Acknowledgement
본 논문은 농촌진흥청 공동연구사업(과제번호:PJ01567802)의 지원에 의해 이루어진 것임.
References
- Bucksch, A., J. Burridge, L. M. York, A. Das, E. Nord, J. S. Weitz, and J. P. Lynch. 2014. Image-based high-throughput field phenotyping of crop roots. Plant Physiol. 166(2) : 470-489. https://doi.org/10.1104/pp.114.243519
- Busch, J., I. A. Mendelssohn, B. Lorenzen, H. Brix, and S. Miao. 2006. A rhizotron to study root growth under flooded conditions tested with two wetland Cyperaceae. Flora. 201(6) : 429-439. https://doi.org/10.1016/j.flora.2005.08.007
- Cai, G. J. Vanderborght, A. Klotzsche, J. Kruk, J. Neumann, N. Hermes, H. Vereecken. 2016. Vadose Zone J. 15(9) : vzj2016.05.0043. https://doi.org/10.2136/vzj2016.05.0043
- Chung, Y. S., U. Lee, S. Heo, R. R. Silva, C. I. Na, and Y. Kim. 2020. Image-based machine learning characterizes root nodule in soybean exposed to silicon. Front. Plant Sci. 11 : 520161. https://doi.org/10.3389/fpls.2020.520161
- Das, A., H. Schneider, J. Burridge, A. K. M. Ascanio, T. Wojciechowski, C. N. Topp, J. P. Lynch, J. S. Weitz, and A. Bucksch. 2015. Digital imaging of root traits (DIRT): a high-throughput computing and collaboration platform for field-based root phenomics. Plant Methods. 11(1) : 1-12. https://doi.org/10.1186/s13007-015-0043-0
- Iversen, C. M., M. T. Murphy, M. F. Allen, J. Childs, D. M. Eissenstat, E. A. Lilleskov, T. M. Sarjala, V. L. Sloan, and P. F. Sullivan. 2012. Advancing the use of minirhizotrons in wetlands. Plant Soil. 352(1) : 23-39. https://doi.org/10.1007/s11104-011-0953-1
- Kim, D. W., Y. Kim, K. H. Kim, H. J. Kim, and Y. S. Chung. 2019. Case study: Cost-effective weed patch detection by multi-spectral camera mounted on unmanned aerial vehicle in the buckwheat field. Korean J. Crop Sci. 64(2) : 159-164. https://doi.org/10.7740/KJCS.2019.64.2.159
- Kim, K. S., S. H. Kim, J. Kim, P. Tripathi, J. D. Lee, Y. S. Chung, and Y. Kim. 2021. A large root phenome dataset wide-opened the potential for underground breeding in soybean. Front. Plant Sci. 12 : 704239. https://doi.org/10.3389/fpls.2021.704239
- Kim, Y., Y. S. Chung, E. Lee, P. Tripathi, S. Heo, and K. H. Kim. 2020. Root response to drought stress in rice (Oryza sativa L.). Int. J. Mol. Sci. 21 : 1513. https://doi.org/10.3390/ijms21041513
- Lobet, G., X. Draye, and C. Perilleux. 2013. An online database for plant image analysis software tools. Plant Methods 9: 1-7. https://doi.org/10.1186/1746-4811-9-1
- Ma, J. F., S. Goto, K. Tamai, and M. Ichii, 2001. Role of root hairs and lateral roots in silicon uptake by rice. Plant Physiol. 127(4) : 1773-1780. https://doi.org/10.1104/pp.010271
- Noh, T. K. and D. S. Kim. 2018. Weed research using plant image science. Weed Turf. Sci. 7(4) : 285-296. https://doi.org/10.5660/WTS.2018.7.4.285
- Pang, W., W. T. Crow, J. E. Luc, R. McSorley, R. M. GiblinDavis, K. E. Kenworthy, and J. K. Kruse. 2011. Comparison of water displacement and WinRHIZO software for plant root parameter assessment. Plant Dis. 95(10) : 1308-1310. https://doi.org/10.1094/pdis-01-11-0026
- Trachsel, S., S. M. Kaeppler, K. M. Brown, and J. P. Lynch, 2010. Shovelomics: high throughput phenotyping of maize (Zea mays L.) root architecture in the field. Plant Soil. 341 : 75-87. https://doi.org/10.1007/s11104-010-0623-8
- Tripathi, P., S. Subedi, A. L. Khan. Y. S. Chung, and Y. Kim. 2021. Silicon effects on the root system of diverse crop species using root phenotyping technology. Plants. 10 : 885. https://doi.org/10.3390/plants10050885
- Wachsman, G., E. E. Sparks, P. N. B. 2015. Genes and networks regulating root anatomy and architecture. New Phytol. 208: 26-38. https://doi.org/10.1111/nph.13469
- Water, A., F. Liebisch, and A. Hund. 2015. Plant phenotyping: from bean weight to image analysis. Plant Method.
- Yamaguchi, J. 2002. Measurement of root diameter in field-grown crop under a miscroscope without washing. Soil Sci. Plant Nut. 48(4) : 625-629. https://doi.org/10.1080/00380768.2002.10409248
- Zhao, J., G. Bodner, B. Rewald, D. Leitner, K. A. Nagel, and A. Nakhforoosh, 2017. Root architecture simulation improves the inference from seedling root phenotyping towards mature root systems. J. Exp. Bot. 68 : 965-982. https://doi.org/10.1093/jxb/erw494