Lucerne is a deep-rooted perennial pasture that is promoted to land managers in southern Australia to mitigate the effects of dryland salinity, a problem of national significance caused by the replacement of native trees and shrubs with annual crops and pastures. In recent years, the acceptance of climate change has provided further rationale for increasing the use of perennial legumes in our farming systems. Perennial legumes have a role in offsetting C02 emissions by sequestering C and N in soil, and provide new, resilient options for future farming in a warmer and more variable climate. This research has focused on evaluating the diverse range of germplasm found in lucerne (Medicago sativa spp.) for a range of attributes in order to determine its compatibility with existing and future farming systems in southern Australia. Regional field evaluation at 8 sites in southern Australia showed that lucerne is a broadly adapted and robust plant. After 3 years, plant density ranged from 2-55 plants / m2 with differences in persistence attributed to tolerance to a combination of stresses including soil acidity, saline and sodic subsoils, drought conditions and persistent heavy grazing. Highly winter-active lucerne (class 9-10) was confirmed to be the most suitable group for short phase rotations in southern Australia, providing grazing is well managed. This germplasm was less persistent than other winter activity groups, but produces more total herbage yield in environments with winter dominant rainfall patterns. Highly winter-active lucerne has poor persistence under continuous grazing, but this may aid in its removal when used in rotation with crops. Winteractive germplasm (class 6-8) was more grazing tolerant and persistent, making it the most suitable group for longer phase rotations (>4 years), or where more flexible grazing management practices are required (i.e. 35 days grazing followed by 35 days recovery). Individual grazing tolerant plants from this group were selected and randomly inter-mated to form new breeder’s lines in the development of a grazing tolerant cultivar. For the first time, the high water-use of a farming system involving wheat overcropped into lucerne is presented. Lucerne over-cropped with wheat used an additional 43-88 mm of water in comparison to continuous wheat at Roseworthy and Katanning respectively. Over-cropping reduced wheat yield by 13-63%, but it can be more efficient in terms of land area to grow lucerne and wheat as a mixture than on separate parcels of land. Very winter-dormant lucerne (class 1-2) appears to be less competitive with winter cereal crops during wheat establishment. It may also be possible to reduce lucerne’s competition with wheat at the critical stage of anthesis, with low spring yielding lucerne varieties identified in this research (SA37908). This group of plants provides excellent potential for the development of high water-use farming systems because they are grazing tolerant and persistent, and have summer forage production and sub-soil water extraction rates that are equivalent to winter active lucerne. The research has been used to identify the perfect ideotype for lucerne in phase farming and over-cropping systems, which can be used to set targets in future breeding programs. The research also highlights current opportunities for the integration of lucerne into southern Australian farming systems to help curb the spread of dryland salinity and reduce the impact of climate change. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1344608 / Thesis (Ph.D.) - University of Adelaide, School of Agriculture, Food and Wine, 2008

Made available in DSpace on 2015-03-26T13:32:21Z (GMT). No. of bitstreams: 1 texto completo.pdf: 562430 bytes, checksum: 182da810cb5c6524a339ad2ea7c37142 (MD5) Previous issue date: 2014-02-17 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / In plant breeding, when the objective is to select or recommend genotypes to be planted, the study of the interaction between genotype and environment plays a important role. However, this kind of study does not provide detailed information on the behavior of each cultivar due to environmental variations. Thus become necessary to perform analyzes of stability and adaptability for identification and recommendation superior materials in different environments. Although the literature presents several methods for performing analysis of adaptability and stability, none of them take account of the presence of non-normal phenotype, in other words, phenotypic values asymmetric distributions or heavy tails. Thus, if there is the presence of such phenotypic values, the methods can be influenced and the recommendation may be mistaken, that is, the use of such methods cause inadequate estimates that do