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Terminal drought is one of the major constraints to crop production in chickpea (Cicer arietinum L.). In order to map drought tolerance related traits at high resolution, we sequenced multi-parent advanced generation intercross (MAGIC) population using whole genome resequencing approach and phenotyped it under drought stress environments for two consecutive years (2013–14 and 2014–15). A total of 52.02 billion clean reads containing 4.67 TB clean data were generated on the 1136 MAGIC lines and eight parental lines. Alignment of clean data on to the reference genome enabled identification of a total, 932,172 of SNPs, 35,973 insertions, and 35,726 deletions among the parental lines. A high-density genetic map was constructed using 57,180 SNPs spanning a map distance of 1606.69 cM. Using compressed mixed linear model, genome-wide association study (GWAS) enabled us to identify 737 markers significantly associated with days to 50% flowering, days to maturity, plant height, 100 seed weight, biomass, and harvest index. In addition to the GWAS approach, an identity-by-descent (IBD)-based mixed model approach was used to map quantitative trait loci (QTLs). The IBD-based mixed model approach detected major QTLs that were comparable to those from the GWAS analysis as well as some exclusive QTLs with smaller effects. The candidate genes like FRIGIDA and CaTIFY4b can be used for enhancing drought tolerance in chickpea. The genomic resources, genetic map, marker-trait associations, and QTLs identified in the study are valuable resources for the chickpea community for developing climate resilient chickpeas.

Crop breeders increasingly need to mitigate the effects of climate change. Ideally, their selection strategies are based on an understanding of crop responses to environmental covariates such as temperature. In this study, the height of 352 varieties (European and Swiss) was repeatedly measured in multiple years. P-splines were used to model plant height as a function of time, from which the phenology parameters jointing (start) and end of stem elongation were derived. An asymptotic model was used to estimate the base-temperature of growth (Tmin), the steepness of the response (lrc), and the growth at optimum temperature (rmax). Parameter rmax had the largest effect on final height, whereas the temperature-response parameters in the narrow sense (Tmin, lrc) were closely connected to phenology. Final height and rmax decreased from the more continental, eastern European countries towards the more maritime, western countries. For genotypes registered in Great Bitain, Tmin was distinctly lower compared to most other regions. Integrating such analysis of in-season responsiveness to fluctuating environmental conditions in breeding will help to improve the genetic gain for climate adaptation. It can only be achieved based on high-throughput assessment of phenotypes in the field throughout the season.HighlightWheat phenology and environmental responses have been affected by breeders’ selections since 1970. High throughput field phenotyping methods reveal these developments, allowing to better adapt future varieties to climate change.

While sparse testing methods have been proposed by researchers to improve the efficiency of genomic selection (GS) in breeding programs, there are several factors that can hinder this. In this research, we evaluated four methods (M1–M4) for sparse testing allocation of lines to environments under multi-environmental trails for genomic prediction of unobserved lines. The sparse testing methods described in this study are applied in a two-stage analysis to build the genomic training and testing sets in a strategy that allows each location or environment to evaluate only a subset of all genotypes rather than all of them. To ensure a valid implementation, the sparse testing methods presented here require BLUEs (or BLUPs) of the lines to be computed at the first stage using an appropriate experimental design and statistical analyses in each location (or environment). The evaluation of the four cultivar allocation methods to environments of the second stage was done with four data sets (two large and two small) under a multi-trait and uni-trait framework. We found that the multi-trait model produced better genomic prediction (GP) accuracy than the uni-trait model and that methods M3 and M4 were slightly better than methods M1 and M2 for the allocation of lines to environments. Some of the most important findings, however, were that even under a scenario where we used a training-testing relation of 15–85%, the prediction accuracy of the four methods barely decreased. This indicates that genomic sparse testing methods for data sets under these scenarios can save considerable operational and financial resources with only a small loss in precision, which can be shown in our cost-benefit analysis.

Genomic selection entails the estimation of phenotypic traits of interest for plants without phenotype based on the association between single-nucleotide polymorphisms (SNPs) and phenotypic traits for plants with phenotype. Typically, the number of SNPs far exceeds the number of samples (high-dimensionality) and, therefore, usage of regularization methods is common. The most common approach to estimate marker-trait associations uses the genomic best linear unbiased predictor (GBLUP) method, where a mixed model is fitted to the data. GBLUP has also been alternatively parameterized as a ridge regression model (RRBLUP). GBLUP/RRBLUP is based on the assumption of independence between predictor variables. However, it is to be expected that variables will be associated due to their genetic proximity. Here, we propose a regularized linear model (namely psBLUP: proximity smoothed BLUP) that explicitly models the dependence between predictor effects. We show that psBLUP can improve accuracy compared to the standard methods on both Arabidopsis thaliana data and Barley data.

Hybrid potato breeding has become a novel alternative to conventional potato breeding allowing breeders to overcome intractable barriers (e.g. tetrasomic inheritance, masked deleterious alleles, obligate clonal propagation) with the benefit of seed-based propagule, flexible population design, and the potential of hybrid vigor. Until now, however, no formal inquiry has adequately examined the relevant genetic components for complex traits in hybrid potato populations. In this present study, we use a 2-step multivariate modeling approach to estimate the variance components to assess the magnitude of the general and specific combining abilities in diploid hybrid potato. Specific combining ability effects were identified for all yield components studied here warranting evidence of nonadditive genetic effects in hybrid potato yield. However, the estimated general combining ability effects were on average 2 times larger than their respective specific combining ability quantile across all yield phenotypes. Tuber number general combining abilities and specific combining abilities were found to be highly correlated with total yield’s genetic components. Tuber volume was shown to have the largest proportion of additive and nonadditive genetic variation suggesting under-selection of this phenotype in this population. The prominence of additive effects found for all traits presents evidence that the mid-parent value alone is useful for hybrid potato evaluation. Heterotic vigor stands to be useful in bolstering simpler traits but this will be dependent on target phenotypes and market requirements. This study represents the first diallel analysis of its kind in diploid potato using material derived from a commercial hybrid breeding program.

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Selection processes in plant breeding depend critically on the quality of phenotype predictions. The phenotype is classically predicted as a function of genotypic and environmental information. Models for phenotype prediction contain a mixture of statistical, genetic and physiological elements. In this chapter, we discuss prediction from linear mixed models (LMMs), with an emphasis on statistics, and prediction from crop growth models (CGMs), with an emphasis on physiology. Three modalities of prediction are distinguished: predictions for new genotypes under known environmental conditions, predictions for known genotypes under new environmental conditions, and predictions for new genotypes under new environmental conditions. For LMMs, the genotypic input information includes molecular marker variation, while the environmental input can consist of meteorological, soil and management variables. However, integrated types of environmental characterizations obtained from CGMs can also serve as environmental covariable in LMMs. LMMs consist of a fixed part, corresponding to the mean for a particular genotype in a particular environment, and a random part defined by genotypic and environmental variances and correlations. For prediction via the fixed part, genotypic and/or environmental covariables are required as in classical regression. For predictions via the random part, correlations need to be estimated between observed and new genotypes, between observed and new environments, or both. These correlations can be based on similarities calculated from genotypic and environmental covariables. A simple type of covariable assigns genotypes to sub-populations and environments to regions. Such groupings can improve phenotype prediction. For a second type of phenotype prediction, we consider CGMs. CGMs predict a target phenotype as a non-linear function of underlying intermediate phenotypes. The intermediate phenotypes are outcomes of functions defined on genotype dependent CGM parameters and classical environmental descriptors. While the intermediate phenotypes may still show some genotype by environment interaction, the genotype dependent CGM parameters should be consistent across environmental conditions. The CGM parameters are regressed on molecular marker information to allow phenotype prediction from molecular marker information and standard physiologically relevant environmental information. Both LMMs and CGMs require extensive characterization of genotypes and environments. High-throughput technologies for genotyping and phenotyping provide new opportunities for upscaling phenotype prediction and increasing the response to selection in the breeding process.

