Elisa Masi

Spatiotemporal dynamics of the electrical network activity in the root apex

The study of electrical network systems, integrated with chemical signaling networks, is becoming a common trend in contemporary biology. Classical techniques are limited to the assessment of signals from doublets or triplets of cells at a fixed temporal bin width. At present, full characteristics of the electrical network distribution and dynamics in plant cells and tissues has not been established. Here, a 60-channels multielectrode array (MEA) is applied to study spatiotemporal characteristics of the electrical network activity of the root apex. Both intense spontaneous electrical activities and stimulation-elicited bursts of locally propagating electrical signals have been observed. Propagation of the spikes indicates the existence of excitable traveling waves in plants, similar to those observed in non-nerve electrogenic tissues of animals. Obtained data reveal synchronous electric activities of root cells emerging in a specific root apex region. The dynamic electrochemical activity of root apex cells is proposed to continuously integrate internal and external signaling for developmental adaptations in a changing environment.

DNA fingerprinting and genetic relatedness among cultivated varieties of Olea europaea L. estimated by AFLP analysis

Abstract Amplified fragment length polymorphism (AFLP) analysis was used to evaluate the genetic biodiversity and variability present in some Italian varieties of cultivated olive. A group of 12 genotypes belonging to three varieties was screened using six different AFLP primer combinations. A total of 274 loci (59.8% of which were polymorphic) were investigated. The number of polymorphic loci detected by single primer combination for each variety was calculated. AFLP banding patterns were transformed into binary data of presence–absence and matrices were processed with NTSYS- pc and A rlequin software programmes. Similarity relationships were described graphically by a dendrogram which clustered accessions of the same cultivar. Analysis of molecular variance (AMOVA) revealed greater variation among cultivars than within them, but significant intra-cultivar differentiation was found. For the varieties analysed, the data revealed significant genetic diversity in the cultivated olive tree, despite the fact that they come from a limited geographical area. The DNA fingerprinting technique used was confirmed to be a reproducible and sensitive tool for the study of population genetics of olive trees. The high genomic polymorphism observed suggests a more complex genetic population structure than the conventional variety or cultivar level. The present study confirms the importance of considering the degree of genetic relatedness and variability within populations during clone and variety selection programmes.

Class-modeling approach to PTR-TOFMS data: a peppers case study.

BACKGROUND Proton transfer reaction-mass spectrometry (PTR-MS), in its recently developed implementation based on time-of-flight mass spectrometry (PTR-TOFMS), was used to rapidly determine the volatile compounds present in fruits of Capsicum spp. RESULTS We analyzed the volatile organic compounds emission profile of freshly cut chili peppers belonging to three species and 33 different cultivars. PTR-TOFMS data, analyzed with appropriate and advanced multivariate class-modeling approaches, perfectly discriminated among the three species (100% correct classification in validation set). VIP (variable importance in projection) scores were used to select the 15 most important volatile compounds in discriminating the species. The best candidates for Capsicum spp. were compounds with measured m/z of 63.027, 101.096 and 107.050, which were, respectively, tentatively identified as dimethyl sulfide, hexanal and benzaldehyde. CONCLUSIONS Based on the promising results, the possibility of introducing multivariate class-modeling techniques, different from the classification approaches, in the field of volatile compounds analyses is discussed.

PTR-TOF-MS and HPLC analysis in the characterization of saffron (Crocus sativus L.) from Italy and Iran

Saffron samples from Italy and Iran were analyzed for their content in aroma and bioactive compounds with different analytical techniques. HPLC was used for the identification and quantification of crocins, picrocrocin, safranal and flavonoids content, while the novel proton transfer reaction time-of-flight mass spectrometer was employed for the aroma compounds analysis. Italian saffron turned out to be richer in total crocins and safranal contents. Sample characterization was performed with an unsupervised statistical approach; tests involving different numbers of parameters deriving from the two analytical techniques were performed. The results achieved showed that the best samples classification was obtained by joining the information acquired from both techniques; following such an approach, a sharper separation between Iranian and Italian samples was achieved. Finally, among the variables that most contribute to the description of variability, isophorone, safranal and picrocrocin were identified to be the most significant.

Genomic variability in Vitis vinifera L. “Sangiovese” assessed by microsatellite and non-radioactive AFLP test

EJB Electronic Journal of Biotechnology ISSN: 0717-3458 Vol.5 No.1, Issue of April 15, 2002© 2002 by Universidad Catolica de Valparaiso -- Chile Received July 26, 2001 / Accepted March 11, 2002

Artificial neural networks as a tool for plant identification: a case study on Vietnamese tea accessions

Seventeen tea accessions belonging to Chinese (Camellia sinensis), Assamic (C. sinensis var. assamica), and Shan tea (C. sinensis var. pubilimba) groups, which are either commercially planted or new promising tea germplasm, were morphologically described at Phu Tho province (Viet Nam) and assessed for their diversity. Fourteen phyllometric parameters were qualitatively and quantitatively investigated using digital image analysis. The accessions were then discriminated by a dedicated artificial neural network for univocal plant identification and a hierarchical cluster analysis was performed in order to build a dendrogram reporting the relationships among them. Results proved the diversity of investigated tea morphotypes from Phu Tho province based on a morphological screening. More, the artificial neural network was able to perform a correct identification for almost all the accessions using simple dedicated instruments.

