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264 results on '"Mazzei, Pierluigi"'

7. MRI and HR-MAS NMR spectroscopies to correlate structural characteristics and the metabolome of Fiano and Pallagrello grapes with the action of field spray preparation 500 and the soil spatial microvariability

Author

Mazzei, Pierluigi, primary, Sica, Andrea, additional, Migliaro, Claudio, additional, Altieri, Gessica, additional, Funicello, Nicola, additional, Pasquale, Salvatore, additional, Piccolo, Alessandro, additional, and Celano, Giuseppe, additional

Published
2024
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9. A community-built calibration system: The case study of quantification of metabolites in grape juice by qNMR spectroscopy

Author

Musio, Biagia, Ragone, Rosa, Todisco, Stefano, Rizzuti, Antonino, Latronico, Mario, Mastrorilli, Piero, Pontrelli, Stefania, Intini, Nicola, Scapicchio, Pasquale, Triggiani, Maurizio, Di Noia, Tommaso, Acquotti, Domenico, Airoldi, Cristina, Assfalg, Michael, Barge, Alessandro, Bateman, Lorraine, Benevelli, Francesca, Bertelli, Davide, Bertocchi, Fabio, Bieliauskas, Aurimas, Borioni, Anna, Caligiani, Augusta, Callone, Emanuela, Čamra, Ales, Cesare Marincola, Flaminia, Chalasani, Dinesh, Consonni, Roberto, Dambruoso, Paolo, Davalli, Silvia, David, Taylor, Diehl, Bernd, Donarski, James, Gil, Ana M., Gobetto, Roberto, Goldoni, Luca, Hamon, Erwann, Harwood, John S., Kobrlová, Andrea, Longobardi, Francesco, Luisi, Renzo, Mallamace, Domenico, Mammi, Stefano, Martin-Biran, Magali, Mazzei, Pierluigi, Mele, Andrea, Milone, Salvatore, Molero Vilchez, Dolores, Mulder, Roger J., Napoli, Claudia, Ragno, Daniele, Randazzo, Antonio, Rossi, Maria Cecilia, Rotondo, Archimede, Šačkus, Algirdas, Sáez Barajas, Elena, Schievano, Elisabetta, Sitaram, Bhavaraju, Stevanato, Livio, Takis, Panteleimon G., Teipel, Jan, Thomas, Freddy, Torregiani, Elisabetta, Valensin, Daniela, Veronesi, Marina, Warren, John, Wist, Julien, Zailer-Hafer, Elina, Zuccaccia, Cristiano, and Gallo, Vito

Published
2020
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23. An integrated multilevel approach unveils complex seed-nanoparticle interactions and their implications for seed priming

Author

Università degli Studi di Salerno, European Research Council, European Commission, Agencia Estatal de Investigación (España), Ministerio de Ciencia, Innovación y Universidades (España), Cappetta, Elisa, Del Regno, Carmine, Conte, Marisa, Castro-Hinojosa, Christian, Del Sol-Fernández, Susel, Vergata, Chiara, Buti, Matteo, Curcio, Rossella, Onder, Anil, Mazzei, Pierluigi, Funicello, Nicola, De Pasquale, Salvatore, Terzaghi, Mattia, Del Gaudio, Pasquale, Leone, Antonietta, Martinelli, Federico, Moros, María, Ambrosone, Alfredo, Università degli Studi di Salerno, European Research Council, European Commission, Agencia Estatal de Investigación (España), Ministerio de Ciencia, Innovación y Universidades (España), Cappetta, Elisa, Del Regno, Carmine, Conte, Marisa, Castro-Hinojosa, Christian, Del Sol-Fernández, Susel, Vergata, Chiara, Buti, Matteo, Curcio, Rossella, Onder, Anil, Mazzei, Pierluigi, Funicello, Nicola, De Pasquale, Salvatore, Terzaghi, Mattia, Del Gaudio, Pasquale, Leone, Antonietta, Martinelli, Federico, Moros, María, and Ambrosone, Alfredo

