hohPublica :: Browsing by Subject "Genotyp"

Browsing by Subject "Genotyp"

Now showing 1 - 7 of 7

Analyse komplexer Merkmale beim Schwein mittels SNP-Chip Genotypen, Darmmikrobiota- und Genexpressionsdaten
(2017) Maushammer, Maria; Bennewitz, Jörn
In the present scientific research, SNP chip genotypes, gut microbiota and gene expression data were used for analysing complex traits in a Piétrain population. These data were collected from around 200 performance tested sows and were used for genetic and microbial analyses of complex trait as well as for structural and functional meat quality traits. The gut microbiome plays a major role in the immune system development, state of health and energy supply of the host. Quantitative-genetic methods were applied to analyse the interrelationship between pig gut microbiota compositions, complex traits (daily gain, feed conversion and feed intake) and pig genomes. The specific aims were to characterize the gut microbiota of the pigs, to analyse the effects of host genetics on gut microbial composition, and to investigate the role of gut microbial composition on the host’s complex traits. The pigs were genotyped with a standard 60K SNP chip. Microbial composition was characterized by 16S rRNA gene amplicon sequencing technology. Ten out of 51 investigated bacterial genera showed a significant host heritability, ranging from 0.32 to 0.57. Conducting genome wide association analysis showed associations of 22 SNPs and six bacterial genera. The potential candidate genes identified are involved in the immune system, mucosa structure and secretion of digestive juice. These results show, that parts of the gut microbiota are heritable and that the gut microbiome can be seen as quantitative trait. Microbial mixed linear models were applied to estimate the microbiota variance for each of the investigated traits. The fraction of phenotypic variance explained by the microbial variance was 0.28, 0.21, and 0.16 for daily gain, feed conversion, and feed intake, respectively. The SNP data and the microbiota data were used to predict the phenotypes of the traits using both, genomic best linear unbiased prediction (G-BLUP) and microbial best linear unbiased prediction (M-BLUP) methods. The prediction accuracies of G-BLUP were 0.35, 0.23, and 0.20 for daily gain, feed conversion, and feed intake, respectively. The corresponding prediction accuracies of M-BLUP were 0.41, 0.33, and 0.33. Thus, the gut microbiota can be seen as an explaining variable for complex traits like daily gain, feed conversion and feed intake. In addition, in combination with meat quality traits, transcript levels of muscle tissue were analysed at time of slaughtering. This study should give an insight into the biological processes involved in meat quality characteristics. The aims were to functionally characterise differentially expressed genes, to link the functional information with structural information obtained from GWAS, and to identify potential candidate genes based on these results. An important meat quality trait is the intramuscular fat content, since it affects the juiciness, the taste and the tenderness of the meat. Another important trait is drip loss which causes not only a loss of weight but also a loss of important proteins. Both traits have an impact on the consumer acceptance of fresh meat products. For each of the two traits, eight discordant sibling pairs were selected out of the Piétrain sample and were used for genome-wide gene expression analyses. Thirty five and 114 genes were identified as differentially expressed and trait correlated genes for intramuscular fat content and drip loss, respectively. On the basis of functional annotation, gene groups belonging to the energy metabolism of the mitochondria, the immune response and the metabolism of fat, were associated with intramuscular fat content. Gene groups associated with protein ubiquitination, mitochondrial metabolism, and muscle structural proteins were associated with drip loss. Furthermore, genome-wide association analyses were carried out for these traits and their results were linked to the genome-wide expression analysis by functional annotation. In this context, intramuscular fat was related to muscle contraction, transmembrane transport and nucleotide binding. Drip loss was characterized by the endomembrane system, the energy generation of cells, and phosphorus metabolic processes. Three and four potential candidate genes were identified for intramuscular fat content and drip loss, respectively.
Biometrical approaches for analysing gene bank evaluation data on barley (Hordeum spec.)
