Space life sciences: A status report

The scientific research and supporting technology development conducted in the Space Life Sciences Program is described. Accomplishments of the past year are highlighted. Plans for future activities are outlined. Some specific areas of study include the following: Crew health and safety; What happens to humans in space; Gravity, life, and space; Sustenance in space; Life and planet Earth; Life in the Universe; Promoting good science and good will; Building a future for the space life sciences; and Benefits of space life sciences research

Single measurement detection of individual cell ionic oscillations using an n-type semiconductor - Electrolyte interface

Pollen tubes are used as models in studies on the type of tip-growth in plants. They are an example of polarised and rapid growth because pollen tubes are able to quickly invade the flower pistil in order to accomplish fertilisation. How different ionic fluxes are perceived, processed or generated in the pollen tube is still not satisfactorily understood. In order to measure the H+, K+, Ca2+ and Cl- fluxes of a single pollen tube, we developed an Electrical Lab on a Photovoltaic-Chip (ELoPvC) on which the evolving cell was immersed in an electrolyte of a germination medium. Pollen from Hyacinthus orientalis L. was investigated ex vivo. We observed that the growing cell changed the (redox) potential in the medium in a periodic manner. This subtle measurement was feasible due to the effects that were taking place at the semiconductor-liquid interface. The experiment confirmed the existence of the ionic oscillations that accompany the periodic extension of pollen tubes, thereby providing - in a single run - the complete discrete frequency spectrum and phase relationships of the ion gradients and fluxes, while all of the metabolic and enzymatic functions of the cell life cycle were preserved. Furthermore, the global 1/f α characteristic of the power spectral density, which corresponds to the membrane channel noise, was found

Towards In-situ Based Printed Sensor Systems for Real-Time Soil-Root Nutrient Monitoring and Prediction with Polynomial Regression

This dissertation explores how to increase sensor density in the agricultural framework using low-cost sensors, while also managing major bottlenecks preventing their full commercial adoption for agriculture, accuracy and drift. It also investigated whether low-cost biodegradable printed sensor sheets can result in improved stability, accuracy or drift for use in precision agriculture. In this dissertation, multiple electrode systems were investigated with much of the work focused on printed carbon graphene electrodes (with and without nanoparticles). The sensors were used in two configurations: 1) in varying soil to understand sensor degradation and the effect of environment on sensors, and 2) in plant pod systems to understand growth. It was established that 3) the sensor drift can be controlled and predicted 2) the fabricated low-cost sensors work as well as commercial sensors, and 3) these sensors were then successfully validated in the pod platform. A standardized testing system was developed to investigate soil physicochemical effects on the modified nutrient sensors through a series of controlled experiments. The construct was theoretically modeled and the sensor data was matched to the models. Supervised machine learning algorithms were used to predict sensor responses. Further models produced actionable insight which allowed us to identify a) the minimal amounts of irrigation required and b) optimal time after applying irrigation or rainfall event before achieving accurate sensor readings, both with respect to sensor depth placement within the soil matrix. The pore-scale behavior of solute transport through different depths within the sandy soil matrix was further simulated using COMSOL Multi-physics. This work leads to promising disposable printed systems for precision agriculture

Functional characterization and discovery of modulators of SbMATE, the agronomically important aluminium tolerance transporter from Sorghum bicolor.

About 50% of the world's arable land is strongly acidic (pH ≤ 5). The low pH solubilizes root-toxic ionic aluminium (Al3+) species from clay minerals, driving the evolution of counteractive adaptations in cultivated crops. The food crop Sorghum bicolor upregulates the membrane-embedded transporter protein SbMATE in its roots. SbMATE mediates efflux of the anionic form of the organic acid, citrate, into the soil rhizosphere, chelating Al3+ ions and thereby imparting Al-resistance based on excluding Al+3 from the growing root tip. Here, we use electrophysiological, radiolabeled, and fluorescence-based transport assays in two heterologous expression systems to establish a broad substrate recognition profile of SbMATE, showing the proton and/or sodium-driven transport of 14C-citrate anion, as well as the organic monovalent cation, ethidium, but not its divalent analog, propidium. We further complement our transport assays by measuring substrate binding to detergent-purified SbMATE protein. Finally, we use the purified membrane protein as an antigen to discover native conformation-binding and transport function-altering nanobodies using an animal-free, mRNA/cDNA display technology. Our results demonstrate the utility of using Pichia pastoris as an efficient eukaryotic host to express large quantities of functional plant transporter proteins. The nanobody discovery approach is applicable to other non-immunogenic plant proteins

The role of forest trees and their mycorrhizal fungi in carbonate weathering and phosphorus biogeochemical cycling

