The improvement of sucrose yield in sugarcane is impeded by the crop’s complex polyploid genome and slow progress in breeding. To clarify how arginine (Arg) regulates sugar metabolism and identify key genes associated with sucrose transport and accumulation in sugarcane, a screening experiment was performed by spraying L-arginine hydrochloride on the leaves and leaf sheaths of three sugarcane varieties (YZ05-51, YZ08-1609, and YT93-159), which differ in growth vigor, leaf morphology and other phenotypic traits. YZ05-51 exhibited the most prominent sugar-increasing effect, and subsequent optimization experiments on its leaf sheaths revealed that 20 g/mu L-arginine hydrochloride at pH 7.0 was optimal, significantly enhancing stem sucrose content. Transcriptomic analysis revealed the upregulation of genes related to sucrose synthesis and transport, with candidate genes enriched in pathways such as starch-sucrose metabolism, glycolysis/gluconeogenesis, and ATP-binding cassette (ABC) transporters. Metabolomic analysis detected 32 sugar metabolites across three categories, of which 24 were differentially abundant (e.g., glucose, galactose, fructose, and mannose). Integrated multi-omics analysis identified key regulatory genes, including SBEs and TPS1 (sucrose synthesis and carbon flux regulation), RBSK, α-amylases, GH28 (starch breakdown, glycolysis, and sugar mobilization), ABC transporters, GTs, and TIM10/TIM12 (sucrose transporter). Collectively, these analyses demonstrate enhanced activity of genes and metabolites involved in sucrose synthesis/transport in leaf sheaths, accompanied by reduced synthesis of other monosaccharides and oligosaccharides. Vigorously metabolizing leaf sheaths is more conducive to sucrose transport. This study provides valuable insights into the molecular mechanisms underlying Arg-mediated sucrose accumulation specifically in the sugarcane YZ05-51 sugarcane, highlighting its critical regulatory roles.

Selecting superior families at the seedling stage is crucial for accelerating genetic gain in sugarcane, yet systematic comparisons of selection methods remain limited. This study evaluated seven selection strategies: phenotypic check-based selection (Pheno), a three-trait combined index (CI3), Best Linear Unbiased Prediction (BLUP), Best Linear Unbiased Estimation (BLUE), tiered family selection (Tiered), logistic regression (LASSO), and the Multi-Trait Family Ideotype Distance Index (MFIDI). The experiment followed an augmented block design with four blocks, two check varieties, and included 125 test families comprising 10,955 seedlings. Using a combined index of standardized cane and sugar yields, families were classified as elite (top 20%), moderate (60%), and weak (bottom 20%). BLUP and BLUE rankings were consistent (Spearman’s ρ > 0.95, TCI = 88%, Jaccard = 0.79). Elite families showed median index values of 0.90 (BLUP) and 0.88 (BLUE) with wide interquartile ranges, whereas weak families had medians of −0.70 with narrow ranges. LASSO achieved excellent predictive performance: AUC = 0.95, accuracy = 0.92, sensitivity = 0.90, specificity = 0.94, identifying cane yield, sugar yield, and millable cane as key drivers. Agreement for inferior families was lower across methods (BCI ≤ 68%). BLUP with a multi-trait index proved most effective for discriminating elite families. Families F31 and F71 consistently ranked top. Combining selection approaches with agreement indices improves early-stage decisions for family selection in sugarcane breeding.