Relationships between grain protein, Zn, Cu, Fe and Mn contents in wheat and soil and topographic attributes

Ayoubi, S and Mehnatkesh, A and Jalalian, A and Sahrawat, K L and Gheysari, M (2014) Relationships between grain protein, Zn, Cu, Fe and Mn contents in wheat and soil and topographic attributes. Archives of Agronomy and Soil Science, 60 (5). pp. 625-638. ISSN 0365-0340

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Abstract

The knowledge on the relationships of protein and micronutrient concentration in wheat grain with edaphic characteristics could provide valuable information for site specific fertilization of crops for producing grains denser in micronutrients such as iron (Fe) and zinc (Zn) in rainfed agriculture. In this study, we used soil properties and topographic parameters in the artificial neural network (ANN) methodology as power tool for improving models for predicting wheat grain micronutrient and protein contents in the hilly regions of western Iran. Soil and grain samples were collected from 1 m2 plots using stratified random method, whereas the slope positions were considered as the basis of soil sampling, at 100 selected points. The mean grain Zn, Fe, Cu (copper) and Mn (manganese) concentrations were 37.02, 65.86, 14.79 and 44.93 mg-1 kg-1, respectively, and mean grain protein was 13.76%. Application of the ANN models for predicting of Zn, Fe, Cu, Mn and protein contents in grains improved prediction 96.77, 95.45, 124.13, 125 and 109.75 %, respectively, over the multiple linear regression (MLR) models. The topographic parameters wetness index, plan curvature and shaded relief, and the selected soil properties total nitrogen (TN), soil organic matter, available phosphorus, and DTPA-extractable micronutrients were identified as the most important parameters for explaining the variability in wheat grain quality at the study area.

Item Type:	Article
Divisions:	RP-Resilient Dryland Systems
CRP:	CGIAR Research Program on Agriculture for Nutrition and Health (A4NH)
Uncontrolled Keywords:	artificial neural network, grain micronutrients, protein, terrain parameters
Subjects:	Others > Soil Science
Depositing User:	Mr Sanat Kumar Behera
Date Deposited:	21 Jul 2013 14:31
Last Modified:	19 Aug 2016 04:31
URI:	http://oar.icrisat.org/id/eprint/6942
Official URL:	http://dx.doi.org/10.1080/03650340.2013.825899
Projects:	UNSPECIFIED
Funders:	UNSPECIFIED
Acknowledgement:	UNSPECIFIED
Links:	Google Scholar

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