Over millions of years, atmospheric CO2 concentrations, and Earth’s climate, are regulated by continental silicate weathering and associated marine carbonate deposition. On this geological timescale, carbonate weathering has no net effect on CO2 drawdown. However, over the coming decades-to-centuries, accelerated weathering of carbonate rocks may provide a sink for anthropogenic CO2 emissions and increase alkalinity flux to the oceans to counteract ocean acidification. Recent experimental evidence strongly supports trees and their associated mycorrhizal fungi as key drivers of silicate mineral weathering; however, their role in the context of carbonate weathering is largely unknown. Carbonate lithology is abundant globally and underlies many boreal and temperate forest ecosystems in the northern hemisphere. If biological enhancement of carbonate weathering by forests occurs, this might presents a new opportunity for CO2 sequestration. This thesis presents results from a 14-month field experiment at the UK's national pinetum investigating carbonate rock weathering under a common climate. Overall, I find original evidence for biotic enhancement of calcite- and dolomite weathering by an evolutionary diverse range of trees that host either arbuscular (AM) or ectomycorrhizal (EM) root-associating fungal symbionts. Recent soil analyses are integrated with a re-interpretation of historic data to provide an 85-year record of in-situ soil development under different forestry species. This study challenges the classic dogma that divergence of properties is driven by the major tree functional groups, angiosperms and gymnosperms. Instead, we find that over decades, mycorrhizal functional type plays a dominant role in determining soil physico- chemical characteristics, and conditions generated by EM fungi are likely to enhance mineral weathering. Field trials next investigated the impact of tree-mycorrhizal functional group on weathering of the four main carbonate rock types (chalk, limestone, marble and dolomite) and a quartz silicate. Under EM trees carbonate rock grain dissolution was 12 times faster that silicate weathering. In the initial 3 months, calcite weathering intensity increased from gymnosperm to angiosperm species and from AM to later, but independently-evolved EM fungal partnerships. More extensive weathering after 6 months, especially within EM forest soils, confirms the importance of these fungi for carbonate mineral dissolution and nutrient mobilisation. This effect is linked to rhizosphere acidification by EM fungi and is confirmed by a parallel study of tree species’ influence on soil chemistry. Both AM and EM fungi facilitate the mobilisation of nutrient elements, which are provided to their host plants in exchange for carbon from photosynthesis. I applied a suite of nanoscale surface analysis techniques (VSI, SEM) to quantify mineral alteration and provide direct evidence for mycorrhizal involvement in carbonate weathering in the field. Fungal hyphae preferentially colonised chalk and quartz silicate grains, which contained the highest concentrations of phosphorus (P), a growth limiting elemental nutrient. P was selectively depleted from silicate grains, especially in EM forest soils, but accumulated on carbonates. Although the origin of this accumulated P remains uncertain, extensive analyses of different potential P-pools indicated it is likely to be inorganic, but accumulated via active microbial import. These findings lead to new insights linking carbonate weathering with phosphorus biogeochemical cycling in soils. Results show that P from the surrounding environment is concentrated on carbonate grains and this potentially provides a renewable P resource accessible to host trees. Overall, this thesis builds new support for the role of mycorrhizal partnerships in shaping soil properties important for accelerating carbonate rock weathering (Chapter 2); presenting the first field-based evidence for the enhancement of carbonate dissolution by tree roots and their associated mycorrhizal partners (Chapters 3-5) and generating new insights into biogeochemical P cycling in soils (Chapter 4). More broadly, these findings suggest targeted reforestation/afforestation with EM-tree taxa on carbonate-rich terrain as a possible regional-scale land management strategy for promoting short-term anthropogenic CO2 sequestration and perhaps helping ameliorate ocean acidification

Simulation of site-specific irrigation control strategies with sparse input data

Crop and irrigation water use efficiencies may be improved by managing irrigation application timing and volumes using physical and agronomic principles. However, the crop water requirement may be spatially variable due to different soil properties and genetic variations in the crop across the field. Adaptive control strategies can be used to locally control water applications in response to in-field temporal and spatial variability with the aim of maximising both crop development and water use efficiency. A simulation framework ‘VARIwise’ has been created to aid the development, evaluation and management of spatially and temporally varied adaptive irrigation control strategies (McCarthy et al., 2010). VARIwise enables alternative control strategies to be simulated with different crop and environmental conditions and at a range of spatial resolutions. An iterative learning controller and model predictive controller have been implemented in VARIwise to improve the irrigation of cotton. The iterative learning control strategy involves using the soil moisture response to the previous irrigation volume to adjust the applied irrigation volume applied at the next irrigation event. For field implementation this controller has low data requirements as only soil moisture data is required after each irrigation event. In contrast, a model predictive controller has high data requirements as measured soil and plant data are required at a high spatial resolution in a field implementation. Model predictive control involves using a calibrated model to determine the irrigation application and/or timing which results in the highest predicted yield or water use efficiency. The implementation of these strategies is described and a case study is presented to demonstrate the operation of the strategies with various levels of data availability. It is concluded that in situations of sparse data, the iterative learning controller performs significantly better than a model predictive controller

Air pollution and livestock production

The air in a livestock farming environment contains high concentrations of dust particles and gaseous pollutants. The total inhalable dust can enter the nose and mouth during normal breathing and the thoracic dust can reach into the lungs. However, it is the respirable dust particles that can penetrate further into the gas-exchange region, making it the most hazardous dust component. Prolonged exposure to high concentrations of dust particles can lead to respiratory health issues for both livestock and farming staff. Ammonia, an example of a gaseous pollutant, is derived from the decomposition of nitrous compounds. Increased exposure to ammonia may also have an effect on the health of humans and livestock. There are a number of technologies available to ensure exposure to these pollutants is minimised. Through proactive means, (the optimal design and management of livestock buildings) air quality can be improved to reduce the likelihood of risks associated with sub-optimal air quality. Once air problems have taken hold, other reduction methods need to be applied utilising a more reactive approach. A key requirement for the control of concentration and exposure of airborne pollutants to an acceptable level is to be able to conduct real-time measurements of these pollutants. This paper provides a review of airborne pollution including methods to both measure and control the concentration of pollutants in livestock buildings

A review of wood machining literature with a special focus on sawing

In this review, fundamental wood machining research is evaluated to determine the general cutting mechanics of simple, orthogonal, and oblique cutting tools. Simple tool force trends and chip formation characteristics are indentified here, along with the cause and effects of tool wear. In addition to this, specific methods of evaluating sawing processes have been investigated. These include the use of piezoelectric dynamometers to record tool forces and high speed photography to evaluate chip formation. Furthermore, regression analysis has been previously used to identify tool force trends with respect to both tooth geometry parameters and work-piece properties. This review has identified the original findings of previous research. This will allow for further original research to be conducted