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| 001 | 866522 | ||
| 005 | 20210130003507.0 | ||
| 024 | 7 | _ | |a 10.1111/2041-210X.13156 |2 doi |
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| 100 | 1 | _ | |a Rose, Laura |0 0000-0003-4523-4145 |b 0 |e Corresponding author |
| 245 | _ | _ | |a Accuracy of image analysis tools for functional root traits: A comment on Delory et al. (2017) |
| 260 | _ | _ | |a Oxford [u.a.] |c 2019 |b Wiley |
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| 520 | _ | _ | |a Root traits get increasing attention as functional equivalents of above‐ground traits. Image analysis software such as WinRhizo™ and IJ_Rhizo facilitate root trait analyses. Delory et al. (2017) presented a comparison between the accuracy of WinRhizo™ and IJ_Rhizo for measuring root length. We complement their analyses with a comparison of diameter and volume estimates and a comparison of different image resolutions with manual and automatic threshold. We analysed 100 images of fibrous and taproot systems, which were obtained using the root model ArchiSimple. As a result, for each image, diameter, length and volume were known. The images were analysed with WinRhizo™ and IJ_Rhizo and we compared the estimates of diameter, length and volume to ground‐truth values. We further computed relative errors and their magnitude and analysed their dependency on image characteristics and root system properties. At 1,200 and 800 dpi, diameter and length estimates provided by WinRhizo™ and IJ_Rhizo were of comparable accuracy. Diameter errors were balanced. Volume estimates were subjected to a systematic error caused by the assumption of constant diameter. WinRhizo™, however, provides the opportunity to calculate correctly computed volumes from diameter classes. At 1,200 dpi, IJ_Rhizo failed to automatically find an appropriate threshold for pixel classification, which fundamentally decreased accuracy. The magnitude of diameter errors increased with root overlap for IJ_Rhizo. The length errors increased with increasing root length, overlap and root length density for WinRhizo™. The magnitude of underestimation of the volume (WinRhizo™) decreased with volume. It was higher for taproot than for fibrous root systems. All errors increased with lower resolution. Our results confirm the results of Delory et al. (2017) regarding the accuracy for length. They further confirm that estimates derived from different software packages or at different resolution should not be compared directly. The characteristics of root systems should be standardized for image analysis. The dependency of errors on the response variable of interest can influence the effect size and increase the probability of errors. Validation of methods should be conducted for each analysed dataset. New image analysis tools should be validated against a real ground‐truth. |
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| 700 | 1 | _ | |a Lobet, Guillaume |0 P:(DE-Juel1)171180 |b 1 |u fzj |
| 773 | _ | _ | |a 10.1111/2041-210X.13156 |g Vol. 10, no. 5, p. 702 - 711 |0 PERI:(DE-600)2528492-7 |n 5 |p 702 - 711 |t Methods in ecology and evolution |v 10 |y 2019 |x 2041-210X |
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| 856 | 4 | _ | |y Published on 2019-01-24. Available in OpenAccess from 2020-01-24. |u https://juser.fz-juelich.de/record/866522/files/Rose%20and%20Lobet%202019%20-%20Accuracy%20of%20image%20analysis%20tools%20for%20functional%20root%20traits%20-%20A%20comment%20on%20Delory%20et%20al.%2C%202017.pdf |
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