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Growth and Tissue Elemental Composition Response of Butterhead Lettuce (Lactuca sativa, cv. Flandria) to Hydroponic Conditions at Different pH and Alkalinity
Indexado
WoS WOS:000458694100001
Scopus SCOPUS_ID:85069500918
DOI 10.3390/HORTICULTURAE3030041
Año 2017
Tipo artículo de investigación

Citas Totales

Autores Afiliación Chile

Instituciones Chile

% Participación
Internacional

Autores
Afiliación Extranjera

Instituciones
Extranjeras


Abstract



Biomass and tissue elemental differences were quantified for lettuce grown in deep-water conventional hydroponic conditions at two pH and alkalinity conditions. Nutrient solutions were created using inorganic salts and either reverse osmosis (RO) water or municipal water with high alkalinity. Three treatments were evaluated: (a) nutrient solution created with reverse osmosis (RO) water and maintained at pH 5.8 (H5); (b) same as H5 but maintained at pH 7.0 (H7); and (c) nutrient solution created using municipal water and maintained at pH 7.0, referred to as HA7. Averaged across three trials, the HA7 and H7 treatments produced 26% less shoot fresh weight (FW) than the H5 treatment with an 18% reduction in dry weight (DW). The H5 treatment had the least biomass in root FW and DW. In tissue elemental analyses, both the pH 7.0 treatments showed lower concentrations than H5 in Cu, N, Mo, and Sr, and increased concentrations in Ba, Mg, Na, and Zn. There were no differences in Al, C, Ca, Fe, K, Mn, Ni, P, S, and Si concentrations among treatments (p = 0.05). The results from this experiment can be used to isolate the effects of pH and alkalinity in aquaponic conditions where pH and alkalinity will mimic HA7 conditions.

Revista



Revista ISSN
Horticulturae 2311-7524

Métricas Externas



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Disciplinas de Investigación



WOS
Horticulture
Scopus
Plant Science
Horticulture
SciELO
Sin Disciplinas

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Publicaciones WoS (Ediciones: ISSHP, ISTP, AHCI, SSCI, SCI), Scopus, SciELO Chile.

Colaboración Institucional



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Autores - Afiliación



Ord. Autor Género Institución - País
1 Anderson, Tyler S. Hombre CORNELL UNIV - Estados Unidos
Cornell University - Estados Unidos
2 Martini, Miguel R. Hombre
3 de Villiers, David Hombre CORNELL UNIV - Estados Unidos
Cornell University - Estados Unidos
4 Timmons, Michael B. Hombre CORNELL UNIV - Estados Unidos
Cornell University - Estados Unidos

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Financiamiento



Fuente
U.S. Department of Agriculture
Cooperative State Research, Education, and Extension Service, U.S. Department of Agriculture
Cornell University Agricultural Experiment Station federal formula funds
Cooperative State Research, Education, and Extension Service
Cornell University Agricultural Experiment Station

Muestra la fuente de financiamiento declarada en la publicación.

Agradecimientos



Agradecimiento
This research was supported entirely by the Cornell University Agricultural Experiment Station federal formula funds, Project No. 1237650 and NYC-123421 received from Cooperative State Research, Education, and Extension Service, U.S. Department of Agriculture. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture. We would like to thank Pamela Schwartz, Erica Cartusciello, ZachWielgosz, and Haydn Lenz for their assistance in data collection and daily maintenance of the production systems. We would like to thank Francoise Vermeylen from the Cornell Statistical Consulting Unit for her assistance and guidance in the statistical models and analysis.
Acknowledgments: This research was supported entirely by the Cornell University Agricultural Experiment Station federal formula funds, Project No. 1237650 and NYC-123421 received from Cooperative State Research, Education, and Extension Service, U.S. Department of Agriculture. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture. We would like to thank Pamela Schwartz, Erica Cartusciello, Zach Wielgosz, and Haydn Lenz for their assistance in data collection and daily maintenance of the production systems. We would like to thank Francoise Vermeylen from the Cornell Statistical Consulting Unit for her assistance and guidance in the statistical models and analysis.

Muestra la fuente de financiamiento declarada en la publicación.