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Study Design

Methods
interdisciplinary methodological framework structured in five phases: (1) bibliometric analysis, (2) meta-analysis of physicochemical parameters and biofunctional compounds, (3) exploration of digital trends, (4) agronomic field observation, and (5) consumer perception analysis
Funding
Unclear
Green onion (Allium fistulosum) is among the most highly consumed vegetables in the Andean region and parts around the world, playing a central role in food security, rural livelihoods, and local culinary identity. Green onion lacks a clear and standardized definition of quality, limiting commercial differentiation and value generation in national and international markets. Existing approaches remain fragmented, focusing on isolated attributes without integrating cultural, perceptual, origin-related, and biofunctional dimensions into a unified framework. This study introduces an interdisciplinary methodological framework structured in five phases: (1) bibliometric analysis, (2) meta-analysis of physicochemical parameters and biofunctional compounds, (3) exploration of digital trends, (4) agronomic field observation, and (5) consumer perception analysis. The approach integrates direct and indirect information sources across the value chain and applies data analytics and natural language processing to reach a multidimensional definition of green onion quality. Results indicate that quality in green anion is determined by physical attributes such as firmness, color, pseudostem thickness, freshness, and the absence of visible damage, together with biofunctional components including flavonoids (38.4-73.3 mg quercetin/100 g) and sulfur compounds (71.6-353.6 μmol/g). Unlike earlier studies, our findings demonstrate that quality is a multidimensional and territorialized concept, shaped by cultivation practices, climatic conditions, and cultural contexts. According to consumer preferences, the most important attributes associated with the quality of green anion are freshness (93.6%), pseudostem thickness (89.3%), and absence of damage (87.1%). These results support the development of technical protocols that unify objective criteria with local knowledge, while proposing a replicable model for other traditional crops, with applications in quality standardization, sustainable production, and commercial valorization.

Research Insights

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