Application of MOS Gas Sensors Coupled with Chemometrics Methods to Predict the Amount of Sugar and Carbohydrates in Potatoes

Abstract

Five potato varieties were studied using an electronic nose with nine MOS sensors. Parameters measured included carbohydrate content, sugar level, and the toughness of the potatoes. Routine tests were carried out while the signals for each potato were measured, simultaneously, using an electronic nose. The signals obtained indicated the concentration of various chemical components. In addition to support vector machines (SVMs that were used for the classification of the samples, chemometric methods, such as the partial least squares regression (PLSR) method, the principal component regression (PCR) method, and the multiple linear regression (MLR) method, were used to create separate regression models for sugar and carbohydrates. The predictive power of the regression models was characterized by a coefficient of determination (R2), a root-mean-square error of prediction (RMSEP), and offsets. PLSR was able to accurately model the relationship between the smells of different types of potatoes, sugar, and carbohydrates. The highest and lowest accuracy of models for predicting sugar and carbohydrates was related to Marfona potatoes and Sprite cultivar potatoes. In general, in all cultivars, the accuracy in predicting the amount of carbohydrates was somewhat better than the accuracy in predicting the amount of sugar. Moreover, the linear function had 100% accuracy for training and validation in the C-SVM method for classification of five potato groups. The electronic nose could be used as a fast and non-destructive method for detecting different potato varieties. Researchers in the food industry will find this method extremely useful in selecting the desired product and samples.

Volatile Organic Compounds and Physiological Parameters as Markers of Potato (Solanum tuberosum L.) Infection with Phytopathogens

“…Another method for the detection of different types of volatile organic compounds is the employment of an electronic nose [33]. The method of operation of this device, which is increasingly used, is based on mimicking the sense of smell [34].…”

Investigating Changes in pH and Soluble Solids Content of Potato during the Storage by Electronic Nose and Vis/NIR Spectroscopy

“…The calibration model does not have enough information to make a correct prediction when the principal components are too small. In cases with too many main factors, unwanted information such as experimental errors or noise will be introduced to the model [ 9 ].…”

“…Potato is subjected to various phenomena during storage, cooking, or processing that can affect its final quality [ 8 ]. Cultivar, physical and chemical compounds, and storage conditions of potato (after harvest) can influence the cooking features and final product of the potato [ 9 ].…”

“…The conventional methods to evaluate the internal quality of potatoes are inefficient due to their low accuracy, time-consuming process, high costs, and sample preparation requirements [ 9 ].…”

“…Similar to pH measurement, conventional methods of SSC measurement are often destructive and time-consuming. E-nose and spectroscopic methods are capable of assessing the quality features of food products in a fast and non-destructive manner [ 9 ]. Multivariable statistical analysis methods can also be utilized for the prediction and determination of chemical compounds within food samples [ 30 ].…”