Abstract

Nanotechnology has the potential to revolutionize agriculture with the introduction of engineered nanomaterials. However, their use is hindered by high cost, marginal knowledge of their interactions with plants, and unpredictable effects related to massive use in crop cultivation. Nanopriming is an innovative seed priming technology able to match economic, agronomic, and environmental needs in agriculture. The present study was focused on unveiling, by a multilevel integrated approach, undisclosed aspects of seed priming mediated by iron oxide magnetic nanoparticles in pepper seeds (Capsicum annuum), one of the most economically important crops worldwide. Inductively coupled plasma atomic emission mass spectrometry and scanning electron microscopy were used to quantify the MNP uptake and assess seed surface changes. Magnetic resonance imaging mapped the distribution of MNPs prevalently in the seed coat. The application of MNPs significantly enhanced the root and vegetative growth of pepper plants, whereas seed priming with equivalent Fe concentrations supplied as FeCl3 did not yield these positive effects. Finally, global gene expression by RNA-sequencing identified more than 2,200 differentially expressed genes, most of them involved in plant developmental processes and defense mechanisms. Collectively, these data provide evidence on the link between structural seed changes and an extensive transcriptional reprogramming, which boosts the plant growth and primes the embryo to cope with environmental challenges that might occur during the subsequent developmental and growth stages.

Published
2023

25. An Integrated Multilevel Approach Unveils Complex Seed–Nanoparticle Interactions and Their Implications for Seed Priming.

Author

Cappetta, Elisa, Del Regno, Carmine, Conte, Marisa, Castro-Hinojosa, Christian, Del Sol-Fernández, Susel, Vergata, Chiara, Buti, Matteo, Curcio, Rossella, Onder, Anil, Mazzei, Pierluigi, Funicello, Nicola, De Pasquale, Salvatore, Terzaghi, Mattia, Del Gaudio, Pasquale, Leone, Antonietta, Martinelli, Federico, Moros, Maria, and Ambrosone, Alfredo

Published
2023
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27. Compost-derived thermophilic microorganisms producing glycoside hydrolase activities as new potential biocatalysts for sustainable processes

Author

Finore, Ilaria, primary, Leone, Luigi, additional, Gioiello, Alessia, additional, Romano, Ida, additional, Cangemi, Silvana, additional, Mazzei, Pierluigi, additional, Piccolo, Alessandro, additional, Cattaneo, Andrea, additional, Nicolaus, Barbara, additional, Kambourova, Margarita, additional, Poli, Annarita, additional, and Lama, Licia, additional

Published
2022
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40. Additional file 1 of Assessment of geographical origin and production period of royal jelly by NMR metabolomics

