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All roads lead to growth
(2020)
Plant growth is a highly complex biological process that involves innumerable interconnected biochemical and signalling pathways. Many different techniques have been developed to measure growth, unravel the various processes that contribute to plant growth, and understand how a complex interaction between genotype and environment determines the growth phenotype. Despite this complexity, the term 'growth' is often simplified by researchers; depending on the method used for quantification, growth is viewed as an increase in plant or organ size, a change in cell architecture, or an increase in structural biomass. In this review, we summarise the cellular and molecular mechanisms underlying plant growth, highlight state-of-the-art imaging and non-imaging-based techniques to quantitatively measure growth, including a discussion of their advantages and drawbacks, and suggest a terminology for growth rates depending on the type of technique used.
Heterosis-associated cellular and molecular processes were analyzed in seeds and seedlings of Arabidopsis thaliana accessions Col-0 and C24 and their heterotic hybrids. Microscopic examination revealed no advantages in terms of hybrid mature embryo organ sizes or cell numbers. Increased cotyledon sizes were detectable 4 days after sowing. Growth heterosis results from elevated cell sizes and numbers, and is well established at 10 days after sowing. The relative growth rates of hybrid seedlings were most enhanced between 3 and 4 days after sowing. Global metabolite profiling and targeted fatty acid analysis revealed maternal inheritance patterns for a large proportion of metabolites in the very early stages. During developmental progression, the distribution shifts to dominant, intermediate and heterotic patterns, with most changes occurring between 4 and 6 days after sowing. The highest incidence of heterotic patterns coincides with establishment of size differences at 4 days after sowing. In contrast, overall transcript patterns at 4, 6 and 10 days after sowing are characterized by intermediate to dominant patterns, with parental transcript levels showing the largest differences. Overall, the results suggest that, during early developmental stages, intermediate gene expression and higher metabolic activity in the hybrids compared to the parents lead to better resource efficiency, and therefore enhanced performance in the hybrids.
Soil structure, the complex arrangement of soil into aggregates and pore spaces, is a key feature of soils and soil biota. Among them, filamentous saprobic fungi have well-documented effects on soil aggregation. However, it is unclear what properties, or traits, determine the overall positive effect of fungi on soil aggregation. To achieve progress, it would be helpful to systematically investigate a broad suite of fungal species for their trait expression and the relation of these traits to soil aggregation. Here, we apply a trait-based approach to a set of 15 traits measured under standardized conditions on 31 fungal strains including Ascomycota, Basidiomycota, and Mucoromycota, all isolated from the same soil. We find large differences among these fungi in their ability to aggregate soil, including neutral to positive effects, and we document large differences in trait expression among strains. We identify biomass density, i.e., the density with which a mycelium grows (positive effects), leucine aminopeptidase activity (negative effects) and phylogeny as important factors explaining differences in soil aggregate formation (SAF) among fungal strains; importantly, growth rate was not among the important traits. Our results point to a typical suite of traits characterizing fungi that are good soil aggregators, and our findings illustrate the power of employing a trait-based approach to unravel biological mechanisms underpinning soil aggregation. Such an approach could now be extended also to other soil biota groups. In an applied context of restoration and agriculture, such trait information can inform management, for example to prioritize practices that favor the expression of more desirable fungal traits.
Forage supply of savanna grasslands plays a crucial role for local food security and consequently, a reliable monitoring system could help to better manage vital forage resources. To help installing such a monitoring system, we investigated whether in-situ hyperspectral data could be resampled to match the spectral resolution of multi- and hyperspectral satellites; if the type of sensor affected model transfer; and if spatio-temporal patterns of forage characteristics could be related to environmental drivers. We established models for forage quantity (green biomass) and five forage quality proxies (metabolisable energy, acid/neutral detergent fibre, ash, phosphorus). Hyperspectral resolution of the Hyperion satellite mostly resulted in higher accuracies (i.e. higher R-2, lower RMSE). When applied to satellite data, though, the greater quality of the multispectral Sentinel-2 satellite data leads to more realistic forage maps. By analysing a three-year time series, we found plant phenology and cumulated precipitation to be the most important environmental drivers of forage supply. We conclude that none of the investigated satellites provide optimal conditions for monitoring purposes. Future hyperspectral satellite missions like EnMAP, combining the high information level of Hyperion with the good data quality and resolution of Sentinel-2, will provide the prerequisites for installing a regular monitoring service.