In this thesis the results are described of investigations of various application of genome wide SNP (single nucleotide polymorphism) markers. The set of SNP markers was identified by GBS (genotyping by sequencing) strategy. The resulting dataset of 129,156 SNPs across 83 tetraploid varieties was used directly to map traits, but also as a basis for the development of a 20K SNP array in Potato (Solanum tuberosum L.). Subsequently this array, named SolSTW, was used to collect genotypic data from 569 potato genotypes. This dataset offered insight in the breeding history of potato, population structure, linkage disequilibrium (LD) and the potential of GWAS (genome wide association studies) in potato. In Chapter 2 we describe to development of the SolSTW 20K Infinium SNP array. One third of the SNPs on this array originate from the well-known SolCAP 8303 SNP array. The other SNPs are a subset from a targeted re-sequencing project of 83 tetraploid potato varieties. Because of the high SNP density in potato only a limited number of SNPs is suitable for assay development on a SNP array. An obvious outcome is that flanking SNPs contribute to assay failure, particularly for assays with SNPs located in introns. We used fitTetra software to cluster the distribution of captured signals of each marker into the expected five genotypic classes (nulliplex, simplex, duplex, triplex, quadruplex), resulting in a dataset with 14,530 SNP markers. Subsequently the genotypic data obtained with the SolSTW array was used to characterize a set of 569 potato varieties, advanced breeding clones and progenitors. This resulted in the identification of several footprints of potato breeding. Firstly SNPs were dated i.e. the year of market release of the first variety showing polymorphism for a SNP locus is an indication of the ancestry of a SNP. In such a way we identified SNPs with an ancestry tracing back to heirloom varieties, and SNPs (post-1945 SNPs) tracing back to wild species used in modern introgression breeding. Secondly, the changes in allele frequency were calculated over time. Most SNPs show a relative stable allele frequency over time, and very limited genetic variation is removed from the gene-pool of potato i.e genetic erosion is almost absent. Therefore we conclude that 100 years of breeding has not been able to get rid of non-beneficial genetic variation. Only a limited number of SNPs show a rapid increased in allele frequency, which can be explained by positive selection for disease resistance by breeders, or the more frequent use of several founders. Better understanding of the genome wide decay of Linkage Disequilibrium (LD) and population structure offers relevant knowledge to perform and interpret the results of a genome wide association study (GWAS) (Chapter 3). Linkage disequilibrium (LD) is a complex phenomenon, and the influence of the factors shaping LD in tetraploids is hardly studied. Therefore we used simulated data to disentangle and therewith understand often-confounded factors underlying LD-decay. We simulated datasets differing in number of haplotypes in a population, and differing in percentage of haplotype specific SNPs. In these simulations we observed that the choice of an estimator of LD-decay has a major effect on the outcome of an LD-decay estimate, while the true LD-decay remains the same. Based on the simulation we conclude that a 90% percentile and a so-called D1/2 (the distance where 50% of the initial LD is decayed) performed best to estimate and compare LD-decay in potato. To understand the various aspects of LD-decay in the variety panel of 537 varieties, the panel was subdivided in several groups based on the age of a variety and the population structure groups. This resulted in the identification of LD-decay over time, i.e in relatively young varieties the average size of the LD-blocks is smaller. The differences between subpopulations were smaller and are most likely the effect of the population structure. We also observed that there are very long LD-blocks caused by introgression breeding and that different a priori MAF-thresholds also can influence the outcome of LD-decay estimation. Having both LD-decay and population structure defined a genome wide association study (GWAS) was conducted (Chapter 4). For this purpose α-solanine and α-chaconine were measured in potato tubers. Subsequently the sum of both (total SGA) and the ratio between the two were used to discover QTLs for these traits in a GWAS. Additionally we used three bi-parental populations to validate the GWAS results. Total SGA content was confounded with population structure and therefore it was difficult to explain all phenotypic variation with SNP markers. Two QTLs (Sgt1.1 and Sgt11.1) were identified which could be validated in one of the segregating populations. The ratio between α-solanine and α-chaconine was not confounded with population structure, resulted in the identification of two major-effect QTLs (Sgr7.1 & Sgr8.1) located near the candidate genes SGT1 and SGT2, which are known for being responsible in the final steps towards either α-solanine or α-chaconine. The QTL Sgr8.1 could be validated, however similar phenotypes were explained by different haplotypes in two populations. We show that population structure, low frequent alleles and genetic heterogeneity may explain to some degree the missing heritability in GWAS in potato. In Chapter 5 we describe how the method of graphical genotyping, which is widely used in diploid bi-parental populations, can be applied in a variety panel of tetraploid varieties. We show that a few discrete filtering steps in Excel can be used to display patterns that are visual representations of introgression segments and the locations of historical recombination events. Using this method we identified introgression segments from Solanum vernei including the Gpa5 locus on chromosome 5 and Solanum stoloniferum introgression segment including a gene involved in resistance to Potato Virus Y on chromosome 11. This method requires that the haplotypes that cause the phenotypic effect have to be identical by descent (IBD). In the final chapter 6 the results of chapter 2 to 5 are discussed. We look forward on how our results can be used in future research and applied in marker-assisted breeding. Additionally some new GWAS results are presented for tuber flesh colour, foliage maturity and resistance to Globodera pallida pathotype 3.

