case_images: PMC8427806_01
case_images: Timeline of the growing season for different almond varieties from full bloom to commercial harvest dates in 2019. All harvest dates were recorded from the experimental orchards, while other dates (i.e., full bloom and hull split) were estimated based on the studies of Connell et al. and Lampinen et al., except full bloom date for 'Nonpareil' was also recorded from the experimental orchards.
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case_images: F2
case_images: Figure 11 compares the accuracies (R2) of the different measuring levels [per-tree (VO only), per-block, and per-row] in explaining almond actual kernel yield on June 26.
case_images: Changes of canopy fractional PAR (fPAR) estimated by Virtual Orchard (VO) over the growing season in 2019. Different letters refer to a statistically significant difference over the season for each variety and age using Tukey honestly significant difference (HSD) test (p < 0.05). The size of the confidence intervals of 95% was drawn. Means +- standard deviations (SD) of the yield (lb acre-1) for each group were 2000.76 +- 385.38, nan (no data available), 2121.86 +- 572.39, 1013.60 +- 395.84, 1558.49 +- 520.28, 1055.28 +- 386.69, 988.85 +- 463.91, 1436.00 +- 250.07, nan, respectively, from the top to the bottom of the legend.
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case_images: F3
case_images: Figure 3 shows the overall trend of VO estimated fPAR with individual almond variety and age over the growing season in 2019.
case_images: PMC8427806_02
case_images: Timeline of the growing season for different almond varieties from full bloom to commercial harvest dates in 2019. All harvest dates were recorded from the experimental orchards, while other dates (i.e., full bloom and hull split) were estimated based on the studies of Connell et al. and Lampinen et al., except full bloom date for 'Nonpareil' was also recorded from the experimental orchards.
case_images: fpls-12-715361-g0002.jpg
case_images: PMC8427806_02_fpls-12-715361-g0002.jpg
case_images: F2
case_images: Figure 11 compares the accuracies (R2) of the different measuring levels [per-tree (VO only), per-block, and per-row] in explaining almond actual kernel yield on June 26.
case_images: Calibration of Virtual Orchard (VO) against mobile lightbar platform (both on June 26) estimated canopy fractional PAR (fPAR) with all varieties (A) and 'Nonpareil' only (B) at the per-row level (when forcing a zero intercept).
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case_images: F4
case_images: Figure 4A visualizes the calibration of the VO estimated fPAR against the lightbar estimated midday fPAR over all varieties on June 26. Figure 4B visualized a similar calibration for 'Nonpareil' only with a better R2 of 0.96 and a lower RMSE of 2.06% to the 1:1 line (the difference was significant as shown in
case_images: Correlations of Virtual Orchard (VO) estimated canopy fractional PAR (fPAR) over the growing season in 2019. Scatter plots are shown in the lower-left half, kernel-density-estimate plots are shown in the upper right half, and histograms are shown on the diagonal. The black dotted line indicates the 1:1 line. r refers to Pearson's correlation coefficient.
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case_images: F5
case_images: Figure 5 shows the overall correlations of VO estimated fPAR over the growing season in 2019. Figure 5 illustrates the results of 12 different flights, image processing, and feature extractions conducted by the VO pipeline. High correlations in Figure 5 show the robustness and replicability of the VO methodology that consistently and accurately estimated fPAR in all 12 datasets.
case_images: Comparison of R2 and root mean square error (RMSE) (to regression line) between Virtual Orchard (VO) and the mobile lightbar platform estimated canopy Fractional PAR (fPAR) and actual almond kernel yield for all varieties and 'Nonpareil' only over the season in 2019 at the per-row level. Different letters refer to a statistically significant difference testing the means of absolute errors in predicting actual almond yield with different regression models using analysis of variance (ANOVA) multi-comparison (p < 0.05).
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case_images: F6
case_images: Figure 6 summarizes the overall results, and Figure 7 shows more details in Supplementary Material. Interestingly, a descending trend of yield prediction accuracy is present from May to August when we tested all varieties (Figure 6). When we only considered the 'Nonpareil' variety, we observed an increasing trend in accuracy (R2) similar to the per-row models (Figure 6).
case_images: Comparison of accuracies of actual almond yield explained by Virtual Orchard (VO) estimated canopy Fractional PAR (fPAR) over the season: May 28 (A), June 26 (B), July 26 (C), August 7 (D), and the mobile lightbar platform (June 26) (E) at the per-row level in 2019. The potential almond yield (57.9 lb acre-1) was based on the results reported by Jin et al. using a lightbar.