not reflect the true relationship between the variation environmental and phenotypic response. An interesting solution for treating this problem in a unified way, that is, the presence of outliers or asymmetry is to use the quantile regression (QR). Such methodology, besides the usual regression methods, using the conditional mean to explain the functional relationship between environmental variation and phenotypic response, makes use of conditional quantile functions. This way the QR possible to choose the quantile which best represents the functional relationship of interest in order to naturally cover the lack of normality cited above. Thus, this paper aims to present the methodology of quantile regression, through a detailed discussion of its theorical foundations, demonstrating it by concrete applications, its use in analysis of adaptability and stability, thus providing a easily and accessible material for readers interested in that subject, contributing researchers and those interested in this area. To the technic evaluation symmetric distributions phenotypic values, symmetric with outliers, right asymmetric, right asymmetric with outliers, left asymmetric and left asymmetric with outliers were simulated. Furthermore, we used data from an experiment on dry matter yield of 92 genotypes of alfalfa (Medicago sativa) evaluated in 20 environments. It is suggested that, for symmetrical phenotypic values should be determined if it has outlier, if it has a QR ( τ = 0,50 ) should be used, if not, should be used either Eberhart and Russell methodology (1966) or QR ( τ = 0,50 ). Since the phenotype is asymmetric, with or without the presence of outlier, it uses QR ( τ = 0,25 ) to right asymmetry and QR ( τ = 0,75) to the left asymmetry. According to the results the QR method was efficient for classifying alfalfa genotypes. / No melhoramento genético de plantas, quando o objetivo é selecionar ou recomendar genótipos para o plantio, o estudo da interação entre genótipo x ambiente é de extrema importância. Entretanto, tal estudo não fornece informações pormenorizadas sobre o comportamento de cada cultivar diante das variações ambientais. Assim, tornam-se necessárias as análises de adaptabilidade e de estabilidade para a identificação e recomendação de materiais superiores em diferentes ambientes. Embora a literatura apresente diversos métodos, para realização da análise de adaptabilidade e estabilidade, nenhum leva em consideração a presença de fenótipos não normais, ou seja, distribuições de valores fenótipos assimétricos ou com caudas pesadas. Desta forma, caso haja a presença desse tipo de valores fenotípicos, os métodos podem sofrer a influência de modo que a recomendação pode ser errônea, ou seja, o uso de tais métodos ocasionam estimativas inadequadas, que não refletem a verdadeira relação existente entre a variação ambiental e a resposta fenotípica. Uma solução interessante para tratar este problema de maneira unificada, isto é, a presença de pontos discrepantes ou assimetria, é a utilização de regressão quantílica (RQ). Tal metodologia, diferentemente dos métodos de regressão usuais, que utilizam a média condicional para explicar a relação funcional entre a variação ambiental e a resposta fenotípica, faz uso de funções quantílicas condicionais. Desta forma, a RQ possibilita escolher o quantil que melhor representa a relação funcional de interesse com o intuito de contemplar naturalmente a mencionada falta de normalidade. Desta forma, o presente trabalho tem como objetivo apresentar a metodologia de regressão quantílica, através de uma discussão detalhada de seus fundamentos teóricos, evidenciando, com aplicações concretas, seu uso em análise de adaptabilidade e estabilidade, fornecendo assim um material de fácil acesso para leitores interessados no assunto, contribuindo com pesquisadores e interessados nesta área. Para avaliação da técnica foram simulados valores fenotípicos, com distribuições simétrica, simétrica com outliers, assimétrica à direita, assimétrica à direita com outliers, assimétrica à esquerda e assimétrica à esquerda com outliers. Além disso, foram utilizados dados provenientes de um experimento sobre produção de matéria seca de 92 genótipos de alfafa (Medicago sativa) avaliados em 20 ambientes. Sugere-se que, para valores fenotípicos simétricos deve-se averiguar se este possui outlier, se sim é utilizada ou a regressão não paramétrica ou a RQ (τ = 0,50) , se não, se utiliza ou a metodologia de Eberhart e Russell (1966) ou a RQ (τ = 0,50) . Já se o fenótipo for assimétrico, com ou sem a presença de outlier, utiliza-se RQ (τ = 0,25) para assimetria a direita e RQ (τ = 0,75) para assimetria à esquerda. De acordo com os resultados encontrados a RQ foi eficiente para classificação de genótipos de alfafa.