In this thesis we describe the results of a number of quantitative techniques that were used to understand the genetics of yield in pepper as an example of complex trait measured in a number of environments. Main objectives were; i) to propose a number of mixed models to detect QTLs for multiple traits and multiple environments, ii) to extend the multi-trait QTL models to a multi-trait genomic prediction model, iii) to study how well the complex trait yield can be indirectly predicted from its component traits, and iv) to understand the ‘causal’ relationships between the target trait yield and its component traits. The thesis is part of an EU-FP7 project “ S mart tools for P rediction and I mprovements of C rop Y ield” (SPICY- http://www.spicyweb.eu/). This project generated phenotypic data from four environments using 149 individuals from the sixth generation of recombinant inbred lines obtained from intraspecific cross between large – fruited inbred pepper cultivar ‘Yolo Wonder’ (YW) and the hot pepper cultivar ‘Criollo de Morelos 334’ (CM 334). A total of 16 physiological traits were evaluated across the four trials and various types of genetic parameters were estimated. In a first analysis, the traits were univariately analyzed using linear mixed model. Trait heritabilities were generally large (ranging between 0.43 – 0.96 with an average of 0.86) and mostly comparable across trials while many of the traits displayed heterosis and transgression. The same QTLs were detected across the four trials, though QTL magnitude differed for many of the traits. We also found that some QTLs affected more than one trait, suggesting QTL pleiotropy (a QTL region affecting more than one trait). We discussed our results in the light of previously reported QTLs for these and similar traits in pepper. We addressed the presence of genotype-by-environment interaction (GEI) in yield and the other traits through a multi-environment (ME) mixed model methodology with terms for QTL-by-environment interaction (QEI). We opined that yield would benefit from joint analysis with other traits and so deployed two other mixed model based multi-response QTL approaches: a multi-trait approach (MT) and a multi-trait multi-environment approach (MTME). For yield as well as the other traits, MTME was superior to ME and MT in the number of QTLs, the explained variance and accuracy of predictions. Many of the detected QTLs were pleiotropic and showed quantitative QEI. The results confirmed the feasibility and strengths of novel mixed model QTL methodology to study the architecture of complex traits. The QTL methods considered thus far are not well suited for prediction purposes as only a limited set of QTL-related markers are used. Since the main interest of this research includes improvement of yield prediction, we explored both single-trait and multi-trait versions of genomic prediction (GP) models as alternatives to the QTL-based prediction (QP) models. This was termed direct prediction. The methods differed in their predictive accuracies with GP methods outperforming QP methods in both single and multi-traits situations. We borrowed ideas from crop growth model (CGM) to dissect complex trait yield into a number of its component traits. Here, we integrated QTL/genomic prediction and CGM approaches and showed that the target trait yield can be predicted via its component traits together with environmental covariables. This was termed indirect prediction. The CGM approach seemed to work well at first sight, but this is especially due to the fact that yield appeared to be strongly driven by just one of its components, the partitioning to fruit. An alternative representation of the biological knowledge of a complex target trait such as yield is provided by network type models. We constructed both conditional and unconditional networks across the four environments to understand the ‘causal’ relationships between target trait yield and its component traits. The final networks for each environment from both conditional and unconditional methods were used in a structural equation model to assess the causal relationships. Conditioning QTL mapping on network structure improved detection of refined genetic architecture by distinguishing between QTL with direct and indirect effects, thereby removing non-significant effects found in the unconditional network and resolving QTL pleiotropy. Similar to the CGM topology, yield was established to be downstream to its component traits, indicating that yield can be studied and predicted from its component traits. Thus, the genetic improvements of yield would benefit from improvements on the component traits. Finally, complex trait prediction can be enhanced by a full integration of the methods described in the different chapters. Recent research efforts have been channelled to incorporating both multivariate whole genome prediction models and crop growth models. Further research is required, but we hope that the present thesis presents useful steps towards better prediction models for complex traits exhibiting genotype by environment interaction.

Background Measurement error in exposure variables is an important issue in epidemiological studies that relate exposures to health outcomes. Such studies, however, usually pay limited attention to the quantitative effects of exposure measurement error on estimated exposure-outcome associations. Therefore, the estimators for exposure-outcome associations are prone to bias. Existing methods to adjust for the bias in the associations require a validation study with multiple replicates of a reference measurement. Validation studies with multiple replicates are quite costly and therefore, in some cases only a single–replicate validation study is conducted besides the main study. For a study that does not include an internal validation study, the challenge in dealing with exposure measurement error is even bigger. The challenge is how to use external data from other similar validation studies to adjust for the bias in the exposure-outcome association. In accelerometry research, various accelerometer models have currently been developed. However, some of these new accelerometer models have not been properly validated in field situations. Despite the widely recognized measurement error in the accelerometer, some accelerometers have been used to validate other instruments, such as physical activity questionnaires, in measuring physical activity. Consequently, if an instrument is validated against the accelerometer, and the accelerometer itself has considerable measurement error, the observed validity in the instrument being validated will misrepresent the true validity. Methodology In this thesis, we adapted regression calibration to adjust for exposure measurement error for a single-replicate validation study with zero-inflated reference measurements and assessed the adequacy of the adapted method in a simulation study. For the case where there is no internal validation study, we showed how to combine external data on validity for self-report instruments with the observed questionnaire data to adjust for the bias in the associations caused by measurement error in correlated exposures. In the last part, we applied a measurement error model to assess the measurement error in physical activity as measured by an accelerometer in free-living individuals in a recently concluded validation study. Results The performance of the proposed two-part model was sensitive to the form of continuous independent variables and was minimally influenced by the correlation between the probability of a non-zero response and the actual non-zero response values. Reducing the number of covariates in the model seemed beneficial, but was not critical in large-sample studies. We showed that if the confounder is strongly linked with the outcome, measurement error in the confounder can be more influential than measurement error in the exposure in causing the bias in the exposure-outcome association, and that the bias can be in any direction. We further showed that when accelerometers are used to monitor the level of physical activity in free-living individuals, the mean level of physical activity would be underestimated, the associations between physical activity and health outcomes would be biased, and there would be loss of statistical power to detect associations. Conclusion The following remarks were made from the work in this thesis. First, when only a single-replicate validation study with zero-inflated reference measurements is available, a correctly specified regression calibration can be used to adjust for the bias in the exposure-outcome associations. The performance of the proposed calibration model is influenced more by the assumption made on the form of the continuous covariates than the form of the response distribution. Second, in the absence of an internal validation study, carefully extracted validation data that is transportable to the main study can be used to adjust for the bias in the associations. The proposed method is also useful in conducting sensitivity analyses on the effect of measurement errors. Lastly, when “reference” instruments are themselves marred by substantial bias, the effect of measurement error in an instrument being validated can be seriously underestimated.

