Effects of Potassium Nutrition on Corn (Zea mays L.) Physiology and Growth for Modeling

Author:

Thenveettil Naflath1ORCID,Reddy Krishna N.2,Reddy Kambham Raja1ORCID

Affiliation:

1. Department of Plant and Soil Sciences, Mississippi State University, 117 Dorman Hall, P.O. Box 9555, Mississippi State, MS 39762, USA

2. Crop Production Systems Research Unit, U.S. Department of Agriculture-Agricultural Research Service, 141 Experimental Station Road, P.O. Box 350, Stoneville, MS 38776, USA

Abstract

Potassium (K) deficiency in corn is an emerging concern, especially when the crop is exposed to stress conditions. The insufficient replenishment of K in soil heightens the severity. A good K management requires adequate knowledge of its effect on plant growth and physiology. A sunlit growth chamber study was conducted under five levels of potassium concentrations, 100% (control; 193 ppm), 40%, 20%, 5%, and 0%, using modified Hoagland’s nutrient solution applied at first leaf stage and continued until tasseling. The plant growth and development were monitored at different growth stages. Physiological parameters were measured at the tasseling stage. Significant differences (p < 0.05 to 0.001) in plant growth and physiological parameters were recorded in response to potassium rates. The 0% K treatment reduced the leaf K content and addition of leaf area day−1 by 85% and 8%, respectively, compared to the control. The rate of total biomass accumulation reduced to 5.4 g day−1 under 0% K compared to 7.7 g day−1 under the control. The root-to-shoot ratio increased to 0.33 at 5% K compared to 0.16 at the control treatment. The photosynthetic rate was reduced by 30% and 35% under 5% and 0% potassium concentrations, respectively, compared to the control. The 0% K deficiency decreased the stomatal conductance by 60% over control, lowering the internal CO2 level and transpiration. Linear and quadratic relationships were observed between leaf K content and electron transport rate (R2 = 0.98) and transpiration rate (R2 = 0.96), respectively. The functional relationships generated from this study will help improve corn models for field applications.

Funder

United States Department of Agriculture

USDA NIFA

USDA-ARS NACA

Mississippi Corn Promotion Board

Publisher

MDPI AG

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