Author

Mazzei, Pierluigi, Piccolo, Alessandro, Brescia, Marianna, and Caprio, Emilio

Abstract

Additional file 1: Fig. S1. Pollen traps fastened at the hive entrance and enabling the pollen stripping and collection. The pollen accumulates in a side opening drawer when the bees, during their access into the hive, walk through the metallic mesh which connects the pollen trap to the landing board of the hive. The trap is composed of round shaped holes that strip the pollen grains from either the pollen basket or the corbicula on outside of the tibia on the hind legs of the bees. Fig. S2. 1H-NMR spectrum of a representative Italian RJ dissolved in phosphate buffer solution (0.2M, pH 7.3) prepared with d2O and containing TMSPA (d = 0 ppm) as internal standard. The proton acquisition was carried out by applying the presaturation technique to suppress the residual water signal at ≈ 4.704 ppm. Fig. S3. 2D 1H-1H NMR COSY spectrum of a representative Italian RJ dissolved in phosphate buffer solution (0.2M, pH 7.3) prepared with d2O and containing TMSPA (d = 0 ppm) as internal standard. The acquisition was carried out by applying the presaturation technique to suppress the residual water signal at ≈ 4.704 ppm. Fig. S4. Superimposition of 2D 1H-13C NMR HSQC (red) and HMBC (blue) spectra of a representative Italian RJ dissolved in phosphate buffer solution (0.2M, pH 7.3) prepared with d2O and containing TMSPA as internal standard. Fig. S5. Significant loading vectors related to the PCA score-plot shown in Fig. 3 and based on 1H NMR spectra of Royal Jelly samples produced from two Bologna (Bo1 and Bo6) and four Grosseto (Gr2, Gr3, Gr4 and Gr5) farms on the 30th of May 2016. Fig. S6. PLS-DA results based on 1H NMR spectra of Royal Jelly samples produced from Bologna (squares) and Grosseto (circles) farms on the 30th of May 2016. (A) PLS-DA Cross-validation score-plot, where full and holed objects differentiate samples belonging to either the training or the test set, respectively. (B) PLS-DA classification results and Q2/R2 values related to the PLS-DA components 1 and 2; (C) PLS-DA cross-validation results.Fig. S7. PLS-DA results based on 1H NMR spectra of Royal Jelly samples produced from the two Bologna farms Bo1 (blue squares) and Bo6 (green squares) on the 30th of May 2016. (A) PLS-DA Cross-validation score-plot, where full and holed squares differentiate samples belonging to either the training or the test set, respectively. (B) PLS-DA classification results and Q2/R2 values related to the PLS-DA components 1 and 2; (C) PLS-DA cross-validation results. Fig. S8. PLS-DA results based on 1H NMR spectra of Royal Jelly samples produced from the four Grosseto farms Gr2, Gr3, Gr4 and GR5 (light green, dark green, orange and red circles, respectively) on the 30th of May 2016. (A) PLS-DA Cross-validation score-plot, where full and holed circles differentiate samples belonging to either the training or the test set, respectively. (B) PLS-DA classification results and Q2/R2 values related to the PLS-DA components 1 and 2; (C) PLS-DA cross-validation results. Fig. S9. Significant loading vectors related to the PCA score-plot shown in Fig. 4 and based on 1H NMR spectra of Royal Jelly samples of Italian (produced the 8th of July 2016) and Chinese (distributed in 2016) geographical origin. Fig. S10. PLS-DA results based on 1H NMR spectra of Royal Jelly samples of Italian and Chinese geographical origin. (A) PLS-DA Cross-validation score-plot, where full and holed objects differentiate samples belonging to either the training or the test set, respectively. (B) PLS-DA classification results and Q2/R2 values related to the PLS-DA component 1; (C) PLS-DA cross-validation results. Fig. S11. Significant loading vectors related to the PCA score-plots shown in Fig. 5A (A), 5B (B) and 5C (C) and based on 1H NMR spectra of Royal Jelly samples produced by three Grosseto farms in different days (see the legend). The label 3-hydroxy correspond to 3-hydroxybutyrate. Fig. S12. Significant loading vectors related to the PCA score-plots shown in Fig. 6 and based on 1H NMR spectra of Royal Jelly samples produced by three Italian farms (Bo1, Bo6 and Gr5) on the 13th of June and deriving from a monofloral production conducted in the presence of either chestnut, trifolium or linden flowerings. Table S1. The table reports the name and the most relevant information related to the Italian farms involved in the project. Table S2. Results of ANOVA test (Benjamini-Hochberg’s test, a = 0.05) informing on the significance of the most discriminant variables associated to the PCs of score-plots shown in Figs. 3 and 4, respectively, and explaining a total variance

Published
2020
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42. A community-built calibration system: The case study of quantification of metabolites in grape juice by qNMR spectroscopy

