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Real‐time CO2 monitoring for early detection of grain spoilage and mycotoxin contamination

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2025-09-22

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0022-5142

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Kiaitsi E, Zanardi S, Sulyok M, et al., (2025) Real‐time CO2 monitoring for early detection of grain spoilage and mycotoxin contamination. Journal of the Science of Food and Agriculture, Volume 105, Issue 15, December 2025, pp. 8985-8993

Abstract

BACKGROUND

This study aimed to compare the use of real‐time CO2, temperature (T) and relative humidity (RH) sensors as indicators of stored grain quality management, specifically for early detection of mould activity and mycotoxin contamination. Initial experiments were conducted using mini‐silos containing naturally contaminated wheat grain (1.5 kg) stored at different moisture contents of 15–30% (water activity, aw = 0.78 to 0.98), to evaluate their effects on grain respiration.

RESULTS

Respiration rates and dry matter losses increased with grain moisture content. A larger‐scale, nine‐month study was then conducted using two pilot‐scale silos (2.5 t; 1400 cm diameter; 2050 cm height) equipped with ATEX‐compliant CO2/RH/T sensors. A ‘wet pocket’ was simulated by introducing water to a localised area to mimic a water ingress event. This led to a rapid rise in CO2 levels while T remained relatively stable. Mycotoxin analyses of the affected and unaffected regions showed a clear increase in the concentration and diversity of mycotoxins, particularly aflatoxin B1, aflatoxin B2, deoxynivalenol, deoxynivaenol‐3‐glucoside and moniliformin, in the wet pocket area.

CONCLUSION

Real‐time CO2 monitoring provided a faster and more sensitive indication of spoilage and mycotoxin risk compared to T and RH measurements. This highlights the potential for developing early‐warning systems for stored grain management based predominantly on continuous CO2 monitoring.

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Git repository

Keywords

wheat, silo, fungi, relative humidity, cereals, food waste, 3004 Crop and Pasture Production, Food Science, 30 Agricultural, veterinary and food sciences, 40 Engineering

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Attribution 4.0 International

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This research was funded by European Union's Horizon 2020 research and innovation pro-gramme under grant agreement no. 678012-Mytoolbox project.

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