Automated image analyses for separating plant roots from soil debris elutrated from soil cores

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Abstract

Historically, destructive root sampling has been labor intensive and requires manual separation of extraneous organic debris recovered along with the hydropneumatic elutriation method of separating plant roots from soils. Quantification of root system demographics by public domain National Institute of Health (NIH-Image) and Root Image Processing Laboratory (RIPL) image processing algorithms has eliminated much of the labor-intensive manual separation. This was accomplished by determining the best length to diameter ratio for each object during image analyses. Objects with a length to diameter ratio less than a given threshold are considered non-root materials and are rejected automatically by computer algorithms. Iterative analyses of length to diameter ratios showed that a 15:1 ratio was best for separating images of maize (Zea mays L.) roots from associated organic debris. Using this threshold ratio for a set of 24 soil cores, a highly significant correlation (r2 = 0.89) was obtained between computer image processed total root length per core and actual root length. A linear relationship (r2 = 0.80) was observed between root lengths determined by NIH-Image analyses and lengths determined independently by the RIPL imaging system, using the same maize root + debris samples. This correlation demonstrates that computer image processing provides opportunities for comparing root length parameters between different laboratories for samples containing debris.

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