Literature DB >> 11513671

Comparison of major and trace element concentrations in Danish greenhouse tomatoes (Lycopersicon esculentum Cv. Aromata F1) cultivated in different substrates.

V Gundersen1, D McCall, I E Bechmann.   

Abstract

The concentration of major and trace elements was determined for tomato (Lycopersicon esculentumcv. Aromata F1) fruits grown in three different substrate systems. The systems were soil and rockwool irrigated with a normal nutrient solution and rockwool irrigated with a nutrient solution with elevated electrical conductivity (EC). At three harvest times, tomato fruits were analyzed for Ca, Cu, Fe, K, Mg, Mn, Na, P, S, Sr, and Zn by ICP-AES and for Cd, Cr, Mo, Ni, Pb, Sn, and V by HR-ICPMS. The concentrations of Ca, Cd, Fe, Mn, Mo, Na, Ni, Sr, and Zn were significantly different (p < 0.05) for tomato fruits grown on the different substrates. Between the harvest times different levels (p < 0.05) were shown for Ca, Cd, Fe, Mn Na, Ni, Sr, Zn Cu, K, Mg, P, Sn, and V. The concentration of Cd was >15 times higher and the concentration of Ca was 50-115% higher in soil-grown fruits than in rockwool-grown fruits. Principal component analysis applied on each harvest split the data into two groups. One group includes soil-grown fruits, and the other group includes rockwool-grown fruits with the two different nutrient solutions.

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Year:  2001        PMID: 11513671     DOI: 10.1021/jf0103774

Source DB:  PubMed          Journal:  J Agric Food Chem        ISSN: 0021-8561            Impact factor:   5.279


  3 in total

1.  Health-promoting substances and heavy metal content in tomatoes grown with different farming techniques.

Authors:  Filippo Rossi; Francesco Godani; Terenzio Bertuzzi; Marco Trevisan; Federico Ferrari; Sergio Gatti
Journal:  Eur J Nutr       Date:  2008-07-05       Impact factor: 5.614

2.  Identification of Relevant Phytochemical Constituents for Characterization and Authentication of Tomatoes by General Linear Model Linked to Automatic Interaction Detection (GLM-AID) and Artificial Neural Network Models (ANNs).

Authors:  Marcos Hernández Suárez; Gonzalo Astray Dopazo; Dina Larios López; Francisco Espinosa
Journal:  PLoS One       Date:  2015-06-15       Impact factor: 3.240

3.  A tool to assure the geographical origin of local food products (glasshouse tomatoes) using labeling with rare earth elements.

Authors:  Donata Bandoniene; Thomas Meisel; Alessandra Rachetti; Christoph Walkner
Journal:  J Sci Food Agric       Date:  2018-06-12       Impact factor: 3.638

  3 in total

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