By organism › Green plants › Poaceae › Bothriochloa ischaemum

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

YOLOv12-DAN achieved 91.6% mAP for spike detection.

Taxon: Bothriochloa ischaemumBothriochloa ischaemumt0
Outcome: mean average precision (mAP)e0
Value: 91.6%e0

Verbatim

e0
“this study developed a modified model named YOLOv12-DAN by integrating DySample dynamic upsampling, ASFF feature fusion, and NWD loss, which achieved a mean average precision (mAP) of 91.6%.”
✓ located verbatim in the source · abstract, characters 686–876

t0
“Bothriochloa ischaemum”
✓ located verbatim in the source · title, characters 76–98

Title

Research on a Precision Counting Method and Web Deployment for Natural-Form Bothriochloa ischaemum Spikes and Seeds Based on Object Detection

Huamin Zhao; Yongzhuo Zhang; Yabo Zheng; et al. Agronomy 2026. doi:10.3390/agronomy16070706

Other claims from this paper (8)

Method / resource The kernel detection model attained 96.5% bounding box precision.
Method / resource The kernel detection model attained 86.4% recall.
Method / resource The kernel detection model attained 94.3% mAP50.
Method / resource The kernel detection model attained 73.9% mAP50-95.
Method / resource Seed count regression had MAE of 6.30.
Method / resource Seed count regression had MAPE of 9.35.
Method / resource Seed count regression had R2 of 0.808.
Method / resource The model was deployed in a web application enabling real-time field operation.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

The kernel detection model attained 96.5% bounding box precision.

Taxon: Bothriochloa ischaemumBothriochloa ischaemumt0
Outcome: bounding box precisione0
Value: 96.5%e0

Verbatim

e0
“The optimized model attained a bounding box precision of 96.5%, a recall rate of 86.4%, an mAP50 of 94.3%, and an mAP50-95 of 73.9%.”
✓ located verbatim in the source · abstract, characters 1088–1220

t0
“Bothriochloa ischaemum”
✓ located verbatim in the source · title, characters 76–98

Title

Research on a Precision Counting Method and Web Deployment for Natural-Form Bothriochloa ischaemum Spikes and Seeds Based on Object Detection

Huamin Zhao; Yongzhuo Zhang; Yabo Zheng; et al. Agronomy 2026. doi:10.3390/agronomy16070706

Other claims from this paper (8)

Method / resource YOLOv12-DAN achieved 91.6% mAP for spike detection.
Method / resource The kernel detection model attained 86.4% recall.
Method / resource The kernel detection model attained 94.3% mAP50.
Method / resource The kernel detection model attained 73.9% mAP50-95.
Method / resource Seed count regression had MAE of 6.30.
Method / resource Seed count regression had MAPE of 9.35.
Method / resource Seed count regression had R2 of 0.808.
Method / resource The model was deployed in a web application enabling real-time field operation.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

The kernel detection model attained 86.4% recall.

Taxon: Bothriochloa ischaemumBothriochloa ischaemumt0
Outcome: recall ratee0
Value: 86.4%e0

Verbatim

e0
“The optimized model attained a bounding box precision of 96.5%, a recall rate of 86.4%, an mAP50 of 94.3%, and an mAP50-95 of 73.9%.”
✓ located verbatim in the source · abstract, characters 1088–1220

t0
“Bothriochloa ischaemum”
✓ located verbatim in the source · title, characters 76–98

Title

Research on a Precision Counting Method and Web Deployment for Natural-Form Bothriochloa ischaemum Spikes and Seeds Based on Object Detection

Huamin Zhao; Yongzhuo Zhang; Yabo Zheng; et al. Agronomy 2026. doi:10.3390/agronomy16070706

Other claims from this paper (8)

Method / resource YOLOv12-DAN achieved 91.6% mAP for spike detection.
Method / resource The kernel detection model attained 96.5% bounding box precision.
Method / resource The kernel detection model attained 94.3% mAP50.
Method / resource The kernel detection model attained 73.9% mAP50-95.
Method / resource Seed count regression had MAE of 6.30.
Method / resource Seed count regression had MAPE of 9.35.
Method / resource Seed count regression had R2 of 0.808.
Method / resource The model was deployed in a web application enabling real-time field operation.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

The kernel detection model attained 94.3% mAP50.

