Kalluri, U. | Search bioRxiv

bioRxiv2024

Divide and conquer: Using RhizoVision Explorer to aggregate data from multiple root scans using image concatenation and statistical methods

Roots are important in agricultural and natural systems for determining plant productivity and soil carbon inputs. The collection of root samples from the field and their subsequent cleaning and scanning in a water-filled tray ranging in size from 5 to 20 cm, followed by digital image analysis has been commonly used since the 1990s for measuring root length, volume, area, and diameter. However, one common issue has been neglected. Sometimes, the amount of roots for a sample is too much to fit into a single scanned image, so the sample is divided among several scans. There is no standard method to aggregate the root measurements across the scans of the same sample. Here, we describe and validate two methods for standardizing measurements across multiple scans: image concatenation and statistical aggregation. Both methods rely on standardizing file naming conventions to identify scans that belong to the same sample. Image concatenation refers to combining digital images into a single larger image while maintaining the original resolution. We developed a Python script that identifies which images belong to the same sample and returns a single, larger concatenated image for every set of images in a directory. These concatenated images (combining up to 10 scans) and the original images were processed with RhizoVision Explorer, a free and open-source software developed for estimating root traits from images, with the same settings. An R script was developed that can identify the rows of data belonging to the same sample in RhizoVision Explorer data files and apply correct statistical methods such as summation, weighted average by length, and average to the appropriate measurement types to return a single data row for each sample. These two methods were compared using example images from switchgrass, poplar, and various tree and ericaceous shrub species from a northern peatland and the Arctic. Overall, the new methods accomplished the goal of standardizing measurement aggregation. Most root measurements were nearly identical except median diameter, which can not be accurately computed by statistical aggregation. We believe the availability of these methods will be useful to the root biology community.

plant biology↗

bioRxiv2023

Intraspecies variability in plant and soil chemical properties in a common garden plantation of the energy crop Populus

Optimizing crops for synergistic soil carbon (C) sequestration represents a frontier approach toward CO2 removal in food and bioenergy production systems. While the central roles of plants in biological C capture and storage belowground in soils is well known, we lack an understanding of how intraspecies variation in bioenergy plants affects soil biogeochemistry. This knowledge gap is exacerbated by spatial heterogeneity in soil and plant systems, and by the difficulty of characterizing belowground plant traits. Here, we sought to obtain first insights on the spatial variation of C and nutrients in soil and plant tissues from a common garden field site of diverse, natural variant, Populus trichocarpa genotypes--grown and characterized previously for aboveground biomass-to-biofuels research. Such field sites represent a potential resource for evaluating genotype-specific effects on soil C, but this usage may be complicated due to dense plantings of intermixed genotypes. Thus, we sampled soils at the scale of individual trees to determine whether it is feasible to detect soil property variation with different plant genotypes in this system. We additionally sampled stem and root tissues to evaluate the potential for inferring important belowground traits based on aboveground-belowground correlations. We found that substantial variation in soil properties could be explained at the scale of individual trees, suggesting that genetically diverse plantations can be used to assess plant-soil correlations. Though we did not observe genotype-specific patterns in soil C, other properties such as soil acid-base chemistry (soil pH and base cations) and bulk density showed genotype-specific correlations. Stem and root nutrient levels were generally not correlated, suggesting that belowground traits should be measured directly. In conclusion, our pilot study suggests that long-term common gardens of genome-wide association study populations represent useful resources for understanding plant genotypic relationships with soil properties in Populus field study test plots. These resources could be used to develop verified plant species, geographic region-specific standardized sampling methods, and baseline data. Such context-specific, empirically verified data and models will be necessary for informing applied research strategies in selecting high aboveground productivity genotypes for enhanced soil C storage in managed, commercial scale, woody bioenergy crop plantation systems.

plant biology↗