Sugarcane (Saccharum spp.) is a globally important crop for sugar and bioenergy production. However, genetic improvement through conventional breeding is constrained by long breeding cycles, low genetic gain, and considerable operational complexity arising from its highly allopolyploid and aneuploid genome. With the increasing global demand for sustainable food and renewable energy, sugarcane breeding programs must accelerate the development of high-yielding, stress-tolerant cultivars through the integration of advanced biotechnological tools with traditional breeding approaches. Recent advances in genetic engineering, genomic selection (GS), and high-throughput omics technologies, including genomics, transcriptomics, proteomics, metabolomics, and phenomics, have substantially enhanced the efficiency of trait improvement related to growth, development, yield, and stress resilience. The integration of multi-omics data enables the dissection of regulatory networks linking genotype to phenotype, improves predictive accuracy, and provides deeper insights into the molecular mechanisms underlying complex traits. These integrative approaches support more informed selection decisions and accelerate genetic gain in sugarcane breeding programs. This review synthesizes recent technological developments and their practical applications in sugarcane improvement. It highlights the strategic implementation of transgenic and genome-editing technologies, genomic selection, and multi-omics integration to enhance yield potential and resistance to biotic and abiotic stresses, thereby contributing to sustainable sugarcane production and global food and bioenergy security.

The hill tribes of northern Thailand comprise nine officially recognized groups: the Austroasiatic-speaking (AA) Khmu, Htin and Lawa; the Hmong-Mien-speaking (HM) IuMien and Hmong; and the Sino-Tibetan-speaking (ST) Akha, Karen, Lahu and Lisu. Except the Lawa, the rest of the hill tribes migrated into their present habitats only very recently. The Thai hill tribes were of much interest to research groups focusing on study of cultural and genetic variation because of their unique languages and cultures. So far, there have been several genetic studies of the Thai hill tribes. However, complete forensic microsatellite database of the Thai hill tribes is still lacking. To construct such database, we newly generated 654 genotypes of 15 microsatellites commonly used in forensic investigation that belong to all the nine hill tribes and also non-hill tribe highlanders from northern Thailand. We also combined 329 genotypes from previous studies of northern Thai populations bringing to a total of 983 genotypes, which were then subjected to genetic structure and population relationships analyses. Our overall results indicated homogenous genetic structure within the HM- and Tai-Kadai (TK)-speaking groups, large genetic divergence of the HM-speaking Hmong but not IuMien from the other Thai groups, and genetic heterogeneity within the ST- and AA-speaking groups, reflecting different population interactions and admixtures. In addition to establishing genetic relationships within and among these populations, our finding, which provides a more complete picture of the forensic microsatellite database of the multiple Thai highland dwellers, would not only serve to expand and strengthen forensic investigation in Thailand, but would also benefit its neighboring countries of Laos and Myanmar, from which many of the Thai hill tribes originated and where large populations of these ethnic groups still reside.

Flowering often perturbs carbon allocation in sugarcane, yet its transcriptomic–metabolomic basis remains unclear. We profiled two contrasting cultivars, Gui Tang 16-3285 (sugar increases during flowering) and Gui Tang 44 (sugar decreases), sampling apical tissues at five stages (Non-spikelet-bearing stage (NSB), Early booting stage (ESB), Late booting stage (LSB), Tasseling stage (TS), and Flowering stage (FS)). RNA-seq and untargeted LC–MS revealed a strong stage/genotype structure (PCA) with high reproducibility. Pairwise contrasts (FS vs. earlier stages) and time series clustering (Mfuzz) showed extensive, stage-resolved reprogramming with small cross-cultivar overlaps. GO/KEGG indicated that GT16 is enriched for central carbon processes and glucose response, whereas GT44 favors cell-wall remodeling (xylan/xyloglucan), amino/nucleotide sugar, and phenylpropanoid pathways. Integrated analysis identified opposing temporal features across omics layers: in GT16, late-rising metabolites—including sedoheptulose—were consistent with enhanced pentose phosphate/Calvin coupling that regenerates fructose-6-phosphate for sucrose biosynthesis; in GT44, early activation of wall and secondary sinks, together with trehalose/(trehalose-6-phosphate) T6P signatures, paralleled declining soluble sugars. Across cultivars we resolved 11 and 18 genes in reciprocal opposite-trend sets (most with clear temporal order) and eight vs. five metabolites with mirrored dynamics, nominating actionable biomarkers (e.g., sedoheptulose/S7P) and regulatory nodes. These results provide a mechanistic framework linking flowering stage to carbon partitioning and suggest practical levers—timing growth moderation/ripeners, prioritizing sucrose phosphate synthase/Sucrose Phosphate Phosphatase, tempering wall flux, to sustain sucrose during reproductive development and inform breeding for high-sugar, flowering-resilient ideotypes.