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Y = 29.09+ 0.24 x - 0.005( x- 61.57) 2 + 0.00008( x- 61.57) 3 r 2 = 0.86. Breeding and Genetics of Field Dry Down and Test Weight in Short-Season Elite Maize Hybrids † Junyun Yang 1 , Marcelo Carena 1 , and Jim Uphaus 2

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  1. Y = 29.09+ 0.24x - 0.005(x-61.57)2 + 0.00008(x-61.57)3 r2 = 0.86 Breeding and Genetics of Field Dry Down and Test Weight in Short-Season Elite Maize Hybrids †Junyun Yang1, Marcelo Carena1, and Jim Uphaus2 1Department of Plant Sciences, North Dakota State University; 2 AgReliant Genetics, LLC ASA-CSSA-SSSA Meeting November 1-5, 2009 Results Results Methods Introduction Table 4. GCA and SCA values for inbred lines in NC II group 1† • Moisture meter calibration Table 1. Three groups of North Carolina (NC II) mating designs between NDSU experimental lines and industry lines representing a wide range of test weight. Maize (Zea mays L.)production in northern U.S. Corn Belt area requires hybrids that can efficiently utilize the short growing season. Chase (1964) concluded that higher yield in maize is expected in early hybrids that flower later in the season and then lose moisture rapidly after physiological maturity of the grain. This implied that a fast dry down rate after physiological maturity should be an important feature for maize hybrids grown especially in the northern U.S. Corn Belt where early frost is common. Fast field dry down can reduce grower’s production cost related to artificial grain drying and economical losses due to delayed harvesting (e.g., yield losses caused by lodging, bird and insect damage, and ear rot disease). With a faster dry down rate, hybrids reach an optimum level of grain test weight and quality at harvest. Test weight of maize accounts for the packing densities of grain, which are caused by weather, production practice, and/or genetic difference among hybrids. It can be improved by avoiding late planting and by selecting early maturing hybrids with excellent genetic potential in test weight and dry down. Genetic factors contribute to maize hybrid differences in field dry down rate (Cross and Kabir, 1969; Purdy and Crane, 1967; Zhang et al, 1996). Although the importance of dry down rate has been recognized by maize breeders, it is still difficult to apply a simple and reliable method to measure and screen inbred lines and hybrids for dry down rate. Field dry down is a dynamic process influenced by various environmental factors. Therefore, a method that can reflect dynamic change of grain moisture and minimize environmental influence is needed. In addition to conventional oven-dried and laboratory moisture tester methods, the application of electronic moisture meters were reported by Kang et al. (1978) and Freppon et al. (1992). These methods are non-destructive when estimating ear moisture several times on the same ear. In this research, an index, area under the dry down progress curve (AUDDC), was created and used to represent field dry down rate. We propose this index as a new method for screening genetic differences among maize genotypes for dry down. The quantitative nature of dry down and test weight with large environmental influence increases the difficulty for utilizing traditional and modern breeding methods to develop hybrids with good performance on both traits. Increasing our understanding of their genetic nature could aid breeders in selecting the right germplasm and breeding methodology for a successful genetic improvement. Although previous studies have suggested additive gene action is important for field dry down, more genetic information is desirable for breeding purposes. In addition, this study proposes the exploitation of a linkage between traditional and modern techniques for the best possible generation of knowledge and it is application. †: test weight grade: 3 = high (>55.5 lb/bu), 2 = medium (54.0-55.4 lb/bu), 1 = low (<53.9 lb/bu). ‡: test weight grade is not available. • Field evaluation • 138 crosses (NDSU × Industry elite lines) + 6 commercial checks • Four environments: 2007 Fargo and Oakes, ND; 2008 Fargo and Casselton, ND • 12x12 partially balanced lattice design, two reps for each environment • Traits collected: • Field dry down: AUDDC calculated based on meter reading