Genotype × Environment Interactions within Iron Deficiency Chlorosis‐Tolerant Soybean Genotypes

• Published in: Agronomy journal Vol. 98; no. 3; pp. 808 - 814
• Main Authors: Naeve, Seth L., Rehm, George W.
• Format: Journal Article
• Language: English
• Published: Madison American Society of Agronomy 01.05.2006
• Subjects: Adaptation to environment and cultivation conditions; Agronomy. Soil science and plant productions; Biological and medical sciences; Fundamental and applied biological sciences. Psychology; Genetics and breeding of economic plants; Genotypes; Nutrient deficiency; Soybeans; Varietal selection. Specialized plant breeding, plant breeding aims; Deficiency; Group VIII metal; Iron chlorosis; Tolerance; Genetic parameter; Genotype; Iron; Soybean; Inorganic element; Glycine max; Grain legume; Leguminosae; Genotype environment interaction; Dicotyledones; Agronomy; Angiospermae; Spermatophyta; Trace element (nutrient); Oil plant (vegetal)
• ISSN: 0002-1962; 1435-0645
• DOI: 10.2134/agronj2005.0281

Iron deficiency chlorosis (IDC) reduces total soybean [Glycine max (L.) Merr.] production in the USA by several million metric tonnes each year. Although IDC‐tolerant soybean varieties are available, variety screening is difficult and does not always provide reproducible results. More robust screening methods are needed, but it is unclear how soil properties impact varietal responses to IDC. This study evaluated genotype by environment (G × E) interactions among nine IDC‐tolerant soybean genotypes and one moderately tolerant genotype in IDC prone environments in Minnesota to determine which environmental factors most affect this putative G × E effect. Although visual severity of IDC within environments varied from moderate to severe over time, relative genotypic responses were similar, indicating that the timing of IDC ratings may not be critically important in ranking varieties for IDC. Across all environments a highly significant G × E interaction for yield was discovered, with soil factors creating a larger impact than year to year variation. Moreover, G × E interactions were found for visual IDC scores even when significant effects on yield were not found, indicating that variety screening based on IDC scores requires multiple locations to be predictive. Seed quality characteristics, as measured by protein and oil concentrations, were significantly affected by genotype, environment, and their interaction; however, these traits are likely indirectly affected by IDC through its effect on yield. A linear model based on three common soil chemical factors was developed to help predict future IDC severity by soil analysis alone.