Artificial Intelligence Tools to Better Understand Seed Dormancy and Germination

  1. Ayuso, Manuel
  2. Pablo Gallego, Pedro
  3. Landín, Mariana
  4. Esther Barreal, Mª
Libro:
Seed Dormancy and Germination

Año de publicación: 2020

Tipo: Capítulo de Libro

DOI: 10.5772/INTECHOPEN.90374 GOOGLE SCHOLAR lock_openAcceso abierto editor

Objetivos de desarrollo sostenible

Referencias bibliográficas

  • Bewley J. Seeds of hope; seeds of conflict. In: Nicolas G, Bradford K, Come D, Pritchard H, editors. Biology of Seeds: Recent Research Advances. 1st ed. Wallingford, UK: CAB International; 2003. pp. 1-4. DOI: 10.1017/S001447970425205X
  • Bewley JD, Bradford KJ, Hilhorst HWM, Nonogaki H. Seeds: Physiology of Development, Germination and Dormancy. 3rd ed. New York: Springer-Verlag; 2013. 392 p. DOI: 10.1007/978-1-4614-4693-4
  • Baskin JM, Baskin CC. A classification system for seed dormancy. Seed Science Research. 2004;14:1-16. DOI: 10.1079/SSR2003150
  • Baskin CC, Baskin JM. Seeds: Ecology, Biogeography, and Evolution of Dormancy and Germination. 2nd ed. San Diego: Elsevier Science; 2014. 1601 p. DOI: 10.1016/B978-0-12-080260-9.X5000-3
  • Finch-Savage WE, Leubner-Metzger G. Seed dormancy and the control of germination. New Phytologist. 2006;171:501-523. DOI: 10.1111/j.1469-8137.2006.01787.x
  • Struik PC, Yin X, de Visser P. Complex quality traits: Now time to model. Trends in Plant Science. 2005;10:513-516. DOI: 10.1016/J.TPLANTS.2005.09.005
  • Gallego PP, Gago J, Landin M. Artificial neural networks technology to model and predict plant biology process. In: Suzuki K, editor. Artificial Neural Networks - Methodological Advances and Biomedical Applications. 1st ed. Rijeka, Croatia: IntechOpen; 2011. pp. 197-217. DOI: 10.5772/14945
  • Hudson DL, Cohen ME. Neural Networks and Artificial Intelligence for Biomedical Engineering. 1st ed. New York: Institute of Electrical and Electronics Engineers; 1999. 306 p. DOI: 10.1109/9780470545355
  • Huang Y. Advances in artificial neural networks – Methodological development and application. Algorithms. 2009;2:973-1007. DOI: 10.3390/algor2030973
  • Cartwright H. Using Artificial Intelligence in Chemistry and Biology. 1st ed. Boca Raton: CRC Press; 2008 360 p
  • Gago J, Landín M, Gallego P. Strengths of artificial neural networks in modeling complex plant processes. Plant Signaling & Behavior. 2010;5:743-745. DOI: 10.4161/psb.5.6.11702
  • Gago J, Martínez-Núñez L, Landín M, Gallego P. Artificial neural networks as an alternative to the traditional statistical methodology in plant research. Journal of Plant Physiology. 2010;167:23-27. DOI: 10.1016/j.jplph.2009.07.007
  • Finkelstein R, Reeves W, Ariizumi T, Steber C. Molecular aspects of seed dormancy. Annual Review of Plant Biology. 2008;59:387-415. DOI: 10.1146/annurev.arplant.59.032607.092740
  • Nikolaeva M. Factors controlling the seed dormancy pattern. In: Khan A, editor. The Physiology & Biochemistry of Seed Dormancy and Germination. Amsterdam: North-Holland Publ. Co; 1977. pp. 51-74
  • Bewley JD. Seed germination and dormancy. The Plant Cell. 1997;9:1055-1066. DOI: 10.1105/tpc.9.7.1055
