リケラボ論文検索は、全国の大学リポジトリにある学位論文・教授論文を一括検索できる論文検索サービスです。

リケラボ 全国の大学リポジトリにある学位論文・教授論文を一括検索するならリケラボ論文検索大学・研究所にある論文を検索できる

リケラボ 全国の大学リポジトリにある学位論文・教授論文を一括検索するならリケラボ論文検索大学・研究所にある論文を検索できる

大学・研究所にある論文を検索できる 「スイレンの理論形態モデル : 花形態のデザインに向けて」の論文概要。リケラボ論文検索は、全国の大学リポジトリにある学位論文・教授論文を一括検索できる論文検索サービスです。

コピーが完了しました

URLをコピーしました

論文の公開元へ論文の公開元へ
書き出し

スイレンの理論形態モデル : 花形態のデザインに向けて

切江, 志龍 東京大学 DOI:10.15083/0002006861

2023.03.24

概要





















切江

志龍

花卉の育種では、花の観賞価値や美しさを向上させる目的が、花形態の多様化をもたら
してきた。スイレンについても、19 世紀後半にヨーロッパで品種改良が開始され、現代ま
でに様々な品種が作出された。申請者は、スイレンの育種から生み出されてきた花形態の
多様性をテーマに、その花形態の定量化とモデル化、育種家による花の特徴記述との関連、
そしてマーカー遺伝子型との関連解析を組み合わせ、育種で生み出された花形態変異の評
価を行った。また、花形態を新たにデザインするための手法について考察を行った。
第 1 章では、研究の背景となる各種話題(園芸文化、芸術と育種、スイレンの花の形態
形成、スレインの園芸史・文化史、理論形態学)が紹介された。
第 2 章では、花被片形状の定量的評価とその花型との関連について研究が行われた。ス
イレンでは、カタログや特性表に花形態の品種特性として花型が記載されている。申請者
は、花の構成要素である花被片の形状が花型とどのような関係をもつのかを明らかにする
ために、まず、花被片形状の定量的評価を行った。フランスの SARL Latour-Marliac で採
取された 41 品種 103 輪の花について、花被片の長さ、アスペクト比、楕円フーリエ記述子
を用いて花被片形状を定量的に評価した。また、形状の定量値と花型の関係、特に、主要
な花型であるカップ型、星型、カップ-星型との関係を調べた。その結果、星型はカップ型
よりも細長い花被片をもち、花被片枚数は星型のほうが多いことを明らかにした。同時に、
花被片形状の分布は花型間で互いに重なっており、花被片形状のみに基づく花型の判断は
難しいことが示された。
第 3 章では、
スイレンの花形態の定量的記述のための理論形態モデルの開発が行われた。
スイレンの花は 3 次元構造をもつために、その形態の定量的な評価や解析は容易ではない。
申請者は、スイレンの花形態の定量的な評価と解析を可能にするための 3 次元理論形態モ
デルを開発した。同モデルは、花器官の漸次的な形態変化、らせん葉序、花器官の仰角を
表すパラメータをもち、それらパラメータを変化させることで理論形態空間(モデルパラ
メータで張られる仮想的な形態のスペクトラムからなる空間)を構築する。同モデルをも
とに、神代植物園で採取された 28 品種 100 輪の花の花被片画像からパラメータを推定し、
理論形態空間での各花型の占有パターンを明らかにした。また、モデルから生成される花
のシルエットの幾何学的特徴指標を計算し、理論形態空間を花形態の全体的な特徴に結び
つけた。

第 4 章では、スイレン品種のもつ遺伝的背景の推定と花の形態特徴のゲノミック予測に
関する研究が行われた。申請者は、品種を生み出した育種家と、品種のもつ遺伝的背景や
花形態との関連を明らかにするため、ゲノムワイドマーカー遺伝子型に基づく集団構造解
析を行った。また、マーカー遺伝子型をもとに、花形態パラメータのゲノムワイド関連解
析とゲノミック予測を行った。材料には温帯性園芸品種が主に用いられた。RAD-Seq で得ら
れたマーカー遺伝子型の主成分分析の結果、同じ育種家に開発された品種が特定の位置に
クラスターを形成することが明らかになり、各育種家が用いることができた遺伝資源に制
約があった可能性が示唆された。また、育種家ごとに花径の大きさや花被片枚数に違いが
みられ、育種家ごとの“作風”の違いが示唆された。ゲノムワイド関連解析では、花の形
態変異に有意に関連するマーカーは検出されなかった。ゲノミック予測では、花被片の短
縮長、花径、花被片のアスペクト比で予測精度が比較的高かったが、各品種のもつマクロ
な遺伝的背景をもとに予測された可能性が高かった。
第 5 章では、スプライン曲面を用いた 3 次元理論形態モデルに関する研究が行われた。
申請者は、上述の理論形態モデルを NURBS 曲面を用いて拡張した。このモデルでは輪郭形
状から NURBS 曲面として記述される花被片形状モデルを生成し、同モデルを葉序モデルと
組み合わせることで、3 次元花形態の精緻なモデル化を可能とした。また、同モデルをゲノ
ミック予測と組み合わせることで、マーカー遺伝子型からモデルパラメータを予測し、そ
のパラメータに基づき 3 次元花形態を可視化できることを示した。また、全く仮想的なマ
ーカー遺伝子型や、実在する品種間交配から得られる後代のマーカー遺伝子型から 3 次元
花形態を構築できることを示した。以上の結果は、同モデルをもとに新たな花形態をデザ
インし、ゲノミック選抜を用いて“造形”できることを示唆するものであった。
第 6 章では、研究結果の総括と意義付けが行われた。また、開発モデルに基づく花のデ
ザインと造形の可能性、および、花のデザインと育種史の関連について議論がなされた。
これらの研究成果は、学術上応用上寄与するところが少なくない。よって、審査委員一
同は本論文が博士(農学)の学位論文として価値あるものと認めた。

