Lynch J. Root architecture and plant productivity. Plant Physiol. 1995;109:7–13.
Article
CAS
Google Scholar
Gowariker V, Krishnamurthy VN, Gowariker S, Dhanorkar M, Paranjape K. The fertilizer encyclopedia. Hoboken: John Wiley & Sons; 2009.
Google Scholar
Uga Y, Sugimoto K, Ogawa S, Rane J, Ishitani M, Hara N, et al. Control of root system architecture by deeper rooting 1 increases rice yield under drought conditions. Nat Genet. 2013;45:1097–102.
Article
CAS
Google Scholar
Kitomi Y, Hanzawa E, Kuya N, Inoue H, Hara N, Kawai S, et al. Root angle modifications by the DRO1 homolog improve rice yields in saline paddy fields. Proc Natl Acad Sci U S A. 2020;117:21242–50.
Article
CAS
Google Scholar
Oo AZ, Tsujimoto Y, Mukai M, Nishigaki T, Takai T, Uga Y. Synergy between a shallow root system with a DRO1 homologue and localized P application improves P uptake of lowland rice. Sci Rep. 2021;11:9484.
Article
CAS
Google Scholar
Khare D, Mitsuda N, Lee S, Song WY, Hwang D, Ohme-Takagi M, et al. Root avoidance of toxic metals requires the GeBP-LIKE 4 transcription factor in Arabidopsis thaliana. New Phytol. 2017;213:1257–73.
Article
CAS
Google Scholar
Uga Y. Challenges to design-oriented breeding of root system architecture adapted to climate change. Breed Sci. 2021;71:3–12.
Article
CAS
Google Scholar
Trachsel S, Kaeppler SM, Brown KM, Lynch JP. Shovelomics: high throughput phenotyping of maize (Zea mays L.) root architecture in the field. Plant Soil. 2011;341:75–87.
Article
CAS
Google Scholar
Teramoto S, Kitomi Y, Nishijima R, Takayasu S, Maruyama N, Uga Y. Backhoe-assisted monolith method for plant root phenotyping under upland conditions. Breed Sci. 2019;69:508–13.
Article
Google Scholar
Cheng W, Coleman DC, Box JE. Measuring root turnover using the minirhizotron technique. Agric Ecosyst Environ. 1991;34:261–7.
Article
Google Scholar
Satomura T, Fukuzawa K, Horikoshi T. Considerations in the study of tree fine-root turnover with minirhizotrons. Plant Root. 2007;1:34–45.
Article
Google Scholar
Eshel A, Beeckman T. Plant roots: the hidden half. Florida: CRC Press; 2013.
Book
Google Scholar
Huck MG, Taylor HM. The rhizotron as a tool for root research. Adv Agron. 1982;35:1–35.
Article
Google Scholar
Neufeld HS, Durall DM, Rich PM, Tingey DT. A rootbox for quantitative observations on intact entire root systems. Plant Soil. 1989;117:295–8.
Article
Google Scholar
Wang T, Rostamza M, Song Z, Wang L, McNickle G, Iyer-Pascuzzi AS, et al. SegRoot: a high throughput segmentation method for root image analysis. Comput Electron Agric. 2019;162:845–54.
Article
Google Scholar
Xu W, Yu G, Zare A, Zurweller B, Rowland DL, Reyes-Cabrera J, et al. Overcoming small minirhizotron datasets using transfer learning. Comput Electron Agric. 2020;175:105466.
Article
Google Scholar
Smith AG, Petersen J, Selvan R, Rasmussen CR. Segmentation of roots in soil with U-Net. Plant Methods. 2020;16:13.
Article
Google Scholar
de Dorlodot S, Forster B, Pagès L, Price A, Tuberosa R, Draye X. Root system architecture: opportunities and constraints for genetic improvement of crops. Trends Plant Sci. 2007;12:474–81.
