Genetic Analysis for Quantitative Traits, Strach and Oil in Single Cross Hybrids of Maize (zea Mays L.) PDF Download
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Author: SHRIKANTH S. G
Publisher:
ISBN:
Category :
Languages : en
Pages : 194
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Author: SHRIKANTH S. G
Publisher:
ISBN:
Category :
Languages : en
Pages : 194
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Author: David Frederick Austin
Publisher:
ISBN:
Category :
Languages : en
Pages : 426
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The first objective of this study was to compare quantitative trait loci (QTL) detection in two climatically diverse environments in a population of F6:-- lines of an elite maize (Zea mays L.) single-cross. The second objective was to detect QTL for general (GCA) and specific (SCA) combining ability effects in hybrid progeny of F2:3 and F6: lines from the same population. Evaluations of both inbred per se and hybrid progeny from the same population enabled comparisons between QTL controlling the two progeny types. The results from the F6:-- inbred progeny evaluations suggest that QTL detection can be greatly affected by environmental conditions with only 17% (grain yield traits) and 35% (morphological traits) of the QTL detected among the stress and nonstress environments being detected in both environments. The mean environment was effective in detecting 68% (morphological traits) and 54% (grain yield traits) of the QTL detected in either of the individual environments.
Author: Arnel R. Hallauer
Publisher: Springer Science & Business Media
ISBN: 1441907661
Category : Science
Languages : en
Pages : 669
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Maize is used in an endless list of products that are directly or indirectly related to human nutrition and food security. Maize is grown in producer farms, farmers depend on genetically improved cultivars, and maize breeders develop improved maize cultivars for farmers. Nikolai I. Vavilov defined plant breeding as plant evolution directed by man. Among crops, maize is one of the most successful examples for breeder-directed evolution. Maize is a cross-pollinated species with unique and separate male and female organs allowing techniques from both self and cross-pollinated crops to be utilized. As a consequence, a diverse set of breeding methods can be utilized for the development of various maize cultivar types for all economic conditions (e.g., improved populations, inbred lines, and their hybrids for different types of markets). Maize breeding is the science of maize cultivar development. Public investment in maize breeding from 1865 to 1996 was $3 billion (Crosbie et al., 2004) and the return on investment was $260 billion as a consequence of applied maize breeding, even without full understanding of the genetic basis of heterosis. The principles of quantitative genetics have been successfully applied by maize breeders worldwide to adapt and improve germplasm sources of cultivars for very simple traits (e.g. maize flowering) and very complex ones (e.g., grain yield). For instance, genomic efforts have isolated early-maturing genes and QTL for potential MAS but very simple and low cost phenotypic efforts have caused significant and fast genetic progress across genotypes moving elite tropical and late temperate maize northward with minimal investment. Quantitative genetics has allowed the integration of pre-breeding with cultivar development by characterizing populations genetically, adapting them to places never thought of (e.g., tropical to short-seasons), improving them by all sorts of intra- and inter-population recurrent selection methods, extracting lines with more probability of success, and exploiting inbreeding and heterosis. Quantitative genetics in maize breeding has improved the odds of developing outstanding maize cultivars from genetically broad based improved populations such as B73. The inbred-hybrid concept in maize was a public sector invention 100 years ago and it is still considered one of the greatest achievements in plant breeding. Maize hybrids grown by farmers today are still produced following this methodology and there is still no limit to genetic improvement when most genes are targeted in the breeding process. Heterotic effects are unique for each hybrid and exotic genetic materials (e.g., tropical, early maturing) carry useful alleles for complex traits not present in the B73 genome just sequenced while increasing the genetic diversity of U.S. hybrids. Breeding programs based on classical quantitative genetics and selection methods will be the basis for proving theoretical approaches on breeding plans based on molecular markers. Mating designs still offer large sample sizes when compared to QTL approaches and there is still a need to successful integration of these methods. There is a need to increase the genetic diversity of maize hybrids available in the market (e.g., there is a need to increase the number of early maturing testers in the northern U.S.). Public programs can still develop new and genetically diverse products not available in industry. However, public U.S. maize breeding programs have either been discontinued or are eroding because of decreasing state and federal funding toward basic science. Future significant genetic gains in maize are dependent on the incorporation of useful and unique genetic diversity not available in industry (e.g., NDSU EarlyGEM lines). The integration of pre-breeding methods with cultivar development should enhance future breeding efforts to maintain active public breeding programs not only adapting and improving genetically broad-based germplasm but also developing unique products and training the next generation of maize breeders producing research dissertations directly linked to breeding programs. This is especially important in areas where commercial hybrids are not locally bred. More than ever public and private institutions are encouraged to cooperate in order to share breeding rights, research goals, winter nurseries, managed stress environments, and latest technology for the benefit of producing the best possible hybrids for farmers with the least cost. We have the opportunity to link both classical and modern technology for the benefit of breeding in close cooperation with industry without the need for investing in academic labs and time (e.g., industry labs take a week vs months/years in academic labs for the same work). This volume, as part of the Handbook of Plant Breeding series, aims to increase awareness of the relative