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- Empowering Eco-Friendly Choices: An Environmental Impact Assessment Decision Support System for Textile and ClothingPublication . Gomes, Carolina; Pires, Irina; Monteiro, Letícia; Lima, Tânia M.; Gaspar, Pedro DinisThe textile and clothing industry is one of the industries with the highest environmental impact, with a huge amount of waste during the product life cycle. However, there are few tools available for companies to assess the environmental impact of their production process. In this way, a decision support system was developed so that producers can calculate the environmental impact associated with the textile and clothing production process, with the main objective of helping producers and, consequently, consumers to make environmentally conscious decisions given the increasingly demanding market. The methodology of this study integrated the accounting of a set of indicators, allowing producers to calculate the environmental impact associated with the textile and clothing production process. The decision support system returns, depending on the results of the calculations of the indicators, different ecolabels that allow consumers to compare different products based on their environmental performance. In short, the study in question allows us to contribute to environmentally conscious decision making, both for the producer and the consumer, to promote sustainable practices in the textile and clothing industry. The decision support system is flexible and adaptable for different companies and industries in order to meet their needs and improve their environmental performance.
- Fostering Awareness on Environmentally Sustainable Technological Solutions for the Post-Harvest Food Supply ChainPublication . Fernandez, Carlos M.; Alves, Joel; Gaspar, Pedro Dinis; Lima, Tânia M.This study presents a current status and future trends of innovative and environmentally sustainable technological solutions for the post-harvest food supply chain and the food industry, in terms of ecological packaging, active, and/or intelligent packaging. All these concerns are currently highlighted due to the strong increase in the purchase/sale of products on online platforms, as well as the requirements for stricter food security and safety. Thus, this study aims to increase the global awareness of agro-industrial micro, small, and medium size enterprises for the adoption of innovative food solutions though industry digitalization (Industry 4.0), associated logistics and circular economy, with a concern for cybersecurity and products information, communication and shelf-life extension. The adoption of these guidelines will certainly foster along the complete food chain (from producer to consumer, with all intermediary parties) the awareness on environmentally sustainable technological solutions for the post-harvest food supply chain, and thus, promoting the future food sustainability required by the population increase, the climate change, the exodus of rural population to urban areas, and food loss and waste.
- Decision Support System in Dynamic Pricing of Horticultural Products Based on the Quality Decline Due to Bacterial GrowthPublication . Pina, Miguel; Gaspar, Pedro Dinis; Lima, Tânia M.A decision support system (DSS) was developed to help reduce food waste at traditional food retailers while selling fresh horticultural products, but also to promote food safety and quality. This computational tool includes two major functions: (1) the prediction of the remaining shelf life of fresh horticultural product, namely lettuce, onion, carrot, and cabbage based on its microbial growth status, governed by extrinsic and intrinsic parameters (temperature, water activity and pH, respectively). The remaining shelf life of the studied horticultural products is determined by using the online predictive food microbiology tool— the Combined Database for Predictive Microbiology (Combase). The time to reach the infectious doses of bacteria considered in the study for each of the four horticultural products are predicted; (2) the calculation of the dynamic price of the produce that should be set each day, depending on the predicted end of the marketing period to increase the demand and potential for sale to the final consumer. The proposed dynamic pricing model assumes a linear relation with the remaining shelf life of the analyzed vegetable to set the selling price. The shelf life determined by the DSS for optimal storage conditions is, in general, conservative, ensuring food safety. The automatic dynamic pricing gives new opportunities to small retailers to manage their business, fostering profit and simultaneously contributing to reduce food waste. Thus, this decision support system can contribute to the sustainable value of reducing food waste by providing information to small grocers and retailers on the safety of their perishable status depending on storage conditions and allowing them to suggest a fair price depending on that quality.