The effect of leaf shape variation on plantherbivore interactions has primarily been studied from the perspective of host seeking behavior. Yet for leaf shape to affect plant-herbivore coevolution, there must be reciprocal effects of leaf shape variation on herbivore consumption and performance. We investigated whether alternative leaf morphs affected the performance of three generalist insect herbivores by taking advantage of a genetic polymorphism and developmental plasticity in leaf shape in the Ivyleaf morning glory, Ipomoea hederacea. Across four experiments, we found variable support for an effect of leaf shape genotype on insects. For cabbage loopers (Trichoplusia ni) and corn earworms (Helicoverpa zea) we found opposing, non-significant trends: T. ni gained more biomass on lobed genotypes, while H. zea gained more biomass on heartshaped genotypes. For army beetworms (Spodoptera exigua), the effects of leaf shape genotype differed depending on the age of the plants and photoperiod of growing conditions. Caterpillars feeding on tissue from older plants (95 days) grown under long day photoperiods had significantly greater consumption, dry biomass, and digestive efficiency on lobed genotypes. In contrast, there were no significant differences between heart-shaped and lobed genotypes for caterpillars feeding on tissue from younger plants (50 days) grown under short day photoperiods. For plants grown under short days, we found that S. exigua consumed significantly less leaf area when feeding on mature leaves than juvenile leaves, regardless of leaf shape genotype. Taken together, our results suggest that the effects of leaf shape variation on insect performance are likely to vary between insect species, growth conditions of the plant, and the developmental stage and age of leaves sampled.
A tool to facilitate the feasibility study of a newly proposed multi-station injection molding system is developed. The conceptual design and proposed embodiment of the new system are geared toward the development of a system flexible enough to handle multiple part types and production volumes. A comprehensive design model is used to structure the problem by identifying the desired design objectives and the effect the system variables have on the final design. An Evolutionary Algorithm optimization is used to find the combination of system variables that yields optimal system outputs. The algorithm uses a number of components customized to suit the design requirements of the proposed system. This optimization and evaluation process provides a basis by which the new system can be compared with traditional injection molding practices. Results confirm that the new multi-station system is less affected by the degree of product variety than traditional molding machines.
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