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Protocol for life cycle assessment modeling of US fruit and vegetable supply chains- cases of processed potato and tomato products.

ABSTRACT: This article elaborates on the life cycle assessment (LCA) protocol designed for formulating the life cycle inventories (LCIs) of fruit and vegetable (F&V) supply chains. As a set of case studies, it presents the LCI data of the processed vegetable products, (a) potato: chips, frozen-fries, and dehydrated flakes, and (b) tomato-pasta sauce. The data can support to undertake life cycle impact assessment (LCIA) of food commodities in a "cradle to grave" approach. An integrated F&V supply chain LCA model is constructed, which combined three components of the supply chain: farming system, post-harvest system (processing until the consumption) and bio-waste handling system. We have used numbers of crop models to calculate the crop yields, crop nutrient uptake, and irrigation water requirements, which are largely influenced by the local agro-climatic parameters of the selected crop reporting districts (CRDs) of the United States. For the farming system, LCI information, as shown in the data are averaged from the respective CRDs. LCI data for the post-harvest stages are based on available information from the relevant processing plants and the engineering estimates. The article also briefly presents the assumptions made for evaluating future crop production scenarios. Future scenarios integrate the impact of climate change on the future productivity and evaluate the effect of adaptation measures and technological advancement on the crop yield. The provided data are important to understand the characteristics of the food supply chain, and their relationships with the life cycle environmental impacts. The data can also support to formulate potential environmental mitigation and adaptation measures in the food supply chain mainly to cope with the adverse impact of climate change.

SUBMITTER: Parajuli R

PROVIDER: S-EPMC7749376 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundReducing food loss and waste (FLW) may narrow gaps between fruit and vegetable production and recommended intake. However, FLW estimates are inconsistent due to varying estimation methods.ObjectivesUsing multiple estimation approaches, we examined the extent and determinants of FLW along tomato supply chains in South India, from farm to retail. We also explored tomato quality assessments.MethodsWe surveyed 75 farm households and 83 tomato traders in the Chittoor district, Andhra Pradesh, and 52 vegetable traders and 50 vegetable retailers in Hyderabad, Telangana, on harvest and market days. We calculated declared FLW values using participant-reported losses to estimate the preharvest quality FLW and quantitative FLW values at the farmer, vegetable-trader, and vegetable-retailer stages. We calculated the destination FLW based on counted crates diverted to loss destinations, using participant-reported destinations (animal feed, field discard), to estimate the postharvest FLW from farm to retail. We used pile sorting with farmers to explore on-farm quality assessments.ResultsThe average preharvest quality FLW was 13.9% of harvested tomatoes. From farm to retail, the quantitative FLW was greatest at the postharvest, farm level. Among all harvests, the median postharvest, farm-level FLW was 0.0% (IQR, 0.0%-7.9%) using the destination FLW approach (tomatoes diverted to nonfood uses) and 2.3% (IQR, 0.0%-12.5%) using the declared FLW approach (P < 0.05). Among harvests with a non-zero postharvest, farm-level FLW, the median FLW was 9.1% (IQR, 2.4%-16.7%) using the destination FLW approach (tomatoes diverted to nonfood uses) and 10.0% (IQR, 2.9%-16.7%) using the declared FLW approach. Harvesting during peak season was a determinant of postharvest, farm-level and preauction, market-level FLW values. Farmers prioritize color/ripeness attributes while harvesting and tomato size while grading.ConclusionsSingle-point estimates may obscure FLW patterns for perishable, indeterminate crops and depend on data collection and estimation methods. Reducing FLW of perishables requires the integration of quantitative and qualitative FLW estimation methods.

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Protocol for life cycle assessment modeling of US fruit and vegetable supply chains- cases of processed potato and tomato products.

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