Keywords
Soil quality
Principal Component Analysis
Multiple regression analysis.
How to Cite
Abstract
The vertical heterogeneity of soil nutrients significantly influences rice growth; however, its effects on leaf and stem development in the Liaohe Delta remain unclear. This study analyzed 35 rice fields in Panjin, China, and measured soil physicochemical properties (0–20 cm, 20–40 cm, and 40–60 cm) as well as rice morphological/physiological indicators (plant height, leaf length, stem thickness, and soluble sugar/protein). Principal component analysis (PCA) revealed three dominant components, which accounted for 75.97% of the variation, with leaf length, soluble sugar, and soluble proteins as key drivers. Multivariate regression revealed that 0–20 cm soil nitrogen (N) and phosphorus (P) promoted leaf growth and photosynthetic efficiency, whereas the 20–40 cm soil pH and water content regulated soluble sugar accumulation. Deep-layer (40–60 cm) organic matter and N improved the root environment and enhanced the stem’s mechanical strength. The study establishes a "surface-middle-deep" correlation model, demonstrating that stratified soil nutrients differentially affect rice growth. These findings provide a targeted fertilization strategy"surface layer for leaf promotion, deep layer for stem strengthening"to optimize nutrient management and improve rice productivity in the Liaohe Delta.
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