Reproductive Performance and Fiber Quality Responses of Cotton to Potassium Nutrition

Abstract

Potassium (K) deficiency affects cotton growth and development and fiber properties. An experiment was conducted in an outdoor pot culture facility by imposing four potassium stress treatments (100%, 40%, 20% and 0% of optimum K level) prior to flowering during 2010 and 2011 growing season. Upland cotton cultivar, TM-1, was seeded in the pots comprised of fine sand as rooting medium. Flowers and bolls were tagged daily to estimate boll maturation period (BMP). Leaf samples were collected every four days from flowering to maturity to estimate leaf K content. Plant height and node numbers were recorded from emergence to 21 days after treatment. Photosynthesis and stomatal conductance were measured weekly from day of treatment imposition to physiological maturity at an interval of seven days. Stem, leaf, and boll dry-component weights, and boll numbers were recorded at the end of the experiment in each year. From each boll, the lint samples were collected and grouped based on average leaf potassium concentration during BMP, and fiber quality parameters were recorded for each group in each treatment. At high K deficient (0 K) condition, total biomass declined by 27% and 28% in years 2010 and 2011, respectively. Significantly, lower numbers of bolls were retained per plant at 0 K stress treatment during both the years. Leaf photosynthesis (r2 = 0.92) and stomatal conductance (r2 = 0.80) declined with declining leaf K levels. Fiber length, strength, micronaire, and uniformity declined linearly with decrease in leaf K content. Weaker fibers with medium length were produced under K-deficient conditions with micronaire values in the discount range. Fiber uniformity, however, did not decline with decrease in leaf K. The identified leaf K status-specific relationships for fiber properties could be used to improve management practices under potassium deficiency and to develop new sub-routines of the existing cotton simulation models. New and improved models will be useful not only in management, but also in arena of policy decisions including future climate change impact assessment analysis.