(2007) Hartung, Karin; Piepho, Hans-Peter
This thesis explored methods to statistically analyse phenotypic data of gene banks. Traits of the barley data (Hordeum spp.) of the gene bank of the IPK-Gatersleben were evaluated. The data of years 1948-2002 were available. Within this period the ordinal scale changed from a 0-5 to a 1-9 scale after 1993. At most gene banks reproduction of accessions is currently done without any experimental design. With data of a single year only rarely do accessions have replications and there are only few replications of a single check for winter and summer barley. The data of 2002 were analysed separately for winter and summer barley using geostatistical methods. For the traits analysed four types of variogram model (linear, spherical, exponential and Gaussian) were fitted to the empirical variogram using non-linear regression. The spatial parameters obtained by non-linear regression for every variogram model then were implemented in a mixed model analysis and the four model fits compared using Akaike's Information Criterion (AIC). The approach to estimate the genetical parameter by Kriging can not be recommended. The first points of the empirical variogram should be explained well by the fitted theoretical variogram, as these represent most of the pairwise distances between plots and are most crucial for neighbour adjustments. The most common well-fitting geostatistical models were the spherical and the exponential model. A nugget effect was needed for nearly all traits. The small number of check plots for the available data made it difficult to accurately dissect the genetical effect from environmental effects. The threshold model allows for joint analysis of multi-year data from different rating scales, assuming a common latent scale for the different rating systems. The analysis suggests that a mixed model analysis which treats ordinal scores as metric data will yield meaningful results, but that the gain in efficiency is higher when using a threshold model. The threshold model may also be used when there is a metric scale underlying the observed ratings. The Laplace approximation as a numerical method to integrate the log-likelihood for random effects worked well, but it is recommended to increase the number of quadrature points until the change in parameter estimates becomes negligible. Three rating methods (1%, 5%, 9-point rating) were assessed by persons untrained (A) and experienced (B) in rating. Every person had to rate several pictograms of diseased leaves. The highest accuracy was found with Group B using the 1%-scale and with Group A using the 5%-scale. With a percentage scale Group A tended to use values that are multiples of 5%. For the time needed per leaf assessment the Group B was fastest when using the 5% rating scale. From a statistical point of view both percent ratings performed better than the ordinal rating scale and the possible error made by the rater is calculable and usually smaller than with ratings by rougher methods. So directly rating percentages whenever possible leads to smaller overall estimation errors, and with proper training accuracy and precision can be further improved. For gene banks augmented designs as proposed by Federer and by Lin et al. offer themselves, so an overview is given. The augmented designs proposed by Federer have the advantage of an unbiased error estimate. But the random allocation of checks is a problem. The augmented design by Lin et al. always places checks in the centre plot of every whole plot. But none of the methods is based on an explicit statistical model, so there is no well-founded decision criterion to select between them. Spatial analysis can be used to find an optimal field layout for an augmented design, i.e. a layout that yields small least significant differences. The average variance of a difference and the average squared LSD were used to compare competing designs, using a theoretical approach based on variations of two anisotropic models and different rotations of anisotropy axes towards field reference axes. Based on theoretical calculations, up to five checks per block are recommended. The nearly isotropic combinations led to designs with large quadratic blocks. With strongly anisotropic combinations the optimal design depends on degree of anisotropy and rotation of anisotropy axes: without rotation small elongated blocks are preferred; the closer the rotation is to 45° the more squarish blocks and the more checks are appropriate. The results presented in this thesis may be summarised as follows: Cultivation for regeneration of accessions should be based on a meaningful and statistically analysable experimental field design. The design needs to include checks and a random sample of accessions from the gene pool held at the gene bank. It is advisable to utilise metric or percentage rating scales. It can be expected that using a threshold model increases the quality of multivariate analysis and association mapping studies based on phenotypic gene bank data.
Characterization and management of Jatropha curcas L. germplasm
(2018) Senger, Elisa; Melchinger, Albrecht E.