  • Lefebvre V, North H, Frey A, Sotta B, Seo M, Okamoto M, et al. Functional analysis of Arabidopsis NCED6 and NCED9 genes indicates that ABA synthesized in the endosperm is involved in the induction of seed dormancy. The Plant Journal. 2006;45:309-319. DOI: 10.1111/j.1365-313X.2005.02622.x
  • Cadman CSC, Toorop PE, Hilhorst HWM, Finch-Savage WE. Gene expression profiles of Arabidopsis cvi seeds during dormancy cycling indicate a common underlying dormancy control mechanism. The Plant Journal. 2006;46:805-822. DOI: 10.1111/j.1365-313X.2006.02738.x
  • Fenner M, Thompson K. The Ecology of Seeds. 1st ed. Cambridge: Cambridge University Press; 2005. 250 p. DOI: 10.1017/CBO9780511614101
  • Gutterman Y. Maternal effects on seeds during development. In: Fenner M, editor. Seeds : The Ecology of Regeneration in Plant Communities. Vol. 2. Wallingford,UK: CABI Pub; 2000. p. 410
  • Nambara E, Marion-Poll A. ABA action and interactions in seeds. Trends in Plant Science. 2003;8:213-217. DOI: 10.1016/S1360-1385(03)00060-8
  • Raz V, Bergervoet JH, Koornneef M. Sequential steps for developmental arrest in Arabidopsis seeds. Development. 2001;128:243-252
  • Finkelstein RR, Gampala SSL, Rock CD. Abscisic acid signaling in seeds and seedlings. The Plant Cell. 2002;14(Suppl):S15-S45. DOI: 10.1105/tpc.010441
  • Robichaud CS, Wong J, Sussex IM. Control of in vitro growth of viviparous embryo mutants of maize by abscisic acid. Developmental Genetics. 1979;1:325-330. DOI: 10.1002/dvg.1020010405
  • Nambara E, Hayama R, Tsuchiya Y, Nishimura M, Kawaide H, Kamiya Y, et al. The role of ABI3 and FUS3 loci in Arabidopsis thaliana on phase transition from late embryo development to germination. Developmental Biology. 2000;220:412-423. DOI: 10.1006/DBIO.2000.9632
  • Hilhorst HWM. A critical update on seed dormancy. I. Primary dormancy. Seed Science Research. 1995;5:61-73. DOI: 10.1017/S0960258500002634
  • Kucera B, Cohn MA, Leubner-Metzger G. Plant hormone interactions during seed dormancy release and germination. Seed Science Research. 2005;15:281-307. DOI: 10.1079/SSR2005218
  • Grappin P, Bouinot D, Sotta B, Miginiac E, Jullien M. Control of seed dormancy in Nicotiana plumbaginifolia: Post-imbibition abscisic acid synthesis imposes dormancy maintenance. Planta. 2000;210:279-285. DOI: 10.1007/PL00008135
  • Le Page-Degivry MT, Garello G. In situ abscisic acid synthesis: A requirement for induction of embryo dormancy in Helianthus annuus. Plant Physiology. 1992;98:1386-1390. DOI: 10.1104/pp.98.4.1386
  • Wang M, Heimovaara-Dijkstra S, Van Duijn B. Modulation of germination of embryos isolated from dormant and nondormant barley grains by manipulation of endogenous abscisic acid. Planta. 1995;195:586-592. DOI: 10.1007/BF00195719
  • Liu X, Zhang H, Zhao Y, Feng Z, Li Q , Yang H-Q , et al. Auxin controls seed dormancy through stimulation of abscisic acid signaling by inducing ARF-mediated ABI3 activation in Arabidopsis. Proceedings of the National Academy of Sciences of the United States of America. 2013;110:15485-15490. DOI: 10.1073/pnas.1304651110
  • Shu K, Liu X, Xie Q , He Z. Two faces of one seed: Hormonal regulation of dormancy and germination. Molecular Plant. 2016;9:34-45. DOI: 10.1016/J.MOLP.2015.08.010
