Gamma radiation effects on seed germination, growth and pigment content, and ESR study of induced free radicals in maize (Zea mays)

The effects of gamma radiation are investigated by studying plant germination, growth and development, and biochemical characteristics of maize. Maize dry seeds are exposed to a gamma source at doses ranging from 0.1 to 1 kGy. Our results show that the germination potential, expressed through the final germination percentage and the germination index, as well as the physiological parameters of maize seedlings (root and shoot lengths) decreased by increasing the irradiation dose. Moreover, plants derived from seeds exposed at higher doses (≤0.5 kGy) did not survive more than 10 days. Biochemical differences based on photosynthetic pigment (chlorophyll a, chlorophyll b, carotenoids) content revealed an inversely proportional relationship to doses of exposure. Furthermore, the concentration of chlorophyll a was higher than chlorophyll b in both irradiated and non-irradiated seedlings. Electron spin resonance spectroscopy used to evaluate the amount of free radicals induced by gamma ray treatment demonstrates that the relative concentration of radiation-induced free radicals depends linearly on the absorbed doses.     

A generalizing,analytic model for 2-way cross-classifications. extensions and ramifications. part 1

A generalizing, analytic model is developed for 2-way cross-classifications with fixed class sizes The model is expressed in closed form as a simple operator formula, and is readily extended to n-way cross-classifications, and to such cases where one or more cells are vacuous or fixed. The model permits easy derivation, by means of simple differential operators, of the exact power moments, product moments, and factorial moments of the cell frequencies. From this, the moments of the exact sampling distribution of the conventional x₂-statistic can be computed, which, in turn, leads to a reappraisal of the Chi-square approximation for sparse and isotropic contingency tables. Here, the Gamma distribution is considered, and numerical results are presented that would suggest preference of the Gamma approximation over the Chi-square in such cases.