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Simple Summary: High salinity poses a threat to crop growth and yield. Increasing evidence suggests that environmentally friendly plant growth-promoting rhizobacteria (PGPRs) can mitigate the negative impacts of salt stress by modulating various molecular, biochemical, and physiological processes. In the present study, Microbacterium azadirachtae strain CNUC13 was isolated from maize rhizosphere soil. This strain tolerated up to 1000 mM NaCl and 30% PEG 6000 and showed growth-promoting traits like phosphate solubilization and siderophore and indole-acetic acid (IAA) production. The impacts of M. azadirachtae strain CNUC13 on maize (Zea mays L.) germination, growth, and development with salinity were further examined. The results showed that seed priming with M. azadirachtae CNUC13 strain could protect maize from salt stress by modulating plant growth parameters, photosynthetic efficiency, lipid peroxidation, reactive oxygen species, and antioxidant enzyme activities. This is the first study of M. azadirachtae on plant growth enhancement and salt stress tolerance in vivo, and the results indicated the vital contribution of M. azadirachtae CNUC13 in alleviating the adverse effects of salinity on maize seedlings. Soil salinization is one of the leading threats to global ecosystems, food security, and crop production. Plant growth-promoting rhizobacteria (PGPRs) are potential bioinoculants that offer an alternative eco-friendly agricultural approach to enhance crop productivity from salt-deteriorating lands. The current work presents bacterial strain CNUC13 from maize rhizosphere soil that exerted several PGPR traits and abiotic stress tolerance. The strain tolerated up to 1000 mM NaCl and 30% polyethylene glycol (PEG) 6000 and showed plant growth-promoting (PGP) traits, including the production of indole-3-acetic acid (IAA) and siderophore as well as phosphate solubilization. Phylogenetic analysis revealed that strain CNUC13 was Microbacterium azadirachtae. Maize plants exposed to high salinity exhibited osmotic and oxidative stresses, inhibition of seed germination, plant growth, and reduction in photosynthetic pigments. However, maize seedlings inoculated with strain CNUC13 resulted in significantly improved germination rates and seedling growth under the salt-stressed condition. Specifically, compared with the untreated control group, CNUC13-treated seedlings exhibited increased biomass, including fresh weight and root system proliferation. CNUC13 treatment also enhanced photosynthetic pigments (chlorophyll and carotenoids), reduced the accumulation of osmotic (proline) and oxidative (hydrogen peroxide and malondialdehyde) stress indicators, and positively influenced the activities of antioxidant enzymes (catalase, superoxide dismutase, and peroxidase). As a result, CNUC13 treatment alleviated oxidative stress and promoted salt tolerance in maize. Overall, this study demonstrates that M. azadirachtae CNUC13 significantly enhances the growth of salt-stressed maize seedlings by improving photosynthetic efficiency, osmotic regulators, oxidative stress resilience, and antioxidant enzyme activity. These findings emphasize the potential of utilizing M. azadirachtae CNUC13 as a bioinoculant to enhance salt stress tolerance in maize, providing an environmentally friendly approach to mitigate the negative effects of salinity and promote sustainable agriculture. [ABSTRACT FROM AUTHOR]

Global climate change is a serious threat to food and energy security. Crop growth modelling is an important tool for simulating crop food production and assisting in decision making. Planting date is one of the important model parameters. Larger-scale spatial distribution with high accuracy for planting dates is essential for the widespread application of crop growth models. In this study, a planting date prediction method based on environmental similarity was developed in accordance with the third law of geography. Spring maize planting date observations from 124 agricultural meteorological experiment stations in China over the years 1992–2010 were used as the data source. Samples spanning from 1992 to 2009 were allocated as training data, while samples from 2010 constituted the independent validation set. The results indicated that the root mean square error (RMSE) for spring maize planting date based on environmental similarity was 10 days, which is better than that of multiple regression analysis (RMSE = 13 days) in 2010. Additionally, when applied at varying scales, the accuracy of national-scale prediction was better than that of regional-scale prediction in areas with large differences in planting dates. Consequently, the method based on environmental similarity can effectively and accurately estimate planting date parameters at multiple scales and provide reasonable parameter support for large-scale crop growth modelling. [ABSTRACT FROM AUTHOR]