Taxon: Bothriochloa ischaemumBothriochloa ischaemumt0
Outcome: mAP50e0
Value: 94.3%e0

Verbatim

e0
“The optimized model attained a bounding box precision of 96.5%, a recall rate of 86.4%, an mAP50 of 94.3%, and an mAP50-95 of 73.9%.”
✓ located verbatim in the source · abstract, characters 1088–1220

t0
“Bothriochloa ischaemum”
✓ located verbatim in the source · title, characters 76–98

Title

Research on a Precision Counting Method and Web Deployment for Natural-Form Bothriochloa ischaemum Spikes and Seeds Based on Object Detection

Huamin Zhao; Yongzhuo Zhang; Yabo Zheng; et al. Agronomy 2026. doi:10.3390/agronomy16070706

Other claims from this paper (8)

Method / resource YOLOv12-DAN achieved 91.6% mAP for spike detection.
Method / resource The kernel detection model attained 96.5% bounding box precision.
Method / resource The kernel detection model attained 86.4% recall.
Method / resource The kernel detection model attained 73.9% mAP50-95.
Method / resource Seed count regression had MAE of 6.30.
Method / resource Seed count regression had MAPE of 9.35.
Method / resource Seed count regression had R2 of 0.808.
Method / resource The model was deployed in a web application enabling real-time field operation.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

The kernel detection model attained 73.9% mAP50-95.

Taxon: Bothriochloa ischaemumBothriochloa ischaemumt0
Outcome: mAP50-95e0
Value: 73.9%e0

Verbatim

e0
“The optimized model attained a bounding box precision of 96.5%, a recall rate of 86.4%, an mAP50 of 94.3%, and an mAP50-95 of 73.9%.”
✓ located verbatim in the source · abstract, characters 1088–1220

t0
“Bothriochloa ischaemum”
✓ located verbatim in the source · title, characters 76–98

Title

Research on a Precision Counting Method and Web Deployment for Natural-Form Bothriochloa ischaemum Spikes and Seeds Based on Object Detection

Huamin Zhao; Yongzhuo Zhang; Yabo Zheng; et al. Agronomy 2026. doi:10.3390/agronomy16070706

Other claims from this paper (8)

Method / resource YOLOv12-DAN achieved 91.6% mAP for spike detection.
Method / resource The kernel detection model attained 96.5% bounding box precision.
Method / resource The kernel detection model attained 86.4% recall.
Method / resource The kernel detection model attained 94.3% mAP50.
Method / resource Seed count regression had MAE of 6.30.
Method / resource Seed count regression had MAPE of 9.35.
Method / resource Seed count regression had R2 of 0.808.
Method / resource The model was deployed in a web application enabling real-time field operation.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

Seed count regression had MAE of 6.30.

Taxon: Bothriochloa ischaemumBothriochloa ischaemumt0
Outcome: mean absolute error (MAE)e0
Value: 6.30e0

Verbatim

e0
“a univariate linear regression model based on 132 spike samples verified the reliable consistency between the predicted and actual seed counts, with a mean absolute error (MAE) of 6.30, a mean absolute percentage error (MAPE) of 9.35, and an R-squared (R2) value of 0.808.”
✓ located verbatim in the source · abstract, characters 1234–1506

t0
“Bothriochloa ischaemum”
✓ located verbatim in the source · title, characters 76–98

Title

Research on a Precision Counting Method and Web Deployment for Natural-Form Bothriochloa ischaemum Spikes and Seeds Based on Object Detection

Huamin Zhao; Yongzhuo Zhang; Yabo Zheng; et al. Agronomy 2026. doi:10.3390/agronomy16070706

Other claims from this paper (8)

Method / resource YOLOv12-DAN achieved 91.6% mAP for spike detection.
Method / resource The kernel detection model attained 96.5% bounding box precision.
Method / resource The kernel detection model attained 86.4% recall.
Method / resource The kernel detection model attained 94.3% mAP50.
Method / resource The kernel detection model attained 73.9% mAP50-95.
Method / resource Seed count regression had MAPE of 9.35.
Method / resource Seed count regression had R2 of 0.808.
Method / resource The model was deployed in a web application enabling real-time field operation.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

Seed count regression had MAPE of 9.35.

