生物炭改性堆肥成熟度综合评价框架

IF 9.7 1区 环境科学与生态学 Q1 AGRICULTURAL ENGINEERING
Jianmei Zou , Yihao Hua , Yushu Cheng , Lingyue Zhang , Huichun Zhang , Fei Shen
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引用次数: 0

摘要

建立了一个结合机器学习和加权技术的预测框架,以解决生物炭改性堆肥成熟度评估的不一致性。结果表明,该非线性模型具有较好的堆肥成熟度预测精度。具体而言,梯度增强(GB)、额外树(ET,用于GI和NO3—N)和极端梯度增强(XGB)分别在C/N比(0.84)、GI(0.64)、NO3—N(0.77)和NH4+-N(0.81)上获得了最高的R2值。SHAP分析发现,堆肥过程参数如水分含量(MC_P)、温度(TEMP_P)和pH (pH_P)是酶活性和微生物演为的关键驱动因素,对成熟度有显著影响。通过余弦相似度和实际堆肥试验验证了模型的适用性和预测能力。基于加权预测指标的综合成熟度评分强调GI是最具影响力的因素(47.62%)。该框架通过预测准确性和系统评估,增强了智能堆肥、更安全的农业和环境管理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Comprehensive evaluation framework for compost maturity with biochar amendment

Comprehensive evaluation framework for compost maturity with biochar amendment
A predictive framework combining machine learning and weighting techniques was established to resolve inconsistencies in maturity evaluation of biochar-amended composting. The results indicated that the nonlinear model showed superior compost maturity prediction accuracy. Specifically, Gradient boosting (GB), extra trees (ET, used for both GI and NO3-N), and extreme gradient boosting (XGB) achieved the highest R2 values for C/N ratio (0.84), GI (0.64), NO3-N (0.77), and NH4+-N (0.81), respectively. SHAP analysis identified composting process parameters such as moisture content (MC_P), temperature (TEMP_P), and pH (pH_P) as key drivers of enzymatic activity and microbial succession, significantly affecting maturity. The model’s applicability and predictive capability were validated through cosine similarity and real-world composting experiments. An integrated maturity score, based on weighted predicted indicators, highlighted GI as the most influential factor (47.62 %). This framework enhances intelligent composting, safer agriculture, and environmental management through predictive accuracy and systematic evaluation.
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来源期刊
Bioresource Technology
Bioresource Technology 工程技术-能源与燃料
CiteScore
20.80
自引率
19.30%
发文量
2013
审稿时长
12 days
期刊介绍: Bioresource Technology publishes original articles, review articles, case studies, and short communications covering the fundamentals, applications, and management of bioresource technology. The journal seeks to advance and disseminate knowledge across various areas related to biomass, biological waste treatment, bioenergy, biotransformations, bioresource systems analysis, and associated conversion or production technologies. Topics include: • Biofuels: liquid and gaseous biofuels production, modeling and economics • Bioprocesses and bioproducts: biocatalysis and fermentations • Biomass and feedstocks utilization: bioconversion of agro-industrial residues • Environmental protection: biological waste treatment • Thermochemical conversion of biomass: combustion, pyrolysis, gasification, catalysis.
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