Portable vs. Benchtop NIR-Sensor Technology for Classification and Quality Evaluation of Black Truffle.

Klemens Losso,Matthias Rainer,Christian W Huck,Günther K Bonn,Christoph Kappacher,Benedikt Trübenbacher

doi:10.3390/molecules27030589

Klemens Losso, Matthias Rainer + Show 4 more

Open Access

https://doi.org/10.3390/molecules27030589

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Abstract

Truffles represent the best known and most expensive edible mushroom. Known as Ascomycetes, they belong to the genus Tuber and live in symbiosis with plant host roots. Due to their extraordinary taste and smell, truffles are sold worldwide for high prices of up to 3000–5000 euros per kilogram (Tuber magnatum PICO). Amongst black truffles, the species Tuber melanosporum VITTAD. is highly regarded for its organoleptic properties. Nonetheless, numerous different sorts of black truffle are offered at lower prices, including Tuber aestivum VITTAD., Tuber indicum and Tuber uncinatum, which represent the most frequently consumed types. Because truffles do not differ visually for inexperienced consumers, food fraud is likely to occur. In particular, for the highly prized Tuber melanosporum, which morphologically forms very similar fruiting bodies to those of Tuber indicum, there is a risk of fraud via imported truffles from Asia. In this study, 126 truffle samples belonging to the four mentioned species were investigated by four different NIR instruments, including three miniaturized devices—the Tellspec Enterprise Sensor, the VIAVI solutions MicroNIR 1700 and the Consumer Physics SCiO—working on different technical principles. Three different types of measurement techniques were applied for all instruments (outer shell, rotational device and fruiting body) in order to identify the best results for classification and quality assurance in a non-destructive manner. Results provided differentiation with an accuracy up to 100% for the expensive Tuber melanosporum from Tuber indicum. Classification between Tuber melanosporum, Tuber indicum, Tuber aestivum and Tuber uncinatum could also be achieved with success of 100%. In addition, quality monitoring including discrimination between fresh and frozen/thawed, and prediction of the approximate date of harvesting, was performed. Furthermore, feasibility studies according to the geographical origin of the truffle were attempted. The presented work compares the performance for prediction and quality monitoring of portable vs. benchtop NIR devices and applied measurement techniques in order to be able to present a suitable, accurate, fast, non-destructive and reliable method for consumers.

Highlights

It can be observed that T. indicum and T. melanosporum can be separated from T. aestivum and T. uncinatum by the naked eye, especially in the range of higher wavenumbers
Classification between these two groups is hardly feasible without spectroscopic pretreatment and chemometric analysis
To be able to compare the results of the four different NIR devices, the root mean square error of calibration (RMSEC)

Summary

Introduction

Food fraud occurs globally in many kinds of food products, including most common food categories such as olive oil [1], fish [2], milk [3] and coffee [4]. In addition to minimizing the risk to health if toxic substances are applied for adulteration, a means of developing high-quality products with verifiable origin and quality is desired. Food fraud scandals, such as the addition of melamine in baby formula in China [10] or the European horse-meat scandal [11], have increased the pressure on food laboratories to investigate and explore fast screening methods for the detection of food adulteration. Spectroscopic methods are ideally suited for this purpose as they enable non-destructive, fast, green and reliable measurements [12,13,14,15,16,17,18]

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