Braglia, Chiara ;
Alberoni, Daniele ;
Di Gioia, Diana ;
Giacomelli, Alessandra ;
Bocquet, Michel ;
Bulet, Philippe
(2024)
Data for the application of a robust MALDI mass spectrometry approach for bee pollen investigation.
University of Bologna.
DOI
10.6092/unibo/amsacta/7717.
[Dataset]
Full text available as:
Abstract
The dataset contains results on honeybee pollen extracted and analyzed with MALDI MS.
Our experiment involved honeybee pollen grains from five different Italian regions (Campania, Sardinia, Sicily, South Tirol and Tuscany) through the spring 2023. Pollen sample were collected from the honeybee colonies with standard pollen traps every two weeks for four months. The generated dataset concern different pollen extraction methods. In order to define the best experimental conditions to record robust and the most representative and distinguishable spectra for a pollen species, different conditions of extraction were tested, four different solutions: (a) 2M acetic acid 2M (2M AA) and 50% acetonitrile (50% ACN); (b) AA 2M; (c) 2% ACN and 0.1% trifluoroacetic acid (0.1% TFA); and (d) a solution of 1% TFA) and two mechanical extraction methods (stirring and ultrasonication). Moreover, 10-fold serial dilutions of the crude extracted material from the different bee pollen balls were evaluated (10, 100 and 1,000 times) to determine the most appropriate sample to matrix ratio.
Abstract
The dataset contains results on honeybee pollen extracted and analyzed with MALDI MS.
Our experiment involved honeybee pollen grains from five different Italian regions (Campania, Sardinia, Sicily, South Tirol and Tuscany) through the spring 2023. Pollen sample were collected from the honeybee colonies with standard pollen traps every two weeks for four months. The generated dataset concern different pollen extraction methods. In order to define the best experimental conditions to record robust and the most representative and distinguishable spectra for a pollen species, different conditions of extraction were tested, four different solutions: (a) 2M acetic acid 2M (2M AA) and 50% acetonitrile (50% ACN); (b) AA 2M; (c) 2% ACN and 0.1% trifluoroacetic acid (0.1% TFA); and (d) a solution of 1% TFA) and two mechanical extraction methods (stirring and ultrasonication). Moreover, 10-fold serial dilutions of the crude extracted material from the different bee pollen balls were evaluated (10, 100 and 1,000 times) to determine the most appropriate sample to matrix ratio.
Document type
Dataset
Creators
Keywords
mass spectrometry, molecular mass fingerprint, trifluoroacetic acid, acetonitrile, machine learning model, plant biodiversity.
Subjects
DOI
Contributors
Deposit date
10 Jun 2024 16:09
Last modified
10 Jun 2024 16:09
Project name
Funding program
MUR-EC - PNRR Missione 4 Componente 2 Investimento 1.4
URI
Other metadata
Document type
Dataset
Creators
Keywords
mass spectrometry, molecular mass fingerprint, trifluoroacetic acid, acetonitrile, machine learning model, plant biodiversity.
Subjects
DOI
Contributors
Deposit date
10 Jun 2024 16:09
Last modified
10 Jun 2024 16:09
Project name
Funding program
MUR-EC - PNRR Missione 4 Componente 2 Investimento 1.4
URI
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