Jatropha curcas L. (jatropha) is a perennial plant of the Euphorbiaceae family that grows in the tropics and subtropics worldwide. Jatropha is targeted to be grown in marginal environments. The seeds are used mainly for production of food products and bioenergy, amongst others. Jatropha breeding is at an early stage. The first obstacle is to generate competitive cultivars for economically feasible cultivation. Mayor breeding objectives are to increase seed yield and yield stability, to decrease production costs, and to improve product quality adapted to specific markets. Jatropha breeding needs to be optimized in several research areas, such as methods and tools for germplasm characterization and breeding techniques, while considering requirements of the agronomic management and product processing. The germplasm can be separated into two naturally occurring germplasm pools that differ in the presence of phorbol esters (PE). These chemical compounds have antinutritional effects on humans and animals and cannot be inactivated or eliminated from the plant material on an industrial scale yet. Therefore, food production is based on cultivars lacking PE, while bioenergy production is less affected from PE presence. The germplasm needs to be characterized and grouped depending on breeding objectives and strategies. Tools for identification of plants that synthesize PE exist, but bear decisive disadvantages or need to be advanced. These tools are exploited for germplasm management and food safety strategies. The objectives of this study were to i) examine the variation of relevant traits among genotypes and between germplasm pools, ii) estimate phenotypic and genotypic trait correlations, iii) investigate location effects and genotype by environment interactions, iv) investigate parental and heterotic effects of genotypes from different germplasm pools as well as the effect of the mating type on expression of relevant traits, and v) develop recommendations for implementation of the findings in jatropha breeding programs. In the first two publications, stress response was investigated. Leaf chlorophyll content (SPAD) was used as a dynamic trait that can be influenced by e.g. water stress and nutrient deficiency. Different genotypes were screened at several locations and at different time points. High genetic diversity was found not only in stress response but also in SPAD value. The fast and non-destructive method is highly promising to be applied in further screenings or stress response studies. In the second publication, genotypic differences in aluminum tolerance were found among seedlings in a greenhouse trial. The rapid test method is applicable in further screenings. However, it needs to be proven that aluminum tolerance at the seedling stage observed under greenhouse conditions is expressed also at later plant developmental stages in the field. In the consecutive three publications, several traits were assessed on seeds and seedlings to detect significant differences between genotypes and/or between germplasm pools. Such traits would be highly valuable for germplasm management. We found that random variation is a disadvantage of quantitative traits and hinders clear assignment of each experimental unit to the respective germplasm pool. Thus, qualitative traits might be favored, such as the “silver shimmer inside the seed testa” that differentiated toxic from non-toxic seeds with a low error rate. However, these results need to be validated. Another application area of the investigated traits is the identification of self-fertilized material within hybrid progeny. In our study, self-fertilized seeds could be differentiated from cross-fertilized ones in specific genotype combinations. Similarly, many seedling traits showed heterotic effects. In the sixth publication, genotype by environment interactions were investigated and recommendations for breeding programs elaborated. A large set of genotypes was grown for four years at three different locations. We showed that selection at only one testing location is highly risky because cultivars with low yield stability could be selected. Therefore, it is indispensable for breeders to work in a network of testing locations that differ in edapho-climatic conditions and apply appropriate experimental designs and statistical tools. In the final publication, several parameters related to the nutritional value of kernels of non-toxic genotypes grown at two locations were assessed. The high nutritional value of this material was presented and compared to soybean, peanut, hazelnut, and corn. Furthermore, preliminary conclusions related to location effects and product processing were drawn. The findings of this thesis contribute to characterization of this novel crop with regard to stress tolerances, seed and seedling characteristics as well as food quality, and help to increase breeding efficiency by presenting simple methods for fast genotype screening as well as grouping of germplasm and by efficient exploitation of testing facilities.