この論文で使われている画像

参考文献

1.

Friedman WE. The meaning of Darwin’s “abominable mystery.” Am J Bot. 2009;96(1):5–

21.

2.

Crepet WL. Progress in understanding angiosperm history, success, and relationships:

Darwin’s abominably “perplexing phenomenon.” Proc Natl Acad Sci U S A.

2000;97(24):12939–41.

3.

Schemske DW, Bradshaw HD. Pollinator preference and the evolution of floral traits in

monkeyflowers (Mimulus). Proc Natl Acad Sci U S A. 1999;96(21):11910–5.

4.

Bleiweiss R. Mimicry on the QT(L): Genetics of speciation in Mimulus. Evolution (N Y).

2001;55(8):1706–9.

5.

Fenster CB, Armbruster WS, Wilson P, Dudash MR, Thomson JD, Fenster CB, et al.

Pollination Syndromes and Floral Specialization. Rev Lit Arts Am [Internet].

2004;35(2004):375–403. Available from: http://www.jstor.org/stable/30034121

6.

Wilkins AS, Wrangham RW, Tecumseh Fitch W. The “domestication syndrome” in

mammals: A unified explanation based on neural crest cell behavior and genetics.

Genetics. 2014;197(3):795–808.

7.

Driscoll CA, Macdonald DW, O’Brien SJ. From wild animals to domestic pets, an

evolutionary view of domestication. Light Evol. 2009;3:89–109.

8.

Meyer RS, Purugganan MD. Evolution of crop species : genetics of domestication and

diversification. Nat Publ Gr [Internet]. 2013;14(12):840–52. Available from:

http://dx.doi.org/10.1038/nrg3605

9.

Milla R, Osborne CP, Turcotte MM, Violle C. Plant domestication through an ecological

lens. Trends Ecol Evol. 2015;30(8):463–9.

10.

Gerbault P, Allaby RG, Boivin N, Rudzinski A, Grimaldi IM, Pires JC, et al. Storytelling

and story testing in domestication. Proc Natl Acad Sci U S A. 2014;111(17):6159–64.

11.

Ota KG, Abe G. Goldfish morphology as a model for evolutionary developmental biology.

Wiley Interdiscip Rev Dev Biol. 2016;5(3):272–95.

12.

似田坂英二. 変化朝顔図鑑. 初版. 化学同人; 2014.

13.

柴田道夫[編]. 花の品種改良の日本史. 悠書館; 2016.

14.

山口裕文[著・編]. 栽培植物の自然史II ―東アジア原産有用植物と照葉樹林帯の民族文

化. 北海道大学出版会; 2013.

15.

日高敏隆[編], 白幡洋三郎[編集]. 人はなぜ花を愛でるのか. 八坂書房; 2007.

16.

中尾佐助. 花と木の文化史. 岩波書店; 1986.

17.

Nitasaka E. Insertion of an En/Spm-related transposable element into a floral homeotic

gene DUPLICATED causes a double flower phenotype in the Japanese morning glory.

169

Plant J. 2003;36(4):522–31.

18.

Gessert G. Green Light Toward an Art of Evolution. Cambridge: MIT press; 2010. 233 p.

19.

Duthie R. Florists’ Flowers and Societies. Shire Pubns; 1988.

20.

Carter T. The Victorian Garden. Bracken Books; 1988.

21.

Glenny G. The Culture of Flowers and Plants. Houlston and Wright; 1861.

22.

アレックス・メスーディ[著], 竹澤正哲[解説], 野中香方子[訳]. 文化進化論:ダーウィン

進化論は文化を説明できるか. NTT出版; 2016.

23.

中尾央[著], 松木武彦[著], 三中信宏[著]. 文化進化の考古学. 勁草書房; 2017.

24.

田村光平. 文化進化の数理. 森北出版; 2020.