Taxon: Bothriochloa ischaemumBothriochloa ischaemumt0
Outcome: mean absolute percentage error (MAPE)e0
Value: 9.35e0

Verbatim

e0
“a univariate linear regression model based on 132 spike samples verified the reliable consistency between the predicted and actual seed counts, with a mean absolute error (MAE) of 6.30, a mean absolute percentage error (MAPE) of 9.35, and an R-squared (R2) value of 0.808.”
✓ located verbatim in the source · abstract, characters 1234–1506

t0
“Bothriochloa ischaemum”
✓ located verbatim in the source · title, characters 76–98

Title

Research on a Precision Counting Method and Web Deployment for Natural-Form Bothriochloa ischaemum Spikes and Seeds Based on Object Detection

Huamin Zhao; Yongzhuo Zhang; Yabo Zheng; et al. Agronomy 2026. doi:10.3390/agronomy16070706

Other claims from this paper (8)

Method / resource YOLOv12-DAN achieved 91.6% mAP for spike detection.
Method / resource The kernel detection model attained 96.5% bounding box precision.
Method / resource The kernel detection model attained 86.4% recall.
Method / resource The kernel detection model attained 94.3% mAP50.
Method / resource The kernel detection model attained 73.9% mAP50-95.
Method / resource Seed count regression had MAE of 6.30.
Method / resource Seed count regression had R2 of 0.808.
Method / resource The model was deployed in a web application enabling real-time field operation.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

Seed count regression had R2 of 0.808.

Taxon: Bothriochloa ischaemumBothriochloa ischaemumt0
Outcome: R-squared (R2)e0
Value: 0.808e0

Verbatim

e0
“a univariate linear regression model based on 132 spike samples verified the reliable consistency between the predicted and actual seed counts, with a mean absolute error (MAE) of 6.30, a mean absolute percentage error (MAPE) of 9.35, and an R-squared (R2) value of 0.808.”
✓ located verbatim in the source · abstract, characters 1234–1506

t0
“Bothriochloa ischaemum”
✓ located verbatim in the source · title, characters 76–98

Title

Research on a Precision Counting Method and Web Deployment for Natural-Form Bothriochloa ischaemum Spikes and Seeds Based on Object Detection

Huamin Zhao; Yongzhuo Zhang; Yabo Zheng; et al. Agronomy 2026. doi:10.3390/agronomy16070706

Other claims from this paper (8)

Method / resource YOLOv12-DAN achieved 91.6% mAP for spike detection.
Method / resource The kernel detection model attained 96.5% bounding box precision.
Method / resource The kernel detection model attained 86.4% recall.
Method / resource The kernel detection model attained 94.3% mAP50.
Method / resource The kernel detection model attained 73.9% mAP50-95.
Method / resource Seed count regression had MAE of 6.30.
Method / resource Seed count regression had MAPE of 9.35.
Method / resource The model was deployed in a web application enabling real-time field operation.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

The model was deployed in a web application enabling real-time field operation.

Taxon: Bothriochloa ischaemumBothriochloa ischaemumt0
Outcome: real-time field operatione0

Not reportedComparatorValue

Verbatim

e0
“the model was deployed through a lightweight end-to-end web application, enabling real-time field operation”
✓ located verbatim in the source · abstract, characters 1516–1623

t0
“Bothriochloa ischaemum”
✓ located verbatim in the source · title, characters 76–98

Title

Research on a Precision Counting Method and Web Deployment for Natural-Form Bothriochloa ischaemum Spikes and Seeds Based on Object Detection

Huamin Zhao; Yongzhuo Zhang; Yabo Zheng; et al. Agronomy 2026. doi:10.3390/agronomy16070706

Other claims from this paper (8)

Method / resource YOLOv12-DAN achieved 91.6% mAP for spike detection.
Method / resource The kernel detection model attained 96.5% bounding box precision.
Method / resource The kernel detection model attained 86.4% recall.
Method / resource The kernel detection model attained 94.3% mAP50.
Method / resource The kernel detection model attained 73.9% mAP50-95.
Method / resource Seed count regression had MAE of 6.30.
Method / resource Seed count regression had MAPE of 9.35.
Method / resource Seed count regression had R2 of 0.808.

Observationobservedoriginal resultmeasured

Claim · model-written summary

The maximum composite root parameter occurred in Bothriochloa ischaemum.

Taxon: Bothriochloa ischaemum (Linn.) KengBothriochloa ischaemume0
Outcome: maximum valuee0
Direction: maximume0

Verbatim

e0
“The maximum value was observed in Bothriochloa ischaemum (Linn.) Keng”
✓ located verbatim in the source · abstract, characters 1020–1089

Title

Construction of a Comprehensive Root Parameter to Reflect the Effect of Plant Root Systems on Soil Erosion

JianFang Wang; GuoBin Liu; YanFen Yang; et al. Land Degradation and Development 2026. doi:10.1002/ldr.70456

Other claims from this paper (11)

Bothriochloa ischaemum 382 claims

382 claims