To ensure effective nutritional surveillance of athletes on a national scale, it is essential to collect reliable and representative data on dietary intakes. This requires the design and validation of standardised tools that are regularly updated to reflect recent changes in the composition of food products and the nutritional habits of the population. The aim of this study was to create and validate a digital tool designed to assess the dietary profiles of elite Chadian martial arts practitioners. A total of 63 elite Chadian martial artists (33 men and 31 women) with an average age of 18.58 ± 2.36 years participated in this study. Anthropometric parameters, including height, body weight and body mass index (BMI) were measured. To validate the Food Survey software package, energy, macro- and micronutrient intakes were assessed using a 24-hour food intake recall (reference method) and compared with the same data collated from Food Survey (tested method) in order to analyse reconciliation agreements between the results of the two methods. The comparison of energy and nutrient intakes for women and men revealed similar results for most nutrients, indicating overall consistency. Analyses of the various Bland-Altman distribution curves indicate that the majority of the parameters from the two methods studied show good agreement: the biases (y = absolute bias) are, for the most part, perfect, with most of their values close to 0. The limits of agreement (y = absolute bias ± 1.96 × standard deviation) are also narrow for all the data analysed, with the exception of phosphorus (？371.299; 250.113). This IT tool represents an innovative alternative for assessing food choices, particularly in contexts where dietary behaviour is measured only once. Unlike 24-hour dietary recalls or food frequency questionnaires, which require repeated administrations to provide a more comprehensive assessment of dietary habits, this tool stands out for its ability to be effective in studies with limited time and budget. It is a practical solution for rapidly collecting reliable data on food choices in constrained research environments.
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