Ruixin Bi

To evaluate how composted agricultural and forestry organic materials function as components of horticultural growing media, a pot experiment was conducted with chrysanthemum (Chrysanthemum morifolium Ramat.) grown in a cinnamon-soil-based medium. The composted material, produced from chestnut shells, chicken manure, and spent mushroom substrate, was incorporated at 0%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, and 50% (v/v). Water-extractable dissolved organic matter (WE-DOM) was characterized by excitation-emission matrix fluorescence spectroscopy coupled with parallel factor analysis (EEM-PARAFAC), together with the fluorescence index (FI), biological index (BIX), humification index (HIX), and fluorescence regional integration (FRI). Growing-medium physicochemical properties, chrysanthemum traits, and an entropy-weighted comprehensive evaluation were also assessed. Compost amendment increased soil organic matter (SOM), dissolved organic carbon (DOC), total nitrogen, and total phosphorus, lowered pH, and was associated with improved porosity and water-retention characteristics. FI ranged from 1.810 to 2.371 and exceeded 1.9 at amendment rates of 30–35%, suggesting a greater contribution from microbially derived DOM. BIX, HIX, and P_V,n/P_III,n were generally higher in amended treatments than in the control, although their responses were non-monotonic across amendment rates, suggesting greater contributions from recently produced DOM and stronger humification-related fluorescence signals. EEM-PARAFAC resolved five fluorescent components. C1, C2, C3, and C5 were predominantly humic-like, whereas C4 displayed both protein-like and humic-like features. With increasing amendment rate, the relative contributions of C1–C4 generally increased, whereas that of C5 declined, suggesting a shift from the native soil fluorescence profile toward a more complex DOM composition influenced by compost inputs and subsequent biological transformation. Chrysanthemum height, stem diameter, flower number, and biomass were generally more favorable at amendment rates of 30–40%. The entropy-weighted evaluation yielded the highest overall response score at 30%, while the 35% treatment also maintained a high score. Considering WE-DOM fluorescence characteristics, growing-medium properties, and plant performance together, a volumetric amendment rate of 30–35% represents a relatively favorable range for the tested composted material under the present pot-experiment conditions.

The Northeast black soil region is a major grain-producing area in China, where county-scale assessment of topsoil quality is essential for soil conservation and provides a potential indicator framework for regional soil quality monitoring. In this study, 500 composite cultivated-layer samples were collected from dryland croplands in Keshan County, Heilongjiang Province. Soil physical properties, basic chemical properties, and macro-, secondary, and micronutrient contents were measured to establish a total data set (TDS). Three hierarchical total data sets (TDS1, TDS2, and TDS3) were established from the original TDS according to the progressive incorporation of soil physical properties, basic chemical properties, macronutrients, secondary nutrients, and micronutrients. Within each hierarchical TDS, key indicators were selected using random forest (RF), mutual information (MI), principal component analysis (PCA), and minimum spanning tree (Tree) methods to construct algorithm-specific minimum data sets (MDSs). TDS1 included soil physical properties, basic chemical properties, and macronutrients; TDS2 further incorporated secondary nutrients; and TDS3 additionally included micronutrients to represent progressively comprehensive soil nutrient information. The soils exhibited considerable soil organic matter and cation exchange capacity, with mean values of 51.45 g kg⁻¹ and 34.85 cmolc kg⁻¹, respectively, and a mean pH of 6.04. Across the four algorithms, commonly retained indicators included SOM, TN, pH, CEC, and Silt, while nutrient-related indicators such as AP, AK, S, Zn, and Fe were additionally selected under different hierarchical MDSs, reflecting the importance of multi-nutrient information in soil quality characterization. Available phosphorus, available potassium, sulfur, and zinc showed greater spatial variability than basic physicochemical properties. The four algorithms differed in indicator selection, reflecting their distinct sensitivities to linear variation, information gain, multilevel contributions, and network structure. RF_MDS1 showed the highest agreement with the TDS (R² = 0.924), indicating its strong capability in preserving overall soil quality information using a simplified indicator set. RF_MDS3 maintained a high consistency with the TDS (R² = 0.836) while incorporating additional secondary nutrients and micronutrients. Therefore, RF_MDS3 was considered a more comprehensive MDS framework when multi-nutrient representation and potential nutrient constraint identification were prioritized, whereas RF_MDS1 remained an efficient option for simplified soil quality assessment. This framework may provide a transferable approach for soil quality assessment and nutrient management in comparable black-soil regions and dryland farming systems.