Author

Musio, B, Ragone, R, Todisco, S, Rizzuti, A, Latronico, M, Mastrorilli, P, Pontrelli, S, Intini, N, Scapicchio, P, Triggiani, M, Di Noia, T, Acquotti, D, Airoldi, C, Assfalg, M, Barge, A, Bateman, L, Benevelli, F, Bertelli, D, Bertocchi, F, Bieliauskas, A, Borioni, A, Caligiani, A, Callone, E, Čamra, A, Cesare Marincola, F, Chalasani, D, Consonni, R, Dambruoso, P, Davalli, S, David, T, Diehl, B, Donarski, J, Gil, A, Gobetto, R, Goldoni, L, Hamon, E, Harwood, J, Kobrlová, A, Longobardi, F, Luisi, R, Mallamace, D, Mammi, S, Martin-Biran, M, Mazzei, P, Mele, A, Milone, S, Molero Vilchez, D, Mulder, R, Napoli, C, Ragno, D, Randazzo, A, Rossi, M, Rotondo, A, Šačkus, A, Sáez Barajas, E, Schievano, E, Sitaram, B, Stevanato, L, Takis, P, Teipel, J, Thomas, F, Torregiani, E, Valensin, D, Veronesi, M, Warren, J, Wist, J, Zailer-Hafer, E, Zuccaccia, C, Gallo, V, Musio, Biagia, Ragone, Rosa, Todisco, Stefano, Rizzuti, Antonino, Latronico, Mario, Mastrorilli, Piero, Pontrelli, Stefania, Intini, Nicola, Scapicchio, Pasquale, Triggiani, Maurizio, Di Noia, Tommaso, Acquotti, Domenico, Airoldi, Cristina, Assfalg, Michael, Barge, Alessandro, Bateman, Lorraine, Benevelli, Francesca, Bertelli, Davide, Bertocchi, Fabio, Bieliauskas, Aurimas, Borioni, Anna, Caligiani, Augusta, Callone, Emanuela, Čamra, Ales, Cesare Marincola, Flaminia, Chalasani, Dinesh, Consonni, Roberto, Dambruoso, Paolo, Davalli, Silvia, David, Taylor, Diehl, Bernd, Donarski, James, Gil, Ana M., Gobetto, Roberto, Goldoni, Luca, Hamon, Erwann, Harwood, John S., Kobrlová, Andrea, Longobardi, Francesco, Luisi, Renzo, Mallamace, Domenico, Mammi, Stefano, Martin-Biran, Magali, Mazzei, Pierluigi, Mele, Andrea, Milone, Salvatore, Molero Vilchez, Dolores, Mulder, Roger J., Napoli, Claudia, Ragno, Daniele, Randazzo, Antonio, Rossi, Maria Cecilia, Rotondo, Archimede, Šačkus, Algirdas, Sáez Barajas, Elena, Schievano, Elisabetta, Sitaram, Bhavaraju, Stevanato, Livio, Takis, Panteleimon G., Teipel, Jan, Thomas, Freddy, Torregiani, Elisabetta, Valensin, Daniela, Veronesi, Marina, Warren, John, Wist, Julien, Zailer-Hafer, Elina, Zuccaccia, Cristiano, Gallo, Vito, Musio, B, Ragone, R, Todisco, S, Rizzuti, A, Latronico, M, Mastrorilli, P, Pontrelli, S, Intini, N, Scapicchio, P, Triggiani, M, Di Noia, T, Acquotti, D, Airoldi, C, Assfalg, M, Barge, A, Bateman, L, Benevelli, F, Bertelli, D, Bertocchi, F, Bieliauskas, A, Borioni, A, Caligiani, A, Callone, E, Čamra, A, Cesare Marincola, F, Chalasani, D, Consonni, R, Dambruoso, P, Davalli, S, David, T, Diehl, B, Donarski, J, Gil, A, Gobetto, R, Goldoni, L, Hamon, E, Harwood, J, Kobrlová, A, Longobardi, F, Luisi, R, Mallamace, D, Mammi, S, Martin-Biran, M, Mazzei, P, Mele, A, Milone, S, Molero Vilchez, D, Mulder, R, Napoli, C, Ragno, D, Randazzo, A, Rossi, M, Rotondo, A, Šačkus, A, Sáez Barajas, E, Schievano, E, Sitaram, B, Stevanato, L, Takis, P, Teipel, J, Thomas, F, Torregiani, E, Valensin, D, Veronesi, M, Warren, J, Wist, J, Zailer-Hafer, E, Zuccaccia, C, Gallo, V, Musio, Biagia, Ragone, Rosa, Todisco, Stefano, Rizzuti, Antonino, Latronico, Mario, Mastrorilli, Piero, Pontrelli, Stefania, Intini, Nicola, Scapicchio, Pasquale, Triggiani, Maurizio, Di Noia, Tommaso, Acquotti, Domenico, Airoldi, Cristina, Assfalg, Michael, Barge, Alessandro, Bateman, Lorraine, Benevelli, Francesca, Bertelli, Davide, Bertocchi, Fabio, Bieliauskas, Aurimas, Borioni, Anna, Caligiani, Augusta, Callone, Emanuela, Čamra, Ales, Cesare Marincola, Flaminia, Chalasani, Dinesh, Consonni, Roberto, Dambruoso, Paolo, Davalli, Silvia, David, Taylor, Diehl, Bernd, Donarski, James, Gil, Ana M., Gobetto, Roberto, Goldoni, Luca, Hamon, Erwann, Harwood, John S., Kobrlová, Andrea, Longobardi, Francesco, Luisi, Renzo, Mallamace, Domenico, Mammi, Stefano, Martin-Biran, Magali, Mazzei, Pierluigi, Mele, Andrea, Milone, Salvatore, Molero Vilchez, Dolores, Mulder, Roger J., Napoli, Claudia, Ragno, Daniele, Randazzo, Antonio, Rossi, Maria Cecilia, Rotondo, Archimede, Šačkus, Algirdas, Sáez Barajas, Elena, Schievano, Elisabetta, Sitaram, Bhavaraju, Stevanato, Livio, Takis, Panteleimon G., Teipel, Jan, Thomas, Freddy, Torregiani, Elisabetta, Valensin, Daniela, Veronesi, Marina, Warren, John, Wist, Julien, Zailer-Hafer, Elina, Zuccaccia, Cristiano, and Gallo, Vito

