Morpho-colorimetric characterisation of Malva alliance taxa by seed image analysis.

Seed morphometric and -colorimetric features describing shape, size and textural seed traits of 28 taxa belonging to the genera Lavatera L. and Malva L., were recorded by means of computer vision techniques. The data were statistically analysed to contribute to the taxonomical treatment of the Malva alliance and to assess some doubtful systematic positions. A clear differentiation between taxa traditionally attributed to Lavatera or Malva was highlighted. Furthermore, the identification system proposed here was able to discriminate among the Lavatera sections, confirming the taxonomic organization of this genus. The results obtained for Malva, both at the species level and among sections, supported this analytical tool as diagnostic for systematic purposes.

[1]  O. Grillo,et al.  Inter- and intraspecific morphometric variability in Juniperus L. seeds (Cupressaceae) , 2014 .

[2]  F. Gyulai,et al.  Computer-assisted morphometry: A new method for assessing and distinguishing morphological variation in wild and domestic seed populations , 2007, Economic Botany.

[3]  S. Haberman The Analysis of Residuals in Cross-Classified Tables , 1973 .

[4]  M.,et al.  Statistical and Structural Approaches to Texture , 2022 .

[5]  Gianfranco Venora,et al.  Identification of Italian landraces of bean (Phaseolus vulgaris L.) using an image analysis system , 2009 .

[6]  A. C. Rencher Methods of multivariate analysis , 1995 .

[7]  O. Grillo,et al.  Morpho-colorimetric analysis and seed germination of Brassica insularis Moris (Brassicaceae) populations. , 2015, Plant biology.

[8]  G. Venora,et al.  Computerised image analysis applied to inspection of vetch seeds for varietal identification , 2011 .

[9]  O. Grillo,et al.  Seeds morpho-colourimetric analysis as complementary method to molecular characterization of melon diversity , 2015 .

[10]  Robert Tibshirani,et al.  The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition , 2001, Springer Series in Statistics.

[11]  D. F. Morrison,et al.  Multivariate Statistical Methods , 1968 .

[12]  M. F. Ray Systematics ofLavatera andMalva (Malvaceae, Malveae)—a new perspective , 1995, Plant Systematics and Evolution.

[13]  O. Hâruța Elliptic Fourier analysis of crown shapes in Quercus petraea trees. , 2011 .

[14]  Pedro Escobar García,et al.  Seed image analysis provides evidence of taxonomical differentiation within the Lavatera triloba aggregate (Malvaceae) , 2011 .

[15]  Raul H. C. Lopes,et al.  Pengaruh Latihan Small Sided Games 4 Lawan 4 Dengan Maksimal Tiga Sentuhan Terhadap Peningkatan VO2MAX Pada Siswa SSB Tunas Muda Bragang Klampis U-15 , 2022, Jurnal Ilmiah Mandala Education.

[16]  Borja Jiménez-Alfaro,et al.  Conservacion ex situ de plantas silvestres , 2007 .

[17]  Gianluigi Bacchetta,et al.  Statistical seed classifiers of 10 plant families representative of the Mediterranean vascular flora. , 2010 .

[18]  M. Kuhn,et al.  Discriminant Analysis and Other Linear Classification Models , 2013 .

[19]  O. Grillo,et al.  Characterisation of Italian bean landraces ('Phaseolus vulgaris' L.) using seed image analysis and texture descriptors , 2015 .

[20]  Identification of Sardinian Species of Astragalus Section Melanocercis (Fabaceae) by Seed Image Analysis , 2011 .

[21]  O. Grillo,et al.  Seed image analysis provides evidence of taxonomic differentiation within the Medicago L. sect. Dendrotelis (Fabaceae) , 2015 .

[22]  Smýkalová Iva,et al.  Phenotypic evaluation of flax seeds by image analysis , 2013 .

[23]  M. A. Shahin And S.J. Symons,et al.  Lentil type identification using machine vision , 2003 .

[24]  O. Grillo,et al.  Seed image analysis and taxonomy of Diplotaxis DC. (Brassicaceae, Brassiceae) , 2012 .