25.

Chitwood DH. Imitation, genetic lineages, and time influenced the morphological

evolution of the violin. PLoS One. 2014;9(10).

26.

Gessert G. Why I Breed Plants. In: Signs of Life Bio Art and Beyond. the MIT press;

2007.

27.

Fisher RA. The use of multiple measurements in taxonomic problems. Ann Eugen.

1936;7:179–88.

28.

石橋友也. キンギョの逆品種改良と実験生物学を内包するアート作品としての展開. 早

稲田大学; 2014.

29.

Abe G, Ota KG. Evolutionary developmental transition from median to paired

morphology of vertebrate fins: Perspectives from twin-tail goldfish. Dev Biol [Internet].

2017;427(2):251–7. Available from: http://dx.doi.org/10.1016/j.ydbio.2016.11.022

30.

Chen Z, Omori Y, Koren S, Shirokiya T, Kuroda T, Miyamoto A, et al. De novo assembly

of the goldfish (Carassius auratus) genome and the evolution of genes after wholegenome duplication. Sci Adv. 2019;5(6):1–13.

31.

Abe G, Lee SH, Chang M, Liu SC, Tsai HY, Ota KG. The origin of the bifurcated axial

skeletal system in the twin-tail goldfish. Nat Commun. 2014;5:1–7.

32.

Kon T, Omori Y, Fukuta K, Wada H, Watanabe M, Chen Z, et al. The Genetic Basis of

Morphological Diversity in Domesticated Goldfish. Curr Biol [Internet].

2020;30(12):2260-2274.e6. Available from: https://doi.org/10.1016/j.cub.2020.04.034

33.

ISHIBASHI T. TOMOYA ISHIBASHI [Internet]. [cited 2020 Dec 3]. Available from:

https://www.shibashiishibashi.com/

34.

美術手帖編集部. 美術手帖6月号. 美術出版社. 2020 Jun;77.

35.

Sansom RS, Gabbott SE, Purnell MA. Unusual anal fin in a Devonian jawless vertebrate

reveals complex origins of paired appendages. Biol Lett. 2013;9(3).

36.

Chase MW, Christenhusz MJM, Fay MF, Byng JW, Judd WS, Soltis DE, et al. An update

of the Angiosperm Phylogeny Group classification for the orders and families of flowering

plants: APG IV. Bot J Linn Soc. 2016;181(1):1–20.

170

37.

Borsch T, Löhne C, Wiersema J. Phylogeny and evolutionary patterns in Nymphaeales:

integrating genes, genomes and morphology Thomas. Taxon. 2008;57(November):1052–

81.

38.

Warner KA, Rudall PJ, Frohlich MW. Environmental control of sepalness and petalness in

perianth organs of waterlilies: A new Mosaic Theory for the evolutionary origin of a

differentiated perianth. J Exp Bot. 2009;60(12):3559–74.

39.

Goethe JW von, Miller. GL. THE METAMORPHOSIS OF PLANTS. London, England:

MIT press; 2009.

40.

Volkova PA, Choob V V., Shipunov AB. The flower organ transition in water lily

(Nymphaea alba s.l., Nymphaeaceae) under cross-examination with different

morphological approaches. Belgian J Bot. 2007;140(1):60–72.

41.

Buzgo M, Soltis PS, Soltis DE. Floral developmental morphology of Amborella trichopoda

(Amborellaceae). Int J Plant Sci. 2004;165(6):925–47.

42.

Soltis DE, Chanderbali AS, Kim S, Buzgo M, Soltis PS. The ABC model and its

applicability to basal angiosperms. Ann Bot [Internet]. 2007 Aug 1;100(2):155–63.

Available from: http://academic.oup.com/aob/article/100/2/155/104506/The-ABCModel-and-its-Applicability-to-Basal

43.

Theissen G, Melzer R. Molecular mechanisms underlying origin and diversification of the

angiosperm flower. Ann Bot. 2007;100(3):603–19.

44.

ES C, EM M. The war of the whorls: genetic interactions controlling flower development.

Nature. 1991;353(6339):31.

45.

Chanderbali AS, Yoo MJ, Zahn LM, Brockington SF, Wall PK, Gitzendanner MA, et al.

Conservation and canalization of gene expression during angiosperm diversification

accompany the origin and evolution of the flower. Proc Natl Acad Sci U S A.

2010;107(52):22570–5.

46.

Yoo M, Soltis PS, Soltis DE. Expression of Floral MADS‐Box Genes in Two Divergent

Water Lilies: Nymphaeales and Nelumbo. Int J Plant Sci. 2010;171(2):121–46.

47.

Luo H, Chen S, Jiang J, Chen Y, Chen F, Teng N, et al. The expression of floral organ

identity genes in contrasting water lily cultivars. Plant Cell Rep. 2011;30(10):1909–18.

48.

