Roberti Joshua A, SanClements Michael D, Loescher Henry W, Ayres Edward
National Ecological Observatory Network (NEON), Boulder, Colorado, United States of America.
National Ecological Observatory Network (NEON), Boulder, Colorado, United States of America; Institute of Arctic and Alpine Research (INSTAAR), University of Colorado, Boulder, Colorado, United States of America.
PLoS One. 2014 Nov 12;9(11):e112362. doi: 10.1371/journal.pone.0112362. eCollection 2014.
Even though fine-root turnover is a highly studied topic, it is often poorly understood as a result of uncertainties inherent in its sampling, e.g., quantifying spatial and temporal variability. While many methods exist to quantify fine-root turnover, use of minirhizotrons has increased over the last two decades, making sensor errors another source of uncertainty. Currently, no standardized methodology exists to test and compare minirhizotron camera capability, imagery, and performance. This paper presents a reproducible, laboratory-based method by which minirhizotron cameras can be tested and validated in a traceable manner. The performance of camera characteristics was identified and test criteria were developed: we quantified the precision of camera location for successive images, estimated the trueness and precision of each camera's ability to quantify root diameter and root color, and also assessed the influence of heat dissipation introduced by the minirhizotron cameras and electrical components. We report detailed and defensible metrology analyses that examine the performance of two commercially available minirhizotron cameras. These cameras performed differently with regard to the various test criteria and uncertainty analyses. We recommend a defensible metrology approach to quantify the performance of minirhizotron camera characteristics and determine sensor-related measurement uncertainties prior to field use. This approach is also extensible to other digital imagery technologies. In turn, these approaches facilitate a greater understanding of measurement uncertainties (signal-to-noise ratio) inherent in the camera performance and allow such uncertainties to be quantified and mitigated so that estimates of fine-root turnover can be more confidently quantified.
尽管细根周转是一个受到广泛研究的课题,但由于其采样过程中存在的固有不确定性,例如量化空间和时间变异性,人们对它的理解往往并不充分。虽然有许多方法可用于量化细根周转,但在过去二十年中,微根管的使用有所增加,这使得传感器误差成为另一个不确定性来源。目前,尚无标准化方法来测试和比较微根管相机的性能、图像及表现。本文提出了一种可重复的、基于实验室的方法,通过该方法可以以可追溯的方式对微根管相机进行测试和验证。确定了相机特性的性能并制定了测试标准:我们量化了连续图像中相机定位的精度,估计了每台相机量化根直径和根颜色能力的准确性和精度,并评估了微根管相机和电气元件产生的散热影响。我们报告了详细且具有说服力的计量分析,该分析考察了两款市售微根管相机的性能。这些相机在各项测试标准和不确定性分析方面表现各异。我们建议采用一种可靠计量方法,在野外使用前量化微根管相机特性的性能,并确定与传感器相关的测量不确定性。这种方法也可扩展到其他数字成像技术。反过来,这些方法有助于更深入地理解相机性能中固有的测量不确定性(信噪比),并使此类不确定性得以量化和减轻,从而能够更有信心地量化细根周转估计值。