Key words: Potato (Solanum tuberosum L.), segregating population, canopy cover dynamics, tuber bulking dynamics, beta function, thermal time, components of variance, genotype-by-environment interaction (GE), heritability, QTL mapping, QTL-by-environment (QTLE) interaction, complex traits, ecophysiological crop model, GECROS, cultivar choice, maturity type, ideotype breeding, tuber yield. Due to increasing food demand and changing diets potato (Solanum tuberosum L.) is becoming a subsistence crop in many regions. However, the agronomy and whole crop physiology of tuber yield production is extremely complex, due to genotype and environment specific effects on crop physiological and morphological characteristics. Such intrinsic complexities complicate the manipulation of yield determining traits and make their prediction a challenging task. The genetic improvement of tuber yield can be understood more mechanistically by investigating and interpreting the relationships between the main attributes of crop growth. This thesis aims to develop an approach to quantify the yield of individual genotypes and to estimate parameters which may reveal the effects of genetic and environmental factors on the important plant processes controlling tuber yield variation among a large set of F1 (SH83-92-488  RH89-039-16) genotypes of potato and a set of standard cultivars covering a wide range of maturity types. It first presents a model approach to analyse the time course of canopy cover and tuber bulking during the entire crop cycle as a function of thermal time in terms of large number of physiological component traits and explain their inter-relationships and impact on crop maturity and tuber yield production across six contrasting field experiments. The results indicated that the length of the canopy build-up phase (DP1) was conservative with respect to genotype’s maturity type, but the duration of maximum canopy cover (DP2) and the decline phase (DP3) varied greatly, with later genotypes having longer DP2 and DP3 and thus a higher area under whole green canopy curve (Asum). Values of tuber bulking rate (cm) were highest for early maturing genotypes followed by mid-late and then late genotypes. Late maturing genotypes had longest effective duration of tuber bulking (ED) followed by mid-late and early genotypes. As a result tuber yield (wmax) was higher in late genotypes than in early genotypes. The radiation use efficiency (RUE) values were highest for early maturing genotypes followed by mid-late and late genotypes whereas nitrogen (N) use efficiency (NUE) was highest in late maturing genotypes followed by mid-early and early genotypes. High genetic variability and high heritability for most of these traits were found. Results indicated that increased tuber yield by indirect selection for optimal combination of important physiological traits can be achieved. While using these traits as a criterion for selection, the causal physiological relationships and trade-offs must be considered simultaneously. Our molecular dissection of traits determining the dynamics of canopy cover, tuber bulking, and resource (radiation, nitrogen) use efficiencies identified several QTLs, the mapping position of each identified QTL, the interaction of QTL with environment (QTLE) and the magnitude of the QTL effect in explaining genetic variance in both SH and RH parental genomes. The QTL results indicated that one particular chromosomal position at 18.2 cM on paternal (RH) linkage group V was tightly linked to the genotype’s earliness and controlling nearly all the traits and explaining the phenotypic variance by up to 79%. This suggested the pleiotropic nature of the QTL for most of the traits determining crop maturity and tuber yields. A number of QTLs for traits were not detected when tuber yield per se was subjected to QTL analysis. The phenotypic variance explained by the QTLs for tuber yield per se was also lower than for other traits. The physiological and quantitative knowledge gained was used to evaluate the conventional system of maturity type and to quantify and re-define the concept of maturity type on a physiological basis for a large set of genotypes. Four new physiological based maturity criteria were developed based on four canopy cover and tuber bulking traits. Physiological maturity type criteria tended to define maturity classes less ambiguously and were easily and clearly interpretable compared to the conventionally used method of defining maturity. The capability of an ecophysiological model ‘GECROS’ was tested to analyse differences in tuber yield of potato. The model yielded a reasonably good prediction of differences in tuber yield across environments and across genotypes. Model analysis identified the genotypic key-parameters affecting tuber yield production and Nmax (i.e. total crop N uptake) contributed most to the determination of tuber yield. The results concluded that genotypes with higher Nmax and lower tuber N content exhibited higher tuber dry matter yield. Further analysis of the genotypic parameters should be performed in conjunction with molecular markers in order to determine their genetic control and to proceed towards QTL-based crop modelling approach. This thesis identified the dominant component traits mostly involved in the formation of a tuber yield and gave insight into the possibilities of genetically and physiologically manipulating the size or number of such traits. The information obtained should help in marker-assisted selection as well as in designing ideotypes for specific and/or diverse environments. However, to make significant contributions for breeding, there is a need for further research efforts to evaluate the combined physiological and genetic approach.

Wageningen UR Plant Breeding has carried out studies on different developmental processes of potato making use of a segregating population evaluated in the field under different environmental conditions and day length regimens. The field trials have included the evaluation of below and above ground traits during different stages of the growing season. Extensive molecular data is available on this experimental potato population as well. Thus, this population provided an excellent opportunity for genetic studies based on information previously generated in research projects making use of statistical methods and models to integrate the different data sets and developmental stages. We have been able to get insights about the correlation between above and below ground traits over different environments, to identify stable QTLs under different multi-location and multi-year field trials, as well as QTLxE interactions. Valuable information have been generated regarding stability of developmental traits and common genetic factors influencing them. In this sense our study brings new insights related with potato development and adaptation to different environmental conditions.

Reciprocal translocations (RT) are one of the most common structural chromosomal rearrangements occurring in plant species. Spontaneous RT are extremely uncommon in cultivated barley. In fact, ‘Albacete’ is the only extensively cultivated barley variety known to carry a RT without any major reduction in fitness. Previous results have shown that 1H and 3H chromosomes are involved in this translocation which may have a potential interest for plant breeding. A depth understanding of this RT could allowed us to know whether this translocation is involved or not in their drought tolerance and find some interesting phenotypic attributes that could be transfer to other barley genotypes to develop specific germoplasm adapted to stress. In a first step, a set of 230 doubled haploid lines derived from the cross between ‘Albacete’ and the non-translocation barley variety ‘Barberousse’ was used to develop a statistical-genetic approach for the construction of a linkage maps in populations obtained from RT heterozygotes. A preliminary linkage study revealed six main linkage groups, compared to the seven linkage groups on the barley consensus map. One of the linkage groups contained markers of chromosomes 1H and 3H. This union was due to the presence of a RT between chromosomes 1H and 3H in the variety ‘Albacete’. The results of this study revealed that the position of the translocation breakpoints was placed around the centromeric regions for both chromosomes. In a second step, a combination of cytological and molecular genetic approaches was used in order to know how large the segments are that are involved in the interchange between the two chromosomes. The results obtained in this study indicate that the translocation is quite large with breakpoints located on the long arms of chromosomes 1H and 3H resulting in the RT 1HS.1HL-3HL and 3HS.3HL-1HL. The gene content around the translocation breakpoints was estimated at approximately 1,100 and 710 gene models for 1H and 3H, respectively. A large number of doubled haploid lines derived from four crosses involving ‘Albacete’ as one of the parents were used to phenotypically characterize the effects of the RT on some interesting agronomic traits.The results suggested that the RT alone is not causing the drought tolerance of ‘Albacete’; thousand kernel weight is the only trait which is clearly enhanced in the lines carrying the RT. Further work combining the results from this study with QTL analysis was carried out to phenotypically characterize the effects of the reciprocal translocation and QTL simultaneously. For that, an integrated map was constructed making used of a modified version of an algorithm developed by Jansen (2005). Finally, specific QTL methodology for the simultaneous analysis of these interconnected populations was developed; two traits: days to heading (independent of the RT) and thousand kernel weight (affected by the RT) were used as an example.