Genotypic responses of upland rice to an altitudinal gradient
(2012) Shrestha, Suchit Prasad; Asch, Folkard
Adaptation strategies are required for crops to cope with changing climate. The impact of climate change on crop production is not straight forward to predict as extreme events comprise multiple combination of abiotic stresses and their impact differs in crop physiological growth stages. The mechanism on how new abiotic stress combinations translate into phenology and yield, and which cultivars are better adapted is yet unclear. Crop growth models are available that have been parameterized and validated for some aspects of possible climate change scenarios but in view of complex interactions crop responses to climate change are difficult to predict. On the other hand, prediction of the complex ideotype trait combinations may be interesting for breeders but physiological models are required that are well validated for the target environments. In upland rice grown under rainfed conditions without surface water accumulation methane emission is negligible and therefore greenhouse gas emission much lower compared to irrigated paddy rice systems. In addition, growing demand for rice and the increasing pressure on irrigated land leads to development of upland rice areas to supplement irrigated rice. Therefore, this study investigates genetically diverse upland rice genotypes from a wide range of origins across altitudinal gradient locations. The main objective of this study is to investigate genotypic responses of upland rice to different environments in order to calibrate crop growth models, which allow the evaluation of effects of climate change on upland rice systems. Multi-locational field (three locations: 1625, 965 and 25 m asl) trials comprising non-replicated phenological plots with five sowing dates (monthly staggered) in two consecutive years creating thirty different environments, and replicated physiological yield trials with two sowing dates (monthly staggered; early and late sowing) in two consecutive years creating twelve different environments were established in Madagascar. Ten contrasting upland rice genotypes were included in both field trials. Meteorological data were recorded on a daily basis during trial periods. Developmental stages were observed in the phenological plots; in the physiological plots yield and yield components were recorded. In addition, greenhouse trials were conducted with one upland rice genotype subjected to seven N-supply levels in a hydroponic system at the University of Hohenheim in order to understand the relationship between chlorophyll index, photochemical reflectance index and chlorophyll fluorescence parameters. Various statistical tools were applied to analyse field and greenhouse data sets. The phenological trial showed that duration to flowering was 117, 81 and 67 d in high (HA), mid (MA) and low (LA) altitudinal locations respectively. 90% of the total variance was explained by location when pooled over genotype, location, sowing dates and year. In HA, factors such as genotype, sowing date and year equally contributed to the observed variability whereas in MA year was the most determining factor and genotype had no significant contribution. Similarly, in LA sowing date was the main influencing factor and year had no significant effect. Aggregated data over locations, sowing dates and years indicated that each degree Celsius rise in mean air temperature decreased crop duration by 5 to 9 days depending upon genotype. Basic genotypic thermal constants Tbase ranged from 9.8 to 13.9 °C and Tsum from 816 to 1220 °C d within the selected genotypes. Cold tolerant genotypes were less affected by lower Tmin (14 °C) at booting to heading stage regarding spikelet sterility in HA, whereas others were highly affected at 15 °C (cold stress). Similarly, both cold sensitive and tolerant genotypes were affected by Tmax (above 30 °C) at flowering in MA and LA locations (heat stress). Grain yield and yield components were highly affected by location, year, sowing date, and genotypes and the interactions between these yield-determining factors were obvious. In HA, early sown cold tolerant genotypes had more than 5 t ha-1 grain yield and one month delay in sowing led to highly reduced yield whereas other genotypes had very poor yield on both sowing dates due to cold stress. In MA, yield difference between sowing date and genotypes was small (4.3 - 4.9 t ha-1). Grain yield in LA was vulnerable due to frequent tropical storms. Yield stability analysis showed that cold tolerant genotypes had above average stability. AMMI model for grain yield showed that environment and genotype by environment interactions were highly significant. Yield components determined during specific development stages of the genotype such as tillers per hill and percentage of filled spikelets were mainly influenced by environment, spikelets per panicle and thousand grain weight were influenced by genotype, and percentage of productive tillers was equally influenced by both genotype and environment. PCA biplots showed that all HA environments were equally influenced by all weather parameters with minimum air temperature having the strongest positive influence on genotypic performance. In all MA environments genotypic performance in all phenophases was strongly and positively influenced by rainfall, and strongly and negatively influenced by vapour pressure deficit, solar radiation and potential evapotranspiration. In the LA environments, main weather parameters influencing genotypic performance were maximum temperature and high rainfall accompanied by strong