and decreased parameters.
Method / resource YOLO-MECD precision was 84.4%, 0.2 points above baseline.
Method / resource YOLO-MECD recall was 73.3%.
Method / resource YOLO-MECD mAP was 81.6%.
Method / resource Against baseline, precision improved 0.2 percentage points.
Method / resource Against baseline, recall improved 4.1 percentage points.
Method / resource Against baseline, mAP improved 3.9 percentage points.
Method / resource Model size fell from 18.2 MB to 4.66 MB, a 74.4% reduction.
Method / resource mAP exceeded YOLOv8s by 3.8%.
Method / resource mAP exceeded YOLOv9s by 3.2%.
Method / resource mAP exceeded YOLOv10s by 5.5%.
Method / resource The model detected pomelos and kumquats well.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

Photodiode LEDIF tracked the drought-associated decrease in photochemical quenching (R2 = 0.69).

Taxon: Polygala myrtifoliaPolygala myrtifoliat0
Outcome: photochemical quenchinge0
Direction: decreasee0
Value: R2 = 0.69e0

Verbatim

e0
“LEDIFphotodiode closely tracked drought responses associated with a decrease in photochemical quenching (R2 = 0.69)”
✓ located verbatim in the source · abstract, characters 1701–1816

t0
“Polygala myrtifolia”
✓ located verbatim in the source · abstract, characters 985–1004

Title

Tracking canopy chlorophyll fluorescence with a low-cost light emitting diode platform

Logan E G Brissette; Christopher Y S Wong; Devin P McHugh; et al. AoB Plants 2023. doi:10.1093/aobpla/plad069

Other claims from this paper (3)

Method / resource Photodiode and hyperspectral LEDIF retrievals performed similarly, with R2 = 0.77.
Method / resource Photodiode LEDIF tracked the drought-associated decrease in Fv/Fm (R2 = 0.59).
Method / resource Photodiode LEDIF tracked the drought-associated decrease in leaf photochemical reflectance index (R2 = 0.59).

Method / resourceauthor interpretationoriginal resultpositiveprojected

Claim · model-written summary

The authors project direct operating costs will decrease up to 40% with AMS-7.

Taxon: FRUIT TREESt0
Outcome: direct operating costse0
Direction: decreasee0
Value: 40 %e0

Verbatim

e0
“a decrease in direct operating costs up to 40 %”
✓ located verbatim in the source · abstract, characters 1983–2030

t0
“FRUIT TREES”
✓ located verbatim in the source · title, characters 34–45

Title

MECHANIZATION OF CROWN PRUNING OF FRUIT TREES

G. I. Kadykalo POMICULTURE & SMALL FRUITS CULTURE IN RUSSIA 2020. doi:10.31676/2073-4948-2020-63-260-267

Other claims from this paper (7)

Observation Pruning accounts for 12–15% of maintenance labor costs.
Method / resource ASV-8 increased pruning labor productivity 2.8-fold.
Method / resource ASV-8 saved 3682 labor hours annually.
Method / resource ASV-8 reduced reduced costs by 33.3%.
Method / resource The AMS-7 unit is designed for contour pruning and other orchard operations.
Method / resource The authors project that AMS-7 will increase labor productivity up to 1.8-fold.
Method / resource The authors project labor costs will decrease up to 45% with AMS-7.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

The rate of soil water decrease was independent of sunflower genotype.

Taxon: sunflowerHelianthus annuust0
Outcome: rate of decrease in soil water contente0

Not reportedComparator

Verbatim

e0
“the rate of decrease in soil water content is independent of the genotype being evaluated”
✓ located verbatim in the source · abstract, characters 791–880

t0
“sunflower”
✓ located verbatim in the source · title, characters 44–53

Title

A method for drought tolerance screening in sunflower

G. A. Pereyra‐Irujo; L. Velázquez; C. Granier; et al. Plant Breeding 2007. doi:10.1111/j.1439-0523.2007.01375.x

Other claims from this paper (4)

Method / resource The method reproducibly evaluated drought tolerance in four sunflower inbred lines.
Method / resource The proposed method reached desired soil water content quickly.
Method / resource The resulting soil water content was uniform within pots.
Intervention effect Maize plants had no effect on sunflower genotype growth.

“decrease in A”

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