This thesis addresses the issue of how special players (crisis entrepreneurs) try to generate attention to a latent crisis and how government communication can contribute to identifying and interpreting such a crisis. In chapter 1, I show how crisis communication is an activity that is often associated with organizations. This study takes a different view. It is based on the concept that strategic crisis communication is used by those in the immediate environment to achieve certain goals. In society, certain individuals and groups can decide to oppose and denounce a given crisis. Some of those involved often start signalling the risk of an impending crisis before any such crisis has actually developed. In this study, I refer to individuals who generate signals of this kind as ‘crisis entrepreneurs’. These crisis entrepreneurs typically take the initiative when it comes to airing their concerns about a potential crisis situation. However, such individuals often have to deal with certain interactional problems that make it difficult for them to raise the issue of a crisis. They have to deal with certain ‘interactional’ challenges, while running the risk that their signals will not be picked up. For instance, they can be held responsible for raising the problem in question. They can be accused of bearing some degree of personal responsibility for the problem, through negligence, incompetence, or laziness, for example. In this study, I have explored the way in which crisis entrepreneurs issue signals. This is an attempt to identify the problems that they encounter as they attempt to draw people’s attention to a given crisis. The goal of this study is to enhance our understanding of crisis entrepreneurs’ interactional problems. The study makes use of the ‘discursive perspective’, which is based on the discursive psychological approach developed in the 1990s by two British social psychologists, Derek Edwards and Jonathan Potter. To date, this interaction-based approach has seldom been used in the context of crisis communication. Chapter 2 underlines the value of examining the way in which stakeholders within an organization’s environment raise the issue of a crisis. In terms of crises as a phenomenon, it is important to do justice to the dynamics of risks and crises. In essence, this is about what happens in the course of interactions. In such an environment, it is vital for an organization to keep pace with those in its surroundings if it is to observe signals in interaction with this dynamic environment. This requires a view of crisis communication that allows sufficient scope for the interactional dimension. Chapter 3 explores various elements that characterize crises in general, while describing a particularly significant phase - the latent crisis. I have identified two forms of latent crisis, a lingering form and a creeping form. These two forms differ chiefly in terms of the dynamics involved. While the dynamics of both types exhibit both peaks and troughs, there are differences. Lingering crises are entirely lacking in dynamism for extended periods of time. The dynamics of creeping crises, on the other hand, tend to increase gradually. After describing the theoretical framework of the study, chapter 4 proceeds to explore the theoretical and methodological scope of discursive psychology, in terms of an interactional approach to crisis communication. Discursive psychology offers the valuable option of using discourse analysis to examine the social context of risks from the standpoint of everyday reality. A discursive perspective characteristically focuses on a) everyday interactions that are not shaped by the study itself and b) the transactions that, either consciously or unconsciously, feature in such interactions. The discursive perspective offers a specific form of discourse analysis that communications professionals can use to understand how those in the environment express their ideas relative to others. The significance of this is that it can help professionals to understand the specific interactional problems facing crisis entrepreneurs. These involve dealing with certain ‘interactional’ challenges, while running the risk that their signals will not be picked up. Chapter 5 discusses the two cases selected for this study. The selected case domain is education in the Netherlands. I have investigated the ways in which crisis entrepreneurs have signalled problems in this sector. I used discourse analysis (Edwards, 1997; Potter, 1992) to first examine the interactional efforts of those behind collective social movements, then those of individual whistleblowers. To this end, I studied an interview with Matthé Sjamaar, the rector of a secondary school, which was published in Onderwijsblad (education journal) in May 1998. I also examined the manifesto of Beter Onderwijs Nederland (better education for the Netherlands; BON), which was published in the NRC Handelsblad newspaper in June 2006. Both sources raised the issue of a crisis. One of the criteria that I used in selecting these texts was whether the crisis entrepreneur in question had the ability to influence the public debate. In both cases, both local and national media responded to the statements made by these crisis entrepreneurs. Using a discursive response analysis, I explored the way in which newspapers dealt with the interactional problems faced by these crisis entrepreneurs. Chapters 6 and 7 form the empirical part of this study. The analysis identified three important discursive activities that are carried out by crisis entrepreneurs. These are: 1. demonstrating the validity of the problem, 2. establishing the messenger’s credibility, and 3. creating the belief in a solution. The analysis showed that Matthé Sjamaar creates indirectly undetermined others in the environment as being partly responsible for the cause of the problem, while exhibiting a degree of fatalism and holding out no prospect of a solution. He makes an indefinite-side group responsible for the problems. He shows he can not control the problem because it is too large. He creates the crisis as an isolated entity. They are merely the facts which he shows, which are independent of him. He suggests that he has done a lot of hard work and now others have to do something. The media portrayed Rector Sjamaar as symbolizing a problem that was primarily a personal issue. BON, on the other hand, presents itself as a collective that is committed to achieving better education in the Netherlands. The writers display insight and overview of the education problem and create the association to BON as a group consisting of ‘outspoken thinkers’ who are not hindered by doubts. The authors set themselves superior in their attitude towards the education reformers. The writers poses the problem as clear and relevant to everyone and so they create their own need for existence. So now they start a movement and give voice to something that has long been going on: BON is the solution to turn the tide. We can jointly fate a twist. Various media sources reinforced this image, portraying this social movement as the solution to the problem. The study has shown that crisis entrepreneurs may differ in terms of the strategies used and the interactional problems encountered. The solutions put forward by BON have proved more effective than those suggested by Rector Sjamaar. As a result, the discursive activities pursued by the former have been more successful than those of the latter. The diverse reactions exhibited by the media sources in this study serve to underline the precarious nature of a crisis entrepreneur’s operation. For instance, the analysis shows that rather than focusing on the authenticity of his signal, the responses to Matthé Sjamaar’s article dismiss his views as a purely private emotion. Based on this study, I show that the Rector’s initiative was undermined by his presentation of the problem. It failed to trigger a general sense of crisis as a result of segregation. BON fared very differently, as the problem of educational reform is already widely recognized. Moreover, as the analysis shows, BON’s spokespersons are important actors in this connection. Ad and Marijke Verbrugge have put forward polarizing arguments, in which they distance themselves from the New Learning concept. These views have clearly been taken on board by supporters and opponents in the debate triggered by these authors. The study has also shown that certain interactional problems are not necessarily inevitable, but that such problems can be triggered by crisis entrepreneurs themselves. Its content is inextricably linked to people’s goals in making specific comments. Chapter 8 summarizes the main observations in this thesis. It shows that the problems created by raising the issue of a latent crisis are not purely substantive in nature (‘is this crisis genuine?’), there is also an interactional aspect (for example, ‘how do I get people to accept the urgency and validity of the problem?’). My study provides a greater understanding of the course that crises can take. It also shows that crisis entrepreneurs can be seen as dynamic elements within society. They express dissenting views, and launch new initiatives through various forms of traditional and electronic media. This process can be very instructive. Communications professionals can better understand how crises develop among those in their environment if they are aware of the types of interactional problems, and the types of responses, that can result from raising the issue of a crisis. Moreover, this might also help communications professionals to achieve better outcomes in their dealings with crisis entrepreneurs. A discursive approach is valuable in this respect because it shows how certain themes in communication can deal with policy development. This approach can lead to a better hold on these themes in practice and can provide another perspective to widespread failure of interaction between government and citizens. The government is often unable to understand what the citizen means, because their interactional problems are not recognized. Knowledge of their doubts on an issue, can help the organization to acquire a better understanding of objections – from inside and out – against a particular policy. A discourse analysis of the interactional contributions of crisis entrepreneurs may give a rich and structured insight into latent crisis supply, including the strategies, interactional problems and reactions of the actors involved and how they are able to recognize a potential crisis.

AFLP is a widely used DNA fingerprinting technique, resulting in band absence - presence profiles, like a bar code. Bands represent DNA fragments, sampled from the genome of an individual plant or other organism. The DNA fragments travel through a lane of an electrophoretic gel or microcapillary system, and are separated by length, with shorter fragments traveling further. Multiple individuals are simultaneously fingerprinted on a gel. One of the applications of AFLP is the estimation of genetic similarity between individuals, e.g. in diversity and phylogenetic studies. In that case, profiles of two individuals are compared, and the fraction of shared (comigrating) bands is calculated, e.g. using the Dice similarity coefficient. Two comigrating bands may share the same fragment, but band sharing could also be due to chance, if two equally sized, but different fragments are amplified. This is called homoplasy. Homoplasy biases similarity coefficients. Homoplasy could also occur within a lane, if two different fragments of equal length are amplified, resulting in a single band. We call this collision. The main objective of this thesis is the study of collision and homoplasy in AFLP. The length distribution of AFLP fragments plays an important role. This distribution is highly skewed with more abundant short fragments. By simulation the expected similarity for unrelated genotypes is calculated. As much as 40% of the bands may be shared by chance in case of profiles with 120 bands. The collision problem is analogous to the birthday problem, which has a surprising solution. The collision problem is even more extreme, making it even more surprising. Profiles with only 19 bands contain collision(s) with probability 1/2. These findings have consequences for practice. In some cases it is better to prevent the occurrence of collisions by decreasing the number of bands, in other cases a correction for homoplasy and collision is preferred. Modified similarity coefficients are proposed, that estimate the fraction of homologous fragments, correcting for homoplasy and collision. Partially related to homoplasy and collision, we study the codominant scoring of AFLP in association panels. Examples of AFLP in lettuce and tomato serve as illustrations.

