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Abstract. Power generated from the direct burning of biomass, or biomass-coal cofiring, is useful in many applications. It can effectively reduce the use of fossil fuels, including coal and petroleum, and eliminate harmful emissions. Also, residual substances from the process can be recycled and turned into potassium fertilizer. Thus, a rapid quantitative analysis of potassium content in cotton stalks is of great significance. In the presented study, the application of laser-induced breakdown spectroscopy (LIBS) technique was used to quantitatively analyze potassium (K) content in cotton stalks from Chinese main regions. The dominant factors were selected via spectral collection to determine the optimal combination of parameters, which were: 80 collection dots with 25% laser energy, 400 μm spot size, delay time of 1.0 μs, and preforming pressure at 25 tons (T). The initial linear model constructed from the characteristic wavebands of K presented relatively low precision and accuracy. Thus, additional models were prepared that incorporated partial least squares (PLS) of wavebands at 760-781 nm, 400-780 nm, and the whole spectrum (190-950 nm) to enhance results. PLS models with wavebands at 760-781 nm and 190-950 nm exhibited the best effects with validation set relative standard deviations (RSD_v) of 5.95% and 7.38%, respectively. The PLS model considered 20 variables, which were selected by genetic algorithm (GA) in the waveband at 760-781 nm, and presented an RSD_v of 8.63%. We further analyzed the presence of other elements in stalks from GA-selected variables as well as their antagonistic and synergistic effects with K.