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Sweet corn response to combined nitrogen and salinity environmental stresses
Year:
2003
Source of publication :
Plant and Soil
Authors :
Ben-Gal, Alon
;
.
Volume :
256
Co-Authors:
Shenker, M., Dept. of Soil and Water Sciences, Fac. Agric., Food Environ. Qual. S., Hebrew University of Jerusalem, Rehovot 76100, Israel
Ben-Gal, A., Arava Research and Development, M.E. Eilot 8882, Israel
Shani, U., Dept. of Soil and Water Sciences, Fac. Agric., Food Environ. Qual. S., Hebrew University of Jerusalem, Rehovot 76100, Israel
Facilitators :
From page:
139
To page:
147
(
Total pages:
9
)
Abstract:
To define the nature of the combined response curve of sweet corn (Zea mays L.) plants to nitrogen and salinity, a lysimeter study was designed to follow water and solute budgets with combinations of the two variables over wide ranges of 0.5-7.5 dS m-1 and 0-150% of local N-fertilization recommendations. Patterns of water-use efficiency, N content, N uptake, and shoot dry-matter yield indicated the predominance of environmental interactions over Cl-nitrate physiological antagonism. At low salinities, the leaf N content, N uptake, and yield increased with increased N fertilization up to 45% of local N-fertilization recommendations, nitrogen was efficiently stripped from the percolating water and practically no nitrate was leached. At higher N fertilization the amount of leached N increased linearly with increased N input, and N uptake and yield were independent of N rates, levelling off at increased values for decreased salinities. The Liebig-Sprengel and Mitscherlich-Baule models were evaluated against measured data; both achieved similar values for the system's inherent N, the salinity level corresponding with zero-yield, and the predicted yields, which were highly correlated with the experimental data (R2 > 0.9). It is suggested that both models can be used successfully in mechanistic-based plant-soil solution models to predict yield, water and nutrient needs, and the resulted N leaching.
Note:
Related Files :
Environmental stress
growth response
Interactions
nitrogen
salinity
water use efficiency
Zea
Zea mays
Show More
Related Content
More details
DOI :
10.1023/A:1026274015858
Article number:
Affiliations:
Database:
Scopus
Publication Type:
article
;
.
Language:
English
Editors' remarks:
ID:
27936
Last updated date:
02/03/2022 17:27
Creation date:
17/04/2018 00:35
Scientific Publication
Sweet corn response to combined nitrogen and salinity environmental stresses
256
Shenker, M., Dept. of Soil and Water Sciences, Fac. Agric., Food Environ. Qual. S., Hebrew University of Jerusalem, Rehovot 76100, Israel
Ben-Gal, A., Arava Research and Development, M.E. Eilot 8882, Israel
Shani, U., Dept. of Soil and Water Sciences, Fac. Agric., Food Environ. Qual. S., Hebrew University of Jerusalem, Rehovot 76100, Israel
Sweet corn response to combined nitrogen and salinity environmental stresses
To define the nature of the combined response curve of sweet corn (Zea mays L.) plants to nitrogen and salinity, a lysimeter study was designed to follow water and solute budgets with combinations of the two variables over wide ranges of 0.5-7.5 dS m-1 and 0-150% of local N-fertilization recommendations. Patterns of water-use efficiency, N content, N uptake, and shoot dry-matter yield indicated the predominance of environmental interactions over Cl-nitrate physiological antagonism. At low salinities, the leaf N content, N uptake, and yield increased with increased N fertilization up to 45% of local N-fertilization recommendations, nitrogen was efficiently stripped from the percolating water and practically no nitrate was leached. At higher N fertilization the amount of leached N increased linearly with increased N input, and N uptake and yield were independent of N rates, levelling off at increased values for decreased salinities. The Liebig-Sprengel and Mitscherlich-Baule models were evaluated against measured data; both achieved similar values for the system's inherent N, the salinity level corresponding with zero-yield, and the predicted yields, which were highly correlated with the experimental data (R2 > 0.9). It is suggested that both models can be used successfully in mechanistic-based plant-soil solution models to predict yield, water and nutrient needs, and the resulted N leaching.
Scientific Publication
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