食品科学-预测易腐食品的有效期以减少损失和浪费

Trewon Weerasooriya, Kishore Kumar
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引用次数: 0

摘要

“食物损失和浪费”是全球环境、经济和社会日益严重的问题。它对社会、环境和经济问题都有不利影响。计划不周、过度生产和顾客感知是造成食物损失和浪费的主要原因。在过期前对易腐食品的低效利用是造成粮食损失和浪费的另一个重要因素。这项研究主要集中在斯里兰卡的酒店和餐馆,这是酒店和食品服务业务的两个主要子行业之一。为了减少酒店和餐馆食品供应链过程中的食物损失和浪费,该研究建议使用人工智能来预测易腐食品的过期。它还建议建立一个捐赠平台,将剩余或未消耗的易腐食品分发给有需要的人/受益人。该预测器使酒店和餐馆能够知道使用他们购买的易腐食品的最佳日期,如果有剩余或变质的,可以使用新鲜度指数列出,以便有需要的人可以要求购买,并在酒店和餐馆指定的价格范围内购买。该解决方案旨在减少食品供应链中的浪费,并在可行的最大程度上控制浪费。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Foodligence – Predicting Expiry Date of Perishable Foods to Reduce Loss and Waste
“Food loss and waste” is a growing issue for the environment, the economy, and society worldwide. It has an adverse effect on social, environmental, and economic issues. Poor planning, excessive production, and customer perception are the main causes of food loss and waste. Inefficient use of perishables before to expiration is another significant contributor to food loss and waste. The study primarily concentrates on Sri Lanka's hotels and restaurants, one of the two main sub-sectors of the hospitality and food services business. To reduce food loss and waste during the processes of the food supply chain of hotels and restaurants, the research suggests an expiry predictor for perishable food items using artificial intelligence. It also suggests a donation platform to distribute any surplus or unconsumed perishables to the needy/beneficiaries. The predictor enables hotels and restaurants to be aware of the best dates to use the perishables they have purchased, while if any are left over or spoil, they can be listed using the freshness index so that people in need can request them and make purchases for a price range the hotels and restaurants have specified. The solution aims to reduce waste in the food supply chain and control it to the greatest extent feasible.
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