Against the background of increasing global soil salinity, exogenous salicylic acid (SA) and melatonin (MT) have attracted much attention for their potential in regulating plant stress tolerance and have become an important research direction for the development of green and sustainable agriculture. In this study, the alleviating effects of different concentrations of SA (100–900 μM) and MT (100–900 μM) on salt stress (50 mM NaCl) and their physiological mechanisms were systematically investigated using the Tianjin specialty rice, Xiaozhan rice, as the research object. The results showed that salt stress significantly inhibited the germination and seedling growth of the two varieties, in which the salt-sensitive variety Jinchuan No. 1 showed significantly higher decreases in root length, plant height, and biomass (54.7–69.1%) than the salt-tolerant variety Jindao 919 (4.0–28.9%). Exogenous SA and MT were effective in mitigating salt stress injury, but there were genotypic differences in their pathways of action. For the first time in japonica rice, the genotype specificity of the SA/MT response was clearly revealed: SA dominated the response of salt-tolerant varieties by enhancing antioxidant defences, whereas MT optimized the overall performance of the salt-sensitive varieties through scavenging of reactive oxygen species, and in addition, it was further determined that SA and MT exhibited optimal mitigating effects on both varieties in the 300–700 μM concentration range, showing the best mitigation effect for both varieties. This finding provides an important theoretical basis and technological paradigm for precision stress tolerance cultivation of saline rice, and the application of appropriate concentrations of SA/MT according to genotype specificity to reduce the dependence on agrochemicals is of practical value in promoting green and sustainable production in saline agriculture.

Salt stress severely impairs rice (Oryza sativa L.) germination and seedling establishment. Exogenous spermidine (Spd) has been shown to regulate stress tolerance in plants, but whether it acts during rice germination and seedling establishment under salt stress remains unclear. Here, rice seeds (cv. Jindao 919) were exposed to 75 mM NaCl with different Spd concentrations (0–1.4 mM), and physiological, biochemical, and transcriptomic responses were evaluated. The findings showed that salt stress had a pronounced inhibitory effect on both seed germination and seedling development. Exogenous Spd effectively alleviated these negative effects, with the most significant improvements observed at 1.0–1.2 mM: germination rate increased by 3.98–8.52%, seedling root length increased by 17.74–37.68%, soluble sugar content increased by 29.83–230%, and SOD and POD activities increased by 29.81–40.3% and 18.45–44.0%, respectively, while MDA content decreased by 36.28–40.3%. Further transcriptomic analysis identified a total of 1835 differentially expressed genes (DEGs). KEGG enrichment analysis revealed these genes were concentrated in key pathways including terpenoid biosynthesis, phenylpropanoid biosynthesis, and amino sugar and nucleotide sugar metabolism, thus alleviating the negative impact of salt stress on rice germination and seedling development. These pathways are closely related to gibberellin metabolism, lignin biosynthesis, and amino sugar metabolism, further revealing the regulatory role of Spd. Overall, 1.0–1.2 mM Spd was most effective in alleviating salt stress by synergistically regulating antioxidant defense, osmoregulation, and metabolic reprogramming, enhancing rice’s overall stress tolerance. This study provides theoretical guidance for precise regulation of Spd concentration to improve rice performance in saline-alkaline soils, and reveals the sustained promoting effects of Spd across various developmental stages of rice and its underlying molecular mechanisms.

Simultaneous improvement of grain yield, milling quality, and eating quality requires coordinated selection across correlated traits and assessment of whether line performance remains consistent across successive generations. Two segregating japonica rice populations, P1 (Jinchuan No. 1 × Jinyujing 22; 74 lines) and P2 (Koshihikari × Jinyujing 22; 45 lines), were evaluated in the F₄ and F₅ generations for grain yield and indicators of milling and eating quality. Multiple analytical approaches covering intergenerational trait variation, correlation analysis, radar charts, principal component analysis and two-dimensional comprehensive-consistency evaluation were used. Several eating-quality-related indicators showed significant correlations between the F₄ and F₅ generation-year observations, whereas grain yield showed no significant F₄–F₅ correlation in either population. Five P1 lines and eight P2 lines combined above-average composite performance with relatively high apparent F₄–F₅ intergenerational consistency. These lines represent candidates for subsequent validation in replicated multi-environment trials, and the results illustrate the potential value of jointly considering composite performance and apparent intergenerational consistency in early-generation rice selection.

UAV multispectral imagery can support rice yield estimation, but spectral–yield relationships may change with cultivar and planting density. We evaluated three japonica rice cultivars under five planting-density treatments in a split-plot experiment and collected UAV multispectral imagery on 13 dates. We examined five vegetation indices: NDVI, RVI, NDRE, OSAVI, and CLRE. Cultivar significantly affected grain yield and yield components. Planting density had no significant main effect, while the cultivar × density interaction was significant for grain yield. Spectral–yield correlations were strongest during 19–25 August, which broadly matched reproductive development based on field observations. NDRE and CLRE showed the most consistent associations. A four-index PLSR model using 19 August data achieved an outer-LOOCV R² of 0.773 and an RMSE of 530.28 kg ha⁻¹. Tuned RF gave comparable performance (R² = 0.783, RMSE = 518.60 kg ha⁻¹). Adjustment for cultivar, planting density, and block substantially reduced the pooled mid-August correlations. However, the four-index spectral set still improved prediction beyond cultivar, planting density, and their interaction. Grouped validation changed little when density levels or cultivar × density combinations were withheld, but performance declined sharply when an entire cultivar was excluded. These results show that mid-August UAV observations were informative in this experiment, but wider use will require validation across more cultivars, years, and sites.