on four dates (7-day interval) , started 45 days after pollination • Test weight, yield, harvest moisture, stand, stalk logging, root logging • Quality: High extractable starch (HES), starch, oil, protein • Field evaluation • Table 2. Mean square value for multiple traits across four environments †:to demonstrate selection of inbreds and crosses for yield, test weight, and fast dry down ‡: GCAm – general combining ability of males; §: GCAf – general combining ability of females. • Estimation of dry down • Area under the disease progress curve (AUDPC) • AUDPC is used to summarize the progress of disease severity. • We propose: Area under the dry down curve (AUDDC) †: physiologic moisture; ‡: harvest moisture;§: test weight, ¶ : Broad sense heritability *** Significant at 0.001 level Conclusions • Correlation among traits • Moisture meter BLD5604 is reliable to estimate corn kernel moisture content after physiologic maturity. • Field dry down rate can be estimated by the AUDDC method, based on several field readings at a constant interval. • AUDDC has relatively high heritability compared with yield and test weight, and similar to quality traits such as starch, oil, and protein content. • Earlier maturing genotypes tend to have faster dry down rate in this set of genotypes. • Selection for fast dry down in inbreds and hybrids is recommended based on AUDDC. • Based on GCA and SCA data, several hybrids have been identified to generate additional genetic information in cooperation with Ag-Reliant Genetics. F2 mapping populations have been produced from these hybrids and new lines are being developed through doubled-haploid technology. The only limitation is the number of segregating populations that can be studied compared to the 138 hybrids studied with classical mating designs. Larger AUDDC area, representing slower dry down progress Smaller AUDDC area, representing faster dry down progress † Pollination day (days from planting to pollination) *** Significant at 0.001 level • NC II groups • Table 3. Mean square values of different traits for NC II group I Objectives Bibliography • Moisture meter calibration • Electronic moisture meter BLD5604:(range: 7~99%; General Electric Co.) • Plug probes through the husk into the ear/kernels • Each ear was probed at its middle part • Regression model for meter reading and actual kernel moisture content • A total of 107 hybrid + inbred ears from Fargo field in 2007 and 2008 • randomly sampled, 30 days after pollination until harvest (7-day intervals) • using electronic meter and oven-dried methods • Converted field meter reading to kernel moisture based on regression model • This research was conducted to: • develop a simple and reliable procedure to select for fast dry down in early maturing maize inbreds and hybrids, • better understand the genetic base controlling the expression of test weight and dry down rate through the integration of classical and modern quantitative genetic approaches, • identify new and elite high-yielding inbred lines and hybrids with high test weight and fast rate of dry down. • Chase, S.S. 1964. Relation of yield and number of days from planting to flowering in early maturity maize hybrids of equivalent grain moisture at harvest. Crop Sci. 4:111-112. • Cross, H.Z., and K.M. Kabir. 1989. Evaluation of field dry-down rates in early maize. Crop Sci. 29:54-58. • Freppon, J.T., S.K. St Martin, R.C. Pratt, and P.R. Henderlong. 1992. Selection for low ear moisture in corn using a hand-held meter. Crop Sci. 32:1062-1064. • Kang, M.S., M.S. Zuber, and R.D. Horrocks. 1978. An electronic probe for estimating ear moisture content of maize. Crop Sci, 18:1083-1084. • Purdy, J.L., and P.L. Crane. 1967. Inheritance of drying rate in "Mature" corn (Zea mays L.). Crop Sci. 7:294-297. • Zhang, Y., M.-S. Kang, and R. Magari. 1996. A diallel analysis of ear moisture loss rate in maize. Crop Sci. 36:1140-1144. *: significant at 0.5 level; ***: Significant at 0.001 level. • For each NC II group, GCA effects (male and female expectation) were significant for most traits, except for stand, root logging, and stalk logging. • SCA (male x female) effect was not significant for most traits, except for GRAIN yield, test weight, and oil grain content in some NC II groups.

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