Towards Real-Time Sustainable Post-Harvest Operations: Gate-to-Gate Life Cycle Assessment of Sensor-Informed Sweet Cherry Sorting and Packing in Greece
ギリシャにおけるセンサーを活用したスイートチェリーの選別・包装のリアルタイム持続可能な収穫後処理：ゲート・トゥ・ゲートLCA (AI 翻訳)
K. Spanos, Nikolaos Kladovasilakis, Charisios Achillas, Dimitrios Aidonis
🤖 gxceed AI 要約
日本語
本研究は、ギリシャのスイートチェリー選別・包装施設を対象に、ゲート・トゥ・ゲートLCAを実施。センサーによる高分解能データを用いて、気候変動影響を定量化し、包装材最適化、太陽光発電導入、水リサイクル向上などの対策をモデル化。組み合わせシナリオでGWP100を19%削減可能と示した。仮想センサーアーキテクチャにより、ほぼリアルタイムでの環境パフォーマンス監視が可能に。
English
This study performs a gate-to-gate LCA of a sweet cherry sorting and packing facility in Greece using high-resolution sensor data. It quantifies climate change impacts and models mitigation scenarios including packaging optimization, PV substitution, and water recirculation. Combined scenario reduces GWP100 by 19%. The proposed virtual sensor architecture enables near-real-time environmental monitoring and eco-efficiency management.
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
本論文は、ギリシャの事例だが、食品加工・選別工程のLCA手法は日本企業のサプライチェーン排出量算定に応用可能。太陽光発電や包装材最適化による削減対策は、日本の農業・食品セクターの脱炭素化に示唆を与える。
In the global GX context
Globally, this paper contributes to LCA methodology for post-harvest operations, providing sensor-based data collection and mitigation scenarios. It aligns with ISSB and CSRD requirements for supply chain emissions disclosure. The virtual sensor architecture offers a path to real-time LCA, supporting operational sustainability in agri-food globally.
👥 読者別の含意
🔬研究者:Provides a detailed gate-to-gate LCA with sensor data integration and mitigation scenario analysis for post-harvest agri-food systems.
🏢実務担当者:Offers actionable mitigation measures (packaging optimization, PV, water recirculation) with quantified CO2 reductions for cherry sorting/packing operations.
🏛政策担当者:Demonstrates the potential of sensor-informed LCA for monitoring and improving environmental performance in food supply chains, informing policy on data-driven sustainability.
📄 Abstract（原文）
This study presents a gate-to-gate life cycle assessment (LCA) of an industrial sweet cherry sorting and packing facility in Greece, directly addressing environmental sustainability in agri-food supply chains through data-driven impact quantification and improvement pathways in post-harvest operations. The assessment focuses on a gate-to-gate system boundary encompassing all processes inside the cherry sorting and packing facility, while upstream cherry production and downstream waste management are modeled and reported separately to provide system-level context. Core-stage hotspots are then analyzed in detail in the Results section, highlighting the dominant role of electricity use compared with packaging materials. The functional unit is defined as 1 kg of packed, market-ready cherries at the factory gate. Primary data are obtained from high-resolution, batch-level measurements of mass flows, energy use, water consumption, packaging materials and waste streams over a full processing season, structured as virtual sensor outputs. These sensor-informed operational data are combined with secondary life cycle inventory information from established databases to quantify climate change impacts and identify environmental hotspots across materials, energy, water, and waste, thereby delivering a quantified picture of environmental performance in the post-harvest stage. The results show that corrugated cardboard and associated packaging components are among the main contributors within the facility-level, gate-to-gate system, while the Core stage accounts for 28.43% of total GWP100. Upstream cherry production dominates the overall Upstream–Core–Downstream climate footprint with 70.61% of total impacts. Moreover, practical mitigation scenarios are modeled, including packaging optimization, partial substitution of grid electricity with photovoltaic generation, and increased water recirculation. Ιn the combined mitigation scenario, where packaging optimization, low-carbon electricity and improved water management are implemented simultaneously, total GWP100 decreases from 114,207.32 to 92,500.27 kg CO2-eq (−19.0%) relative to the baseline, providing actionable sustainability improvements for industry stakeholders and supporting Sustainable Development Goals (SDGs) related to climate action and resource efficiency. In addition, the proposed virtual sensor architecture and data workflow support continuous monitoring, eco-efficiency management and near-real-time LCA implementation in post-harvest agri-food systems, enabling operational sustainability.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3390/su18126097first seen 2026-07-06 04:44:02
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