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Contrasting oxygen and carbon dioxide contributions to respiratory quotient variability in fresh and fresh-cut produce under modified atmospheres
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DOI：10.1007/s11694-026-04811-y.png)
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Abstract
En 中文
Respiratory quotient (RQ) integrates carbon dioxide production and oxygen consumption, but its ratio structure can amplify variability when oxygen consumption is low. This study quantified treatment-dependent RQ dynamics and compared the contributions of oxygen and carbon dioxide to RQ variability in fresh and fresh-cut produce under modified atmospheres. Time-series data for lettuce, spinach, baby plum tomato, and mixed salad exposed to four gas treatments and three cutting classes were analysed using generalized estimating equations (GEE). An empirical second-order response surface supported Monte Carlo simulation, Tornado analysis, partial rank correlation coefficients (PRCC), and blockwise semi-partial R2 analysis. GEE identified significant coefficients for Air, spinach, baby plum tomato, selected gas × cutting interactions, and selected time-dependent terms. The Mix C × fine-cut interaction showed the largest positive interaction coefficient (β = 0.4378, p = 0.042). In the baseline-filtered analysis, the CO₂ Tornado span exceeded the O₂ span (3.258 versus 0.733), with similar results after winsorization (3.367 versus 0.743). Under restriction to the higher-RO2 subset, however, the ranking reversed (O₂: 1.136; CO₂: 0.797). Winsorized PRCC showed a nominally statistically significant but extremely weak association for CO₂ (− 0.0708, p = 0.0148) and no meaningful association for O₂ (0.0006, p = 0.9824). Removal of the O₂-associated predictor block produced a larger reduction in model fit than removal of the CO₂-associated block (0.0677 versus 0.0377). These contrasting rankings demonstrate that atmospheric influence on RQ is both metric- and response-domain dependent. RQ is therefore best interpreted as a treatment-dependent trajectory alongside RO₂ and RCO₂, rather than as a standalone biochemical marker of fermentation. • GEE identified atmosphere × cutting effects on respiratory quotient dynamics. • CO₂ dominated Tornado spans in baseline and winsorized analyses. • Strict response-domain restriction reversed the ranking toward O₂. • PRCC showed only a weak conditional CO₂ association with RQ. • RQ sensitivity depended on both analytical metric and response domain.
Keywords:
Respiratory quotient
Food characterization
Monte Carlo simulation
Sensitivity analysis
Uncertainty quantification
Generalized estimating equations
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3.3
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