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Sweet fig (M. acuminata cv. Sotoumon) is an economically important dessert banana in Benin, with high nutritional, medicinal, and cultural values. Nevertheless, its productivity and yield are threatened by biotic and abiotic stresses. Relevant knowledge of the genetic diversity of this economically important crop is essential for germplasm conservation and the development of breeding programs. However, very little is known about the genetic makeup of this cultivar in Benin. To advance the understanding of genetic diversity in sweet fig banana germplasm, a Genotype-By-Sequencing (GBS) was performed on a panel of 273 accessions collected in different phytogeographical zones of Benin. GBS generated 8,457 quality SNPs, of which 1992 were used for analysis after filtering. The results revealed a low diversity in the studied germplasm (He = 0.0162). Genetic differentiation was overall very low in the collection as suggested by the negative differentiation index (Fstg = -0.003). The Analysis of Molecular Variance (AMOVA) indicated that the variation between accessions within populations accounted for 83.8% of the total variation observed (P < 0.001). The analysis of population structure and neighbor-joining tree partitioned the germplasm into three clusters out of which a predominant major one contained 98.1% of all accessions. These findings demonstrate that current sweet fig banana genotypes shared a common genetic background, which made them vulnerable to biotic and abiotic stress. Therefore, broadening the genetic base of the crop while maintaining its quality attributes and improving yield performance is of paramount importance. Moreover, the large genetic group constitutes an asset for future genomic selection studies in the crop and can guide the profiling of its conservation strategies., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Capo-Chichi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Increasing production requires the development of high yielding cultivars adapted to various environments. Multi-environment trials (MET) remains the best approach to assess the performance of accessions across environments. The objective of this study was to select the best performing and stable accessions of sesame across different environments in Benin Republic. Nineteen sesame accessions were evaluated across eight environments using a randomized complete block design with four replicates. The accessions were evaluated for three traits: days to 50% flowering (D50F), thousand-seed weight (TSW), and seed yield (SY) during 2020 growing season. The stable and top-performing accessions across environments were determined using AMMI (Additive main effects and multiplicative interaction), GGE (Genotype main effect and genotype × environment interaction), and MTSI (Multi-trait stability index). AMMI analysis of variance showed a significant difference across environments for the three traits. The accessions were affected by environmental conditions for the three traits. The broad-sense heritability estimates were high (>0.60) for all the traits, indicating the improvement is achievable through selection. AMMI1 and AMMI2 biplots identified G10 and G13 as high seed yielding accessions adapted to environments E1, E2. The GGE biplot showed two mega-environments for TSW and three mega-environments for D50F and SY. For SY, G11 and G13 were the best accessions in the first mega-environment, G10 the best accession in the second mega-environment; G3 and G8 were the best accessions in the third mega-environment. AMMI and GGE analyses identified G10, G5, G12 as high seed yielding and stable accessions across environments. GGE biplot revealed that E1 and E2 were the most suitable environments for multi-location trials based on their discriminating ability and representativeness. MTSI indicated G10, G13, G19 as promising germplasm to be recommended for breeding program., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

C 4 photosynthesis has evolved multiple times in the angiosperms and typically involves alterations to the biochemistry, cell biology and development of leaves. One common modification found in C 4 plants compared with the ancestral C 3 state is an increase in vein density such that the leaf contains a larger proportion of bundle sheath cells. Recent findings indicate that there may be significant intraspecific variation in traits such as vein density in C 4 plants but to use such natural variation for trait-mapping, rapid phenotyping would be required. Here we report a high-throughput method to quantify vein density that leverages the bundle sheath-specific accumulation of starch found in C 4 species. Starch staining allowed high-contrast images to be acquired permitting image analysis with MATLAB- and Python-based programmes. The method works for dicotyledons and monocotolydons. We applied this method to Gynandropsis gynandra where significant variation in vein density was detected between natural accessions, and Zea mays where no variation was apparent in the genotypically diverse lines assessed. We anticipate this approach will be useful to map genes controlling vein density in C 4 species demonstrating natural variation for this trait., (© 2023 The Authors. Plant, Cell & Environment published by John Wiley & Sons Ltd.)