Analysis of Petal Shape Variation of Primula sieboldii by Elliptic Fourier Descriptors and Principal Component Analysis

Yoshioka, Yosuke; Iwata, Hiroyoshi; Ohsawa, Ryo; Ninomiya, S.

doi:10.1093/aob/mch190

Cited by 107 publications

(96 citation statements)

References 18 publications

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“…The 80 coefficients could be classified into two groups related to symmetrical variation (40 coefficients, hereafter referred to as group A) and asymmetrical variation (40 coefficients, group B) (Iwata et al, 1998;Yoshioka et al, 2004). To summarise the information contained in the coefficients in each group, we performed a PCA based on a variance-covariance matrix.…”

Section: Methodsmentioning

confidence: 99%

“…We previously reported that the use of elliptic Fourier descriptors and principal component analysis (EF-PCA) was effective in the quantitative evaluation of P. sieboldii petal shape (Yoshioka et al, 2004). EF-PCA has two major advantages: first, it can detect small variations in shape, and second, it can be used to evaluate the shapes of objects independently of their size.…”

Section: Introductionmentioning

confidence: 99%

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Quantitative evaluation of the petal shape variation in Primula sieboldii caused by breeding process in the last 300 years

et al. 2005

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Primula sieboldii (E. Morren) has been a popular garden plant at least since the Edo period, about 300 years ago. We compared petal form between cultivars and wild populations in order to characterise the changes that have occurred during domestication. The comparison was made using EF-PCA analysis, which describes overall petal shape mathematically by transforming petal contour coordinates into elliptic Fourier descriptors; it subsequently summarises these descriptors by principal component analysis (PCA). Rearing cultivars in a common-garden experiment identified the PCs with a substantial genetic element. A clear heritable component was detected for the PCs characterising symmetrical variation in flower shape, but not the asymmetrical variation. Wild populations of this species have become endangered owing to habitat destruction by human activity, and many lowland floodplain habitats have been lost. Variation within the remaining wild populations was significantly lower than in the cultivars for PC1 (aspect ratio), PC3 (curvature of proximal and distal parts) and petal area; but not for PC2 (depth of head notch) and PC4 (position of the centre of gravity). The shifts in petal form from the wild populations to the cultivars parallel those seen in other croptypes following domestication, including an increase in size and diversity of forms: cultivars have shallower head notches, more fan-shaped petals and larger petals than do wild P. sieboldii. Heredity (2005) 94, 657-663.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Quantitative evaluation of the petal shape variation in Primula sieboldii caused by breeding process in the last 300 years

et al. 2005

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“…This software package evaluates contour shapes based on Elliptic Fourier descriptor (EFDs). EFDs have been effectively applied to the analysis of various biological shapes in animals (Rohlf and Archie, 1984;Ferson et al, 1985;Bierbaum and Ferson, 1986;Diaz et al, 1989;Liu et al, 1996;Laurie et al, 1997) and plants (Yoshioka et al, 2004). The SHAPE software contains four programs: ChainCoder, Chc2Nef, PrinComp and PrinPrint (Iwata and Ukai, 2002).…”

Section: Morphometric Analysismentioning

confidence: 99%

Further Data on Sesamoid Identity from Two Anuran Species

Vera

Ponssa

Abdala

2015

The Anatomical Record

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Considering that the identification of equivalent entities is the basis for any comparative analysis, we compare the histology, histochemistry, shape and dimensions of epiphyses, carpal and sesamoids in two anuran frogs. Our goal was to explore the morphological correspondence among these three skeletal elements in order to clarify the sesamoid identity. We studied the skeletogenesis, contour geometric morphometry and dimensions of forelimb elements of juveniles of two anurans species Leptodactylus bufonius and Rhinella arenarum. Skeletogenesis in anurans present a common trait between carpals and sesamoids: both elements exhibit endochondral ossification. A difference between these elements is the presence of fibrocartilage in the development of sesamoids. The geometric morphometry does not allow us to establish a shape pattern that can be compared either between sesamoids and epiphyses or carpals. With regard to dimensions, our data indicate that bones categorization based on these aspects is ambiguous and therefore is useless to classify of skeletal bones. The data about tissue differentiation of sesamoids provide evidence that support the idea that these elements should be considered part of the typical endowment of the vertebrate skeleton. Anat Rec, 298:1376Rec, 298: -1394Rec, 298: , 2015. V C 2015 Wiley Periodicals, Inc.

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“…Kuhl and Giardina [4] introduced in their work a method for shape analysis based on elliptic Fourier descriptors. This method was widely used for shape analysis of plant organs by many researchers [5][6][7]. Mebatsion et al [8] developed an algorithm to classify cereal grains.…”

Section: Introductionmentioning

confidence: 99%

Shape development of wheat seeds during germination

Lev¹,

Chalupa²,

Blahovec³

2017

Engineering for Rural Development

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Abstract. Image analysis is a useful tool for seed monitoring during germination. An important advantage of the image analysis consists in easy determination of the dimensional changes in time without any manipulation with the germinated seeds. Many researches focus on the final germination phase and the image analysis is used for automatic detection of the visible radicle protrusion from the seed coat. However, an interesting behavior can be found in the whole germination process. The aim of this paper consists in development of an automatic method for observation and detection the image processes connected with seed germination. The setup consists of a photographic camera, a stand, an illumination LED panel and a glass vessel for the germination test. The camera is controlled via a computer and images are stored in the hard disk. The area of the seeds and their shape parameters were determined by a special program. The development of image moments is presented in our work. It was found that image moments can be useful tools for automatic detection of the primary shoot during the final germination phase as well as during the imbibition process.Keywords: imbibition, water movement, image moments, image analysis. IntroductionThe seed germination is a critical process for plant propagations. Germination starts by a quick water uptake and it is terminated with an elongation of the embryonic axis [1]. The final germination stage is usually represented by penetration of the radicle through the structures surrounding the embryo. This stage is often called visible germination [2].Image analysis is a useful tool for seed monitoring during germination. Shouche et al.[3] tested several shape parameters of Indian wheat seeds as a tool for identification of different varieties. The authors stated that the use of over 45 different parameters enabled them to distinguish between 15 samples of Indian wheat varieties. The moment analysis played a key role in their work. Kuhl and Giardina [4] introduced in their work a method for shape analysis based on elliptic Fourier descriptors. This method was widely used for shape analysis of plant organs by many researchers [5][6][7]. Mebatsion et al. [8] developed an algorithm to classify cereal grains. The authors tested their algorithm with barley, oat, rye and two varieties of wheat. The results show that the method can be used for seed classification. The classification accuracies were almost 100 %.Dell'Aquila [9] dealt with the application of the digital imaging information technology to seed germination testing. In his review article, he presents several parameters, which can be monitored during germination. The presented parameters are, e.g.: area, perimeter, length, width, roundness, calculated with the formula: perimeter 2 / 4π Area, and aspect, calculated with the ratio between the longer axis and the shorter axis of the ellipse equivalent to the seed area. The author noted one particular example of roundness factor utilization: a seed with a circular shape has the roundness f...

show abstract

Analysis of Petal Shape Variation of Primula sieboldii by Elliptic Fourier Descriptors and Principal Component Analysis

Cited by 107 publications

References 18 publications

Quantitative evaluation of the petal shape variation in Primula sieboldii caused by breeding process in the last 300 years

Quantitative evaluation of the petal shape variation in Primula sieboldii caused by breeding process in the last 300 years

Further Data on Sesamoid Identity from Two Anuran Species

Shape development of wheat seeds during germination

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