In-season soil moisture content is recognized as an important factor relating to post-harvest cotton fiber quality. Soil moisture can be controlled by irrigation, which is the most practical tool available to farmers in controlling the growth of cotton. The objective of this study is to quantify the relationship between post-harvest cotton fiber quality and in-season soil moisture content for both irrigated and rain-fed regimes. This experiment was conducted on the 321.9-ac. Impact Center Research Farm of Texas A&M University. Three 0.75-ac. regular grids were laid out in both irrigated and dry-land areas. A total of 86 sampling points (40 irrigated and 46 non-irrigated) were selected from the grids for data collection. At each sampling point, soil moisture content was measured and recorded weekly from seedling to boll maturation. Seedcotton was hand picked, ginned with a laboratory saw gin, and subjected to HVI testing to obtain fiber quality measurements. Also included in this study were NRCS soil survey data, weather data, NRCS grid soil sampling data from 2001, and remote-sensing data from 2003. The hypotheses to be tested were as follows: 1) there are underlying factors (e.g., irrigation and precipitation for moisture content replenishment, and soil texture for drainage and moisture retention) governing the soil moisture content over time, and 2) the variability of post-harvest cotton fiber quality can be largely explained by in-season soil moisture content. Factor analysis will be applied to identify the underlying factors governing soil moisture content during the cotton growing season. Multiple linear regression analysis will be applied to develop prediction models for cotton fiber quality based on in-season soil moisture content measurements or the factor scores for both irrigated and rain-fed cotton. Valid prediction models for cotton fiber quality developed in this study are expected to provide irrigation strategies for desired cotton fiber quality, both spatially and temporally.