Dish Carbon Analysis Case Study

The Business Problem

The research method gave sound answers, but only to people prepared to work through a detailed spreadsheet ingredient by ingredient. A school cook or catering manager needed to start from a dish they actually serve, not from a list of emission factors. At the same time, every figure had to stay consistent with the established method, or the results could not be trusted or compared.

The Solution

wildesoft.net built the dish analyser at the heart of Meal Analyser. Users choose one of three routes: name a dish and let AI suggest its typical ingredients, enter their own recipe with exact quantities, or pick from a collection of recipes and compare their ingredients first. Ingredients can be edited, added or removed at any time.

AI then matches each ingredient to Agribalyse, the most comprehensive food emissions database currently available. The maths, however, is never left to AI. The software itself works out the dish's greenhouse gas emissions per kilogram, checked against successive versions of the master spreadsheet, so the same dish always gives the same answer. Results are shown as charts by ingredient and food category, with a colour-coded carbon intensity band that shows at a glance whether a dish is low, medium or high impact.

The Result

A caterer can go from a dish name to a clear, consistent carbon figure in minutes, without specialist knowledge. The research method is now a practical tool, and every result rests on the same calculations as the original model.

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