Sorghum is a C4 crop that has substantial food, fodder, and bioenergy implications globally; however, the genetic basis of cultivated accessions is limited. Thus, current investigation assessed the morphological diversity among fifty exotic USDA sorghum germplasm and performed a preliminary SSR-based assessment of five selected genotypes. Biomass-related parameters were recorded from a replicated field experiment, showed substantial variation in plant height (PH), days to flowering, fresh weight (FW) and dry weight (DW), germination (
Efficient irrigation management is crucial for improving sugarcane productivity and profitability under water-limited conditions. However, suitable lateral depth and emitter spacing for subsurface drip irrigation (SSDI) in paired-row trench-planted sugarcane under subtropical conditions are not well established. This research article presents findings from a comprehensive two-year field study conducted in Agro-climatic Zone IV of Indian Punjab during 2022–2023 (plant crop) and 2023–2024 (ratoon crop). The study primarily investigated the growth, productivity, and economics of paired-row trench (30–30:120 cm)-planted spring sugarcane and its single ratoon under varying combinations of lateral depth, emitter spacing, and irrigation schedules SSDI. The experiment was laid out in a split-plot design, including three factors: lateral depths (20 cm, 25 cm, and 30 cm), emitter spacings (20 cm, 30 cm, and 40 cm), and irrigation schedules (80
Sugarcane bagasse (SCB), an abundant agricultural residue, is a promising feedstock for second-generation bioethanol, a sustainable biofuel of increasing relevance amid global energy challenges. Biological pretreatment using fungi is eco-friendly, economical, and less energy-intensive compared to physicochemical methods, but is constrained by long delignification times. In this study, a novel process intensification strategy was evaluated using the white rot fungus Phanerochaete chrysosporium. Ligninolytic enzyme production stimulators, manganese sulphate (30 mM) and copper sulphate (30 mM), were continuously supplemented for 1–4 days following fungal growth initiation. Continuous feeding of CuSO4 resulted in a maximum delignification of 18.4
The period from 2024 to 2026 witnessed an unprecedented genomic revolution in sugarcane, with four landmark studies transforming our understanding of Saccharum genome architecture and diversity. The polyploid reference genome of hybrid cultivar R570 (Healey et al. 2024), the chromosomal-scale assembly of hybrid cultivar ZZ1 (Bao et al. 2024), the first fully haplotype-phased genome of foundational cultivar POJ2878 (Wang et al. 2026a), and the first multiscale graph-based pangenome across four Saccharum-related species (Huang et al. 2026) together established that no single-reference genome can adequately represent a crop with 10–12 chromosome sets, variable chromosome numbers (100–130), and extraordinary genetic complexity arising from interspecific hybridization. High-throughput sequencing has yielded multiple genome assemblies from different sugarcane cultivars, revealing extensive genomic structural variations, such as copy number variations (CNVs) and presence/absence variations (PAVs), that play critical roles in agronomic traits, stress responses, and breeding potential. Pangenome approaches are essential for comprehensively capturing this diversity. The Saccharum graph pangenome, integrating nine assemblies, captured approximately 82
Cold stress is a major constraint for sugarcane production, limiting yield and geographic distribution. This study establishes a proof-of-concept framework for characterising physiological responses related to cold tolerance by integrating Vis–NIR reflectance spectroscopy with machine learning. Three sugarcane varieties with contrasting cold tolerance (GT28, GT49, ROC22) were subjected to controlled low-temperature stress (4 ± 2 °C for 24 h) and a subsequent 80-day recovery. The dynamic responses of leaf Soil and Plant Analysis Development (SPAD) values and point-based Vis–NIR reflectance spectra (400.79–1050.93 nm) were systematically tracked at four time points (0, 7, 40, and 80 days after stress). Distinct, time-dependent physiological and spectral response patterns among the varieties were identified, with the resilient GT28 exhibiting stability and relative recovery, whereas the sensitive ROC22 showed severe fluctuations and higher-than-control SPAD values during recovery. Correlation analysis and three feature selection algorithms (LASSO, SPA, and RFECV) consistently identified a red-edge sensitive interval ( 723–732 nm) as the most negatively correlated with SPAD (r = − 0.786). By evaluating nine model combinations plus benchmark methods (PLSR, MLR, spectral indices), the Multilayer Perceptron (MLP) model coupled with LASSO feature selection delivered the best performance among the evaluated methods, achieving a test R2 of 0.830 and RMSE of 2.231. This study indicates that the efficacy of a “feature selection + machine learning” strategy can be applied for precise SPAD estimation in sugarcane. It demonstrates potential as a high-throughput phenotyping approach under controlled conditions and provides a foundation for developing portable field-monitoring devices based on the identified diagnostic wavelengths. However, further validation under diverse field conditions and across a wider range of genotypes is necessary to establish its reliability and practical applicability.
