How can we measure food loss

Step 1.6 introduced why it’s important to measure food loss and some of the challenges to this. This article explores what data we need to collect to start addressing the issue.

There have been significant EU wide research programmes for FOOD WASTE, which set out a common definition and quantified food waste along the food supply chain according to this definition. Over the years, this has been developed further into a full methodology and an obligation to reduce post-harvest food waste under EU waste legislation (Waste Framework Directive).

In comparison, there is a lack of focus on FOOD LOSS in primary production and a need to increase access to reliable data by developing a standard definition and common methodology before any legal framework can be put in place. But what are the data gaps and the kinds of information we need to collect?

At first glance the food loss definition graphic in Step 2.2 looks straightforward. In reality, there are some tricky questions around where the ‘food loss’ boundaries are drawn and how data are measured. Let’s explore some of these gaps in more detail.

Identifying the starting point of food loss

Identifying the point at which a product is ‘mature’ and ready to be harvested, caught or slaughtered is not always straightforward. A range of factors need to be considered, including edibility, maturity level and market requirements. For example, salmon are defined as edible at 1kg but marketable at 3kg.

Figure 1: Fish farming in Torskefjorden, Senja, Troms, Norway. ©Ximonic (Simo Räsänen), CC BY-SA 4.0, via Wikimedia Commons

Establishing the sampling area

It would be impractical to directly measure food loss from a whole crop. Would you sample 0.1%, 1%, or 10% of a mature crop? Different studies have suggested all these options but we need to establish an agreed suitable sample size. Remember, data measurement decisions (including establishing the sample area) need to balance data robustness with the practicalities of collecting the data, see Step 1.6.

Figure 2: Wheat field. ©Richard Casebow

Multiple cuts

Some crops (e.g. brassicas) may be harvested more than once during an agricultural campaign​ so we require a plan to estimate food loss from multiple cuts per year.

Figure 3: Cabbage field. ©Photo by Egor Myznik on Unsplash

Pre-harvest vs. harvest losses

What we measure needs to be appropriate to the commodity and circumstance. For example, it’s helpful to track pre-harvest losses from fruit farms e.g. by collecting fallen fruit data. In other cases, loss only occurs at the point of ‘harvest’ e.g. milk production. It’s important to focus on what is material, useful and practical.

Figure 4: Dairy cows being milked on a University of Reading farm. ©UoR

Identifying the reasons for food loss

Understanding why food loss happens is as important as measuring the loss itself. Reasons include not meeting aesthetic criteria, environmental conditions, lack of labour, market saturation and demand changes (there are many more). Contextual information will help us understand the bigger picture. For a reminder of direct and indirect causes of food loss, revisit Step 1.8.

Figure 5: Barley which has been flattened due to environmental conditions.©UoR

Measuring diversity

Food loss is typically estimated to be around 10% of production, but it depends on different factors e.g. the commodity and territory. A study of oranges showed a range of 1 kg – 18 kg per tree. We should consider the range and complexity of the problem.

Figure 6: Oranges of different shapes and sizes being collected from the ground. © WWF/Santi Donaire.

The FOLOU project is developing a manual to provide a standard methodology. It will address data gaps and concerns, including the ones listed above. The manual will also provide recommendations that balance data reliability with limited resources. The final version is due in April 2026.

Resources

• EU parallel session during the COP28 conference (2023) Reducing consumer food waste, protecting the planet (Hosted on YouTube).
• Fernandez-Zamudio, M. A., Barco, H., & Schneider, F. (2020). Direct measurement of mass and economic harvest and post-harvest losses in Spanish persimmon primary production. Agriculture, 10(12), 581
• FOLOU 2nd Meeting (2024) Navigating Reliable Diagnoses for Measuring Food Losses in the Primary Sector of the Supply Chain. (Meeting recording hosted on YouTube).
• Feedback (2018) Farmers talk food waste: supermarkets’ role in crop waste on UK farms. London: Feedback.