• Journal of Plant Biotechnology
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• v.43 no.4
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• pp.444-449
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• 2016

Deep rooting, which enables plants to extract water from greater soil depths, is a critical strategy for improving plant survival under water-deficient conditions. However, as it is difficult to observe intact root systems belowground, several techniques have been developed to screen deep- and shallow-rooting phenotypes in rice. Here, we introduce a simple and convenient method for deep- and shallow-rooting phenotyping using a unique combination of sand, soil, and plastic mesh netting. Vandana, a drought-tolerant rice variety, and Dongjin, a Korean japonica rice variety, were used to analyze root phenotypes. No significant differences in root length were observed in rice grown under irrigated conditions regardless of net position, whereas roots were significantly longer, and ratio of deep root (RDR) values were significantly higher in Vandana rice grown under semi-drought conditions. In summary, this simple and useful method represents a low-cost means of phenotyping the roots of rice and other crops grown in various-sized pots and at multiple plant growth stages.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.4
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• pp.452-458
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• 2021

Roots are the most important organs in plants that absorb nutrients and moisture from the soil. However, owing to difficulties in root data collection, root research is still poorly conducted as compared to shoot research. Recent advancements in crop phenotyping, through advanced imagery data, are rapidly increasing, and artificial intelligence has been applied in various crop root research. Depending on the purpose, different root analysis methods have been developed that measure roots directly in soil or after separation from the soil. Each method has its advantages and disadvantages; therefore, it can be used in accordance with the research interest. Therefore, this review introduces root analysis methods that use imagery systems to help domestic researchers precisely study plant roots or root architecture.