Color relationships between lint and seed cotton

It is desirable to predict lint cotton color in advance of processing the cotton in a gin. Improvements over the use of seed cotton color as the lone predictor are needed. Standard lint color and trash content measurements were made on 61 samples of lint and seed cotton to determine the predictability of lint color from that of seed cotton. Also, visible spectral data were collected from the seed cotton and lint samples, and from corresponding samples of fuzzy and seed. Simple and multiple linear regression were conducted to determine the relationships among lint color, seed cotton color, and spectral data. Trash content data and spectral data from cotton seed were applied in addition to seed cotton data in an effort to enhance the predictability of lint color. Results from linear regression showed that seed cotton color correlated moderately (R2 approximately 0.6) with lint color. Seed cotton and lint reflectances at individual 50-nm spectral bands correlated poorly (R2 approximately 0.2). With trash content in the analysis, the fit was improved (R2 approximately 0.4). Seed spectral data also improved the correlations (R2 approximately 0.4). In addition, seed spectral data improved the correlations between seed cotton color and lint color (from R2 approximately 0.6 to R2 approximately 0.7). Ratios of seed spectral data were about as effective as the spectral data themselves. The inclusion of seed cotton spectral data in these models improved correlations slightly more (from R2 approximately 0.7 to R2 approximately 0.8). Adjusting lint and seed cotton spectral data for trash and seed reflectance was largely unsuccessful in improving correlations between lint and seed cotton spectral data. The regression methods and data relationships mentioned above are discussed in detail in the article.