Testing of two methods novel to ultrasonic measurements was carried out on cheese samples to estimate the Time-of-Flight (TOF) parameter. The Short Time Average/Long Time Average (STA/LTA) method and the Autoregressive Akaike Information Criterion Picker (AR-AIC picker) method are used mainly in seismology for earthquake event detection. The STA/LTA method proved to be ineffective with such noise level that is present during ultrasonic measurements, but the AIC picker algorithm yielded reliable results. A new approach for classification was tested on two types of samples, those were matching in composition, but different in treatment and texture. The method used is based on the results of wavelet decomposition, and after retrieving sufficient spectral data, a linear discriminant analysis (DA) resulted in 100% correct classification, which was compared to the DA classification results based on other methods.
Authors:J. Felföldi, I. Kertész, D. Nagy, and V. Zsom-Muha
In the case of organic production the quality assessment of the fruits and vegetables is especially important. Monitoring of the maturation and ripening process, early detection of diseases, decision about harvest date and postharvest treatment need reliable, objective and – preferably – non-destructive quality testing methods. Dynamic hardness or stiffness measurement methods (resonance, impact, wave propagation) offer very useful tools in this field, but with strong limitations in applicability area and/or physical interpretation of the measured parameters. Our objective was to develop method and appropriate portable instrumentation to measure surface hardness – as quality measure – with a nondestructive method.
The computer controlled instrument has an electromagnetically excited impactor fitted with a piezoelectric acceleration sensor, a signal conditioner and A/D converter. To ensure the uniform contact behavior (contact area) between the impactor and the tested produce of wide range of shape, spherical head was applied. Conclusively, Hertz contact theory is to be applied for evaluation of the impact signal. Instead of using empirical “hardness index” – as in the case of several existing instruments – our objective was the physical interpretation of the contact phenomena. The measured acceleration signal was mathematically processed to calculate real physical parameters (force, speed, deformation), and to characterize the process similarly to the widely used texture analyzers, penetrometers. A new hardness parameter – “dynamic elastic modulus” – was introduced. According to the methodological investigations, the measurement was found to be perfectly non-destructive for a wide range of products. Conclusively, the developed method offers a useful tool for quality evaluation of organic horticultural products.
Authors:Zs. Bodor, Cs. Benedek, T. Kaszab, J.-L. Zinia Zaukuu, I. Kertész, and Z. Kovacs
Honey is produced by honeybees from nectar, sap of plant parts, or the juicy material secreted by sucking insects living on trees. It is rich in nutritionally useful components, the occurrence of which highly depends on the botanical and geographical origin of honey. Our goal is to develop a new, rapid, and accurate combination of analytical methods for identification of botanical and geographical origin.
Physicochemical parameters (pH, electrical conductivity, moisture, and ash content), colour (L*a*b*), and antioxidant properties were determined in addition to correlative techniques, such as electronic tongue and near infrared spectroscopy. For the statistical evaluation ANOVA, principal component analysis, and linear discriminant analysis were applied.
Results showed significant differences (P<0.05) in physicochemical properties, colour, and antioxidant capacity according to the botanical origin of honeys. Electronic tongue (ET) and near infrared spectroscopy (NIR) techniques were useful in the identification of the botanical and geographical origin, showing generally good accuracy.
The physicochemical parameters are important and can serve as reference methods, completing NIR and ET as target techniques, which are promising, but need further improvement for the determination of honey origin.
Authors:Z. Áy, Z. Kerényi, A. Takács, M. Papp, I. Petróczi, R. Gáborjányi, D. Silhavy, J. Pauk, and Z. Kertész
The reliable monitoring of field virus infections of crop species is important for both farmers and plant breeders. The aim of this study was to detect virus infections of winter wheat in the 2006/2007 season. Twelve well-known winter wheat varieties were sown on two different dates (11
of October and 3
of November 2006). Leaves of two individuals from each genotype were collected on 23rd of April 2007 to detect the virus infections (
Barley stripe mosaic virus
Barley yellow dwarf virus
Wheat dwarf virus
— WDV and
Wheat streak mosaic virus
— WSMV) after an extra mild autumn- and wintertime. Virus infections were detected by enzyme-linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR). The aphid-transmitted BYDV-PAV was found frequently whereas other viruses were presented very rarely or were not detected. Forty-six per cent of the tested wheat plants proved to be infected by BYDV-PAV in ELISA, while using PCR, the virus infections with BYDV-PAV was found in 58% of the samples. Further, these results suggest that the optimal sowing time is critical in the control of cereal virus diseases, and additionally, that wheat varieties respond to the virus infections differently.
Authors:G. Ónodi, Gy. Kröel-Dulay, E. Kovács-Láng, P. Ódor, Z. Botta-Dukat, B. Lhotsky, S. Barabás, J. Garadnai, and M. Kertész
Aboveground plant biomass is one of the most important features of ecosystems, and it is widely used in ecosystem research. Non-destructive biomass estimation methods provide an important toolkit, because the destructive harvesting method is in many cases not feasible. However, only few studies have compared the accuracy of these methods in grassland communities to date. We studied the accuracy of three widely used methods for estimation of aboveground biomass: the visual cover estimation method, the point intercept method, and field spectroscopy. We applied them in three independent series of field samplings in semi-arid sand grasslands in Central Hungary. For each sampling method, we applied linear regression to assess the strength of the relationship between biomass proxies and actual aboveground biomass, and used coefficient of determination to evaluate accuracy. We found no evidence that the visual cover estimation, which is generally considered as a subjective method, was less accurate than point intercept method or field spectroscopy in estimating biomass. Based on our three datasets, we found that accuracy was lower for the point intercept method compared to the other two methods, while field spectroscopy and visual cover estimation were similar to each other in the semi-arid sand grassland community. We conclude that visual cover estimation can be as accurate for estimating aboveground biomass as other approaches, thus the choice amongst the methods should be based on additional pros and cons associated with each of the method and related to the specific research objective.