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Figure 8. F1 scores for YOLOv5 in Use of open-source object detection algorithms to detect Palmer amaranth (Amoronthus polmeri) in soybean

Figure 8. F1 scores for YOLOv5 indicating the harmonic mean between precision and recall scores. Data indicated that detection results for both species would be best at a confidence threshold of 0.298.

Figure 11. YOLOv5 in Use of open-source object detection algorithms to detect Palmer amaranth (Amoronthus polmeri) in soybean

Figure 11. YOLOv5 precision (A), recall (B), and F1 score (C) changes as a function of Amoronthus polmeri density (plants m−2).

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Figure 2 in Seed-shattering phenology at soybean harvest of economically important weeds in multiple regions of the United States. Part 1: Broadleaf species

Figure 2. Cumulative percent shatter over four time periods (soybean physiological maturity, maturity þ 2 wk,maturity þ 3 wk, maturity þ 4 wk) for each species.The darker the bar, the greater percent of sampled site-years that corresponded to the percent shatter value. This normalizes across species with different sampling efforts. Species sampled in just a single site-year are indicated by a single black square, which represents 100% of the sampling effort. Species are denoted by their EPPO codes.

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Figure 3 in Seed-shattering phenology at soybean harvest of economically important weeds in multiple regions of the United States. Part 1: Broadleaf species

Figure 3. Cumulative percent seed shatter for all species from planting date to soybean physiological maturity (black vertical line) for each state in 2016 and 2017. Species are denoted by their EPPO codes.

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Figure 1. Heat map indicating the cumulative percent seed shatter across the participating states for a in Seed-shattering phenology at soybean harvest of economically important weeds in multiple regions of the United States. Part 1: Broadleaf species

Figure 1. Heat map indicating the cumulative percent seed shatter across the participating states for a window starting from soybean physiological maturity to 4 wk past maturity in 2016 and 2017. States were included in these maps only if they conducted sampling during the week indicated (e.g., In 2017, Arkansas sampled on October 2, October 18, and November 3, none of which are within ±3 d of the October 10 maturity date or maturity þ2 wk on October 24 in the state that year. Hence only data from maturity þ3 wk are for Arkansas for 2017.)

Figure 10. Detection results for YOLOv5 with a in Use of open-source object detection algorithms to detect Palmer amaranth (Amoronthus polmeri) in soybean

Figure 10. Detection results for YOLOv5 with a confidence interval of 0.15. False-positive detections of Mollugo verticillata and Abutilon theophrasti as Amoronthus polmeri are denoted by arrows pointing from "A" and "B," respectively.

Figure 9. YOLOv5 in Use of open-source object detection algorithms to detect Palmer amaranth (Amoronthus polmeri) in soybean

Figure 9. YOLOv5 detection results for Amoronthus polmeri and soybean using confidence thresholds of 0.15 (A) and 0.70 (B). The likelihood of false-negative (FN) detections increases as confidence thresholds increase, as can be seen in B. Objects assigned a confidence interval of less than 0.70 are not detected in B. FN A. palmeri and soybean detections in B are indicated by the orange and white arrows, respectively.

Figure 7 in Use of open-source object detection algorithms to detect Palmer amaranth (Amoronthus polmeri) in soybean

Figure 7. Image annotation of soybean at the R2 growth stage. As soybean populations were much higher than Amoronthus polmeri populations, there was a high level of soybean overlap. Therefore, it was necessary to include multiple soybean plants in each image. However, A. polmeri plants typically did not have as much overlap, and in most cases, it was much easier to identify and label individual plants.

Figure 3 in Use of open-source object detection algorithms to detect Palmer amaranth (Amoronthus polmeri) in soybean

Figure 3. Intersection over union (IoU) equation, defined as the overlap between the ground truth annotation and the computer prediction bounding box, divided by the total area of the two bounding boxes.IoU overlaps greater than 0.5 were considered true-positive predictions,whereas overlaps less than 0.5 were considered false-positive predictions.

Figure 2 in Use of open-source object detection algorithms to detect Palmer amaranth (Amoronthus polmeri) in soybean

Figure 2. Illustration of the annotation process. Amoronthus polmeri and soybean plants are labeled in this figure with orange and white boxes, respectively. Bounding boxes overlap with neighboring bounding boxes when plant features are irregular. In cases where a single bounding box could not encompass a plant without including a plant of another species, multiple irregular bounding boxes were drawn on a single specimen.

Figure 4 in Use of open-source object detection algorithms to detect Palmer amaranth (Amoronthus polmeri) in soybean

Figure 4. Mean average precision (mAP) results of each model after training. YOLOv5 was considered the best-performing algorithm of each tested model with a mAP of 0.77.

