Electronic nose technique potential monitoring mandarin maturity

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Abstract

Over the past years, electronic nose technology opened the possibility to exploit information on behavior aroma to assess fruit ripening stage. The objective in this study was to evaluate the capacity of electronic nose to monitoring the change in volatile production of mandarin during different picking-date, using a specific electronic nose device (PEN 2). Principal component analysis (PCA) and linear discriminant analysis (LDA) were used in order to investigate whether the electronic nose was able to distinguish among different picking-date (ripeness states). The loadings analysis was used to identify the sensors responsible for discrimination in the current pattern file. The results obtained prove that the electronic nose PEN 2 can discriminate successfully different picking-date on mandarin using LDA analysis. But, electronic nose was not able to detect a clear difference in volatile profile on mandarin using PCA analysis. During external validation using LDA was obtained to classified 92% of the total samples properly. Some sensors have the highest influence in the current pattern file for electronic nose PEN 2. A subset of few sensors can be chosen to explain all the variance. This result could be used in further studies to optimize the number of sensors.

Introduction

In recent years, extensive research has been focused on the development of non-destructive techniques for measuring quality attributes of fruit. In fact the quality concept is mainly related to the consumer perception and preference for foods. The consumer perception is based on the application of the five senses and for this reason the instrument “par excellence” to determine the quality are the human senses. Actually, panels of trained people are used to fix and label the criteria of quality, to assess the quality of food, and to help in the development of new products. From an instrumental point of view there is an obvious correlation between the human senses and the application of optical, chemical and tactile sensors. For several years the instrumental measure of the fruit quality has been mostly based on the basis of rheological properties such as texture and firmness [1].

The main disadvantage of the majority of these techniques is that they are not practical for cultivars or storage stations. Moreover, most of them require the destruction of the samples used for analysis. This is why, nowadays, optimal harvest dates and predictions of storage life are mainly based on practical experience, but, let these critical decisions to subjective interpretation implies that large quantities of fruit are harvested too soon or too late and reach consumer markets in poor condition.

In particular, many researches have been focused on the development of non-destructive techniques for measuring quality attributes of fruit. Among them aroma sensing are particularly promising to provide information on those parameters affected by the overall fruit quality.

A strategy for determining the state of ripeness consists of sensing the aromatic volatiles emitted by fruit using electronic olfactory systems [2]. These systems are concerning with the exploitation of the information contained in the headspace of fruits, they have been studied in the recent past with the conventional analytical chemistry equipment, and the correlation between the state of over-ripening and the fruit aroma has also been found both in quantitative and qualitative terms. Beside, some specific compounds have been identified as the responsible of the aroma of particular fruit.

In the last decade, the electronic nose technology has opened the possibility to exploit, from a practical point of view, the information contained in the headspace in many different application fields. Among them, food analysis is certainly one of the most often practiced.

The electronic nose offers a fast and non-destructive alternative to sense aroma, and, hence, may be advantageously used to predict the optimal harvest date. Commercially available electronic noses use an array of sensors combined with pattern recognition software. There have been several reports on electronic sensing in environmental control, medical diagnostics and the food industry [3], [4]. Some authors reported positive applications of electronic nose technology to the discrimination of different fruits quality, and many experiments were performed, such as: testing orange [5], melons [2], [6], blueberries [7], pears [8], [9], peaches [10], [11], [12], bananas [13], apples [11], [14], [15], [16] and nectarines [12].

The objectives in this research are: (1) to evaluate the capacity of electronic nose monitoring mandarin maturity during the different harvest periods, using a specific electronic nose device (PEN 2) based on sensor array and suitable pattern recognition techniques; (2) to study principal component analysis (PCA) and linear discriminant analysis (LDA) techniques to obtain whether the electronic nose be able to distinguish different ripeness; (3) to identify the sensors responsible for a discrimination in the current pattern file, using loading analysis.

Section snippets

Experimental material

Chinese variety, Satsuma mandarin “Zaojin Jiaogan” (C. reticulata) was selected to the experiment. All the samples were hand harvested in 2003 from the experimental orchard in Department of Horticulture, Zhejiang University. Mandarin were harvested at five different picking-dates with 15 intermittent days: September 19 (the first picking-day, day 0), October 3, 18, 31 (the second, third and fourth picking-day; were expressed as day 15, day 30, day 45 and day 60, respectively) and November 15

Electronic nose response to fruit aroma

Fig. 2 shows a typical response of ten sensors during measuring mandarin fruit. Each curve represents a different sensor transient. The curves represent sensor conductivity of one sensor of array against time due to electro-valve action when the volatiles from the fruit reach the measurement chamber. In that transition, the clean airflow that reaches the measurement chamber is substituted by airflow that comes from the concentration chamber, closing a loop circuit between both chambers. It can

Conclusions

The obtained results prove that the electronic nose PEN 2 can differ successfully the mandarin ripeness, and have been demonstrated that electronic nose technology has excellent sensitivity and selectivity for differentiating mandarin on the basis of picking-date.

The electronic nose was not able to detect a clear difference in volatile profile on mandarin using PCA analysis; but it achieves a clear separation in all the cases using LDA analysis.

Sensors 2, 7 and 9 in mandarin have the highest

Acknowledgement

The authors acknowledge the financial support of Program for New Century Excellent Talents in Chinese University.

Antihus Hernández Gómez received his Eng Degree, MEng Degree in agricultural mechanization in 1993 and 1998, respectively from Havana Agricultural University, Cuba, and Dr Eng Degree in 2005 from Zhejiang University, China. He has been an Assistant Professor at Havana Agricultural University since 1995. His current interests are non-destructive technologies in agriculture include using electronic noses.

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Antihus Hernández Gómez received his Eng Degree, MEng Degree in agricultural mechanization in 1993 and 1998, respectively from Havana Agricultural University, Cuba, and Dr Eng Degree in 2005 from Zhejiang University, China. He has been an Assistant Professor at Havana Agricultural University since 1995. His current interests are non-destructive technologies in agriculture include using electronic noses.

Jun Wang received his BEng Degree and MEng Degree in Agricultural Engineering in 1986 and 1988, respectively, and Dr Eng Degree in 1991 from Zhejiang Agricultural University. He has been a Professor at Zhejiang University since 1999. His main areas of current interest are in electronic noses and measurement automation for evaluation of food quality.

Annia García Pereira received her Eng Degree, MEng Degree in agricultural mechanization in 1997 and 2000, respectively from Havana Agricultural University, Cuba, and Dr Eng Degree in 2005 from Zhejiang University, China. She has been working as an Assistant Professor at Havana Agricultural University since 1999. Her current interests include the introduction of non-destructive technologies in agriculture.

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