‘Heterosis’ is a term used in genetics and breeding referring to hybrid vigour or the superiority of hybrids over their parents in terms of traits such as size, growth rate, biomass, fertility, yield, nutrient content, disease resistance or tolerance to abiotic and abiotic stress. Parental plants which are two different inbred (pure) lines that have desired traits are crossed to obtain hybrids. Maximum heterosis is observed in the first generation (F1) of crosses. Heterosis has been utilised in plant and animal breeding programs for at least 90 years: by the end of the 21st century, 65% of worldwide maize production was hybrid-based. Generally, it is believed that an understanding of the molecular basis of heterosis will allow the creation of new superior genotypes which could either be used directly as F1 hybrids or form the basis for the future breeding selection programmes. Two selected accessions of a research model plant Arabidopsis thaliana (thale cress) were crossed to obtain hybrids. These typically exhibited a 60-80% increase of biomass when compared to the average weight of both parents. This PhD project focused on investigating the role of selected regulatory genes given their potentially key involvement in heterosis. In the first part of the project, the most appropriate developmental stage for this heterosis study was determined by metabolite level measurements and growth observations in parents and hybrids. At the selected stage, around 60 candidate regulatory genes (i.e. differentially expressed in hybrids when compared to parents) were identified. Of these, the majority were transcription factors, genes that coordinate the expression of other genes. Subsequent expression analyses of the candidate genes in biomass-heterotic hybrids of other Arabidopsis accessions revealed a differential expression in a gene subset, highlighting their relevance for heterosis. Moreover, a fraction of the candidate regulatory genes were found within DNA regions closely linked to the genes that underlie the biomass or growth heterosis. Additional analyses to validate the role of selected candidate regulatory genes in heterosis appeared insufficient to establish their role in heterosis. This uncovered a need for using novel approaches as discussed in the thesis. Taken together, the work provided an insight into studies on the molecular mechanisms underlying heterosis. Although studies on heterosis date back to more than one hundred years, this project as many others revealed that more investigations will be needed to uncover this phenomenon.
OPTIMIZATION OF THE BIOSORPTION OF Cr3+, Cd2+ AND Pb2+ USING A NEW BIOWASTE: Zea mays SEED CHAFF
(2016)
This study highlights the potential use of yellow Zea mays seed chaff (YZMSC) biomass as a biosorbent for the removal of Cr3+, Cd2+ and Pb2+ ions from aqueous solutions. Fourier transformed Infrared analysis of the biomass suggests that YZMSC biomass is basically composed of cellulose and methyl cellulose. The biosorption capacities, q(max), of YZMSC biomass for Cr3+, Cd2+ and Pb2+ are 14.68, 121.95 and 384.62 mg/g respectively. Biosorption equilibrium was achieved at 20, 30 and 60 min for Cr3+, Cd2+ and Pb2+ respectively. YZMSC biomass was found to have higher biosorption capacity and overall kinetic rate of uptake for Pb2+ than for Cd2+ and Cr3+. However, Cr3+ had better initial kinetic rate of uptake by the biomass than Pb2+ and Cd2+. The Freundlich equilibrium isotherm model was found to describe equilibrium data better than Langmuir model suggesting that biosorption of these metal ions could be on more than one active site on the surface of YZMSC biomass. Kinetic study predicted the pseudo-second kinetic model as being able to better describe kinetic data obtained than either modified pseudo-first order or Bangham kinetic models. Biosorption of Cr3+, Cd2+ and Pb2+ onto YZMSC biomass was endothermic in nature with large positive entropy values. Biosorption of these metal ions onto YZMSC biomass was observed to be feasible and spontaneous above 283 K. Optimization of biomass weight for the removal of these metal ions suggest that 384 kg, 129 kg and 144 kg of YZMSC biomass is required for the removal of 95% of Cr3+, Cd2+ and Pb2+ metal ions respectively from 100 mg/L of metal ions in 10 tonnes of aqueous solutions.