Chanderbali AS, Berger BA, Howarth DG, Soltis PS, Soltis DE, Museum F, et al.

Evolving Ideas on the Origin and Evolution of Flowers : New Perspectives in the

Genomic Era. Genetics. 2016;202(April):1255–65.

49.

Chen F, Liu X, Yu C, Chen Y, Tang H, Zhang L. Water lilies as emerging models for

Darwin’s abominable mystery. Hortic Res [Internet]. 2017;4(July). Available from:

http://dx.doi.org/10.1038/hortres.2017.51

50.

Lohaus R, Chang X, Dong W, Ho SYW, Liu X, Song A, et al. The water lily genome and

171

the early evolution of flowering plants. Nature [Internet]. 2020;577(January):79–84.

Available from: http://dx.doi.org/10.1038/s41586-019-1852-5

51.

Slocum PD. Waterlilies and Lotuses Species, Cultivars, and New Hybrids. TIMBER

PRESS; 2005.

52.

Conard HS. The Waterlilies: A Monograph of the Genus Nymphaea [Internet]. the

Carnegie Institution of Washington; 1905. Available from:

https://www.biodiversitylibrary.org/item/64590

53.

Songpanich P, Hongtrakul V. Intersubgeneric cross in Nymphaea spp. L. to develop a

blue hardy waterlily. Sci Hortic (Amsterdam) [Internet]. 2010;124(4):475–81. Available

from: http://dx.doi.org/10.1016/j.scienta.2010.01.024

54.

ガブリエル・ターギット[著], 遠山茂樹[訳]. 図説 花と庭園の文化史事典. 八坂書房;

2014.

55.

Hariot P, Hariot P. Atlas colorié des plantes médicinales indigènes [Internet]. Paris : P.

Klincksieck,; 1900 [cited 2020 Dec 3]. 1–377 p. Available from:

https://www.biodiversitylibrary.org/item/23170

56.

Sheldon RC. Inventing water lilies: Latour-Marliac and the social dynamics of market

creation. Entrep Hist. 2018;88(3):147–65.

57.

Holmes C. Water Lilies: and Bory Latour-Marliac, the Genius Behind Monet’s Water

Lilies. Garden Art Press ACC; 2015.

58.

SARL Latour-Marliac Webpage - history [Internet]. [cited 2020 Dec 3]. Available from:

http://latour-marliac.com/en/content/category/4-history

59.

岡本隆. 理論形態学の方法. In: 古生物学の形態と解析[普及版]. 朝倉書店; 1999. p.

140–73.

60.

McGhee GR. Limits in the evolution of biological form: A theoretical morphologic

perspective. Interface Focus. 2015;5(6).

61.

Stone JR. The spirit of D’Arcy Thompson dwells in empirical morphospace. Math Biosci.

1997;142(1):13–30.

62.

Mitteroecker P, Huttegger SM. The Concept of Morphospaces in Evolutionary and

Developmental Biology: Mathematics and Metaphors. Biol Theory. 2009;4(1):54–67.

63.

Raup DM, Michelson A. Theoretical morphology of the coiled shell. Science (80- ).

1965;147(3663):1294–5.

64.

Raup DM. Geometric Analysis of Shell Coiling: General Problems. J Paleontol.

1966;40(5):1178–90.

65.

OKAMOTO T. Analysis of heteromorph ammonoids by differential geometry. Vol. 31,

Palaeontology. 1988. p. 35–52.

66.

Noshita K, Shimizu K, Sasaki T. Geometric analysis and estimation of the growth rate

172

gradient on gastropod shells. J Theor Biol [Internet]. 2016;389:11–9. Available from:

http://dx.doi.org/10.1016/j.jtbi.2015.10.011

67.

Chartier M, Jabbour F, Gerber S, Mitteroecker P, Sauquet H, Von Balthazar M, et al. The

floral morphospace - a modern comparative approach to study angiosperm evolution.

New Phytol. 2014;204(4):841–53.

68.

Runions A, Tsiantis M, Prusinkiewicz P. A common developmental program can produce

diverse leaf shapes. New Phytol. 2017;216(2):401–18.

69.

Niklas KJ. The evolution of plant body plans - A biomechanical perspective. Ann Bot.

2000;85(4):411–38.

70.

Niklas KJ. Evolutionary walks through a land plant morphospace. J Exp Bot.

1999;50(330):39–52.

71.

Niklas KJ. Morphological evolution through complex domains of fitness. Proc Natl Acad

Sci U S A. 1994;91(15):6772–9.

72.

Kitazawa MS, Fujimoto K. A Dynamical Phyllotaxis Model to Determine Floral Organ

Number. PLoS Comput Biol. 2015;11(5):1–27.

73.

Miriam Leah Zelditch DLS, Sheets HD. Geometric Morphometrics for Biologists: A

Primer. 2nd ed. Academic Press; 2012.

74.