Article
Google Scholar
Teramoto S, Takayasu S, Kitomi Y, Arai-Sanoh Y, Tanabata T, Uga Y. High-throughput three-dimensional visualization of root system architecture of rice using X-ray computed tomography. Plant Methods. 2020;16:66.
Article
Google Scholar
Gao W, Schlüter S, Blaser SRGA, Shen J, Vetterlein D. A shape-based method for automatic and rapid segmentation of roots in soil from X-ray computed tomography images: Rootine. Plant Soil Plant and Soil. 2019;441:643–55.
Article
CAS
Google Scholar
Mairhofer S, Zappala S, Tracy SR, Sturrock C, Bennett M, Mooney SJ, et al. RooTrak: automated recovery of three-dimensional plant root architecture in soil from X-Ray microcomputed tomography images using visual tracking. Plant Physiol. 2012;158:561–9.
Article
CAS
Google Scholar
Iijima M, Oribe Y, Horibe Y, Kono Y. Time lapse analysis of root elongation rates of rice and sorghum during the day and night. Ann Bot. 1998;81:603–7.
Article
Google Scholar
Yazdanbakhsh N, Fisahn J. Analysis of Arabidopsis thaliana root growth kinetics with high temporal and spatial resolution. Ann Bot. 2010;105:783–91.
Article
Google Scholar
Yazdanbakhsh N, Fisahn J. Stable diurnal growth rhythms modulate root elongation of Arabidopsis thaliana. Plant Root. 2011;5:17–23.
Article
Google Scholar
Fisahn J, Yazdanbakhsh N, Klingele E, Barlow P. Arabidopsis thaliana root growth kinetics and lunisolar tidal acceleration. New Phytol. 2012;195:346–55.
Article
Google Scholar
Gao W, Blaser SRGA, Schlüter S, Shen J, Vetterlein D. Effect of localised phosphorus application on root growth and soil nutrient dynamics in situ—comparison of maize (Zea mays) and faba bean (Vicia faba) at the seedling stage. Plant Soil Plant and Soil. 2019;441:469–83.
Article
CAS
Google Scholar
Rellán-Álvarez R, Lobet G, Lindner H, Pradier PL, Sebastian J, Yee MC, et al. GLO-Roots: an imaging platform enabling multidimensional characterization of soil-grown root systems. Elife. 2015;4:1–26.
Article
Google Scholar
Bontpart T, Concha C, Giuffrida MV, Robertson I, Admkie K, Degefu T, et al. Affordable and robust phenotyping framework to analyse root system architecture of soil-grown plants. Plant J. 2020;103:2330–43.
Article
CAS
Google Scholar
Parker JC, Amos DF, Kaster DL. An evaluation of several methods of estimating soil volume change. Soil Sci Soc Am J. 1977;41:1059–64.
Article
Google Scholar
Giraldez JV, Sposito G, Delgado C. A general soil volume change equation: I. The two-parameter model. Soil Sci Soc Am J. 1983;47:419–22.
Article
Google Scholar
Teramoto S, Tanabata T, Uga Y. RSAtrace3D: robust vectorization software for measuring monocot root system architecture. BMC Plant Biol. 2021;21:398.
Article
Google Scholar
Lobet G, Pagès L, Draye X. A novel image-analysis toolbox enabling quantitative analysis of root system architecture. Plant Physiol. 2011;157:29–39.
Article
CAS
Google Scholar
Möller B, Chen H, Schmidt T, Zieschank A, Patzak R, Türke M, et al. rhizoTrak: a flexible open source Fiji plugin for user-friendly manual annotation of time-series images from minirhizotrons. Plant Soil. 2019;444:519–34.
Article
Google Scholar
Bull DR. Communicating pictures: a course in image and video coding. Massachusetts: Academic Press; 2014.
Book
Google Scholar
Jia D, Song C, Cheng C, Shen S, Ning L, Hui C. A novel deep learning-based spatiotemporal fusion method for combining satellite images with different resolutions using a two-stream convolutional neural network. Remote Sens. 2020;12:698.