  • Barrero JM, Jacobsen JV, Talbot MJ, White RG, Swain SM, Garvin DF, et al. Grain dormancy and light quality effects on germination in the model grass Brachypodium distachyon. The New Phytologist. 2012;193:376-386. DOI: 10.1111/j.1469-8137.2011.03938.x
  • Millar AA, Jacobsen JV, Ross JJ, Helliwell CA, Poole AT, Scofield G, et al. Seed dormancy and ABA metabolism in Arabidopsis and barley: The role of ABA 8′-hydroxylase. The Plant Journal. 2006;45:942-954. DOI: 10.1111/j.1365-313X.2006.02659.x
  • Gubler F, Hughes T, Waterhouse P, Jacobsen J. Regulation of dormancy in barley by blue light and after-ripening: Effects on abscisic acid and gibberellin metabolism. Plant Physiology. 2008;84:61-66. DOI: 10.1104/pp.84.1.61
  • Lee S, Cheng H, King KE, Wang W, He Y, Hussain A, et al. Gibberellin regulates Arabidopsis seed germination via RGL2, a GAI/RGA-like gene whose expression is up-regulated following imbibition. Genes and Development. 2002;16:646-658. DOI: 10.1101/gad.969002
  • Yamauchi Y, Takeda-Kamiya N, Hanada A, Ogawa M, Kuwahara A, Seo M, et al. Contribution of gibberellin deactivation by AtGA2ox2 to the suppression of germination of dark-imbibed Arabidopsis thaliana seeds. Plant and Cell Physiology. 2007;48:555-561. DOI: 10.1093/pcp/pcm023
  • Jacobsen SE, Olszewski NE. Mutations at the SPINDLY locus of Arabidopsis alter gibberellin signal transduction. The Plant Cell. 1993;5:887-896. DOI: 10.1105/tpc.5.8.887
  • Bethke PC, Libourel IGL, Aoyama N, Chung Y-Y, Still DW, Jones RL. The Arabidopsis aleurone layer responds to nitric oxide, gibberellin, and abscisic acid and is sufficient and necessary for seed dormancy. Plant Physiology. 2007;143:1173-1188. DOI: 10.1104/pp.106.093435
  • Holman TJ, Jones PD, Russell L, Medhurst A, Tomás SÚ, Talloji P, et al. The N-end rule pathway promotes seed germination and establishment through removal of ABA sensitivity in Arabidopsis. Proceedings of the National Academy of Sciences. 2009;106:4549-4554. DOI: 10.1073/PNAS.0810280106
  • Graeber K, Nakabayashi K, Miatton E, Leubner-Metzger G, Soppe W. Molecular mechanisms of seed dormancy. Plant, Cell & Environment. 2012;35:1769-1786. DOI: 10.1111/j.1365-3040.2012.02542.x
  • Footitt S, Douterelo-Soler I, Clay H, Finch-Savage WE. Dormancy cycling in Arabidopsis seeds is controlled by seasonally distinct hormone-signaling pathways. Proceedings of the National Academy of Sciences. 2011;108:20236-20241. DOI: 10.1073/PNAS.1116325108
  • Allen PS, Benech-Arnold RL, Batlla D, Bradford KJ. Modeling of seed dormancy. In: Bradford KJ, Nonogaki H, editors. Seed Development, Dormancy and Germination. 1st ed. Chichester, UK: John Wiley & Sons, Ltd; 2007. pp. 72-112
  • Probert RJ. The role of temperature in the regulation of seed dormancy and germination. In: M Fenner, editor. Seeds: The Ecology of Regeneration in Plant Communities. Wallingford: CABI; 2000. pp. 261-292
  • Commander LE, Merritt DJ, Rokich DP, Dixon KW. The role of after-ripening in promoting germination of arid zone seeds: A study on six Australian species. Botanical Journal of the Linnean Society. 2009;161:411-421. DOI: 10.1111/j.1095-8339.2009.01009.x