Bookstein FL. Morphometric tools for landmark data: Geometry and biology. Cambridge:

Cambridge University Press; 1991.

75.

Kuhl FP, Giardina CR. Elliptic Fourier Features of a Closed Contour. Comput Graph

image Process. 1982;18:236–58.

76.

Hiroyoshi Iwata, Satoshi Niikura, Seiji Matsuura, Yasushi Takano YU. Evaluation of

variation of root shape of Japanese radish (Raphanus sativus L.) based on image analysis

using elliptic Fourier descriptors. Vol. Volume 102, Euphytica. 1998. p. 143–9.

77.

Freeman H. Computer Processing of Line-Drawing Images. ACM Comput Surv.

1974;6(1):57–97.

78.

Yoshioka Y, Iwata H, Ohsawa R, Ninomiya S. Analysis of petal shape variation of Primula

sieboldii by elliptic fourier descriptors and principal component analysis. Ann Bot.

2004;94(5):657–64.

79.

Yoshioka Y, Iwata H, Ohsawa R, Ninomiya S. Quantitative evaluation of the petal shape

variation in Primula sieboldii caused by breeding process in the last 300 years. Heredity

(Edinb). 2005;94(6):657–63.

80.

Kawabata S, Yokoo M, Nii K. Quantitative analysis of corolla shapes and petal contours in

single-flower cultivars of lisianthus. Sci Hortic (Amsterdam). 2009;121(2):206–12.

81.

農林水産省生産局知的財産課種苗審査室. すいれん(ひつじぐさ)属. 2010.

82.

International water lily society. Idenfitication of hardy nymphaea. Stapeley Water

173

Gardens Ltd; 1993.

83.

Detienne P. Les nymphéas rustiques. Editions “Jardins et décors aquatiques”; 2006.

84.

Schneider CA, Rasband WS, Eliceiri KW. NIH Image to ImageJ: 25 years of image

analysis. Nat Methods. 2012;9(7):671–5.

85.

Schindelin J, Arganda-Carrera I, Frise E, Verena K, Mark L, Tobias P, et al. Fiji: an opensource platform for biological-image analysis. Nat Methods. 2012;9(7):676–82.

86.

Iwata H, Ukai Y. SHAPE: a computer program package for quantitative evaluation of

biological shapes based on elliptic Fourier descriptors. J Hered. 2002;93(5):384–5.

87.

Bonhomme V, Picq S, Gaucherel C, Claude J. Momocs: Outline analysis using R. J Stat

Softw. 2014;56(13):1–24.

88.

Conard HS, Conard HS, Hus H. Water-lilies and how to grow them, with chapters on the

proper making of ponds and the use of accessory plants [Internet]. New York,:

Doubleday, Page & company,; [cited 2020 Dec 3]. 1–284 p. Available from:

https://www.biodiversitylibrary.org/item/91862

89.

Kawabata S, Nii K, Yokoo M. Three-dimensional formation of corolla shapes in relation

to the developmental distortion of petals in Eustoma grandiflorum. Sci Hortic

(Amsterdam) [Internet]. 2011;132(1):66–70. Available from:

http://dx.doi.org/10.1016/j.scienta.2011.09.034

90.

Wang CN, Hsu HC, Wang CC, Lee TK, Kuo YF. Quantifying floral shape variation in 3D

using microcomputed tomography: A case study of a hybrid line between actinomorphic

and zygomorphic flowers. Front Plant Sci. 2015;6(September).

91.

Hsu HC, Wang CN, Liang CH, Wang CC, Kuo YF. Association between petal form

variation and CYC2-like genotype in a hybrid line of Sinningia speciosa. Front Plant Sci.

2017;8(April):1–13.

92.

An N, Palmer CM, Baker RL, Markelz RJC, Ta J, Covington MF, et al. Plant highthroughput phenotyping using photogrammetry and imaging techniques to measure leaf

length and rosette area. Comput Electron Agric [Internet]. 2016;127:376–94. Available

from: http://dx.doi.org/10.1016/j.compag.2016.04.002

93.

An N, Welch SM, Markelz RJC, Baker RL, Palmer CM, Ta J, et al. Quantifying timeseries of leaf morphology using 2D and 3D photogrammetry methods for highthroughput plant phenotyping. Comput Electron Agric [Internet]. 2017;135:222–32.

Available from: http://dx.doi.org/10.1016/j.compag.2017.02.001

94.

Andújar D, Calle M, Fernández-Quintanilla C, Ribeiro Á, Dorado J. Three-dimensional

modeling of weed plants using low-cost photogrammetry. Sensors (Switzerland).

2018;18(4):1–11.

95.

Guo W, Fukano Y, Noshita K, Ninomiya S. Field-based individual plant phenotyping of

174

herbaceous species by unmanned aerial vehicle. Ecol Evol. 2020;10(21):12318–26.

96.