winds. The field measured SPAD values of the upper canopy leaves reflected the location specific N-remobilization and leaf senescence levels after flowering. Similarly, PRI values showed the abiotic stress responses among development stages and locations along the altitudinal gradient. These readings showed that genotypes were efficient in radiation use and N-remobilization after flowering in MA. The unsynchronized relationship between source (leaf) and sink (grain) explained the yield penalty. Emphasis on identification of morpho-physiological traits contributing to cold tolerance should be placed for further breeding. We conclude that genotypic responses of upland rice cultivars differed across altitudinal gradients. Genotypes that are well adapted in HA can easily be adapted in MA without yield decrease. But genotypes well adapted in MA may show a huge yield penalty in HA due to lower temperature during reproductive phase and consequently reduced sink formation. Frequent tropical storms and high temperature reduced yield potential in LA. Therefore, HA has a large potential for the future food security considering climate change scenarios. At present, MA is favorable for upland rice production systems, whereas LA is highly vulnerable and is expected to be even more vulnerable in future. Those results on genotype-specific responses to environmental conditions allow further improvement of crop models such as RIDEV and SAMARA (synthesis of SARRAH and EcoMeristem), which can be used to test a number of phenotypic traits x environments combinations to define ideotypes of upland rice varieties adapted to changing climate and cropping calendars. Genotypic responses of phyllochron, biomass production and crop growth rate, and radiation use efficiency across altitudinal gradients will be included to parameterize these models. In this regard, collaborations with AfricaRice, CIRAD and IRRI are ongoing.
Quantitativ-genetische und genomische Analysen zu den Merkmalen perinataler Saugreflex und Trinkverhalten bei Kälbern der Rasse Braunvieh
(2020) Dreher, Clarissa Susanne; Bennewitz, Jörn
A healthy sucking behavior is important for newborn calves to ensure sufficient colostrum intake in the first few hours postpartum. This is essential for the passive immunization of newborn calves and provides the foundation for raising vital and well developed animals. Insufficient colostrum intake not only results in developmental disorders and increased susceptibility to certain diseases, but also inherits the risk of increased postnatal mortality. Therefore, an insufficient colostrum intake is an animal welfare problem and it also leads to economic losses for the farmers. Brown Swiss breeders are more likely to experience the problem of non-sucking calves (incidence: 10%) than is apparent in other breeds. Studies in the Italian Brown Swiss population have already identified a genetic component with mid-range heritabilities for erroneous perinatal sucking behavior. This indicates that the trait sucking behavior is partly influenced by the genes of the animals and thus breeding for this trait might lead to a selection response. Therefore, the characterization of the genetic background of perinatal sucking reflex and sucking behavior in neonatal calves in the Brown Swiss population was carried out in this work. For this purpose, data were collected on more than 220 dairy cattle farms located in Baden-Württemberg. In addition to an evaluation of the husbandry and feeding management of the farms, the phenotype data of more than 10,000 calves were collected to carry out pedigree-based genetic analyzes using univariate and multivariate sire threshold models. In addition, the collection of tissue samples from over 3,000 calves was carried out for the performance of genomic analyzes. Using high-density marker maps, genome-wide association mapping was performed using both single-marker models and Bayesian multi-marker models. Tissue samples of approximately 900 mothers were also collected and their 50K-genotypes were analyzed. Based on the maternal marker genotypes, maternal genetic effects on an erroneous sucking reflex of the calves were investigated. Low heritabilities for the traits sucking behavior and sucking reflex could be determined. These ranged from 0.06 to 0.23, depending on the trait, the trait coding used and the models used. The heritability estimates for sucking behavior were slightly higher in the univariate model as well as in the multivariate model than for sucking reflex. The GWAS results clearly showed a quantitative-genetic background of both traits. From these findings, it can be deduced for practical breeding strategies that improving the problem by means of genetic tests, as is the case, for example, with monogenic hereditary diseases, would not be expedient. Instead, breeding progress through the use of genomic selection is recommended. A constant trait recording is required for this purpose. The sucking behavior of the calves should be recorded within the first 12 hours postpartum. The results of gene annotation using GO terms and pathway analysis revealed the overrepresentation of genes with functions in the development of the central nervous system, neurogenesis, and signal transduction. In order to effectively estimate maternal genetic effects on calf sucking weakness, both the marker density of 50K was too low and the data set too small. A highly significant farm effect on the investigated traits was found. However, the evaluations carried out with regard to specific influences of the housing and feeding environments on farms did not show any significant differences.
