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 determ ine the predictability of lint color from that of seed cotton. Also, v isible spectral data were collected from the seed cotton and lint samp les, and from corresponding samples of fuzzy and delinted seed. Simple and multiple linear regression were conducted to determine the relati onships among lint color, seed cotton color, and spectral data. Trash content data and spectral data, from cotton seed were applied in addit ion to seed cotton data in an effort to enhance the predictability of lint color. Results from linear regression showed that seed cotton col or correlated moderately (R(2) approximate to 0.6) with lint color. Se ed cotton and lint reflectances at individual 50-nm spectral bands cor related poorly (R(2) approximate to 0.2). With trash content in the an alysis, the fit was improved (R(2) approximate to 0.4). Seed spectral data also improved the correlations (R(2) approximate to 0.4). In addi tion, seed spectral data improved the correlations between seed cotton color and lint color (from R(2) approximate to 0.6 to R(2) approximat e to 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 R(2) approxi mate to 0.7 to R(2) approximate to 0.8). Adjusting lint and seed cotto n spectral data for trash and seed reflectances was largely unsuccessf ul in improving correlations between lint and seed cotton spectral dat a. The regression methods and data relationships mentioned above are d iscussed in detail in the article.