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case_images: F7
case_images: Figure 6 summarizes the overall results, and Figure 7 shows more details in Supplementary Material. Both regression lines in Figures 7B,E had similar slopes (32 for VO; 36 for lightbar) and intercept on the y-axis. Figure 8) had a smaller angle to the 1:1 line for 'Nonpareil' than all varieties combined in Figure 7. First of all, all data points (at the per-row level in Figure 7) were below the 1:1 line, indicating that none of the samples reached the potential yield in this study. Specifically, with the increase of estimated fPAR on the x-axis (0-100%), the slope of the regression lines moved farther (35.6 in Figure 7A to 29.0 in Figure 7D) from the potential yield line over the season for all varieties, suggesting that the actual yield prediction became less accurate.
case_images: Comparison of accuracies of actual 'Nonpareil' almond yield explained by Virtual Orchard (VO) estimated canopy Fractional PAR (fPAR) over the season: May 28 (A), June 26 (B), July 26 (C), August 7 (D), and the mobile lightbar platform (June 26) (E) at the per-row level in 2019. The potential almond yield (57.7 lb acre-1) was based on the results reported by Jin et al. using a lightbar.
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case_images: F8
case_images: Figure 8) had a smaller angle to the 1:1 line for 'Nonpareil' than all varieties combined in Figure 7. First of all, all data points (at the per-row level in Figure 7) were below the 1:1 line, indicating that none of the samples reached the potential yield in this study. Specifically, with the increase of estimated fPAR on the x-axis (0-100%), the slope of the regression lines moved farther (35.6 in Figure 7A to 29.0 in Figure 7D) from the potential yield line over the season for all varieties, suggesting that the actual yield prediction became less accurate. Comparatively, the regression lines directions were closer to the 1:1 line for 'Nonpareil' only (Figures 8A-D).
case_images: Comparison of R2 and root mean square error (RMSE) (to regression line) between fPAR Virtual Orchard (fractional PAR estimated by VO) and actual almond kernel yield for all varieties and 'Nonpareil' only over the season in 2019 at the per-tree level. Different letters refer to a statistically significant difference testing the means of absolute errors in predicting actual almond yield with different regression models using analysis of variance (ANOVA) multi-comparison (p < 0.05).
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case_images: F9
case_images: Specifically, with the increase of estimated fPAR on the x-axis (0-100%), the slope of the regression lines moved farther (35.6 in Figure 7A to 29.0 in Figure 7D) from the potential yield line over the season for all varieties, suggesting that the actual yield prediction became less accurate. Figure 9 visualizes the regressions between per-tree fPAR (estimated by VO) and almond kernel yield over the season in 2019.
case_images: Comparison of accuracies of actual almond yield explained by Virtual Orchard (VO) estimated canopy fractional PAR (fPAR) over the season with all varieties: May 28 (A), June 26 (B), July 26 (C), and August 7 (D); and 'Nonpareil' only: May 28 (E), June 26 (F), July 26 (G), and August 7 (H) at the per-tree level in 2019. The potential almond yield (57.9 lb acre-1 for all varieties; 57.7 lb acre-1 for 'Nonpareil' only) was based on the results reported by Jin et al. using a lightbar.
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case_images: PMC8427806_02_fpls-12-715361-g0010.jpg
case_images: F10
case_images: Specifically, with the increase of estimated fPAR on the x-axis (0-100%), the slope of the regression lines moved farther (35.6 in Figure 7A to 29.0 in Figure 7D) from the potential yield line over the season for all varieties, suggesting that the actual yield prediction became less accurate. Figure 10 provides in-depth details. Two 'Monterey' trees (in yellow "x" symbol) yielded (5094.49 and 3801.04 lb acre-1) more than their potential yields (i.e., the two symbols were above the potential line in Figures 10A-D).
case_images: Comparison of R2 and root mean square error (RMSE) (to regression line) between fPAR Virtual Orchard (fractional PAR estimated by VO) and actual almond kernel yield for all varieties and 'Nonpareil' only at the per-tree, per-block, and per-row spatial precision levels. Both VO and lightbar data were collected on June 26. Different letters refer to a statistically significant difference testing the means of absolute errors in predicting actual almond yield with different regression models using analysis of variance (ANOVA) multi-comparison (p < 0.05).
case_images: fpls-12-715361-g0011.jpg
case_images: PMC8427806_02_fpls-12-715361-g0011.jpg
case_images: F11
case_images: Specifically, with the increase of estimated fPAR on the x-axis (0-100%), the slope of the regression lines moved farther (35.6 in Figure 7A to 29.0 in Figure 7D) from the potential yield line over the season for all varieties, suggesting that the actual yield prediction became less accurate. Figure 11 compares the accuracies (R2) of the different measuring levels [per-tree (VO only), per-block, and per-row] in explaining almond actual kernel yield on June 26.