An efficient subsampling method for estimating corn root characteristics with scanner‐based image analysis

Quantifying root length, surface area, average diameter, and volume of fully‐matured corn (Zea mays L.) is labor intensive, time consuming, and costly. Accurate and efficient subsampling techniques are needed to overcome these limitations. In this study, eight corn root systems were grown to maturit...

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Veröffentlicht in:Agronomy journal 2024-09, Vol.116 (5), p.2630-2637
Hauptverfasser: Ampong, Kwame, Penn, Chad, Camberato, James, Williams, Mark
Format: Artikel
Sprache:eng
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Zusammenfassung:Quantifying root length, surface area, average diameter, and volume of fully‐matured corn (Zea mays L.) is labor intensive, time consuming, and costly. Accurate and efficient subsampling techniques are needed to overcome these limitations. In this study, eight corn root systems were grown to maturity in a sand‐culture hydroponics system to develop and test root system subsampling techniques for accuracy (uncertainty assessment) and efficiency (time). Each entire root system was separated into coarse and fine roots, which were then composited into 65 subsamples, either visually or by mass, followed by subsample scanning to quantify root characteristics. A bootstrap non‐parametric procedure was used to determine the sample size needed to represent the total root system and quantify uncertainty based on the number of subsamples analyzed. When subsamples were composited visually, as many as 60 subsamples (92% of the total root system) were necessary to represent the characteristics of the root system within ±5% of the true mean at a 95% confidence level. In contrast, when subsamples were composited by equal mass, a maximum of 15 subsamples (23% of the total root system) were needed to be representative, requiring 2 h and 15 min per root system. The findings show that separating the entire root system by coarse and fine roots and then weighing into equal mass subsamples before scanning decreased the number of subsamples and time required to accurately estimate corn root characteristics. Thus, this subsampling approach considerably reduced the effort and cost of processing corn root systems. Core Ideas Separating corn roots into coarse and fine portions ensured homogenous and easy subsampling of the root system. Weighing of coarse and fine root portions separately into a composite subsample before scanning reduced within‐subsample variations. Subsampling by root size and mass accurately estimated corn root parameters. Scanning no more than 23% of total root system accurately estimated all corn root parameters with ≤5% error from mean and required 2 h and 15 min per root system.
ISSN:0002-1962
1435-0645
DOI:10.1002/agj2.21645