The results of a four year project within the Centre for BioSystems Genomics (www.cbsg.nl), entitled “Association mapping and family genotyping in potato” are described in this thesis. This project was intended to investigate whether a recently emerged methodology, association mapping, could provide the means to improve potato breeding efficiency. In an attempt to answer this research question a set of potato cultivars representative for the commercial potato germplasm was selected. In total 240 cultivars and progenitor clones were chosen. In a later stage this set was expanded with 190 recent breeds contributed by five participating breeding companies which resulted in a total of 430 genotypes. In a pilot experiment, the results of which are reported in Chapter 2, a subset of 220 of the abovementioned 240 cultivars and progenitor clones was used. Phenotypic data was retrieved through contributions of the participating breeding companies and represented summary statistics of recent observations for a number of traits across years and locations, calculated following company specific procedures. With AFLP marker data, in the form of normalised log-transformed band intensities, obtained from five well-known primer combinations, the extent of linkage disequilibrium (LD), using the r2 statistic, was estimated. Population structure within the set of 220 cultivars was analysed by deploying a clustering approach. No apparent, nor statistically supported population structure was revealed and the LD seemed to decay below the threshold of 0.1 at a genetic distance of about 3cM with this set of marker data. Furthermore, marker-trait associations were investigated by fitting single marker regression models for phenotypic traits on marker band intensities with and without correction for population structure. Population structure correction was performed in a straightforward way by incorporating a design matrix into the model assuming that each breeding company represented a different breeding germplasm pool. The potential of association mapping in tetraploid potato has been demonstrated in this pilot experiment, because existing phenotypic data, a modest number of AFLP markers, and a relatively straightforward statistical analysis allowed identification of interesting associations for a number of agro-morphological and quality traits. These promising results encouraged us to engage into an encompassing genome-wide association mapping study in potato. Two association mapping panels were compiled. One panel comprising 205 genotypes, all of which were also present in the set used for the pilot experiment, and another panel containing in total 299 genotypes including the entire set of 190 recent breeds together with a series of standard cultivars, about 100 of which are in common with the first panel. Phenotypic data for the association panel with 205 genotypes were obtained in a field trial performed in 2006 in Wageningen at two locations with two replicates. We will refer to this set as the “2006 field trial”. Phenotypic data for the other panel with 299 genotypes was contributed by the five participating breeding companies and consisted of multi-year-multi-location data obtained during generations of clonal selection. The 2006 data were nicely balanced, because the trial was designed in that way. The historical breeding dataset was highly unbalanced. Analysis of these two differing phenotypic datasets was performed to deliver insight in variance components for the genotypic main effects and the genotype by environment interaction (GEI), besides estimated genotype main effects across environments. Both phenotypic datasets were analysed separately within a mixed model framework including terms for GEI. In Chapter 3 we describe both phenotypic datasets by comparing variance components, heritabilities (=repeatabilities), intra-dataset relationships and inter-dataset relationships. Broader aspects related to phenotypic datasets and their analysis are discussed as well. To retrieve information about hidden population structure and genetic relatedness, and to estimate the extent of LD in potato germplasm, we used marker information generated with 41 AFLP primer combinations and 53 microsatellite loci on a collection of 430 genotypes. These 430 genotypes contain all genotypes present in the two association mapping panels introduced before plus a few extra genotypes to increase potato germplasm coverage. Two methods were used: a Bayesian approach and a distance-based clustering approach. Chapter 4 describes the results of this exercise. Both strategies revealed a weak level of structure in our material. Groups were detected which complied with criteria such as their intended market segment, as well as groups differing in their year of first registration on a national list. Linkage disequilibrium, using the r2 statistic, appeared to decay below the threshold of 0.1 across linkage groups at a genetic distance of about 5cM on average. The results described in Chapter 4 are promising for association mapping research in potato. The odds are reasonable that useful marker-trait associations can be detected and that the potential mapping resolution will suffice for detection of QTL in an association mapping context. In Chapter 5 a comprehensive genome-wide association mapping study is presented. The adjusted genotypic means obtained from two association mapping panels as a result of phenotypic analysis performed in Chapter 3 were combined with marker information in two association mapping models. Marker information consisted of normalised log-transformed band intensities of 41 AFLP primer combinations and allele dosage information from 53 microsatellites. A baseline model without correction for population structure and a more advanced model with correction for population structure and genetic relatedness were applied. Population structure and genetic relatedness were estimated using available marker information. Interesting QTL could be identified for 19 agro-morphological and quality traits. The observed QTL partly confirm previous studies e.g. for tuber shape and frying colour, but also new QTL have been detected e.g. for after baking darkening and enzymatic browning. In the final chapter, the general discussion, results of preceding chapters are evaluated and their implications for research as well as breeding are discussed.

A large amount of crop genetic diversity is being maintained in farmers' fields worldwide. The population genetics of traditionally managed landraces is therefore of interest to the conservation of genetic resources. The growing trend towards agricultural modernization and the prospect of introducing genetically modified varieties into centers of origin have increased the need to understand the determinants of genetic structure in landraces of our basic food crops. Patterns of genetic diversity are known to be affected by environmental and geographic factors, but there has been an increasing interest in the role of farmers. Recent years have seen work on both genetic differentiation between seedlots, as well as on the agricultural practices that are expected to influence this differentiation. Unfortunately, few studies have been able to link observed patterns of differentiation to farming practice. The lack of a proper analytical framework has probably contributed to this omission. The population genetics of landraces is complex, with many human and environmental factors affecting the distribution of genetic variation. In this thesis, we aim at achieving a better understanding of the processes that underlie the genetic structure maize landraces in their centre of origin, Mexico. We combine a wide range of theoretical and empirical methods in order to provide explanations for observed patterns of genetic structure. In addition, we use these tools to predict some present and future consequences of seed management by farmers on the genetic identity of landrace populations. In chapter II, we present a metapopulation model that accounts for several features that are unique to managed maize populations. We developed a coalescence-based model of a metapopulation undergoing pollen and seed flow as well as extinction in the form of seed replacement. Unlike previous models, our model treats seed migration as episodic-, partial replacement from a single source rather than as constant immigration from the entire metapopulation. We showed that this particular form of migration leads to novel results. Contrary to classical predictions, within-deme coalescence time was not invariant to the amount of migrating seed. Genetic structure had a parabolic relationship to the amount of migrating seed instead of showing the expected exponential decrease. In contrast, the effects of seed migration frequency on diversity and structure were in line with classical predictions. We concluded that is impossible to describe seed migration by a single parameter. Genetic structure was shown to depend on deme size when the amount of migrant seed is large. Extinction decreased or increased genetic structure depending on the level of migration and number of demes. Finally, we demonstrated that higher levels of pollen migration can mask the effects of seed management. This model provides an important first step in our ability to understand the effects of farming practice on the population genetics of maize landraces. In chapter III, we study the joint role of the environment and humans as determinants of genetic differentiation. We present results on the hierarchical genetic structure in a sample of seedlots in highland and lowland environments in central Mexico. Within-and between village Fsl and Qsl values were used as measures of neutral and agronomic genetic differentiation respectively. We developed and used a new computer model to predict Fst in the two environments on the basis of data on local seed management practice and planting patterns. Strong genetic differences were found between highland and lowland maize, for both markers and traits. Three highland villages planted maize of admixed origin, as evidenced by both molecular markers and phenological traits. This suggested that human mediated gene flow from lowland to highland environments has taken place. Molecular differentiation was low for molecular markers but was notably higher in the lowlands. Our model correctly predicted this difference based on lower pollen flow and smaller seedlot sizes in the lowlands. Agronomical traits showed higher differentiation between villages and were probably subject to diversifying selection. Phenological traits showed the strongest differentiation. Field data suggested that different planting dates may explain the observed differences. Phenological differentiation was highest in the transect containing the admixed seedlots, proving that genetic structure may result from the introgression of traits that diverged in a foreign environment. In chapter IV, we address the issue of genetic erosion in modernized subsistence agriculture. Genetic erosion is thought to occur when modern varieties replace traditional landraces. Actual proof of genetic erosion for any particular area or crop has been rarely found however. A complicating factor in the study of diversity loss in traditional agriculture is the often-noted coexistence between traditional and improved varieties. Moreover, adoption of modern varieties into the traditional seed supply system may blur the distinction between modern and traditional varieties. The inability to classify germplasm into discrete types makes it hard to measure diversity. We addressed these problems by means of a case study on modernized smallholder maize agriculture in southern Mexico. We characterized seedlots obtained from both farmers and commercial seed vendors, for agronomical traits and molecular markers. Farmer interviews were used to distinguish between traditional landraces and recycled modern varieties. We calculated genetic diversity, defined as the mean differentiation between individual seedlots, for different types of germplasm. Modem germplasm was clearly distinct from traditional landraces. Close resemblance between modem- and recycled modem varieties proved that despite years of independent evolution, recycled varieties have not diverged much from their ancestral stocks. We showed that different traits reveal different levels of relative diversity, demonstrating the inherent difficulty of assessing diversity loss. The group of recycled modem varieties presented the lowest diversity for all measured traits. We could therefore predict that complete replacement of landraces by these varieties will reduce diversity in the traditional seed system. Under current patterns of coexistence however, the distinctness of modem and traditional varieties caused only a limited reduction of genetic diversity. Chapter V. deals with the effects of reproductive and population genetic processes on the probability of detecting inadvertently introduced transgenes in maize landraces. This subject has become relevant since initial findings suggesting contamination of Mexican landraces with transgenes were followed by contradictory results in subsequent years. Theoretical and simulation results showed that certain aspects of maize reproductive biology negatively affect the detection probability. We demonstrated that the strongest potential limitation on detection was caused by the aggregated frequency distribution that is a consequence of farmer-mediated introduction of transgenes. Analysis of recent sampling efforts reveals that detection probabilities may be much lower than previously assumed, partly explaining the recent inconsistent results 123