[25]  O. Grillo,et al.  Morphological characterisation of Vitis vinifera L. seeds by image analysis and comparison with archaeological remains , 2013, Vegetation History and Archaeobotany.

[26]  M. E. González-Benito,et al.  High viability recorded in ultra-dry seeds of 37 species of Brassicaceae after almost 40 years of storage , 2007 .

[27]  Augustin Pyramus de Candolle,et al.  Prodromus systematis naturalis regni vegetabilis, sive, Enumeratio contracta ordinum generum specierumque plantarum huc usque cognitarium, juxta methodi naturalis, normas digesta / , 1824 .

[28]  J. Gastwirth,et al.  The impact of Levene’s test of equality of variances on statistical theory and practice , 2009, 1010.0308.

[29]  Seishi Ninomiya,et al.  Analysis of petal shape variation of Primula sieboldii by elliptic fourier descriptors and principal component analysis. , 2004, Annals of botany.

[30]  Stephen J. Symons,et al.  Color Calibration of Scanners for Scanner‐Independent Grain Grading , 2003 .

[31]  O. Grillo,et al.  Morpho-colorimetric traits of Pisum seeds measured by an image analysis system , 2011 .

[32]  O. Grillo,et al.  Identification of Sicilian landraces and Canadian cultivars of lentil using an image analysis system , 2007 .

[33]  Harald Ganster,et al.  Glossary of computer vision terms in connection to information fusion , 1995 .

[34]  P. Schönswetter,et al.  Five molecular markers reveal extensive morphological homoplasy and reticulate evolution in the Malva alliance (Malvaceae). , 2009, Molecular phylogenetics and evolution.

[35]  O. Grillo,et al.  Earliest evidence of a primitive cultivar of Vitis vinifera L. during the Bronze Age in Sardinia (Italy) , 2015, Vegetation History and Archaeobotany.

[36]  H. Levene Robust tests for equality of variances , 1961 .

[37]  Takeshi Hayashi,et al.  Genome-wide association study of grain shape variation among Oryza sativa L. germplasms based on elliptic Fourier analysis , 2010, Molecular Breeding.

[38]  O. Grillo,et al.  Morpho-colorimetric characterization by image analysis to identify diaspores of wild plant species , 2008 .

[39]  P. Lootens,et al.  Description of the morphology of roots of Chicorium intybus L. partim by means of image analysis: Comparison of elliptic Fourier descriptors and classical parameters , 2007 .

[40]  Ken Kelley,et al.  A Comparison of Two-Group Classification Methods , 2011 .

[41]  G. Box,et al.  A general distribution theory for a class of likelihood criteria. , 1949, Biometrika.

[42]  Masashi Sugiyama,et al.  Dimensionality Reduction of Multimodal Labeled Data by Local Fisher Discriminant Analysis , 2007, J. Mach. Learn. Res..

[43]  H. K. Mebatsion,et al.  Evaluation of variations in the shape of grain types using principal components analysis of the elliptic Fourier descriptors , 2012 .

[44]  Wiesnerová Dana,et al.  Computer image analysis of seed shape and seed color for flax cultivar description , 2008 .

[45]  Gianfranco Venora,et al.  Quality assessment of durum wheat storage centres in Sicily: Evaluation of vitreous, starchy and shrunken kernels using an image analysis system , 2009 .

[46]  M. Hutchings,et al.  The effects of environmental heterogeneity on root growth and root/shoot partitioning. , 2004, Annals of botany.

[47]  Computer vision as a method complementary to molecular analysis: grapevine cultivar seeds case study. , 2012, Comptes rendus biologies.

[48]  Geographic isolation affects inter- and intra-specific seed variability in the Astragalus tragacantha complex, as assessed by morpho-colorimetric analysis. , 2013, Comptes rendus biologies.

[49]  Robert M. Haralick,et al.  Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..

[50]  Pedro Escobar García,et al.  Phylogenetic relationships in the species-rich Irano-Turanian genus Alcea (Malvaceae) , 2012 .

[51]  E. Banfi,et al.  Notes on systematics and taxonomy for the Italian vascular flora. 2. , 2011 .