  • Yamauchi Y, Ogawa M, Kuwahara A, Hanada A, Kamiya Y, Yamaguchi S. Activation of gibberellin biosynthesis and response pathways by low temperature during imbibition of Arabidopsis thaliana seeds. The Plant Cell. 2004;16:367-378. DOI: 10.1105/tpc.018143
  • Chiwocha SDS, Cutler AJ, Abrams SR, Ambrose SJ, Yang J, Ross ARS, et al. The etr1-2 mutation in Arabidopsis thaliana affects the abscisic acid, auxin, cytokinin and gibberellin metabolic pathways during maintenance of seed dormancy, moist-chilling and germination. The Plant Journal. 2005;42:35-48. DOI: 10.1111/j.1365-313X.2005.02359.x
  • Otroshy M, Zamani A, Khodambash M, Ebrahimi M, Struik PC. Effect of exogenous hormones and chilling on dormancy breaking of seeds of asafoetida (Ferula assafoetida L.). Research Journal of Seed Science. 2009;2:9-15. DOI: 10.3923/rjss.2009.9.15
  • Subhashini Devi P, Satyanarayana B, Arundhati A, Raghava Rao T. Effect of storage temperature and dormancy-breaking treatments on seed germination, moisture content and seed vigor in gum karaya ( Sterculia urens Roxb.). Forest Science and Technology. 2012;8:11-15. DOI: 10.1080/21580103.2012.658235
  • Schütz W. Ecology of seed dormancy and germination in sedges (Carex). Perspectives in Plant Ecology, Evolution and Systematics. 2000;3:67-89. DOI: 10.1078/1433-8319-00005
  • Baskin CC, Baskin JM. Germination ecophysiology of herbaceous plant species in a temperate region. American Journal of Botany. 1988;75:286-305. DOI: 10.1002/j.1537-2197.1988.tb13441.x
  • Li W, Liu X, Ajmal Khan M, Yamaguchi S. The effect of plant growth regulators, nitric oxide, nitrate, nitrite and light on the germination of dimorphic seeds of Suaeda salsa under saline conditions. Journal of Plant Research. 2005;118:207-214. DOI: 10.1007/s10265-005-0212-8
  • Pérez-Piñeiro P, Gago J, Landín M, Gallego PP. Agrobacterium-mediated transformation of wheat: General overview and new approaches to model and identify the key factors involved. In: Ozden Y, editor. Transgenic Plants: Advances and Limitations. Rijeka, Croatia: InTechOpen; 2012. pp. 3-26
  • Yuan JS, Galbraith DW, Dai SY, Griffin P, Stewart CN. Plant systems biology comes of age. Trends in Plant Science. 2008;13:165-171. DOI: 10.1016/J.TPLANTS.2008.02.003
  • Gago J, Martínez-Núñez L, Landín M, Flexas J, Gallego P. Modeling the effects of light and sucrose on In vitro propagated plants: A multiscale system analysis using artificial intelligence technology. PLoS One. 2014;9:e85989. DOI: 10.1371/journal.pone.0085989
  • Shao Q , Rowe RC, York P. Comparison of neurofuzzy logic and decision trees in discovering knowledge from experimental data of an immediate release tablet formulation. European Journal of Pharmaceutical Sciences. 2007;31:129-136. DOI: 10.1016/J.EJPS.2007.03.003
  • Jiménez D, Pérez-Uribe A, Satizábal H, Barreto M, Van Damme P, Tomassini M. A Survey of Artificial Neural Network-Based Modeling in Agroecology. Soft Computing Applications in Industry. 1st ed. Berlin, Heidelberg: Springer Berlin Heidelberg; 2008. pp. 247-269. DOI: 10.1007/978-3-540-77465-5_13
  • Hilbert DW, Ostendorf B. The utility of artificial neural networks for modelling the distribution of vegetation in past, present and future climates. Ecological Modelling. 2001;146:311-327. DOI: 10.1016/S0304-3800(01)00323-4