PTR‐TOF‐MS analysis of volatile compounds in olive fruits

BACKGROUND Volatile compounds of Cellina di Nardò and Ogliarola Barese, two typical Italian olive varieties, have been characterised at different ripening stages. Proton transfer reaction-time-of-flight-mass spectrometry (PTR-TOF-MS) was used for the first time on these fruits with the aim of characterising the volatile profile and, in the case of Ogliarola, the changes which may occur during the maturation process. RESULTS PTR-TOF-MS does not involve any sample pre-treatment, and allows high-resolution measurements, large spectra and small fragmentation of the volatiles. Therefore it allows both compound identification and data statistical treatments. In the present work, about 40 compounds that contribute to the discrimination between samples of the two varieties have been identified. CONCLUSIONS Three groups of compounds were identified: (1) compounds that are typical of mature fruits of Ogliarola, (2) compounds that tend to decrease during the change from green to mature fruits, and (3) compounds that increase during the maturation process.

Use of volatile organic compounds and physicochemical parameters for monitoring the post-harvest ripening of imported tropical fruits

The trade of fresh fruits from tropical countries has steadily increased over the past decades, but limited familiarity of consumers with these products has limited their introduction in worldwide markets. The increasing competition in European and international fruit markets is generating the need for improved ripeness evaluation techniques to assess fruit quality standards. As tropical fruits produce a wide range of volatile organic compounds (VOCs), PTR-ToF-MS was used to fingerprint the volatile profile of four tropical fruits (avocado, banana, mango and mangosteen) and determine whether this instrument could be used to assess fruit ripening stages, which was measured with traditional methods. Data were subsequently subjected to partial least squares discriminant analysis. By pooling the entire dataset together, it emerges that VOCs and chemical analyses enabled the separation of the two different ripening stages of all fruits, while skin color and fruit firmness did not always enable that separation. For avocado, banana and mangosteen, it was possible to observe the process of maturation during the shelf life, via physicochemical parameters and VOC analysis, whereas for mango, the constant production of methanol and acetaldehyde detected at both stages, together with the unchanged of evolution of the physicochemical parameters (TSS, pH and color), indicated a lack of maturation. Given the rapidity and the potential to use this analysis method on a large scale, the PTR-ToF-MS has a high potential to become a commercial standard tool for monitoring food quality from entering the storage chain up to the ‘ready to eat’ labeling.

Forward and inverse modelling approaches for prediction of light stimulus from electrophysiological response in plants

In this paper, system identification approach has been adopted to develop a novel dynamical model for describing the relationship between light as an environmental stimulus and the electrical response as the measured output for a bay leaf (Laurus nobilis) plant. More specifically, the target is to predict the characteristics of the input light stimulus (in terms of on–off timing, duration and intensity) from the measured electrical response – leading to an inverse problem. We explored two major classes of system estimators to develop dynamical models – linear and nonlinear – and their several variants for establishing a forward and also an inverse relationship between the light stimulus and plant electrical response. The best class of models are given by the Nonlinear Hammerstein–Wiener (NLHW) estimator showing good data fitting results over other linear and nonlinear estimators in a statistical sense. Consequently, a few set of models using different functional variants of NLHW has been developed and their accuracy in detecting the on–off timing and intensity of the input light stimulus are compared for 19 independent plant datasets (including 2 additional species viz. Zamioculcas zamiifolia and Cucumis sativus) under similar experimental scenario.

Comparing fractal analysis, electrical impedance and electrolyte leakage for the assessment of cold tolerance in Callistemon and Grevillea spp.

Summary Lethal low temperatures were examined in two species of Grevillea and four species of Callistemon, two taxa originating from Australia. The demand in Europe and America for Australian plants is increasing both as cut flowers and as potted or landscape plants, but there is little information available on the cold hardiness of these species. LT50 (lethal temperature at which 50% of damage occurs) was determined by measuring electrical conductivity (electrolyte leakage), impedance spectroscopy and fractal spectrum of leaf colour. All the experiments were conducted on non-acclimated and cold-acclimated plants. LT50 calculated on non-acclimated plants were about 2–3°C higher than in acclimated plants, except for G. olivacea. In every case, the LT50 estimated by the three methods were very similar and ranged from –4.6°C for G. olivacea, the species most sensitive to freezing, to about –9.5°C for C. salignus, the most resistant to freezing among the species tested.