The advent of DNA-marker technology has made the detection of quantitative trait loci (QTLs) a routine activity in plant breeding. While standard procedures are available for QTL mapping, more flexible strategies are required to analyse the complex data typically produced by plant breeding programs. This thesis presents a general and flexible mixed model QTL mapping approach. The philosophy is to include genotypic information derived from molecular markers as explanatory variables to model complex phenotypic responses, while exploiting the flexibility of mixed models to account for complex variance-covariance structures in the data. Attractive generalisations of our QTL models incorporate explicit information on genotypes and environments, for example, as obtained from crop growth models, thereby opening the way to eco-physiological QTL models.The application of the methodology to cases commonly found in plant breeding is illustrated throughout the various chapters of the thesis. In chapter 2, a QTL model is presented for probably the most typical experimental set up in plant breeding, the multi-environment trial. The QTL model describes the genetic basis of genotype by environment interaction for a single trait and tests for environment-specific QTL effects (QTL by environment interaction). After detection of QTLs underlying genotype by environment interaction, the model is extended to make QTL expression dependent on environmental variables. In a reanalysis of yield data stemming from the North American Barley Genome Mapping Project (NABGMP), a QTL for yield was detected on barley chromosome 2H whose effect was proportional to the temperature range at heading time. In chapter 3, the single trait multi-environment model is elaborated to the multi-trait multi-environment situation. We show with another reanalysis of data from the NABGMP how questions related to pleiotropy and genetic linkage as causing genetic correlations between traits can be addressed. Both pleiotropic and linked QTLs were found to explain genetic correlations between heading date and yield. In chapter 4, the linear mixed model is generalised to a non-linear mixed model to describe parameters of a growth curve as a function of QTL effects. The approach is illustrated by an example on potato leaf senescence. QTLs were identified that affect growth trajectories in different ways, thereby contributing to a better understanding of the genetic control of complex traits over time. In chapter 5, we show that not only designed bi-parental cross populations can be naturally handled by mixed model QTL formulations, but also non-designed populations within association mapping approaches. With another example in potato, we analyse historical disease resistance data produced over 25 years of potato variety trial testing in combination with targeted molecular marker techniques to detect interesting markers for breeders. Pedigree information was used to improve the modelling of genetic variances and correlations between genotypes. An association mapping approach using mixed models incorporating pedigree information performed better than commonly used association mapping strategies. Significant associations were detected that proved to be consistent when tested in a confirmatory data set. Finally, chapter 6 consists in a discussion of the mixed model approach as a general framework for QTL mapping in plant breeding.

Plants is mostly done through linkage analysis. A segregating mapping population Identification and mappping of Quantitative Trait Loci (QTLs) in is created from a bi-parental cross and linkages between trait values and mapped markers reveal the positions ofQTLs. Inthisstudyweexploredlinkagedisequilibrium(LD)mappingof traits in a set of modernbarleycultivars. LDbetweenmolecularmarkerswasfoundup to a distance of 10 centimorgan,whichislargecomparedtootherspecies.Thelarge distancemightbeinducedby LDincreasingfactorssuchasinbreedingandthefactthatthepopulationismostlikelybasedon arathersmallset offoundinggenotypes. Associationsbetweenmarkersandtraitswerefoundforyield,yieldstability,leafrustresistance(LR),barleyyellowdwarfvirusresistance(BYD), plantheight,anddaystoheading.Trait-associatedmarkersfromLDanalysiswerelocatedinregionswherealreadyQTLsforthetraitconsideredhadbeenreportedfromstudiesbasedonbi-parentalcrosses. In addition, newQTLswerefoundforyield,yieldstability, LRandBYD.WeexpectthatLDmappingwillbecomeavaluableextension toconventionalQTLanalysisin plantbreeding.Specialattentionwasgivento traitsdescribinggenotype×environmentinteractions.Statisticalmodelswereusedtodefinemeasuresforyieldadaptabilityandyieldstabilitywithoutincludingenvironmentalfactorsdirectlyinthemodels.Adaptabilitywasdefinedastheresponsivenessofthegenotypetotheenvironment,andstabilitywasdefinedastheunexplaineddeviationfromthestatisticalmodel. LDmappinginbarleycultivarsresultedinmarker-traitassociations foryieldstability. In addition, linkage analyses in fourdoubled-haploidpopulationsresultedindetectionofmanyQTLsforadaptability, butonlya single QTL forstability.Weconcludedthatadaptabilitymeasuresweregeneticallybetterdefinedthanstabilitymeasuresandthatselectionforadaptabilityshouldbepossible.