Strategies for selecting high-yielding and broadly adapted maize hybrids for the target environment in Eastern and Southern Africa
(2012) Windhausen, Sandra Vanessa; Melchinger, Albrecht E.
Maize is a major food crop in Africa and primarily grown by small-holder farmers under rain-fed conditions with low fertilizer input. Projections of decreasing precipitation and increasing fertilizer prices accentuate the need to provide farmers with maize varieties tolerant to random abiotic stress, especially drought and N deficiency. Genetic improvement for the target environment in Eastern and Southern Africa can be achieved by: (i) direct selection of grain yield in random abiotic stress environments, (ii) indirect selection for a secondary trait or grain yield in optimal, low-N and/or managed stress environments, or (iii) index selection using information from all test environments. At present, the maize hybrid testing programs of the International Maize and Wheat Improvement Center (CIMMYT) select primarily for grain yield under managed stress and optimal environments and subdivide the target environment according to geographic and climatic differences. It is not known to what extend the current strategy contributes to selection gains. The same holds true for genomic prediction, a strategy that is not yet implemented into the CIMMYT maize breeding program but that may accelerate breeding progress and reduce cycle length by predicting genotype performance based on molecular markers. Regarding the different strategies mentioned for selecting high-yielding and broadly adapted maize hybrids, the breeder needs to decide which of them are most promising to increase genetic gains. Consequently, the objectives of my thesis were to (1) evaluate the potential of leaf and canopy spectral reflectance as novel secondary traits to predict grain yield across different environments, (2) estimate to what extent indirect selection in managed drought and low-N stress environments is predictive of grain yield in random abiotic stress environments, (3) investigate whether subdividing the target environment into climate, altitude, geographic, yield level or country subregions is likely to increase rates of genetic gain, and (4) evaluate the prospects of genomic prediction in the presence of population structure. The measurement of spectral reflectance (495 ? 1853 nm) of both leaves and canopy at anthesis and milk grain stage explained less than 40% of the genetic variation in grain yield after validation. Consequently, selection based on predicted grain yield is only suitable for pre-screening, while final yield evaluation will still be necessary. Nevertheless, the prospect of developing inexpensive and easy to handle devices that can provide, at anthesis, precise estimates of final grain yield warrants further research. Based on a retrospective analysis across 9 years, more than 600 trials and 448 maize hybrids, it was shown that maize hybrids were broadly adapted to climate, altitude, geographic and country subregions in Eastern and Southern Africa. Consequently, I recommend that the maize breeding programs of CIMMYT in the region should be consolidated. Within the consolidated breeding programs, genotypes should be selected for performance in low- and high yielding environments as the genotype-by-yield level interaction variance was high relative to the genetic variance and genetic correlations between low- and high-yielding environments were moderate. Genetic gains were maximized by index selection, considering the yield-level effect as fixed and appropriately weighting information from all trials. To allow better allocation of resources, locations with high occurrence of random abiotic stress need to be identified. Heritability in trials conducted at these locations may be increased by the use of row- and column designs and/or spatial adjustment. Furthermore, resources invested into managed drought trials should be maintained during early breeding stages but shifted to the conduct of low-N trials at later breeding stages. Investments in a larger number of low-N trials may increase selection gain, because performance under low-N and random abiotic stress was highly correlated and genotypes can be easily selected under different levels of soil N. Prospects are promising to accelerate breeding cycles by the use of genomic prediction. Based on two large data sets on the performance of eight breeding populations, it was shown that prediction accuracy resulted primarily from differences in mean performance of these populations. Genomic prediction may be implemented into the CIMMYT maize breeding program to predict the performance of lines from a diversity panel, segregating lines from the same or related crosses, and progenies from closed populations within a recurrent selection program. The breeding scenarios in which genomic prediction is most promising still need to be defined. Generally, the construction of larger training sets with strong relationship to the validation set and a detailed analysis of the population structure within the training and validation sets are required. In conclusion, combining index and genomic selection is the most promising strategy for providing high-yielding and broadly adapted maize genotypes for the target environments in Eastern and Southern Africa.