Abstract

Nuclear Magnetic Resonance (NMR) is an analytical technique extensively used in almost every chemical laboratory for structural identification. This technique provides statistically equivalent signals in spite of using spectrometer with different hardware features and is successfully used for the traceability and quantification of analytes in food samples. Nevertheless, to date only a few internationally agreed guidelines have been reported on the use of NMR for quantitative analysis. The main goal of the present study is to provide a methodological pipeline to assess the reproducibility of NMR data produced for a given matrix by spectrometers from different manufacturers, with different magnetic field strengths, age and hardware configurations. The results have been analyzed through a sequence of chemometric tests to generate a community-built calibration system which was used to verify the performance of the spectrometers and the reproducibility of the predicted sample concentrations.

Published
2020

45. The fate of cigarette butts in different environments: Decay rate, chemical changes and ecotoxicity revealed by a 5-years decomposition experiment

Author

Bonanomi, Giuliano, primary, Maisto, Giulia, additional, De Marco, Anna, additional, Cesarano, Gaspare, additional, Zotti, Maurizio, additional, Mazzei, Pierluigi, additional, Libralato, Giovanni, additional, Staropoli, Alessia, additional, Siciliano, Antonietta, additional, De Filippis, Francesca, additional, La Storia, Antonietta, additional, Piccolo, Alessandro, additional, Vinale, Francesco, additional, Crasto, Antonio, additional, Guida, Marco, additional, Ercolini, Danilo, additional, and Incerti, Guido, additional

Published
2020
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50. Chapter 5. NMR methodologies in food analysis

Author

Mannina, Luisa, Sobolev, Anatoly Petrovich, Aru, Violetta, Bellomaria, Alessia, Bertocchi, Fabio, Botta, Bruno, Cagliani, Ruth Laura, Caligiani, Augusta, Capozzi, Francesco, Çela, Dorisa, Cesare Marincola, Flaminia, Ciampa, Alessandra, Del Coco, Laura, Consonni, Roberto, Corsaro, Carmelo, Delfini, Maurizio, Di Tullio, Valeria, Fanizzi, Francesco Paolo, Gallo, Vito, Ghirga, Francesca, Gianferri, Raffaella, Girelli, Chiara Roberta, Ingallina, Cinzia, Laghi, Luca, Latronico, Mario, Longobardi, Francesco, Luchinat, Claudio, Mallamace, Domenico, Mammi, Stefano, Mandaliti, Walter, Marini, Federico, Mastrorilli, Pietro, Mazzei, Pierluigi, Miccheli, Alfredo, Micozzi, Alessandra, Salvatore, Milone, Mucci, Adele, Nepravishta, Ridvan, Paci, Maurizio, Palisi, Angelica, Piccolo, Alessandro, Picone, Gianfranco, Proietti, Noemi, Randazzo, Antonio, Righi, Valeria, Rotondo, Archimede, Salvo, Andrea, Savorani, Francesco, Scano, Paola, Schievano, Elisabetta, Sciubba, Fabio, Tenor, Ileonardo, Trimigno, Alessia, Turano, Paola, Vasi, Sebastiano, and Capitani, Donatella

Subjects
food composition, NMR, food science, chemometrics
Published
2017

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