Keywords:Rice, O ryza sativa , yield potential, yield gap, salinity, nitrogen supply, agro-ecosystems, Recombinant Inbred Line, genotype × environment interaction, yield components, adaptability, molecular markers, QTL, biomass, leaf area, leaf N, dry matter allocation, ORYZA1, modelling.Meeting the world's requirement for rice production in the future needs a dual approach: 1. the theoretical yield potential of rice should increase and 2.theyield gaps should be reduced especially in marginal areas where stresses such as salinity, low supply of plant nutrients, droughts and flooding often limit yields. Rice breeding used to be geared towards developing cultivars for high-input management conditions and these cultivars may not be suited to low input environments. In regions such asAfrica, where most of the rice is produced under low-input conditions, breeding should be targeted at rice cultivars that are tolerant to the main stresses encountered in the rice agro-ecosystems. Soil salinity and inadequate supply of plant nutrients (especially nitrogen) are two major stresses limiting rice yields in The Gambia where this study was undertaken. The aim of this study was to determine appropriate selection methods for rice across a range of environments and to identify options at the level of yield components and physiological traits to increase rice yield potentials under both high and low input conditions. For this purpose, a segregating population of rice comprising Recombinant Inbred Lines (RILs) developed from the cross of a high-yielding, semi-dwarf, salt-sensitive cultivar, IR29 and a tall, traditional, salt-tolerant cultivar, Pokkali, was grown in fresh water (EC of 0.15 dS m-1) and saline (EC of 8 dS m-1) conditions with 0 or 100 kg ha-1nitrogen.Analyses of variance revealed significant genotype × environment interaction for yield and for the four yield components, number of panicles m-2, total number of grains per panicle, thousand grainweightand percent spikelet fertility, across the range of test environments. Inter-environmental correlations for grain yield between the 0 and 100 kg ha-1N fertilizer regimes were high and significant in both fresh and saline water signifying that in the lowland, rice can be bred for general adaptability to different N fertilizer levels. However, the inter-environmental correlations for yield between fresh water and saline conditions, especially for the highest yielding cultivars in either environment, were low. This suggests that different sets of rice cultivars should be bred for cultivation in fresh water or saline environments. Analysis of the relationships between yield and yield components by means of regression revealed that generally in fresh waterenvironments,yield was sink-limited and that grain number attributes (comprising number of panicles m-2and total number of grains per panicle) of rice should be enhanced in order to boost yield potential under fresh water conditions. In saline environments, however, salt stress strongly limits assimilate production and translocation. To increase rice yield potential in saline environments, cultivars with better grain filling attributes (comprising grain weight and spikelet fertility) should be developed. The N fertilizer regime influenced the relative importance of panicles m-2and total number of grains per panicle in fresh water and of individual grain weight and spikelet fertility in saline environments, for yield determination.Through molecular marker analysis, putative quantitative trait loci (QTLs) were detected for grain yield and yield components in all four test environments. Overall, markers accounted for 23%-60% of the variation in yield and yield components. Markers associated with more than one trait had either similar or opposite effects on the traits. For all five traits studied, most markers were expressed in only one environment implying strong environmental specificity in expression of the QTLs for rice yield and yield components. Marker-assisted selection, based on AFLP markers, was successfully conducted for grain yield of rice in all four test environments over two years.A study of the physiological basis of yield formation recognized the importance of high biomass production in all test environments for high yielding ability. High biomass production in fresh water environments was associated with high leaf area index and high leaf N concentration while in salineenvironments,high biomass production was better associated with leaf area index than with leaf N concentration. Salt stress reduced leaf area index, biomass production and yield but increased leaf N concentration and prolonged growth. In saline environments, differences in leaf area index and biomass between salt-tolerant and salt-sensitive genotypes were larger during the pre-flowering growth phase than after anthesis.Around flowering time, high stem weights and allocation of more dry matter to shoots instead of roots, reduced yields in fresh water environments but increased yields in saline water environments.High leaf weights and late flowering increased yields in fresh water but in saline environments high leaf weights decreased yields in the zero N fertilizer regime and increased yields in the high N fertilizer regime. In saline environments, late flowering generally reduced yields.The ORYZA1 model gave good predictions of yield and biomass in all test environments although grain yield was better predicted than biomass production and predictions were better in fresh water than in saline environments. The model revealed, through sensitivity analysis, the yield increment that can be achieved by improving leaf area index, specific leaf N and fraction of dry matter allocated to panicles during grain filling, for diverse rice genotypes in different environments. For saline environments, inclusion of effects of salinity on specific leaf N and spikelet fertility in the model are expected to improve its performance.A thorough understanding of the genetic and physiological basis of yield formation in different environments would help breeders develop rice cultivars with high yield potentials under low- and/or high input cultivation environments. Integrating knowledge from different scientific disciplines such as statistics, physiology, biotechnology and systems modelling would facilitate this process.

Keywords: Agro-biodiversity, farmer varieties, indigenous knowledge, farmer-participatory research, genetic diversity, genotype-by-environment interaction, germplasm collection, Ipomoea batatas , specific adaptation, yield stability, sweetpotato, variance component estimates.Between 1999 and 2001, the author conducted various studies, primarily in northeasternUganda, aimed at rapidly assessing the potential of farmer varieties of sweetpotato ( Ipomoea batatas ) from northeasternUgandain contributing to the varietal improvement programme inUganda. These studies included: (i) collection of germplasm (farmer varieties) and farmer knowledge about varieties from five districts in northeastern Uganda; (ii) assessment of morphological diversity and duplication in the collected germplasm; (iii) farmer participatory on-station selection of promising varieties from the collected germplasm for on-farm and multi-locational testing; (iv) farmer-managed on-farm testing in Soroti District (northeastern Uganda) of selected farmer varieties, cultivars from the Ugandan breeding programme and local farmer varieties; (v) multi-locational testing and stability analysis of selected farmer varieties and officially released cultivars from the Ugandan breeding programme in multiple test environments (20 tests over three seasons). Additionally, the author presents results from a multi-national, multi-locational test of elite sweetpotato germplasm in easternAfricaused to study selection efficiency.During germplasm collections, a total of 206 accessions were collected, along with farmer knowledge about them, and of these 188 were classified as distinct accessions, exhibiting considerable morphological variation. Many accessions were collected from remote locations where sweetpotato is not a commercial crop, while relatively few accessions were collected from areas where the crop is important commercially. During the on-station assessment of the collected germplasm, 11 accessions were selected for further testing from a total of 160 accessions evaluated at two sites. Nine of the 11 accessions selected by farmers werecommon to both sites. Farmer selection criteria were verified, with a high weighting given to fresh storage root yield, storage root number and harvest index, in addition to root dry matter content and appearance. During on-farm trials over two years, the 11 farmer varieties were generally preferred over local varieties, and cultivars from the Ugandan breeding programme. During multi-locational trials, the 11 farmer varieties on average performed better with respect to broad adaptation, specific adaptation and yield stability, than the cultivars from the breeding programme. In addition, some of the farmer varieties showed specific adaptation to local environments.Results of the multi-national trial were analyzed to generate recommendations for optimum selection efficiency, and indicated a two-step selection procedure with two locations and one replication at Selection Step 1 and five locations and two replications at Selection Step 2 (total test capacity of between 450 and 950 plots).During the farmer participatory phases of this research, farmers were highly competent in sweetpotato varietal selection and were aware of the genotype-by-environment interactions and biodiversity. Results illustrate the potential that farmer varieties can have in the improvement of sweetpotato inUgandaand other regions where high diversity of sweetpotato landraces exists, and allowed us to recommend an approach for the rapid and efficient selection of superior genotypes from local germplasm inEast Africa