[Construction and Driving Factors Analysis of a Machine Learning-based Prediction Model for Net Carbon Sink in Chinese Agriculture].
摘要
and strong when it was greater than this value. ④ The 3D PDP visualization of the above three driving factors on agricultural net carbon sinks showed that the effective irrigated area had the most significant impact on agricultural net carbon sinks， almost dominating the entire process. The underlying reason is that the intensity and method of irrigation can significantly affect the potential of crop carbon absorption and soil carbon sinks. The research results provide a new method and novel approach for the prediction of agricultural net carbon sinks， also providing decision-making references for the government and relevant departments in formulating agricultural carbon emission reduction and sequestration plans and policies.
引用本文（GB/T 7714）
Xiang-Bo Tang, You-Wei Huang, Han Su. [Construction and Driving Factors Analysis of a Machine Learning-based Prediction Model for Net Carbon Sink in Chinese Agriculture].[J]. PubMed, 2026.
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