The development of phenotypic protocols and adjustment of experimental designs in Pelargonium zonale breeding
(2018) Molenaar, Heike; Piepho, Hans-Peter
Ornamental plant variety improvement is limited by current phenotyping approaches and the lack of use of experimental designs. Robust phenotypic data obtained from experiments laid out to best control local variation by blocking allow adequate statistical analysis and are crucial for any breeding purpose, including MAS. Often experiments consist of multiple phases like in P. zonale breeding, where in the first phase stock plants are cultivated to obtain the stem cutting count and in the second phase the stem cuttings are further assess for root formation. The first analyses of rooting experiments raised questions regarding options for improving the two-phase experimental layout, for example whether there is a disadvantage to using exactly the same design in both phases. The other question was, whether a design can be optimized across both phases, such that the MVD can be decreased. Instead of generating a separate layout for each phase. Moreover, optimal selection methods that maximize selection gain in P. zonale breeding based on available data collected from unreplicated trials and containing pedigree information were sought. This thesis was conducted to evaluate the benefits of using two-phase experimental designs and corresponding analysis in P. zonale for production related traits, for which it was necessary to establish phenotyping protocols. To optimize the rooting experiments with their two-phase nature, alternative approaches were explored involving two-phase design generation either in phase wise order or across phases. Furthermore, selection methods considering pedigreeinformation (family-index selection) or not (individual selection), were evaluated to enhance selection efficiency in P. zonale breeding. The benefits of using experimental designs in P. zonale breeding was shown by the simulated response to selection. Alternative designs were evaluated by the MVD obtained by the intrablock analysis and the joint inter-block-intra-block analysis. The efficiency of individual and family-index selection was evaluated in terms of heritability obtained from linear mixed models implementing the selection methods. Simulated response to selection varied greatly, depending on the genotypic variances of the breeding population and traits. However, by using efficient designs allowing adequate analysis, a varietal improvement of over 20% of stock plant reduction is possible for stem cutting count, root formation, branch count and flower count. The smallest MVD for alternative designs was most frequently obtained for designs generated across phases rather than for each phase separately, in particular when both phases of the design were separated with a single pseudolevel. Family-index selection was superior to individual selection in P. zonale indicating that the pedigree-based BLUP procedure can further enhance selection efficiency in productionrelated traits in P. zonale. The quantification of genotypic variation by phenotypic protocols and the optimized two-phase designs for estimating genotypic values were necessary and successful steps in laying the foundation for effective MAS. Phenotypic protocols effectively characterized the genetic material on an observational unit level, while the two-phase experimental designs enabled effective characterization on a genotype level by adjusting entry means using linear mixed models. The resulting adjusted entry means are the basis for future genotype phenotype association for MAS.

Browsing by Subject "Genotyp"

Results Per Page

Sort Options