Assessment and scenario hypothesis of food waste in China based on material flow analysis

Abstract

Field research limits the possibility of clarifying the current food waste situation in China. Material flow analysis was used to assess the magnitude and characteristics of waste in five stages from 2010–2019 by seven selected types. Wheat was wasted the most at 38%, while milk was wasted the least at 4%. During post-harvest handling and storage, processing and packaging, and consumption, wheat was wasted the most (56%, 36%, and 48%), while during production and marketing, tomatoes were wasted the most (28% and 25%). Wheat, apples, tomatoes, pork, and milk were wasted the most in consumption, while soybeans were wasted the most in processing and packaging, and freshwater fish were wasted the most in production. A scenarios hypothesis proved that a 5% reduction in each stage would reduce import demand for soybeans by 7%. This study provides a data reference and theoretical basis for food waste intervention and food security strategies.

Intervening fish post‐harvest losses to narrow the gap between demand and supply: A review on magnitude of fish post‐harvest losses in some Sub‐Saharan African countries

“…Additionally, the Partnership for African Fisheries Governance Working Group stated that it is projected that the fishing industry would lose USD 2 billion annually (de Graaf & Garibaldi, 2015). It was reported that the majority of freshwater fish is lost during production due to the use of substandard fishing gear, non‐targeted fishing and a lack of policy enforcement in fishery management (Jiang et al., 2023). According to the report, the majority of fish processing methods are inhumane, which lowers the quality of fish products.…”

The concept of food waste and food loss prevention and measuring tools

“…MFA is a quantitative method used to study and quantify the flow of materials, substances and energy within a system defined in space and time and the results that flow (Kaufman, 2012;Voukkali and Zorpas, 2022). MFA does not require the involvement of participants and is able to accommodate large sample sizes, offering greater precision in calculations (Jiang et al, 2023). Since MFA depicts the linear correlation of material flow, it implies that the total input must be equivalent to the total output generated.…”