Submitted to: Agronomy Journal
Publication Type: Peer reviewed journal
Publication Acceptance Date: 4/1/2007
Publication Date: 11/6/2007
Citation: Mahan, J.R., Gitz, D.C. 2007. A dynamic model of cotton emergence based on the thermal dependence of malate synthase. Agronomy Journal. 99(6):668-674. Interpretive Summary: In some regions cotton is commonly planted when soil and air temperatures are lower-than-optimal. Later in the planting period, higher-than-optimal temperatures can occur. Understanding the magnitude and timing of temperature stress on cotton seedlings may prove helpful in the development of cotton cultivars and management practices that will improve performance of seedlings. In this study a basic metabolic indicator of optimum temperature was developed and used to analyze thermal stress on cotton. The metabolic indicator was based on the response of the enzyme malate synthase to temperature. The indicator was used to develop a simple model to predict temperature affects on cotton seedling emergnce. The basic model works as well or better than previous emergence predictors. It is proposed that a metabolic indicator of optimal temperature represents an improvement over previously used definitions.
Technical Abstract: Cotton (Gossypium hirsutum L.) is frequently planted when temperatures are not optimal for germination and emergence. Delayed emergence, a common contributor to diminished plant performance later in the season is often related to delayed emergence resulting from non-optimal temperatures. Improvement of cotton performance requires knowledge of the source, pattern and magnitude of thermal limitations on seedling metabolism. In this study the thermal dependence of malate synthase, an enzyme involved in cotton seedling lipid metabolism, was used to define the pattern and magnitude of thermal limitations and as the basis of a metabolic model to predict emergence under variable temperatures in the field. Soil temperature at seed depth was monitored over the cotton planting season of 2005 and characterized as optimal, sub-optimal and supra-optimal. Sub-optimal temperatures were common and supra-optimal temperatures were limited. A metabolic model to predict emergence was developed and predicted emergence was in agreement with that of field plantings and a widely used degree-day based model. A metabolic indicator of thermal optimality may prove useful in studies of seedling responses to thermal variation.