Assessment of salinity indices to identify Iranian wheat varieties using an artificial neural network-Reference-Cited by-同舟云学术

Assessment of salinity indices to identify Iranian wheat varieties using an artificial neural network

Published:2015-11-20 Issue:2 Volume:168 Page:185-194
ISSN:0003-4746
Container-title:Annals of Applied Biology
language:en
Short-container-title:Ann Appl Biol

Author:

Ravari S.Z.¹,Dehghani H.¹^ORCID,Naghavi H.²

Affiliation:

1. Department of Plant Breeding; Tarbiat Modares University; Tehran The Islamic Republic of Iran

2. Department of Agronomy; Agricultural and Natural Resources Research Centre; Kernan The Islamic Republic of Iran

Publisher

Wiley

Subject

Agronomy and Crop Science

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/aab.12254/fullpdf

Reference38 articles.

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2. Silage maize yield prediction using artificial neural networks;Bagheri;Journal of Plant Production,2012

3. Application salt tolerance indices for screening barley (Hordeum vulgare L.) cultivars;Bchini;International Journal of Current Research,2011

4. Sodium transport in the seedlings of two bread wheat (Triticum aestivum L.) genotypes showing contrasting salt stress tolerance;Benderradji;Australian Journal of Crop Science,2011

5. Stress tolerance in soybeans. I. evaluation of three screening techniques for heat and drought tolerance;Bouslama;Crop Science,1984

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