Seed image analysis provides evidence of taxonomic differentiation within the Medicago L. sect. Dendrotelis (Fabaceae)

Morpho-Colorimetric Characterization of the Sardinian Endemic Taxa of the Genus Anchusa L. by Seed Image Analysis

In this work, the seed morpho-colorimetric differentiation of the Sardinian endemic species of Anchusa (Boraginaceae) was evaluated. In Sardinia, the Anchusa genus includes the following seven taxa: A. capellii, A. crispa ssp. crispa, A. crispa ssp. maritima, A. formosa, A. littorea, A. montelinasana, and A. sardoa. Seed images were acquired using a flatbed scanner and analyzed using the free software package ImageJ. A total of 74 seed morpho-colorimetric features of 2692 seed lots of seven taxa of Anchusa belonging to 17 populations were extrapolated and used to build a database of seed size, shape, and color features. The data were statistically elaborated by the stepwise linear discriminant analysis (LDA) to compare and discriminate each accession and taxon. In addition, the seed morpho-colorimetric differences among coastal and mountainous taxa were evaluated. Considering the ecological conditions, the LDA was able to discriminate among the Anchusa taxa with a correct identification of 87.4% and 90.8% of specimens for mountainous and coastal plants, respectively. Moreover, the LDA of the 17 populations of Anchusa showed a low separation among species and populations within the coastal group, highlighting how the long-distance dispersal by flotation on the sea water surface and the pollination network may influence the similarity patterns observed. In addition, a misattribution was observed for A. crispa ssp. crispa, which was misclassified as A. crispa ssp. maritima in 14.1% of cases, while A. crispa ssp. maritima was misidentified as A. crispa ssp. crispa in 21.1% of cases, highlighting a close phenotypic relationship between these two taxa. The statistical results obtained through the seed image analysis showed that the morpho-colorimetric features of the seeds provide important information about the adaptation and evolution of Anchusa taxa in Sardinia.

High Throughput Phenotyping for Various Traits on Soybean Seeds Using Image Analysis

Data phenotyping traits on soybean seeds such as shape and color has been obscure because it is difficult to define them clearly. Further, it takes too much time and effort to have sufficient number of samplings especially length and width. These difficulties prevented seed morphology to be incorporated into efficient breeding program. Here, we propose methods for an image acquisition, a data processing, and analysis for the morphology and color of soybean seeds by high-throughput method using images analysis. As results, quantitative values for colors and various types of morphological traits could be screened to create a standard for subsequent evaluation of the genotype. Phenotyping method in the current study could define the morphology and color of soybean seeds in highly accurate and reliable manner. Further, this method enables the measurement and analysis of large amounts of plant seed phenotype data in a short time, which was not possible before. Fast and precise phenotype data obtained here may facilitate Genome Wide Association Study for the gene function analysis as well as for development of the elite varieties having desirable seed traits.

Inter- and intraspecific diversity in Cistus L. (Cistaceae) seeds, analysed with computer vision techniques

This work aims to discriminate among different species of the genus Cistus, using seed parameters and following the scientific plant names included as accepted in The Plant List. Also, the intraspecific phenotypic differentiation of C. creticus, through comparison with three subspecies (C. creticus subsp. creticus, C. c. subsp. eriocephalus and C. c. subsp. corsicus), as well as the interpopulation variability among five C. creticus subsp. eriocephalus populations was evaluated. Seed mean weight and 137 morphocolorimetric quantitative variables, describing shape, size, colour and textural seed traits, were measured using image analysis techniques. Measured data were analysed applying step-wise linear discriminant analysis. An overall cross-validated classification performance of 80.6% was recorded at species level. With regard to C. creticus, as case study, percentages of correct discrimination of 96.7% and 99.6% were achieved at intraspecific and interpopulation levels, respectively. In this classification model, the relevance of the colorimetric and textural descriptive features was highlighted, as well as the seed mean weight, which was the most discriminant feature at specific and intraspecific level. These achievements proved the ability of the image analysis system as highly diagnostic for systematic purposes and confirm that seeds in the genus Cistus have important diagnostic value.

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.