Browsing by Subject "Corn"

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Comparison of omics technologies for hybrid prediction
(2019) Westhues, Matthias; Melchinger, Albrecht E.
One of the great challenges for plant breeders is dealing with the vast number of putative candidates, which cannot be tested exhaustively in multi-environment field trials. Using pedigree records helped breeders narrowing down the number of candidates substantially. With pedigree information, only a subset of candidates need to be subjected to exhaustive tests of their phenotype whereas the phenotype of the majority of untested relatives is inferred from their common pedigree. A caveat of pedigree information is its inability to capture Mendelian sampling and to accurately reflect relationships among individuals. This shortcoming was mitigated with the advent of marker assays covering regions harboring causal quantitative trait loci. Today, the prediction of untested candidates using information from genomic markers, called genomic prediction, is a routine procedure in larger plant breeding companies. Genomic prediction has revolutionized the prediction of traits with complex genetic architecture but, just as pedigree, cannot properly capture physiological epistasis, referring to complex interactions among genes and endophenotypes, such as RNA, proteins and metabolites. Given their intermediate position in the genotype-phenotype cascade, endophenotypes are expected to represent some of the information missing from the genome, thereby potentially improving predictive abilities. In a first study we explored the ability of several predictor types to forecast genetic values for complex agronomic traits recorded on maize hybrids. Pedigree and genomic information were included as the benchmark for evaluating the merit of metabolites and gene expression data in genetic value prediction. Metabolites, sampled from maize plants grown in field trials, were poor predictors for all traits. Conversely, root-metabolites, grown under controlled conditions, were moderate to competitive predictors for the traits fat as well as dry matter yield. Gene expression data outperformed other individual predictors for the prediction of genetic values for protein and the economically most relevant trait dry matter yield. A genome-wide association study suggested that gene expression data integrated SNP interactions. This might explain the superior performance of this predictor type in the prediction of protein and dry matter yield. Small RNAs were probed for their potential as predictors, given their involvement in transcriptional, post-transcriptional and post-translational regulation. Regardless of the trait, small RNAs could not outperform other predictors. Combinations of predictors did not considerably improve the predictive ability of the best single predictor for any trait but improved the stability of their performance across traits. By assigning different weights to each predictor, we evaluated each predictors optimal contribution for attaining maximum predictive ability. This approach revealed that pedigree, genomic information and gene expression data contribute equally when maximizing predictive ability for grain dry matter content. When attempting to maximize predictive ability for grain yield, pedigree information was superfluous. For genotypes having only genomic information, gene expression data were imputed by using genotypes having both, genomic as well as gene expression data. Previously, this single-step prediction framework was only used for qualitative predictors. Our study revealed that this framework can be employed for improving the cost-effectiveness of quantitative endophenotypes in hybrid prediction. We hope that these studies will further promote exploring endophenotypes as additional predictor types in breeding.
Factors influencing the accuracy of genomic prediction in plant breeding
(2017) Schopp, Pascal; Melchinger, Albrecht E.
Genomic prediction (GP) is a novel statistical tool to estimate breeding values of selection candidates without the necessity to evaluate them phenotypically. The method calibrates a prediction model based on data of phenotyped individuals that were also genotyped with genome-wide molecular markers. The renunciation of an explicit identification of causal polymorphisms in the DNA sequence allows GP to explain significantly larger amounts of the genetic variance of complex traits than previous mapping-based approaches employed for marker-assisted selection. For these reasons, GP rapidly revolutionized dairy cattle breeding, where the method was originally developed and first implemented. By comparison, plant breeding is characterized by often intensively structured populations and more restricted resources routinely available for model calibration. This thesis addresses important issues related to these peculiarities to further promote an efficient integration of GP into plant breeding.
Improvements of the doubled haploid technology in maize
(2019) Molenaar, Willem; Melchinger, Albrecht E.