value and impact of maize breeding for food, feed, and fuel security. Without breeding programs continuously developing improved germplasm, no technology can develop improved cultivars. Quantitative Genetics in Maize Breeding presents principles and data that can be applied to maximize genetic improvement of germplasm and develop superior genotypes in different crops. The topics included should be of interest of graduate students and breeders conducting research not only on breeding and selection methods but also developing pure lines and hybrid cultivars in crop species. This volume is a unique and permanent contribution to breeders, geneticists, students, policy makers, and land-grant institutions still promoting quality research in applied plant breeding as opposed to promoting grant monies and indirect costs at any short-term cost. The book is dedicated to those who envision the development of the next generation of cultivars with less need of water and inputs, with better nutrition; and with higher percentages of exotic germplasm as well as those that pursue independent research goals before searching for funding. Scientists are encouraged to use all possible breeding methodologies available (e.g., transgenics, classical breeding, MAS, and all possible combinations could be used with specific sound long and short-term goals on mind) once germplasm is chosen making wise decisions with proven and scientifically sound technologies for assisting current breeding efforts depending on the particular trait under selection. Arnel R. Hallauer is C. F. Curtiss Distinguished Professor in Agriculture (Emeritus) at Iowa State University (ISU). Dr. Hallauer has led maize-breeding research for mid-season maturity at ISU since 1958. His work has had a worldwide impact on plant-breeding programs, industry, and students and was named a member of the National Academy of Sciences. Hallauer is a native of Kansas, USA. José B. Miranda Filho is full-professor in the Department of Genetics, Escola Superior de Agricultura Luiz de Queiroz - University of São Paulo located at Piracicaba, Brazil. His research interests have emphasized development of quantitative genetic theory and its application to maize breeding. Miranda Filho is native of Pirassununga, São Paulo, Brazil. M.J. Carena is professor of plant sciences at North Dakota State University (NDSU). Dr. Carena has led maize-breeding research for short-season maturity at NDSU since 1999. This program is currently one the of the few public U.S. programs left integrating pre-breeding with cultivar development and training in applied maize breeding. He teaches Quantitative Genetics and Crop Breeding Techniques at NDSU. Carena is a native of Buenos Aires, Argentina. http://www.ag.ndsu.nodak.edu/plantsci/faculty/Carena.htm
Author: Ramakrishna Wusirika
Publisher: CRC Press
ISBN: 1482228130
Category : Science
Languages : en
Pages : 310
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Sequencing of the maize genome has opened up new opportunities in maize breeding, genetics and genomics research. This book highlights modern trends in development of hybrids, analysis of genetic diversity, molecular breeding, comparative and functional genomics, epigenomicsand proteomics in maize. The use of maize in biofuels, phytoremediation and
Author: S. Swarup
Publisher:
ISBN:
Category :
Languages : en
Pages : 98
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Author: D. Rajeswar Reddy
Publisher:
ISBN:
Category :
Languages : en
Pages : 134
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Category : Agriculture
Languages : en
Pages : 596
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Author: Kathryn Michel
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Maize (Zea mays L.) yield is a highly quantitative trait controlled by many loci of small effect, the environment, and genotype by environment interactions, which make it a difficult trait to study at the gene level. However, yield may be broken into components such as ear and kernel size and shape, which are more heritable than yield measured in small plots. Multiparent advanced generation intercross (MAGIC) populations and diversity panels are two types of populations that are useful for identifying quantitative trait loci (QTL) that influence phenotypes. This dissertation contains three research projects designed to investigate the control of quantitative traits impacting maize yield. First, we present the genomes of five founders of a Stiff Stalk MAGIC population. Between the reference inbred B73 and the other five inbreds, we found substantial genetic and genomic variation in addition to conservation of haplotypes from the base population from which the inbreds were selected. Second, we describe the Wisconsin-Stiff Stalk-MAGIC population, its associated resources, and demonstrate QTL mapping and genomic prediction for flowering time and plant height. Flowering time and plant height are important characteristics in hybrid maize breeding, so we measured them in both the per se population and two test-crossed hybrid populations. We found that QTL detection depended on the tester used, which was consistent with lower genomic predictive ability when training models with per se data to predict hybrid phenotypes. Third, we used a high throughput image analysis pipeline to measure yield components on four MAGIC populations and a diversity panel. We performed genetic mapping to identify candidate genes underlying ear and kernel size and shape. We found substantial overlap of our results across traits within and between populations and overlap with known metaQTL identified through previous studies. The results from these projects provide new insight into the genetic control of traits including flowering time, plant height, and the size and shape of ears and kernels, all of which impact overall maize yield.
Author: Hongwei Wang
Publisher: Frontiers Media SA
ISBN: 2832538606
Category : Science
Languages : en
Pages : 400
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Author: Dwi Asmono
Publisher:
ISBN:
Category :
Languages : en
Pages : 366
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Evidence of consistent detection was observed at 27% (25 of 93) of the QTLS. For grain yield and yield components, seventy-one QTLs were detected across samples, only thirteen were common in both samples. Chromosome 6 was significantly associated with grain yield in both samples. The magnitudes of QTL effects were not always consistent when QTLs were detected in a region for both samples. Most QTLs detected in both samples had the same parental effects.
