← 論文一覧に戻る

Multivariable Analysis of the Carbon Footprint of a Branded Beef Supply Chain Using Individual Animal Data and Carcass Characteristics

個体データと枝肉特性を用いたブランド牛肉サプライチェーンの炭素フットプリントの多変量解析 (AI 翻訳)

Riley O’Shannessy, Stephen Wiedemann

Animals📚 査読済 / ジャーナル2026-08-11#サプライチェーン経営インパクト: 調達リスク対象セクター: agriculture
DOI: 10.3390/ani16162498
原典: https://doi.org/10.3390/ani16162498

🤖 gxceed AI 要約

日本語

本研究は、オーストラリア南部の牛肉サプライチェーンを対象に、個体レベルのデータを統合した初の大規模LCAを実施。200農場、514,922頭の個体データを用い、農場ゲートと加工ゲートのCFを算出。平均CFはそれぞれ11.7kg CO2-e/kg LW、24.1kg CO2-e/kg boxed beefで、地域や枝肉特性による差異を明らかにした。

English

This study conducts a large-scale LCA of a branded beef supply chain in southern Australia, integrating individual animal data for the first time. Using data from 200 farms and 514,922 cattle, it calculates farm gate and processor gate carbon footprints, revealing regional and carcass-based variations. Mean CFs were 11.7 kg CO2-e/kg LW and 24.1 kg CO2-e/kg boxed beef.

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

日本では、牛肉のカーボンフットプリント表示が進む中、個体データを活用した精緻な算定手法は、国産牛肉の差別化や輸出競争力強化に示唆を与える。また、サプライチェーン排出量算定の実践例として、Scope 3対応にも参考になる。

In the global GX context

This study provides a robust methodology for supply chain carbon footprinting using individual animal data, relevant to global efforts on Scope 3 accounting and product-level disclosure. It demonstrates how brand-level CF can be stratified, offering insights for companies responding to TCFD/ISSB and customer requests for verified emissions data.

👥 読者別の含意

🔬研究者:Provides a novel method for integrating individual animal data into LCA, enabling more granular CF analysis.

🏢実務担当者:Offers a practical approach for beef producers and processors to calculate and differentiate product CFs, useful for sustainability reporting and market access.

🏛政策担当者:Highlights the potential for data-driven CF benchmarking in agriculture, informing policies on emissions reduction and product labeling.

📄 Abstract（原文）

Globally, beef customers are seeking verified information regarding the carbon footprint (CF) of the products they buy. As a major supplier of premium grass-finished and natural grain beef supplying markets world-wide, JBS Southern Australia developed a certified Farm Assured (FA) program, launched in 2013, to provide quality beef from independently audited suppliers. This study conducted a life cycle assessment (LCA) with ‘cradle to farm gate’ and ‘cradle to processor gate’ boundaries, using two reference flows—(i) one kilogram (kg) of liveweight (LW) at the farm gate, and (ii) one kg of boxed beef at the processor gate—to assess the greenhouse gas (GHG) CF for beef produced in southern Australia. This study is the first to integrate individual animal carcass characteristics with brand level CF analysis at scale. This was achieved by developing a uniquely comprehensive dataset, with primary data supplied by 200 farms and individual animal data provided for 514,922 heads of cattle. The mean farm gate CF was 11.7 (standard deviation 0.4) kg carbon dioxide equivalent (CO2-e) kg−1 LW, and the mean boxed beef CF was 24.1 kg CO2-e kg−1 boxed beef. The study’s novel approach to data collection allowed for the CF to be stratified by region, carcass characteristics, farm of origin and product brand. Analysis revealed that the lowest farm-average and individual animal CFs were 29% and 48% lower than the supply chain average, respectively. These findings indicate that the CFs of beef produced from grass and natural grain-finished production systems in southern Australia were comparable or lower than the CFs of beef entering similar markets.

🔗 Provenance — このレコードを発見したソース

🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録（無料・3キーワードまで）。

gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。