Effect of selection intensity and population size on percent oil in maize, Zea mays L

Abstract

The effect of selection intensity and population size on the response to selection for percent oil in the grain of maize (Zea mays L.) was evaluated in a replicated experiment over ten cycles of selection. An open-pollinated variety, Armel's Reid Yellow Dent, was divided into subpopulations of 6,10 and 50 plants. Selection proportions of 17% and 5% were imposed upon each subpopulation. Selection was based on the percentage of oil in individual kernels as determined by wide-line nuclear magnetic resonance spectroscopy. As expected, total response to selection increased with larger population sizes and selection intensities. The concave shape of the response curves suggested that an appreciable part of the genetic variance can be attributed to additive genes at high initial frequencies, dominance genes at low initial frequencies, or to the generation of negative linkage disequilibrium due to selection. The consistently greater loss of vigor experienced by the more intensely selected populations reflects the enhancement of inbreeding due to artificial selection, an effect that increases with the intensity of selection. The results indicate that combined selection, based on kernels and using within- and amongfamily information, will be more efficient than other conventional selection procedures, including the normal combined scheme where selection is based on plants.

Relationship of Genetic Variation to Population Size in Wildlife

“…Quantitative genetic variation was related to population size, although there were far fewer data than for allozyme variation. Responses to artificial selection were greater in larger populations of Drosophila melanogaster Jones et al 1968;Hammond 1973;Franklin 1980;Weber 1990;Weber & Diggins 1990), mice (Eisen 1975), and maize (Silvela et al 1989). Phenotypic variation will reflect quantitative genetic variation if environmental variation is similar across populations.…”

Single-Kernel Maize Analysis by Near-Infrared Hyperspectral Imaging

“…Intuitively, the ability to analyze smaller samples of grain will yield greater increases in quality per selection generation, since fewer low-quality seeds will be planted in each group. Silvela et al (1989) demonstrated that the rate of oil content gain was significantly greater if breeding selection occurred on a single-kernel basis, as opposed to composite samples containing all kernels on an ear. NIRS single-seed quality analysis has been applied to predict oil and protein content in maize, wheat, and soybeans (Orman and Schumann, 1992;Abe et al, 1995); moisture content in maize, lima beans, peanuts, soybeans, and sunflower (Norris and Hart, 1965;Finney and Norris, 1978;Norris, 1983;Lamb and Hurburgh, 1991); oil content in meadowfoam (Patrick and Jolliff, 1997); oleic and linoleic acid in sunflower (Sato et al, 1995;Velasco et al, 1999a); and oil, protein, glucosinolate content, and oleic, linoleic, and erucic acid concentration in rapeseed (Sato et al, 1998;Velasco et al, 1999b;Velasco et al, 1999c).…”

Determination of Soybean Oil, Protein and Amino Acid Residues in Soybean Seeds by High Resolution Nuclear Magnetic Resonance (NMRS) and Near Infrared (NIRS)

“…Effective breeding techniques require accurate, inexpensive and reliable soybean composition analysis. Certain areas of breeding and selection research would also benefit from single soybean seed analysis (Silvela et al, 1989). Conventional composition analysis methods such as the Kjeldahl method for protein measurement and the ether extraction method for oil fraction measurements are timeconsuming, expensive and impractical for measurements on large numbers of soybean samples required for molecular genetic mapping and other selection and breeding studies.…”