Compost maturity screening supports safe land application and organic waste recycling, but germination index (GI) assays are not always available for rapid process assessment. This study performed a secondary GI-based maturity classification reconstruction using a published Nature Food composting dataset. From this source, 184 observations from 24 manure-based composting batch trajectories across five feedstock domains were retained when GI and routine physicochemical variables were available. GI values were converted into three maturity stages and a binary mature/non-mature endpoint, while the GI itself was excluded from model inputs. Logistic regression, random forest, and extra trees models were evaluated under random split, batch-aware group split, and leave-one-feedstock-domain-out validation. Random and group splits showed stronger apparent performance than cross-feedstock validation, indicating sensitivity to feedstock-domain transfer. In binary classification, the area under the receiver operating characteristic curve (ROC-AUC) remained relatively high in several model–domain combinations, whereas mature-class F1 declined, revealing a discrimination decision gap under default thresholds. Training-domain threshold calibration partially improved mature-class detection without using the held-out feedstock domain for threshold selection. These results support feedstock-aware validation and calibrated decision thresholds for sustainable compost maturity screening.

The microbial community plays a crucial role in plant health and sustainable agricultural development by influencing plant physiology and development. This study aimed to explore the biocontrol potential of Bacillus subtilis A9, an endophytic bacterium isolated from Morchella sextelata, against rot disease caused by Lecanicillium aphanocladii. Metagenomic and metabolomic analyses were conducted on Morchella sextelata samples sprayed with B. subtilis A9 and a control group sprayed with LB medium. Metagenomic sequencing revealed that B. subtilis A9 significantly altered the microbial community structure and functional composition of Morchella sextelata, enriching genes related to biofilm formation, arginine and proline metabolism, and sulfur metabolism. Metabolomic analysis indicated significant upregulation of stress-resistant metabolites such as L-proline, ketoleucine, and pelargonic acid. Integrated multi-omics analysis demonstrated a strong correlation between the microbial community structure and the metabolomic profile, suggesting that B. subtilis A9 may be related to the disease-resistance response in the Morchella sextelata microecosystem. These findings provide a theoretical basis for the biological control of Morchella sextelata rot disease and support the development of green biocontrol strategies.