In response to one of the most important challenges of the century, i.e., the estimation of the food demands of a growing population, advanced technologies have been employed in agriculture. The potato has the main contribution to people’s diet worldwide. Therefore, its different aspects are worth studying. The large number of potato varieties, lack of awareness about its new cultivars among farmers to cultivate, time-consuming and inaccurate process of identifying different potato cultivars, and the significance of identifying potato cultivars and other agricultural products (in every food industry process) all necessitate new, fast, and accurate methods. The aim of this study was to use an electronic nose, along with chemometrics methods, including PCA, LDA, and ANN as fast, inexpensive, and non-destructive methods for detecting different potato cultivars. In the present study, nine sensors with the best response to VOCs were adopted. VOCs sensors were used at various VOCs concentrations (1 to 10,000 ppm) to detect different gases. The results showed that a PCA with two main components, PC1 and PC2, described 92% of the total samples’ dataset variance. In addition, the accuracy of the LDA and ANN methods were 100 and 96%, respectively.

The article presents an attempt to use an electronic nose together with a new three-parameter method for generation of a digital smellprint in order to specify the mode of processing of rapeseed based on the analysis of volatile compounds contained in cold-pressed rapeseed oil. Prior to the pressing process, the seeds were roasted or improperly stored to obtain oil samples with varied technological quality. The quality of pressed oils was evaluated by determination of the acid value. Furthermore, changes in oil colour were assessed with the use of an imaging colorimeter. Volatile compounds were determined with the use of gas chromatography and an electronic nose with a metal oxide semiconductor (MOS) sensor matrix. It was found that the mode of seed pre-treatment before pressing did not change the colour of the oil significantly. However, it influenced the profile of volatile organic compounds and changed their proportions. Ketones represented the largest proportion of volatile compounds determined for roasted samples and those pressed from seeds moistened up to 25% (w.b.). Alcohols dominated in samples moistened up to 10 and 12%, terpenes were the dominant volatile compounds in samples roasted at 140°C, and other volatile compounds dominated in samples moistened up to 10 and 20% (w.b.). In turn, esters and aromatic compounds accounted for the lowest proportion in the analysed samples. The results shown by the electronic nose were correlated with the presence of particular groups of volatile compounds in rapeseed oil.An enose for analysis of rapeseed oil R. Rusinek et al. 2162

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The aim of the study was to analyze the process of roasting coffee beans in a convection–conduction roaster (CC) without a heat exchanger and a convection–conduction–radiation roaster (CCR) with a heat exchanger for determination of the aroma profile. The aroma profile was analyzed using the SPME/GC-MS technique, and an Agrinose electronic nose was used to determine the aroma profile intensity. Arabica coffee beans from five regions of the world, namely, Peru, Costa Rica, Ethiopia, Guatemala, and Brazil, were the research material. The chemometric analyses revealed the dominance of azines, alcohols, aldehydes, hydrazides, and acids in the coffee aroma profile. Their share distinguished the aroma profiles depending on the country of origin of the coffee beans. The high content of pyridine from the azine group was characteristic for the coffee roasting process in the convection–conduction roaster without a heat exchanger, which was shown by the PCA analysis. The increased content of pyridine resulted from the appearance of coal tar, especially in the CC roaster. Pyridine has an unpleasant and bitter plant-like odor, and its excess is detrimental to the human organism. The dominant and elevated content of pyridine is a defect of the coffee roasting process in the CC roaster compared to the process carried out in the CCR machine. The results obtained with the Agrinose showed that the CC roasting method had a significant effect on the sensor responses. The effect of coal tar on the coffee beans resulted in an undesirable aroma profile characterized by increased amounts of aromatic volatile compounds and higher responses of Agrinose sensors.

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.

A field experiment was carried out in 2013-2016 in the Agricultural Experimental Station -Zawady of the University of Natural Sciences and Humanities in Siedlce, Poland. The examined factors included: Ithree morphotypes of winter rape: population cultivar (Monolit), hybrid semi-dwarf (PR44D06) cultivar, restored hybrid cultivar of conventional growth type (PT205); IItwo sowing methods: row spacing of 22.5 cm, row spacing of 45.0 cm; IIIfour types of applied biostimulators: control variant (without application of biostimulators), Tytanit ® biostimulator, Asahi ® SL biostimulator and Silvit ® biostimulator. The aim of the research was to determine the effect of natural plant preparation on the yield of four cultivars of winter rape. It was found that biostimulators applied in the experiments increased the thousand-seed weight on average from 0.03 to 0.1 g in comparison to the control variant. The highest value of this feature was obtained in the variant with Asahi ® SL treatment and significantly lower in plots treated with Silvit ® and Tytanit ® bioregulators. A significant increase in seed yielding was observed as the effect of natural growth stimulators. The highest value of this feature was observed in all cultivars after the application of Asahi ® SL and Silvit ® .

This paper presents the analyses of the effect of fiber additives on volatile organic compounds in bread. The bread was baked from wheat flour with the addition of 3% of fruit fiber, following common procedures. After baking, volatile organic compounds contained in the control bread and breads supplemented with cranberry, apple, and chokeberry fiber were determined. The SPME/GC-MS technique was used for the identification of the odor profile, and the electronic nose Agrinose (e-nose) was used to assess the intensity of the aroma. The results of the analyses revealed the profile of volatile organic compounds in each experimental variant, which was correlated with responses of the electronic nose. The results indicate that the volatile compound profile depends on the bread additives used and influences the intensity of bread aroma. Moreover, the profile of volatile organic compounds in terms of their amount and type, as well as the intensity of their interaction with the active surface of the electrochemical sensors, was specific exclusively for the additive in each case.

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