Abstract
INTRODUCTION: Cheese maturation is an essential stage in dairy production, significantly influencing the sensory quality and market value of the final product. Traditional monitoring methods are often subjective, costly, and rely on destructive sampling, limiting their effectiveness. Near-infrared (NIR) spectroscopy has emerged as a promising, non-destructive, rapid technique capable of providing objective, quantitative data and integration into real-time industrial processes. However, literature still lacks standardized approaches, validation across different cheese types, and comprehensive, methodologically robust reviews to support its broader application. This protocol outlines a scoping review to map and synthesize the available evidence on the use of NIR for monitoring cheese maturation. By investigating its industrial applications, identifying equipment, configurations, and spectral ranges used, exploring data analysis methods, and highlighting reported limitations, challenges, and research gaps. METHOD: This scoping review protocol follows the JBI methodology and PRISMA-S guidelines, employing a validated search strategy based on the PRESS 2015 checklist, adapted for use across multiple databases. A comprehensive search will be conducted in Scopus, Web of Science, PubMed, Embase, and FSTA, using a PCC-based strategy. Secondary searches through citation tracking will complement the process. All study designs will be considered without language or date restrictions. Screening and selection will be performed independently by reviewers using the Rayyan software. Data will be extracted and analyzed using descriptive and thematic analysis in NVivo. Methodological quality will be assessed using consolidated checklists. Findings will be presented in narrative, tabular, and diagrammatic formats. CONCLUSION: This will be the first systematic synthesis of evidence on the effectiveness of NIR in assessing cheese ripeness, emphasizing its potential for improving production and quality control. By identifying challenges such as the lack of standardization and variability in equipment and models, among others, the review will help define best practices, guide future research, and support the broader adoption of NIR in the dairy industry. TRIAL REGISTER: OSF Registries, Jul 2, 2025: https://doi.org/10.17605/osf.io/2w4bv.