Adeniyi A Jayeola’s research while affiliated with University of Ibadan and other places

Premise: Plant leaves are one of the most important organs for plant identification due to their variability across different taxonomic groups. While traditional morphometrics has contributed tremendously to reducing the problems accompanying plant identification and morphology-based species delimitation, image-analysis digital solutions have made it easy to detect more characters to complement existing leaf data sets. Methods: Here, we apply MorphoLeaf to generate a morphometric data set from 140 leaf specimens of seven Cucurbitaceae species via landmark extraction, the reparameterization of leaf contours, and data quantification and normalization. A statistical analysis was performed on the resulting data set. Results: A principal component analysis revealed that leaf blade area, blade perimeter, tooth area, tooth perimeter, the measure of the distance from tooth position to the tip, and the measure of the distance from tooth position to the base are important and informative landmarks that contribute to the variation within the species studied. Discussion: MorphoLeaf can be applied to quantitatively track leaf diversity, thereby functionally integrating morphometrics and shape visualization into the digital identification of plants. The success of digital morphometrics in leaf outline analyses presents researchers with opportunities to carry out more accurate image-based research in areas such as plant development, evolution, and phenotyping.

Morphometrics has been applied in several fields of science including botany. Plant leaves are been one of the most important organs in the identification of plants due to its high variability across different plant groups. The differences between and within plant species reflect variations in genotypes, development, evolution, and environment. While traditional morphometrics has contributed tremendously to reducing the problems that come with the identification of plants and delimitation of species based on morphology, technological advancements have led to the creation of deep learning digital solutions that made it easy to study leaves and detect more characters to complement already existing leaf datasets. In this study, we demonstrate the use of MorphoLeaf in generating morphometric dataset from 140 leaf specimens from seven Cucurbitaceae species via scanning of leaves, extracting landmarks, data extraction, landmarks data quantification, and reparametrization and normalization of leaf contours. PCA analysis revealed that blade area, blade perimeter, tooth area, tooth perimeter, height of (each position of the) tooth from tip, and the height of each (position of the) tooth from base are important and informative landmarks that contribute to the variation within the species studied. Our results demonstrate that MorphoLeaf can quantitatively track diversity in leaf specimens, and it can be applied to functionally integrate morphometrics and shape visualization in the digital identification of plants. The success of digital morphometrics in leaf outline analysis presents researchers with opportunities to apply and carry out more accurate image-based researches in diverse areas including, but not limited to, plant development, evolution, and phenotyping.

Hydnora species (Hydnoraceae) are parasitic angiosperms endemic to Africa and restricted to the Sudano-Zambezian region. We report here the occurrence of several stands of Hydnora abyssinica A. Braun in Nekong, Wusali ward, a lowland area in the Sudan-Savanna zone in Kanke Local Government Area, Plateau State, Nigeria. Hydnora abyssinica was found parasitizing woody plants, noticeably Acacia hockii De Wild, Piliostigma thonningii (Schum.) Milne-Redh and Tamarindus indica L. Our observations represent the first recorded occurrence of any Hydnora species in the Guineo-Congolian region which, when combined with its well-known Sudano-Zambezian distribution, enlarges and establishes its distributional range as an African endemic species.

Exo-morphological characters of two controversial taxa, Plectranthus esculentus N. E. Br. Natal and Solenostemon rotundifolius (Poir) J. K. Morton were studied using both preserved herbarium specimens and living collections from in situ and ex situ sources. The study aimed at gaining a better understanding of specific relationships between the two species in order to improve their identification and classification. Morphological characters derived from leaf, stem, root and tubers were analyzed numerically, using cluster method. The quantitative characters were mostly continuous rather but not discrete while the qualitative characters revealed multistate nature. The preponderance of intermediate characters coupled with similarity in shared characters are indicative of a weak specific boundary in the circumscription of P. esculentus land races and S. rotundifolius. Cluster analysis revealed a strong overall similarity relationship among the varieties and land races in a range of 56 % (minimum) and 74 % (maximum) with an intermediate of 68 %.The findings in this study are consistent with the current treatment of S. rotundifloius in synonymy with P. esculentus. We propose infraspecific recognition of three varieties in the P. esculentus as follows: variety I (P. esculentus var. "Bebot" and P. esculenstus var. "Longat"), var. II (S. rotundifolius var. alba and S. rotundifolius var. nigra), var. III (P. esculentus var. "Riyom").