The study aimed to evaluate the genetic diversity of 41 sweet sorghum genotypes from seven countries for key biofuel-related traits over two sorghum growing seasons (2020 and 2021) in a semi-arid Mediterranean environment. Genotypes were assessed for key bioethanol production traits such as fresh stalk yield (FSY), juice yield (JY), Brix, dry biomass yield (DBY), theoretical juice ethanol yield (JEY), theoretical lignocellulosic ethanol yield (LEY), theoretical total ethanol yield (TEY), as well as their potential for solid biofuel production, measured through bagasse ash, nitrogen, and moisture content. Significant variations were observed among genotypes across most traits, analyzed using analysis of variance, principal component analysis, and hierarchical cluster analysis, identifying DBY, LEY, and TEY as the primary contributors to overall genetic variation. Cluster analysis grouped the genotypes into five distinct clusters, highlighting the diversity in biofuel-related traits. The correlation analysis revealed significant positive relationships between traits such as FSY, DBY, and TEY, indicating that higher biomass production directly enhances ethanol output. Strong positive correlations between FSY and TEY underscore the importance of biomass yield in maximizing ethanol production. However, traits like bagasse ash and nitrogen contents, which were negatively correlated with JEY, LEY, and TEY, present challenges in improving biomass combustion quality. The study concludes that certain genotypes, particularly ‘Yellow Bonnet’ and ‘IS 3556’, exhibited strong potential for biofuel production in semi-arid Mediterranean climates where water scarcity and high temperature favor genotypes with high biomass and sugar yields. These genotypes demonstrated high JEYs, LEYs, and TEYs, suggesting their adaptability to the unique environmental stresses of this region, making them good candidates for sustainable biofuel production in similar climates.

Specific length amplified fragment sequencing (SLAF-seq) is a recently developed high-resolution strategy for the discovery of large-scale de novo genotyping of single nucleotide polymorphism (SNP) markers. In the present research, in order to facilitate genome-guided breeding in potato, this strategy was used to develop a large number of SNP markers and construct a high-density genetic linkage map for tetraploid potato. The genomic DNA extracted from 106 F₁ individuals derived from a cross between two tetraploid potato varieties YSP-4 × MIN-021 and their parents was used for high-throughput sequencing and SLAF library construction. A total of 556.71 Gb data, which contained 2269.98 million pair-end reads, were obtained after preprocessing. According to bioinformatics analysis, a total of 838,604 SLAF labels were developed, with an average sequencing depth of 26.14-fold for parents and 15.36-fold for offspring of each SLAF, respectively. In total, 113,473 polymorphic SLAFs were obtained, from which 7638 SLAFs were successfully classified into four segregation patterns. After filtering, a total of 7329 SNP markers were detected for genetic map construction. The final integrated linkage map of tetraploid potato included 3001 SNP markers on 12 linkage groups, and covered 1415.88 cM, with an average distance of 0.47 cM between adjacent markers. To our knowledge, the integrated map described herein has the best coverage of the potato genome and the highest marker density for tetraploid potato. This work provides a foundation for further quantitative trait loci (QTL) location, map-based gene cloning of important traits and marker-assisted selection (MAS) of potato.