A model of cotton (Góssypium sp) lint yield that equated yield to the volume of a parallelepiped with three dimensions was developed by Kerr. The model is extended to basic units by dividing the axes of the parallelepiped and the seed is recognized as the basic unit of yield. Yield per seed, per boll, and per unit area of land can be stated in equation form by using the divisions of the axes. The relative contributions of the primary lint yield components decrease as the complexity of the model increases from yield/seed to yield/unit area of land. The summation of each model has an upper R3 limit of 1.0. Therefore by the inclusion of additional components, the relative contribution of yield components from the previous models must decrease. Data are presented that illustrate a use of the model to define the component of yield more susceptible to alteration to increase yield.
Fiber tenacity, elongation, length, fineness, and color were measured for 5 Gossypium barbadense L. and 37 G. hirsutum L. fiber samples. These samples were spun into 12- and 27-tex yarns on a ring system and into 27-tex yarns on an open-end system; yarn tenacity was determined. Fiber tenacity and length were positively correlated with yarn tenacity. No correlations of fiber fineness with tenacity of 27-tex yarns were detected. A substantial portion of the variation in 27-tex yarn tenacity was attributable to variations in fiber tenacity and length.
Oil content, protein content, seed index, and percent immature seed were determined on 136 cottonseed samples (Gossypium hirsutum L.) from the 1973 National Cotton Variety Tests. Samples of four cultivars from two replications at 17 locations were used to study seed quality parameters. Environment influenced the level of oil and seed maturity far more than did the cultivars. A differential response of cultivars across the 17 environments for oil content and seed maturity was explained on the basis of genotypic differences in growth and fruiting patterns and their response to diverse climates. Cultivars had as much influence on protein content as environmental conditions but no interaction was detected. The results indicate that breeders might find it more feasible to screen for protein content than oil content, unless greater diversity for oil content can be found in cotton germplasm.
Cotton fiber cellulose was dissolved in the solvent dimethyl acetamide with lithium chloride without cleanup or formation of derivatives. Molecular weight distributions of cotton fiber samples were obtained by gel permeation chromatography using commercially available instrumentation. Upland cotton fiber samples from three varieties (Deltapine Acala 90, Deltapine 41, and DES 422) possessed similar physical properties, indicated by measurements of fiber length, Micronaire, and strength by Stelometer, except for inconsistencies in the HVI strength values compared to those determined by Stelometer. An evaluation of the samples demonstrated different molecular weight distributions, different peak locations of the secondary wall, and different weight average molecular weights. Fiber quality is a major concern for all segments of Jthe cotton industry. Fiber properties of various varieties cotton from major commercial production areas of the United States have been cataloged for many years [ 7 ] . Physical properties serve as predictors of performance, but interpreting measurements has not always been successful when correlating fiber quality with results from processing.The linear polymer cellulose occurs in relatively pure (about 96% ) form in cotton fibers. Polymers are composed of a distribution of chains of varying molecular weights reflecting the polymerization process. The molecular weight distribution influences the mechanical properties of the polymer. In the plastics and polymer industries, gel permeation chromatography (GPC) is widely used to obtain molecular weight distributions for tailoring materials for desired end uses. The molecular weight distribution of a polymer is considered one of the most useful characteristics to determine [5].For polymers, a direct correlation exists between both increasing molecular weight and narrowing molecular weight distribution and improving tensile strength, abrasion resistance, and toughness. The weight average molecular weight is particularly sensitive to the presence of high molecular weight species. Conversely, the number average molecular weight is very sensitive to changes in the weight fractions of low molecular weight species and relatively insensitive to similar changes for high molecular weight species [ 1 ] . The weight average molecular weight correlates to a greater extent with the mechanical properties of a polymer than does the number average. Properties involving large deformations such as tensile strength depend primarily on the long chain nature of the polymers. Physical properties associated with small deformations like stiffness are influenced by the nature of the crystalline state.The ability to identify and characterize the product has limited advances in fundamental research of cellulose biosynthesis. Molecular weight characterization of cotton has been hampered by the lack of suitable nondegrading solvents for cellulose. Using derivatives such as nitrate makes the analyses tedious and lengthy.New solvents for non-native cellulose to be used for mol...
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