Gerber S. The geometry of morphospaces: Lessons from the classic raup shell coiling

model. Biol Rev. 2017;92(2):1142–55.

97.

Prusinkiewicz P, Mündermann L, Karwowski R, Lane B. The use of positional

information in the modeling of plants. Proc 28th Annu Conf Comput Graph Interact

Tech SIGGRAPH 2001. 2001;289–300.

98.

Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O, et al. Scikitlearn: Machine Learning in Python. J Mach Learn Res. 2012;12:2825–30.

99.

Chacón B, Ballester R, Birlanga V, Rolland-Lagan AG, Pérez-Pérez JM. A quantitative

framework for flower phenotyping in cultivated carnation (Dianthus caryophyllus L.).

PLoS One. 2013;8(12).

100.

Bradski G. The OpenCV Library. Dr Dobb’s J Softw Tools. 2000;

101.

Chanderbali AS, Berger BA, Howarth DG, Soltis PS, Soltis DE. Evolving ideas on the

origin and evolution of flowers: New perspectives in the genomic era. Genetics.

2016;202(4):1255–65.

102.

Qi W, Chen X, Fang P, Shi S, Li J, Liu X, et al. Genomic and transcriptomic sequencing

of Rosa hybrida provides microsatellite markers for breeding, flower trait improvement

and taxonomy studies. BMC Plant Biol. 2018;18(1):1–11.

103.

Yagi M, Shirasawa K, Waki T, Kume T, Isobe S, Tanase K, et al. Construction of an SSR

and RAD Marker-Based Genetic Linkage Map for Carnation (Dianthus caryophyllus L.).

Plant Mol Biol Report [Internet]. 2017;35(1):110–7. Available from:

http://dx.doi.org/10.1007/s11105-016-1010-2

104.

Su J, Jiang J, Zhang F, Liu Y, Ding L, Chen S, et al. Current achievements and future

prospects in the genetic breeding of chrysanthemum: a review. Hortic Res [Internet].

2019;6(1). Available from: http://dx.doi.org/10.1038/s41438-019-0193-8

105.

Yoshida Y, Ueno S, Honjo M, Kitamoto N, Nagai M, Washitani I, et al. QTL analysis of

heterostyly in Primula sieboldii and its application for morph identification in wild

populations. Ann Bot. 2011;108(1):133–42.

106.

Minamikawa MF, Nonaka K, Kaminuma E, Kajiya-Kanegae H, Onogi A, Goto S, et al.

Genome-wide association study and genomic prediction in citrus: Potential of genomicsassisted breeding for fruit quality traits. Sci Rep. 2017;7(1):1–2.

107.

He Y, Wu D, Wei D, Fu Y, Cui Y, Dong H, et al. GWAS, QTL mapping and gene

expression analyses in Brassica napus reveal genetic control of branching morphogenesis.

Sci Rep [Internet]. 2017;7(1):1–9. Available from: http://dx.doi.org/10.1038/s41598017-15976-4

108.

Yamamoto E, Matsunaga H, Onogi A, Kajiya-Kanegae H, Minamikawa M, Suzuki A, et al.

175

A simulation-based breeding design that uses whole-genome prediction in tomato. Sci

Rep. 2016;6(January):1–11.

109.

Baird NA, Etter PD, Atwood TS, Currey MC, Shiver AL, Lewis ZA, et al. Rapid SNP

discovery and genetic mapping using sequenced RAD markers. PLoS One. 2008;3(10):1–

7.

110.

Peterson BK, Weber JN, Kay EH, Fisher HS, Hoekstra HE. Double digest RADseq: An

inexpensive method for de novo SNP discovery and genotyping in model and non-model

species. PLoS One. 2012;7(5).

111.

Bolger AM, Lohse M, Usadel B. Trimmomatic: A flexible trimmer for Illumina sequence

data. Bioinformatics. 2014;30(15):2114–20.

112.

Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform.

Bioinformatics. 2009;25(14):1754–60.

113.

Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The Sequence

Alignment/Map format and SAMtools. Bioinformatics. 2009;25(16):2078–9.

114.

Mckenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, et al. The

Genome Analysis Toolkit : A MapReduce framework for analyzing next-generation DNA

sequencing data. Genome Res. 2010;20:1297–303.

115.

Danecek P, Auton A, Abecasis G, Albers CA, Banks E, DePristo MA, et al. The variant

call format and VCFtools. Bioinformatics. 2011;27(15):2156–8.

116.

Browning SR, Browning BL. Rapid and accurate haplotype phasing and missing-data

inference for whole-genome association studies by use of localized haplotype clustering.

Am J Hum Genet. 2007;81(5):1084–97.

117.

SARL Latour-Marliac Webpage - catalog [Internet]. [cited 2006 Jan 20]. Available from:

http://latour-marliac.com/en/12-hardy-water-lilies

118.