Figure 6. Precision–recall curve for YOLOv5. Amoronthus polmeri achieved a in Use of open-source object detection algorithms to detect Palmer amaranth (Amoronthus polmeri) in soybean

Figure 6. Precision–recall curve for YOLOv5. Amoronthus polmeri achieved a slightly higher average precision (AP) (0.788) than soybean. Solid blue line represents mean average precision (mAP) computed on the test data set. The AP for each class and the mAP for the overall algorithm were representative of the area of the graph under each respective curve.

Figure 5 in Use of open-source object detection algorithms to detect Palmer amaranth (Amoronthus polmeri) in soybean

Figure 5. Change in mean average precision (mAP) @ 0.5 over each epoch during training. mAP was reported after the completion of each epoch. Training was terminated after visual inspection of curve and when mAP @ 0.5 curve was seen to "plateau."

Figure 4 in Effects of Palmer Amaranth (Amoronthus polmeri) Establishment Time and Distance from the Crop Row on Biological and Phenological Characteristics of the Weed: Implications on Soybean Yield

Figure 4. Effects of the interaction of weed establishment time and distance from the crop row on Amoronthus polmeri dry weight before soybean harvest. Vertical bars represent ± standard error of the mean (SE2014 = 1.27; SE2015 = 0.74) from the analysis for comparisons between weed establishment times with sample size n = 72. WAE, weeks after soybean emergence.

Figure 3 in Effects of Palmer Amaranth (Amoronthus polmeri) Establishment Time and Distance from the Crop Row on Biological and Phenological Characteristics of the Weed: Implications on Soybean Yield

Figure 3. Effects of the interaction of weed establishment time and distance from the crop on Amoronthus polmeri plant height at harvest. Vertical bars represent ± standard error of the mean (SE2014 = 4.68; SE2015 = 3.14) from the analysis for comparisons between weed establishment times with sample size n = 72. WAE, weeks after soybean emergence.

Figure 7 in Effects of Palmer Amaranth (Amoronthus polmeri) Establishment Time and Distance from the Crop Row on Biological and Phenological Characteristics of the Weed: Implications on Soybean Yield

Figure 7. Relationship between ground cover and extinction coefficient for each sampling date (n = 12 plots) throughout the 2014 growing season. WAE, weeks after soybean emergence.

Figure 2 in Effects of Palmer Amaranth (Amoronthus polmeri) Establishment Time and Distance from the Crop Row on Biological and Phenological Characteristics of the Weed: Implications on Soybean Yield

Figure 2. Soybean and Amoronthus polmeri (AMAPA) height (averaged across distance from the crop) at 0, 1, 2, 4, 6, and 8 wk after soybean emergence (WAE) (i.e., AMAPA-0, AMAPA-1, AMAPA-2, AMAPA-4, AMAPA-6, and AMAPA-8, respectively). Vertical bars represent ± standard error of the mean from the analysis for comparisons within each sampling date (i.e., n = 12 for 0 WAE, 24 for 1 WAE, etc.).

Figure 9 in Effects of Palmer Amaranth (Amoronthus polmeri) Establishment Time and Distance from the Crop Row on Biological and Phenological Characteristics of the Weed: Implications on Soybean Yield

Figure 9. Effects of weed establishment time on soybean yield averaged across Amoronthus polmeri distances from the crop row. Dashed lines indicate the confidence intervals at 95% confidence level (sample size n = 72). WAE, weeks after soybean emergence.

Figure 10 in Effects of Palmer Amaranth (Amoronthus polmeri) Establishment Time and Distance from the Crop Row on Biological and Phenological Characteristics of the Weed: Implications on Soybean Yield

Figure 10. Effects of Amoronthus polmeri distance from the soybean row on crop yield averaged across A. polmeri establishment times. Vertical bars represent ± standard error of the mean (SE2014 = 337.45; SE2015 = 207.14) from the analysis for comparisons between A. polmeri distances from the crop with sample size n = 72.

Figure 6 in Effects of Palmer Amaranth (Amoronthus polmeri) Establishment Time and Distance from the Crop Row on Biological and Phenological Characteristics of the Weed: Implications on Soybean Yield

Figure 6. Effects of weed establishment time on Amoronthus polmeri (AMAPA) flowering (averaged across distance from the crop) at various sampling occasions for 0, 1, 2, 4, 6, and 8 wk after soybean emergence (WAE) (i.e., AMAPA-0, AMAPA-1, AMAPA-2, AMAPA-4, AMAPA-6, and AMAPA-8 respectively) in 2014 and 2015. Vertical bars represent ± standard error of the mean (i.e., flowering of the entire A. polmeri population was evaluated at each sampling occasion) from the analysis for comparisons within each sampling date (i.e., n = 12 plots for 0 WAE, 24 plots for 1 WAE, 36 plots for 2 WAE, etc.).