Influence of Changes in the Level of Volatile Compounds Emitted during Rapeseed Quality Degradation on the Reaction of MOS Type Sensor-Array

This study presents the applicability of a three-parameters method for digital description of spoiled rapeseed odor based on the use of an electronic nose. The method consists of the use of three parameters to describe the sensor response, i.e., the maximum resistance value, the response time and the cleaning time of the active surface of the sensor. Reference chemical methods, i.e., determination of the ergosterol content and analysis of volatile compounds by gas chromatography-mass spectrometry, were used to monitor qualitative changes occurring in the stored material. A 31-day profile of volatile compounds and changes in the ergosterol content was determined in the study. A total of 18 chemical groups of volatile organic compounds was identified. There was a strong positive correlation between the cleaning time and the percentage content of alcohols and alkenes, as well as ergosterol, as a marker of qualitative changes. The maximum response was another parameter that effectively described the changes occurring in the seeds. This parameter was strongly negatively correlated with esters and amides in the case of six sensors, and with ergosterol, alkenes and to a lesser degree with alcohols in the case of the other two sensors. The study results clearly demonstrated a relationship between the sensor responses and the percentage content of alcohols and alkenes, which provided novel practical information for the oilseed branch.

[1]  W. E. Muir,et al.  Correlation of total ergosterol levels in stored canola with fungal deterioration , 2006 .

[2]  A. Siger,et al.  Degradation of tocopherols during rapeseed storage in simulated conditions of industrial silos** , 2016 .

[3]  Lavanya Ramakrishnan,et al.  Incorporating Scientific Workflows in Computing Research Processes , 2019, Computing in Science & Engineering.

[4]  R. Kobyłka,et al.  Experimental study and discrete element method modeling of temperature distributions in rapeseed stored in a model bin , 2014 .

[5]  Ren Yi,et al.  Electronic nose classification and differentiation of bacterial foodborne pathogens based on support vector machine optimized with particle swarm optimization algorithm , 2019, Journal of Food Process Engineering.

[6]  Roberto Paolesse,et al.  Detection of fungal contamination of cereal grain samples by an electronic nose , 2006 .

[7]  J. Schnitzler,et al.  Sesquiterpene emissions from Alternaria alternata and Fusarium oxysporum: Effects of age, nutrient availability, and co-cultivation , 2016, Scientific Reports.

[8]  L. Torri,et al.  Sensory methods and electronic nose as innovative tools for the evaluation of the aroma transfer properties of food plastic bags. , 2016, Food research international.

[9]  Dariusz Wiącek,et al.  Electronic nose with polymer-composite sensors for monitoring fungal deterioration of stored rapeseed , 2017 .

[10]  Yizhong Huang,et al.  Single-Nanowire Fuse for Ionization Gas Detection , 2019, Sensors.

[11]  Monika Maciejewska,et al.  Semiconductor gas sensor as a detector of Varroa destructor infestation of honey bee colonies - Statistical evaluation , 2019, Comput. Electron. Agric..

[12]  Riyanarto Sarno,et al.  Optimizing Threshold using Pearson Correlation for Selecting Features of Electronic Nose Signals , 2019 .

[13]  Engracia Madejón,et al.  Use of electronic nose and GC-MS in detection and monitoring some VOC , 2012 .

[14]  Robert Rusinek,et al.  Application of an electronic nose for determination of pre‐pressing treatment of rapeseed based on the analysis of volatile compounds contained in pressed oil , 2019, International Journal of Food Science & Technology.

[15]  Zirui Li,et al.  Quantitative and Qualitative Analysis of Multicomponent Gas Using Sensor Array , 2019, Sensors.

[16]  K. Stuper-Szablewska,et al.  Effect of self-heating on the processing quality of rapeseed , 2018, International Agrophysics.

[17]  Ramón Aparicio,et al.  Coupling MOS sensors and gas chromatography to interpret the sensor responses to complex food aroma: Application to virgin olive oil , 2010 .

[18]  S. S. Kim,et al.  A Novel X-Ray Radiation Sensor Based on Networked SnO2 Nanowires , 2019, Applied Sciences.

[19]  Dariusz Wiącek,et al.  Application of electronic nose with MOS sensors to prediction of rapeseed quality , 2017 .

[20]  Jacek Gębicki,et al.  Discrimination of selected fungi species based on their odour profile using prototypes of electronic nose instruments , 2018 .

[21]  H. Tan,et al.  Estimation of fungal growth using the ergosterol assay: a rapid tool in assessing the microbiological status of grains and feeds , 2007, Letters in applied microbiology.

[22]  Z. Suchorab,et al.  Methods for Early Detection of Microbiological Infestation of Buildings Based on Gas Sensor Technologies , 2020 .

[23]  L. Ramos,et al.  Phenolic compounds obtained from alkyl oleates as additives to improve the oxidative stability of methyl rapeseed biodiesel , 2017 .

[24]  Robert Rusinek,et al.  A Novel Method for Generation of a Fingerprint Using Electronic Nose on the Example of Rapeseed Spoilage. , 2019, Journal of food science.

[25]  A. Visconti,et al.  Screening of deoxynivalenol contamination in durum wheat by MOS-based electronic nose and identification of the relevant pattern of volatile compounds , 2014 .

[26]  J. Tys,et al.  The process parameters for non-typical seeds during simulated cold deep oil expression. , 2018 .

[27]  Bohdan Dobrzański,et al.  Detection and Differentiation of Volatile Compound Profiles in Roasted Coffee Arabica Beans from Different Countries Using an Electronic Nose and GC-MS , 2020, Sensors.

[28]  N. Magan,et al.  Volatiles as an indicator of fungal activity and differentiation between species, and the potential use of electronic nose technology for early detection of grain spoilage. , 2000, Journal of stored products research.

[29]  D. Smith,et al.  Determination of ergosterol in canola (Brassica napus L.) by liquid chromatography , 2003 .

[30]  H. Jeleń.  Use of solid phase microextraction (SPME) for profiling fungal volatile metabolites , 2003, Letters in applied microbiology.

[31]  Robert Rusinek,et al.  Identification of Volatile Organic Compounds and Their Concentrations Using a Novel Method Analysis of MOS Sensors Signal. , 2019, Journal of food science.

[32]  Shukai Duan,et al.  Electronic Nose Feature Extraction Methods: A Review , 2015, Sensors.

[33]  R. Rusinek,et al.  Application of an electronic nose with novel method for generation of smellprints for testing the suitability for consumption of wheat bread during 4-day storage , 2020 .