Machine learning-based life cycle assessment for environmental sustainability optimization of a food supply chain.

Effective resource allocation in the agri-food sector is essential in mitigating environmental impacts and moving toward circular food supply chains. The potential of integrating life cycle assessment (LCA) with machine learning has been highlighted in recent studies. This hybrid framework is valuable not only for assessing food supply chains but also for improving them toward a more sustainable system. Yet, an essential step in the optimization process is defining the optimization boundaries, or minimum and maximum quantities for the variables. Usually, the boundaries for optimization variables in these studies are obtained from the minimum and maximum values found through interviews and surveys. A deviation in these ranges can impact the final optimization results. To address this issue, this study applies the Delphi method for identifying variable optimization boundaries. A hybrid environmental assessment framework linking LCA, multilayer perceptron artificial neural network, the Delphi method, and genetic algorithm was used for optimizing the pomegranate production system. The results indicated that the suggested framework holds promise for achieving substantial mitigation in environmental impacts (potential reduction of global warming by 46%) within the explored case study. Inclusion of the Delphi method for variable boundary determination brings novelty to the resource allocation optimization process in the agri-food sector. Integr Environ Assess Manag 2024;00:1-11. © 2024 SETAC.

Life cycle assessment of edible insects (Protaetia brevitarsis seulensis larvae) as a future protein and fat source.

Because it is important to develop new sustainable sources of edible protein, insects have been recommended as a new protein source. This study applied Life Cycle Assessment (LCA) to investigate the environmental impact of small-scale edible insect production unit in South Korea. IMPACT 2002 + was applied as the baseline impact assessment (IA) methodology. The CML-IA baseline, EDIP 2003, EDP 2013, ILCD 2011 Midpoint, and ReCiPe midpoint IA methodologies were also used for LCIA methodology sensitivity analysis. The protein, fat contents, and fatty acid profile of the investigated insect (Protaetia brevitarsis seulensis larvae) were analyzed to determine its potential food application. The results revealed that the studied edible insect production system has beneficial environmental effects on various impact categories (ICs), i.e., land occupation, mineral extraction, aquatic and terrestrial ecotoxicity, due to utilization of bio-waste to feed insects. This food production system can mitigate the negative environmental effects of those ICs, but has negative environmental impact on some other ICs such as global warming potential. By managing the consumption of various inputs, edible insects can become an environmentally efficient food production system for human nutrition.

Life cycle assessment and energy comparison of aseptic ohmic heating and appertization of chopped tomatoes with juice.

The energy balance and life cycle assessment (LCA) of ohmic heating and appertization systems for processing of chopped tomatoes with juice (CTwJ) were evaluated. The data included in the study, such as processing conditions, energy consumption, and water use, were experimentally collected. The functional unit was considered to be 1 kg of packaged CTwJ. Six LCA impact assessment methodologies were evaluated for uncertainty analysis of selection of the impact assessment methodology. The energy requirement evaluation showed the highest energy consumption for appertization (156 kWh/t of product). The energy saving of the ohmic heating line compared to the appertization line is 102 kWh/t of the product (or 65% energy saving). The energy efficiencies of the appertization and ohmic heating lines are 25% and 77%, respectively. Regarding the environmental impact, CTwJ processing and packaging by appertization were higher than those of ohmic heating systems. In other words, CTwJ production by the ohmic heating system was more environmentally efficient. The tin production phase was the environmental hotspot in packaged CTwJ production by the appertization system; however, the agricultural phase of production was the hotspot in ohmic heating processing. The uncertainty analysis results indicated that the global warming potential for appertization of 1 kg of packaged CTwJ ranges from 4.13 to 4.44 kg CO2eq. In addition, the global warming potential of the ohmic heating system ranges from 2.50 to 2.54 kg CO2eq. This study highlights that ohmic heating presents a great alternative to conventional sterilization methods due to its low environmental impact and high energy efficiency.

Measuring Circularity in Food Supply Chain Using Life Cycle Assessment; Refining Oil from Olive Kernel.

Valorization of food waste is a potential strategy toward a circular food supply chain. In this regard, measuring the circularity of food waste valorization systems is highly important to better understand multiple environmental impacts. Therefore, this study investigated the circularity of a food waste valorization system (refining oil from olive kernel) using a life cycle assessment methodology. An inventory of an industrial-based olive kernel oil production system is also provided in this study. The system boundary was the cradle to the factory gate of the production system. The results indicated that natural gas consumption was the highest contributor to most of the investigated impact categories. The global warming potential of one kg of oil produced from olive kernel was calculated to be 1.37 kg CO2eq. Moreover, the calculated damages of 1 kg oil production from olive kernel to human health, ecosystem quality, and resource depletion were 5.29 × 10-7 DALY, 0.12 PDF∙m2∙yr., and 24.40 MJ, respectively.