  • Plumb AP, Rowe RC, York P, Brown M. Optimisation of the predictive ability of artificial neural network (ANN) models: A comparison of three ANN programs and four classes of training algorithm. European Journal of Pharmaceutical Sciences. 2005;25:395-405. DOI: 10.1016/J.EJPS.2005.04.010
  • Osama K, Mishra BN, Somvanshi P. Machine learning techniques in plant biology. In: Barh D, Khan M, Davies E, editors. PlantOmics: The Omics of Plant Science. 1st ed. New Delhi: Springer India; 2015. pp. 731-754
  • Landín M, Rowe RC, York P. Advantages of neurofuzzy logic against conventional experimental design and statistical analysis in studying and developing direct compression formulations. European Journal of Pharmaceutical Sciences. 2009;38:325-331. DOI: 10.1016/J.EJPS.2009.08.004
  • Gago J, Landín M, Gallego PP. A neurofuzzy logic approach for modeling plant processes: A practical case of in vitro direct rooting and acclimatization of Vitis vinifera L. Plant Science. 2010;179:241-249. DOI: 10.1016/J.PLANTSCI.2010.05.009
  • Nezami-Alanagh E, Garoosi G-A, Maleki S, Landín M, Gallego P. Predicting optimal in vitro culture medium for Pistacia vera micropropagation using neural networks models. Plant Cell, Tissue and Organ Culture (PCTOC). 2017;129:19-33. DOI: 10.1007/s11240-016-1152-9
  • Nezami-Alanagh E, Garoosi G, Haddad R, Maleki S, Landín M, Gallego P. Design of tissue culture media for efficient Prunus rootstock micropropagation using artificial intelligence models. Plant Cell Tissue and Organ Culture. 2014;117:349-359. DOI: 10.1007/s11240-014-0444-1
  • Chantre GR, Blanco AM, Lodovichi MV, Bandoni AJ, Sabbatini MR, López RL, et al. Modeling Avena fatua seedling emergence dynamics: An artificial neural network approach. Computers and Electronics in Agriculture. 2012;88:95-102. DOI: 10.1016/J.COMPAG.2012.07.005
  • Blanco AM, Chantre GR, Lodovichi MV, Bandoni JA, López RL, Vigna MR, et al. Modeling seed dormancy release and germination for predicting Avena fatua L. field emergence: A genetic algorithm approach. Ecological Modelling. 2014;272:293-300. DOI: 10.1016/J.ECOLMODEL.2013.10.013
  • Chantre G, Blanco A, Forcella F, Van Acker R, Sabbatini M, Gonzalez-Andujar J. A comparative study between non-linear regression and artificial neural network approaches for modelling wild oat (Avena fatua) field emergence. The Journal of Agricultural Science. 2014;152:254-262. DOI: 10.1017/S0021859612001098
  • Chantre GR, Vigna MR, Renzi JP, Blanco AM. A flexible and practical approach for real-time weed emergence prediction based on artificial neural networks. Biosystems Engineering. 2018;170:51-60. DOI: 10.1016/J.BIOSYSTEMSENG.2018.03.014
  • Ayuso M, Ramil-Rego P, Landin M, Gallego PP, Barreal ME. Computer-assisted recovery of threatened plants: Keys for breaking seed dormancy of Eryngium viviparum. Frontiers in Plant Science. 2017;8:2092. DOI: 10.3389/fpls.2017.02092
  • González-Puelles JE, Landín M, Gallego PP, Barreal ME. Deciphering kiwifruit seed germination using neural network tools. Acta Horticulturae. 2018;1218: 359-366. DOI: 10.17660/ActaHortic.2018.1218.50