Predictions of acidity, soluble solids and firmness of pear using electronic nose technique

Abstract In this paper, responses of sensor array in electronic nose were employed to establish quality indices model able to describe the different picking dates of “xueqing” pear. The multivariate calibration methods, multiple linear regression (MLR), principal component regression (PCR) and partial least-squares regressions (PLS) were applied to predict the quality indices of “xueqing” pear from different picking dates based on the signal of electronic nose. All models for firmness and soluble solids content show a good prediction performance. However the acidity, there was a very poor correlation with the signal of the electronic nose. It was found that MLR led to more precise predictions than the other multivariate calibration methods. The results indicate that it is possible to use this non-destructive technique for measuring “xueqing” pear quality characteristics. The methods have the potential to estimate chemical and physical properties of pear from signal of electronic nose.

[1]  Joseph Maria Kumar Irudayaraj,et al.  Detection of Apple Defects Using an Electronic Nose and zNose , 2005 .

[2]  Peter D. Wentzell,et al.  Comparison of principal components regression and partial least squares regression through generic simulations of complex mixtures , 2003 .

[3]  D. Ballabio,et al.  Evaluation of different storage conditions of extra virgin olive oils with an innovative recognition tool built by means of electronic nose and electronic tongue , 2007 .

[4]  E. Llobet,et al.  Evaluation of an electronic nose to assess fruit ripeness , 2005, IEEE Sensors Journal.

[5]  Yong Yu,et al.  The firmness detection by excitation dynamic characteristics for peach , 2006 .

[6]  Shyam Narayan Jha,et al.  Modeling of color values for nondestructive evaluation of maturity of mango , 2007 .

[7]  J. Brezmes,et al.  Correlation between electronic nose signals and fruit quality indicators on shelf-life measurements with pinklady apples , 2001 .

[8]  S. Oshita,et al.  Discrimination of odors emanating from ‘La France’ pear by semi-conducting polymer sensors , 2000 .

[9]  I. Ortiz,et al.  Granular activated carbon for the recovery of the main pear aroma compound: Viability and kinetic modelling of ethyl-2,4-decadienoate adsorption , 2007 .

[10]  J. Rodríguez-Nogales.  Approach to the quantification of milk mixtures by partial least-squares, principal component and multiple linear regression techniques , 2006 .

[11]  R. Paolesse,et al.  Outer product analysis of electronic nose and visible spectra: application to the measurement of peach fruit characteristics , 2002 .

[12]  C. Natale,et al.  Electronic nose as a non-destructive tool to evaluate the optimal harvest date of apples , 2003 .

[13]  David C. Slaughter,et al.  Freeze damage detection in oranges using gas sensors , 2005 .

[14]  C. Natale,et al.  An electronic nose and a mass spectrometry-based electronic nose for assessing apple quality during shelf life , 2004 .

[15]  J. Rodríguez-Nogales,et al.  Application of electrophoretic and chemometric analysis to predict the bovine, ovine and caprine milk percentages in Panela cheese, an unripened cheese , 2007 .

[16]  M. Valcárcel,et al.  Direct olive oil authentication: detection of adulteration of olive oil with hazelnut oil by direct coupling of headspace and mass spectrometry, and multivariate regression techniques. , 2005, Journal of Chromatography A.

[17]  Lixia Xiao,et al.  Changes in the volatile compounds and chemical and physical properties of Yali pear (Pyrus bertschneideri Reld) during storage , 2006 .

[18]  Eduard Llobet,et al.  Fruit ripeness monitoring using an Electronic Nose , 2000 .

[19]  Shyam Narayan Jha,et al.  Non-destructive Determination of Firmness and Yellowness of Mango during Growth and Storage using Visual Spectroscopy , 2006 .

[20]  David H. Vaughan,et al.  Non-destructive evaluation of apple maturity using an electronic nose system , 2006 .

[21]  Annia García Pereira,et al.  Non-destructive measurement of acidity, soluble solids and firmness of Satsuma mandarin using Vis/NIR-spectroscopy techniques , 2006 .

[22]  E. Martinelli,et al.  The evaluation of quality of post-harvest oranges and apples by means of an electronic nose , 2001 .

[23]  Annia García Pereira,et al.  Discrimination of storage shelf-life for mandarin by electronic nose technique , 2007 .

[24]  E. Martinelli,et al.  Lung cancer identification by the analysis of breath by means of an array of non-selective gas sensors. , 2003, Biosensors & bioelectronics.

[25]  E. Martinelli,et al.  Electronic nose based investigation of the sensorial properties of peaches and nectarines , 2001 .