[Construction and Driving Factors Analysis of a Machine Learning-based Prediction Model for Net Carbon Sink in Chinese Agriculture].
中国農業における正味炭素吸収源の機械学習ベース予測モデルの構築と駆動要因分析 (AI 翻訳)
Xiang-Bo Tang, You-Wei Huang, Han Su
🤖 gxceed AI 要約
日本語
中国農業の正味炭素吸収源を予測する機械学習モデルを構築し、駆動要因を分析。有効灌漑面積が最も重要な要因で、炭素吸収・土壌炭素吸収源に影響。政府の炭素排出削減計画に示唆を与える。
English
This study constructs a machine learning-based prediction model for net carbon sink in Chinese agriculture and analyzes driving factors. Results show that effective irrigated area is the most significant factor, affecting crop carbon absorption and soil carbon sinks. Provides a new method for prediction and policy recommendations for carbon emission reduction and sequestration.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
中国農業に特化しているが、日本農業の炭素吸収源予測にも応用可能な手法。SSBJや日本の農業分野のGX戦略に関連。
In the global GX context
Although focused on Chinese agriculture, the ML methodology for predicting net carbon sinks is globally applicable. It contributes to agricultural climate mitigation strategies and aligns with global frameworks like TCFD and ISSB for land-use emissions.
👥 読者別の含意
🔬研究者:Researchers in agricultural carbon accounting and ML applications can adopt the methodology for similar studies.
🏢実務担当者:Agricultural companies and carbon offset project developers can use the model for carbon sink estimation.
🏛政策担当者:Governments can utilize the results to formulate agricultural emission reduction and sequestration policies.
📄 Abstract（原文）
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.
🔗 Provenance — このレコードを発見したソース
- openalex https://pubmed.ncbi.nlm.nih.gov/42336404first seen 2026-06-26 05:08:25
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