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.

Optimal Concentrations of Silicon Enhance the Growth of Soybean (Glycine Max L.) Cultivars by Improving Nodulation, Root System Architecture, and Soil Biological Properties

“…The results of the present study also showed that the soybean cultivars treated with various levels of Si had a high ability to form nodules and therefore higher concentrations of N in their shoots, for which there are some similar reports from other studies [9,15,22]. For example, in a study, foliar application of 2.0 mM Si as sodium metasilicate boosted nodulation and nodule size as compared to non-Si treated soybean [28].…”

“…It has been reported that Si application-induced increase of the growth of root and nitrogen xed from the nodules depends on the concentrations of Si, growing substrates, and types of Si [24], various plant species (various cultivars), and ability of the plants (e.g., legumes) to absorb this element [27]. For example, in a study [28], the applied Si level was not be adequate to be in uential to lateral root formation in soybean.…”

Competition, Nodule Occupancy, and Persistence of Inoculant Strains: Key Factors in the Rhizobium-Legume Symbioses

“…Indeed, more and more multicomponent interaction studies are being conducted ( Vuong et al, 2017 ; Burghardt et al, 2018 ; Gunnabo et al, 2019 ; Batstone et al, 2020 ; Mendoza-Suárez et al, 2020 ; Fagorzi et al, 2021 ), and they are already generating important knowledge to help understand some of these interactions and give more weight to the performance of rhizobial inoculants. Additionally, the rapid progress in NGS with open-source laboratory equipment automation ( Figure 3C ; Wong et al, 2018 ; Faiña et al, 2020 ), and the application of machine learning in big data analysis of microbiome studies ( Cammarota et al, 2020 ; Ghannam and Techtmann, 2021 ) and in biological-image analysis ( Berg et al, 2019 ; Chung et al, 2020 ; Tausen et al, 2020 ), will make multicomponent interactions studies more achievable, providing the opportunity to identify a larger number of elite strains in less time. The introduction of a wider number of variables in the experimental assays conducted to identify elite strains will increase the probability of designing rhizobial inoculants with better performance under field conditions.…”

Silicon Effects on the Root System of Diverse Crop Species Using Root Phenotyping Technology

“…In the case of leguminous plants, the detection of nodules is complex in field conditions. Therefore, deep learning-based detection and segmentation methods can be employed to accurately determine the size and number of nodules [ 12 ].…”

“…Specifically, Si application increases both the fresh and dry weight of roots and their branching angles under heavy metal stress conditions [ 11 ]. Furthermore, Si treatments on soybean plants were shown to induce increased root length, diameter, and biomass [ 12 ]. In addition to these effects, various changes in root morphology produced by accumulated Si have been reported in many other studies.…”