Based on an integrated analysis, this study summarized the current status of soil quality in Yantai apple orchards, developed a multivariate regulation model for key soil physicochemical properties, and proposed optimized fertilization strategies to improve soil quality in the region. The study analyzed the physicochemical properties of the topsoil (0–30 cm) in 19 representative apple orchards across Yantai, including indicators like pH, organic matter (OM), major nutrient ions, and salinity indicators, using standardized measurements and multivariate statistical methods, including descriptive statistics analysis, frequency distribution analysis, canonical correlation analysis, stepwise regression equation analysis, and regression fit model analysis. The results demonstrated that in apple orchards across the Yantai region, reductions in pH were significantly mitigated under the combined increased OM and exchangeable calcium (Ca). Exchangeable potassium (EK) rose in response to the joint elevation of OM and available nitrogen (AN), and AN was also positively influenced by EK, while OM also exhibited a promotive effect on Olsen phosphorus (OP). Furthermore, Ca increased with higher pH. AN and EK jointly contributed to the increases in electrical conductivity (EC) and chloride ions (Cl), while elevated exchangeable sodium (Na) and soluble salts (SS) were primarily driven by EK. Accordingly, enhancing organic and calcium source fertilizers is recommended to boost OM and Ca levels, reduce acidification, and maintain EC within optimal limits. By primarily reducing potassium’s application, followed by nitrogen and phosphorus source fertilizers, the supply of macronutrients can be optimized, and the accumulation of Na, Cl, and SS can be controlled. Collectively, the combined analysis of soil quality status and the multivariate regulation model clarified the optimized fertilization strategies, thereby establishing a solid theoretical and practical foundation for recognizing the necessity of soil testing and formula fertilization, the urgency of improving soil quality, and the scientific rationale for nutrient input management in Yantai apple orchards.

This study aimed to evaluate the comprehensive effects of foliar fertilization on maize-related traits and to identify nutrient-related factors associated with yield variation. A single-site field experiment was conducted during the 2024 growing season using maize cultivar ‘Zhengdan 958’. Two fertilization treatments, conventional fertilization (CF) and conventional fertilization combined with foliar fertilization (OF), were applied, with each treatment consisting of three replicate plots. Thirty variables related to yield, yield components, plant nutrient status, and grain nutrient accumulation were measured and included in subsequent exploratory analyses. Analysis of variance (ANOVA) combined with exploratory multivariate statistical analyses was employed to evaluate treatment effects, examine statistical associations among measured variables, and develop the exploratory yield regression models. Compared with CF, OF significantly increased several yield component traits, including kernels per row, ear length, and grain weight per ear, with increases ranging from 9.8% to 20.5%. OF increased grain nitrogen and carbon accumulation by 17.8% and 26.8%, respectively, and increased maize yield, gross revenue and net profit by 20.3–20.5%. Exploratory multivariate statistical analyses indicated that foliar fertilization under conventional fertilization conditions significantly improved several maize yield-related traits. Grain nutrient accumulation, yield components, and yield and economic performance were all important variables that distinguished fertilization treatments and exhibited progressively increasing relative contributions. Further analyses indicated a hierarchical pattern of statistical associations among yield components, grain nutrient accumulation, and maize yield. Grain nitrogen, phosphorus, and carbon accumulation were nutrient-related variables showing statistical associations with maize yield, and their associations with yield were mainly mediated through key yield components. Among the evaluated nutrient variables, GNA showed a strong mathematically coupled statistical association with GY within the evaluated dataset. These findings provide new insights into the statistical relationships between nutrient accumulation and maize yield under foliar fertilization and may contribute to the optimization of nutrient management strategies in maize production.