Yu J, Pressoir G, Briggs WH, Bi IV, Yamasaki M, Doebley JF, et al. A unified mixedmodel method for association mapping that accounts for multiple levels of relatedness.

Nat Genet. 2006;38(2):203–8.

119.

Hamazaki K, Iwata H. Rainbow: Haplotype-based genome-wide association study using a

novel SNP-set method. PLoS Comput Biol [Internet]. 2020;16(2):1–17. Available from:

http://dx.doi.org/10.1371/journal.pcbi.1007663

120.

Vitezica ZG, Legarra A, Toro MA, Varona L. Orthogonal Estimates of Variances for

Additive ,. Genetics. 2017;206(July):1297–307.

121.

VanRaden PM. Efficient methods to compute genomic predictions. J Dairy Sci

[Internet]. 2008;91(11):4414–23. Available from: http://dx.doi.org/10.3168/jds.20070980

122.

de Bem Oliveira I, Amadeu RR, Ferrão LFV, Muñoz PR. Optimizing whole-genomic

176

prediction for autotetraploid blueberry breeding. Heredity (Edinb) [Internet].

2020;125(6):437–48. Available from: http://dx.doi.org/10.1038/s41437-020-00357-x

123.

de Bem Oliveira I, Resende MFR, Ferrão LF V., Amadeu RR, Endelman JB, Kirst M, et

al. Genomic prediction of autotetraploids; influence of relationship matrices, allele

dosage, and continuous genotyping calls in phenotype prediction. G3 Genes, Genomes,

Genet. 2019;9(4):1189–98.

124.

Santantonio N, Jannink JL, Sorrells M. Prediction of subgenome additive and interaction

effects in allohexaploid wheat. G3 Genes, Genomes, Genet. 2019;9(3):685–98.

125.

Larson G, Piperno DR, Allaby RG, Purugganan MD, Andersson L, Arroyo-Kalin M, et al.

Current perspectives and the future of domestication studies. Proc Natl Acad Sci U S A.

2014;111(17):6139–46.

126.

Meuwissen THE, Hayes BJ, Goddard ME. Prediction of total genetic value using

genome-wide dense marker maps. Genetics. 2001;157(4):1819–29.

127.

Lindenmayer A. Mathematical models for cellular interactions in development II. Simple

and branching filaments with two-sided inputs. J Theor Biol [Internet]. 1968;18(3):300–

15. Available from:

http://www.sciencedirect.com/science/article/pii/0022519368900805

128.

Prusinkiewicz P, Lindenmayer A. The Algorithmic Beauty of Plants. Springer-Verlag;

1990.

129.

Ridley JN. Ideal phyllotaxis on general surfaces of revolution. Math Biosci. 1986;79(1):1–

24.

130.

Douady S, Couder Y. Phyllotaxis as a dynamical self organizing process part I: The spiral

modes resulting from time-periodic iterations. J Theor Biol [Internet]. 1996;178:255–74.

Available from: http://www.sciencedirect.com/science/article/pii/S0022519396900247

131.

Douady S, Couder Y. Phyllotaxis as a Dynamical Self Organizing Process Part II: The

Spontaneous Formation of a Periodicity and the Coexistence of Spiral and Whorled

Patterns. J Theor Biol. 1996;178(3):275–94.

132.

Douady S, Couder Y. Phyllotaxis as a dynamical self organizing process part III: The

simulation of the transient regimes of ontogeny. J Theor Biol. 1996;178(3):295–312.

133.

Fowler DR, Prusinkiewicz P, Battjes J. Collision-based model of spiral phyllotaxis.

Comput Graph. 1992;26(2):361–8.

134.

Prusinkiewicz P, Erasmus Y, Lane B, Harder LD, Coen E. Evolution and development of

inflorescence architectures. Science (80- ). 2007;316(5830):1452–6.

135.

Owens A, Cieslak M, Hart J, Classen-Bockhoff R, Prusinkiewicz P. Modeling dense

inflorescences. ACM Trans Graph. 2016;35(4).

136.

Godin C, Caraglio Y. A Multiscale Model of Plant Topological Structures. J Theor Biol.

177

1998;1–46.

137.

Pradal C, Boudon F, Nouguier C, Chopard J, Godin C. PlantGL: A Python-based

geometric library for 3D plant modelling at different scales. Graph Models.

2009;71(1):1–21.

138.

Boudon F, Pradal C, Cokelaer T, Prusinkiewicz P, Godin C. L-Py: An L-system

simulation framework for modeling plant architecture development based on a dynamic

language. Front Plant Sci. 2012;3(MAY).

139.

Pradal C, Dufour-Kowalski S, Boudon F, Fournier C, Godin C. OpenAlea: A visual

programming and component-based software platform for plant modelling. Funct Plant

Biol. 2008;35(10):751–60.

140.

Pradal C, Fournier C, Valduriez P, Cohen-Boulakia S. OpenAlea: Scientific workflows

combining data analysis and simulation. ACM Int Conf Proceeding Ser. 2015;29-June-20.

