Dataset Information

Image-Based Machine Learning Characterizes Root Nodule in Soybean Exposed to Silicon.

ABSTRACT: Silicon promotes nodule formation in legume roots which is crucial for nitrogen fixation. However, it is very time-consuming and laborious to count the number of nodules and to measure nodule size manually, which led nodule characterization not to be study as much as other agronomical characters. Thus, the current study incorporated various techniques including machine learning to determine the number and size of root nodules and identify various root phenotypes from root images that may be associated with nodule formation with and without silicon treatment. Among those techniques, the machine learning for characterizing nodule is the first attempt, which enabled us to find high correlations among root phenotypes including root length, number of forks, and average link angles, and nodule characters such as number of nodules and nodule size with silicon treatments. The methods here could greatly accelerate further investigation such as delineating the optimal concentration of silicon for nodule formation.

SUBMITTER: Chung YS

PROVIDER: S-EPMC7655541 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Image-Based Machine Learning Characterizes Root Nodule in Soybean Exposed to Silicon.

Chung Yong Suk YS Lee Unseok U Heo Seong S Silva Renato Rodrigues RR Na Chae-In CI Kim Yoonha Y

Frontiers in plant science 20201028

Silicon promotes nodule formation in legume roots which is crucial for nitrogen fixation. However, it is very time-consuming and laborious to count the number of nodules and to measure nodule size manually, which led nodule characterization not to be study as much as other agronomical characters. Thus, the current study incorporated various techniques including machine learning to determine the number and size of root nodules and identify various root phenotypes from root images that may be asso ...[more]

PMID: 33193467

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Project description:Soybean root nodules are known to contain a high diversity of both rhizobial endophytes and nonrhizobial endophytes (NREs). Nevertheless, the variation of these bacteria among different root nodules within single plants has not been reported. So far, it is unclear whether the selection of NREs among different root nodules within single plants is a random process or is strictly controlled by the host plant to favor a few specific NREs based on their beneficial influence on plant growth. As well, it is also unknown if the relative frequency of NREs within different root nodules is consistent or if it varies based on the location or size of a root nodule. We assessed the microbiomes of 193 individual soybean root nodules from nine plants using high-throughput DNA sequencing. Bradyrhizobium japonicum strains occurred in high abundance in all root nodules despite the presence of other soybean-compatible rhizobia, such as Ensifer, Mesorhizobium, and other species of Bradyrhizobium in soil. Nitrobacter and Tardiphaga were the two nonrhizobial genera that were uniformly detected within almost all root nodules, though they were in low abundance. DNA sequences related to other NREs that have frequently been reported, such as Bacillus, Pseudomonas, Flavobacterium, and Variovorax species, were detected in a few nodules. Unlike for Bradyrhizobium, the low abundance and inconsistent occurrence of previously reported NREs among different root nodules within single plants suggest that these microbes are not preferentially selected as endophytes by host plants and most likely play a limited part in plant growth as endophytes.IMPORTANCE Soybean (Glycine max L.) is a valuable food crop that also contributes significantly to soil nitrogen by developing a symbiotic association with nitrogen-fixing rhizobia. Bacterial endophytes (both rhizobial and nonrhizobial) are considered critical for the growth and resilience of the legume host. In the past, several studies have suggested that the selection of bacterial endophytes within root nodules can be influenced by factors such as soil pH, nutrient availability, host plant genotype, and bacterial diversity in soil. However, the influence of size or location of root nodules on the selection of bacterial endophytes within soybean roots is unknown. It is also unclear whether the selection of nonrhizobial endophytes within different root nodules of a single plant is a random process or is strictly regulated by the host. This information can be useful in identifying potential bacterial species for developing bioinoculants that can enhance plant growth and soil nitrogen.

Dataset Information

Image-Based Machine Learning Characterizes Root Nodule in Soybean Exposed to Silicon.

Publications

Image-Based Machine Learning Characterizes Root Nodule in Soybean Exposed to Silicon.

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