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University of Arizona (1987)

CONTRIBUTION OF YIELD COMPONENTS TO RUBBER PRODUCTION IN GUAYULE

DIERIG, DAVID ALLEN

Titre : CONTRIBUTION OF YIELD COMPONENTS TO RUBBER PRODUCTION IN GUAYULE.

Auteur : DIERIG, DAVID ALLEN.

Université de soutenance : University of Arizona

Grade : Doctor of Philosophy (PhD) 1987

Résumé
Guayule (Parthenium argentatum Gray) has the potential of becoming an important domestic source of natural rubber. Although some progress has been achieved in increasing yields, for guayule to become an economically feasible crop of the southwest desert, further increases in rubber yield, either by increasing biomass or the plant’s rubber content, are necessary. Providing the variability for these desired traits is present in available germplasm, the plant breeder must find a means of selecting for these two traits. It is obvious that biomass can be visually estimated, and it is therefore easier to select for this trait in comparison to the plant’s rubber content. Due to practical consideration such as harvesting and processing, high rubber content becomes more desirable than extremely large plants. However, it is hoped that measured characters can be found to predict both traits in order to aid the plant breeder. The variables measured in this study were percent rubber and resin, rubber and resin yield(g/plt.), plant height (cm), width (cm) and volume m³, fresh and dry weight (kg/plt.), mean steam diameter (cm), total and mean steam area (cm²), total and mean stem circumference (cm), total circumference/total area (cm⁻¹), stem number, percent dry weight, and regeneration. This study examined a field with 234 guayule breeding lines. A high amount of variability existed both within and among these lines. It was found that dry weight (kg/plt.) had the best correlation to rubber yields (r = 0.92) and plant volume best predicts dry weight (r = 0.84), but none of these variables correlated well with rubber content. The best statistical regression model for percent rubber included four variables, fresh and dry weight (kg/plt.), dry weight (%) and plant volume (m³). This model accounted for 51% of the variability. In comparison, the best regression on rubber yield had an R² = 0.85 for our variables including plant height (cm), width (cm), volume (m³) and dry weight (kg/plt.). It is obvious that rubber yields may be more easily increased by selecting for biomass. However, it appears that in the long term, increases in rubber content will be of critical importance for maximum efficiency. Therefore, a measurable indication of rubber content is needed to aid in selecting for this trait.

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