Article
Google Scholar
Bovik AC. The essential guide to video processing. Massachusetts: Academic Press; 2009.
Google Scholar
Zitova B, Flusser J. Image registration methods: a survey. Image Vis Comput Elsevier. 2003;21:977–1000.
Article
Google Scholar
Sharp GC, Lee SW, Wehe DK. ICP registration using invariant features. IEEE Trans Pattern Anal Mach Intell. 2002;24:90–102.
Article
Google Scholar
Yamazaki K, Ohmori Y, Fujiwara T. A positive tropism of rice roots toward a nutrient source. Plant Cell Physiol. 2020;61:546–53.
Article
CAS
Google Scholar
Hodge A. The plastic plant: root responses to heterogeneous supplies of nutrients. New Phytol. 2004;162:9–24.
Article
Google Scholar
Flavel RJ, Guppy CN, Tighe MK, Watt M, Young IM. Quantifying the response of wheat (Triticum aestivum L) root system architecture to phosphorus in an Oxisol. Plant Soil. 2014;385:303–10.
Article
CAS
Google Scholar
Bardhan K, York LM, Hasanuzzaman M, Parekh V, Jena S, Pandya MN. Can smart nutrient applications optimize the plant’s hidden half to improve drought resistance? Physiol Plant. 2021;172:1007–15.
Article
CAS
Google Scholar
Vanhees DJ, Schneider HM, Sidhu JS, Loades KW, Bengough AG, Bennett MJ, et al. Soil penetration by maize roots is negatively related to ethylene-induced thickening. Plant Cell Environ. 2022;45:789–804.
Article
CAS
Google Scholar
Mcneill A, Kolesik P. X-ray CT investigations of intact soil cores with and without living crop roots. SuperSoil 2004 3rd Aust New Zel Soils Conf. 2004.
Correa J, Postma JA, Watt M, Wojciechowski T. Soil compaction and the architectural plasticity of root systems. J Exp Bot. 2019;70:6019–34.
Article
CAS
Google Scholar
Numajiri Y, Yoshino K, Teramoto S, Hayashi A, Nishijima R, Tanaka T, et al. iPOTs: Internet of Things-based pot system controlling optional treatment of soil water condition for plant phenotyping under drought stress. Plant J. 2021;107:1569–80.
Article
CAS
Google Scholar
Luo H, Xu H, Chu C, He F, Fang S. High temperature can change root system architecture and intensify root interactions of plant seedlings. Front Plant Sci. 2020;11:160.
Article
Google Scholar
Magistri F, Chebrolu N, Stachniss C. Segmentation-based 4D registration of plants point clouds for phenotyping. IEEE Int Conf Intell Robot Syst. 2020. 2433–9.
Paproki A, Sirault X, Berry S, Furbank R, Fripp J. A novel mesh processing based technique for 3D plant analysis. BMC Plant Biol. 2012;12:63.
Article
Google Scholar
Teramoto S, Uga Y. Improving the efficiency of plant root system phenotyping through digitization and automation. Breed Sci. 2022;72:48–55.
Article
Google Scholar
Van Rossum G, Drake FL. Python 3 reference manual. Scotts Valley: CreateSpace; 2009.
Google Scholar
Harris CR, Millman KJ, van der Walt SJ, Gommers R, Virtanen P, Cournapeau D, et al. Array programming with NumPy. Nature. 2020;585:357–62.
Article
CAS
Google Scholar
der Walt S, Schönberger JL, Nunez-Iglesias J, Boulogne F, Warner JD, Yager N, et al. scikit-image: image processing in Python. PeerJ. 2014;2:e453.
Article
Google Scholar
Zhou Q-Y, Park J, Koltun V. Open3D: A modern library for 3D data processing. arXiv. 2018. https://doi.org/10.48550/arXiv.1801.09847.
Article
Google Scholar