The in vivo doubled haploid (DH) technology in maize carries many advantages over traditional line development by recurrent selfing and has played an integral role in numerous breeding programs since the early 21st century. A bottleneck in the DH technology is still the success rate of chromosome doubling treatment, which has a strong influence on the costs of DH production. Currently, only a minority (~10%) of treated D0 haploid plants result in DH lines. Improvement in the chromosome doubling step of DH production would not only make DH lines cheaper, but could also change the optimum allocation of resources in hybrid breeding. In addition, the development of treatments using alternative doubling agents to colchicine, which is toxic to humans, would improve worker safety and simplify waste disposal issues for developing countries to benefit from the DH technology. Initiating such developments is the goal of this thesis. In a first step, we evaluated anti-mitotic herbicides with different modes of action as alternatives to colchicine for reducing the toxicity of chromosome-doubling treatment and for potentially increasing the success rates. In a series of experiments, we evaluated anti-mitotic herbicides with different modes of action in different concentrations and combinations. Based on the results of the initial experiments, we chose a specific concentration of amiprophos-methyl for evaluation in combination with varying concentrations of pronamide in a further experiment. This revealed the optimal concentration of pronamide in combination with the chosen concentration of amiprophos-methyl. However, this less-toxic treatment showed slightly lower success rates and slightly higher costs per DH line as compared to the standard colchicine treatment. In a second step after evaluating anti-mitotic herbicides for seedling treatment, we evaluated gaseous treatments using nitrous oxide (N2O), an anti-mitotic gas, in varying concentrations and combinations with air and pure oxygen. In two years of evaluation, we found an N2O treatment which had similar success rates as colchicine. The major benefit of such treatment is that this gas can simply be released into the atmosphere, eliminating the difficulty of proper chemical waste disposal, which is difficult to secure in developing countries. The only requirement is a treatment chamber, in contrast to the laboratory facilities required for handling colchicine. In a third step, we evaluated the potential of spontaneous chromosome doubling (SCD) as an alternative to chemical treatment-based chromosome doubling. Although previous studies found significant genetic variation and high heritability for SCD, a classical quantitative genetic analysis, elucidating the type of gene action governing this trait, and a selection experiment for improving SCD was missing in the literature. We found a predominance of additive genetic effects compared to epistatic effects, and a large selection gain after three cycles of recurrent selection for SCD to levels far beyond those reached by standard colchicine treatment. This indicates the great potential of SCD to improve the DH technology. The approximately ten-fold increase in spontaneous chromosome doubling rate (SDR) reached in our recurrent selection experiment marks a paradigm shift in the chromosome doubling step of DH production in maize. DH production efficiency can be greatly increased by the vast improvement in SDR, and production can be further simplified to enable even higher throughput. Instead of chromosome doubling treatment, which involves much handling of seedlings, haploid seeds from germplasm with a high innate ability to produce seed set without chemical treatment can be simply seeded in the DH nursery, eliminating the most costly production steps. Thus, this thesis has provided new opportunities to increase worker safety and reduce toxic waste in DH production, and further provided a proof of concept for genetic improvement of spontaneous chromosome doubling, which has great prospects for increasing the efficiency of DH production in maize.
Towards sustainable chemical fertilizer management in China : from theory to farm household
(2023) Yu, Xiaomin; Doluschitz, Reiner
Over the past few decades, China’s grain production has expanded drastically. On the one hand, this has eliminated food shortages and allowed China to feed its huge and still growing population. On the other hand, the rapid growth in grain productivity has come at a heavy cost. Excessive fertilizer use has led to a variety of negative consequences that threaten national food security and environmental sustainability. Since the 2010s, the Chinese government and academia have made considerable efforts to reduce the consumption of chemical fertilizers and improve nutrient management. These include a wide range of regulations to control or guide chemical fertilizer use, policies to eliminate subsidies for the fertilizer industry, and nationwide promotion of scientific fertilizer application methods. In response to these efforts, Chinas overall fertilizer application rate has been declining since 2016. However, China still applies far more fertilizers than its crops need, and the current crop Nitrogen Use Efficiency (NUE) and Phosphorus Use Efficiency (PUE) in China are both below the global average. Therefore, reducing dependence on chemical fertilizers for crop production and sustainably feeding a large population remains a key challenge for China. This dissertation aims to contribute to sustainable nutrient management in China by providing a comprehensive and in-depth understanding of fertilizer use and management at the national, regional, farm and household levels. In the first study (Chapter 2), a systematic review of the historical development and current status of chemical fertilizer use and management in China at the national level is presented. In addition, fertilizer nutrient surpluses are estimated for 30 provinces in China and the regional and temporal variations are visualized. In the second study (Chapter 3), the relationship between fertilizer nutrient surpluses and the regional economy at the provincial level is examined within the framework of the Environmental Kuznets curve (EKC) hypothesis. A panel cointegration approach is employed, using time-series data from 1988 to 2019. In the third study (Chapter 4), the research focus is further narrowed to the farm household resolution. Using cross-sectional survey data from 774 maize-growing farms in northern China in 2019, the study investigates the role of farm characteristics, farmers knowledge, perceptions, and socioeconomic context in farmers fertilizer use strategies. The studies confirm that by 2021, China has reached zero growth in fertilizer use and fertilizer nutrient surpluses at the national and regional level. However, regions with a high proportion of cash crops, such as the southeast coast and northwest, still suffer from high nutrient surpluses. Furthermore, in circa 2012, China has reached its EKC turning point between fertilizer nutrient surpluses and GDP per capita. With further economic growth, the fertilizer surpluses in most Chinese provinces will decrease, indicating a moderating of the tension between economic development and the environment. Looking at the farm and household level, the study shows that in northern China, small farms are more likely to overuse fertilizers in maize cultivation without further yield improvement. Current extension programs have had a positive impact on farmers’ fertilizer use strategies and environmental awareness; nevertheless, the coverage and effectiveness of trainings should be improved. In summary, the dissertation identifies the following key factors that impede sustainable chemical fertilizer management in China: small farm size; regional economic dependence on cash crops; the large discrepancy between farmers practices and scientific production guidelines; and the shrinking and aging of Chinas rural labor force. To address these aspects, the dissertation proposes recommendations at the national strategic level, policy level and implementation level, respectively. The findings and recommendations of this dissertation can serve as a robust decision support and scientific basis for policy makers, stakeholders and researchers in the field of sustainable nutrient management in China.