141.

Lintermann B, Deussen O. Interactive modeling of plants. IEEE Comput Graph Appl.

1999;19(1):56–65.

142.

Boudon F, Prusinkiewicz P, Federl P, Godin C, Boudon F, Prusinkiewicz P, et al.

Interactive design of bonsai tree models To cite this version : HAL Id : hal-00827461.

2013;

143.

Dror R, Shimshoni I. Using phyllotaxis for date palm tree 3D reconstruction from a single

image. VISAPP 2009 - Proc 4th Int Conf Comput Vis Theory Appl. 2009;2(c):288–96.

144.

Isokane T, Okura F, Ide A, Matsushita Y, Yagi Y. Probabilistic Plant Modeling via Multiview Image-to-Image Translation. Proc IEEE Comput Soc Conf Comput Vis Pattern

Recognit. 2018;2906–15.

145.

Ubbens J, Cieslak M, Prusinkiewicz P, Stavness I. The use of plant models in deep

learning: An application to leaf counting in rosette plants. Plant Methods [Internet].

2018;14(1):1–10. Available from: https://doi.org/10.1186/s13007-018-0273-z

146.

Toda Y, Okura F, Ito J, Okada S, Kinoshita T, Tsuji H, et al. Training instance

segmentation neural network with synthetic datasets for crop seed phenotyping.

Commun Biol [Internet]. 2020;3(1):1–12. Available from:

http://dx.doi.org/10.1038/s42003-020-0905-5

147.

Sievänen R, Godin C, De Jong TM, Nikinmaa E. Functional-structural plant models: A

growing paradigm for plant studies. Ann Bot. 2014;114(4):599–603.

148.

Han L, Costes E, Boudon F, Cokelaer T, Pradal C, Da Silva D, et al. Investigating the

influence of geometrical traits on light interception efficiency of apple trees: A modelling

study with MAppleT. Proc - 2012 IEEE 4th Int Symp Plant Growth Model Simulation,

Vis Appl PMA 2012. 2012;152–9.

149.

Braghiere RK, Gérard F, Evers JB, Pradal C, Pagès L. Simulating the effects of water

178

limitation on plant biomass using a 3D functional-structural plant model of shoot and

root driven by soil hydraulics. Ann Bot. 2020;126(4):713–28.

150.

Cieslak M, Cheddadi I, Boudon F, Baldazzi V, Génard M, Godin C, et al. Integrating

physiology and architecture in models of fruit expansion. Front Plant Sci.

2016;7(NOVEMBER2016):1–19.

151.

Donald CM. The breeding of crop ideotypes. Euphytica. 1968;17(3):385–403.

152.

Yoshioka Y, Ohashi K, Konuma A, Iwata H, Ohsawa R, Ninomiya S. Ability of

bumblebees to discriminate differences in the shape of artificial flowers of Primula

sieboldii (Primulaceae). Ann Bot. 2007;99(6):1175–82.

153.

Campos EO, Bradshaw HD, Daniel TL. Shape matters: Corolla curvature improves

nectar discovery in the hawkmoth Manduca sexta. Funct Ecol. 2015;29:462–468.

154.

Peng F, Campos EO, Sullivan JG, Berry N, Song B Bin, Daniel TL, et al. Morphospace

exploration reveals divergent fitness optima between plants and pollinators. PLoS One.

2019;14(3):1–12.

155.

Policha T, Davis A, Barnadas M, Dentinger BTM, Raguso RA, Roy BA. Disentangling

visual and olfactory signals in mushroom-mimicking Dracula orchids using realistic threedimensional printed flowers. New Phytol. 2016;210(3):1058–71.

156.

Iwata H, Ebana K, Uga Y, Hayashi T. Genomic prediction of biological shape: Elliptic

Fourier analysis and kernel Partial Least Squares (PLS) regression applied to grain shape

prediction in rice (Oryza sativa L.). PLoS One. 2015;10(3):1–17.

157.

Iwata H, Hayashi T, Terakami S, Takada N, Saito T, Yamamoto T. Genomic prediction of

trait segregation in a progeny population: A case study of Japanese pear (Pyrus pyrifolia).

BMC Genet. 2013;14.

158.

ケイシー・リース, チャンドラー・マクウィリアムス, 久保田晃弘[監], 吉村マサテル

[訳]. FORM+CODE -デザイン/アート/建築における、かたちとコード. ビー・エ

ヌ・エヌ新社; 2011.

159.

秋庭史典. あたらしい美学をつくる. みすず書房; 2011.

160.

秀雄岩崎. 〈生命〉とは何だろうか――表現する生物学、思考する芸術. 講談社; 2013.

179

...

参考文献をもっと見る

全国の大学の
卒論・修論・学位論文

一発検索!

この論文の関連論文を見る