基于机器学习的评估,在中国东部大豆-小麦轮换中的土壤有机碳动态
1School of Information Engineering, Liaoning Vocational College of Light Industry, Dalian, 116100, Liaoning, China. yu13478956885@163.com.
Scientific reports
|February 4, 2026
概括
在中国,大豆种植增加了土壤有机碳 (SOC),而小麦则减少了它. 农作物轮换显著影响土壤健康和碳捕获,提供了减缓气候变化的潜力.
科学领域:
- 农业科学 农业科学
- 土壤科学 土壤科学
- 环境科学 环境科学
背景情况:
- 土壤有机碳 (SOC) 对于农业生态系统的健康至关重要,影响生育能力,结构和作物产量.
- 了解SOC动态对于可持续农业和气候变化缓解至关重要.
研究的目的:
- 评估中国东部SOC库存的空间分布和动态.
- 评估大豆-小麦作物轮换在不同的环境条件下对SOC的影响.
主要方法:
- 利用先进的机器学习模型,特别是随机森林 (RF),用于准确的SOC预测.
- 在中国东部七个省份的两个土壤深度 (0-15厘米和15-30厘米) 收集了SOC数据.
- 分析了环境因素如NDVI,温度季节性和LS因素对SOC变化的影响.
主要成果:
- 随机森林模型在预测SOC方面取得了很高的准确性 (R2 = 0.89对于0-15厘米深度).
- 观察到大豆种植后显著的SOC增加,小麦收获后减少.
- 鉴定了SOC动态的区域差异,受环境因素和作物生物质的影响.
结论:
- 由于较高的生物质和根系,大豆种植对SOC产生了积极的影响.
- 小麦种植有助于SOC枯竭,需要谨慎的管理策略.
- 包括大豆在内的作物轮换显示出改善土壤健康和农业系统中碳封存的前景.
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