Tag Archives: hydroponic barley fodder system

Cuttings were placed in pots with approximately 400 cm3 of potting soil in a greenhouse

One and two weeks after inoculation, the roots were carefully removed from the Magenta jars, were rinsed, and were prepared either for GUS-staining or for viewing under a Zeiss Axiophot fluorescent microscope. Nodulation in potting soil. Stem cuttings of the transgenic alfalfa plants were made as described above and allowed to root.One week before inoculation, nitrogen nutrition was withdrawn from the plants, but other macronutrients were supplied. The potting soil was leached with large quantities of tap water four and one days before inoculation. Rm1021 cells were grown in RDM medium , containing 100 mg of streptomycin per liter to an OD600 of 0.11 or 0.13, depending on the experiment. Rhizobia were pelleted in a clinical centrifuge and were suspended in sterile milli-Q water to an OD600 of 0.1 . Rm1021 suspension was placed on the surface of the potting soil of each plant. The plants were grown for 21 dpi. Stems were cut off at the crown, and the potting soil was gently removed from the nodulated roots in standing tap water. The nodules were separated from the roots, were divided into pink and senescent types, and were counted. The external morphology of the nodules was also examined. Nodulation in Turface rooting medium. Rooted cuttings were placed in pots with approximately 400 cm3 of inert Turface rooting medium and were allowed to grow in the presence of a complete, dilute nutrient solution. One day before inoculation, nitrogen was withdrawn from the plants. Rm1021, grown to early stationary phase,barley fodder system was prepared as described above. Rm1021 suspension was inoculated onto each plant. The plants grew for 34 more days, and then, the stems were cut off at the crown. The Turface was removed from the nodulated roots in standing tap water. The external nodule morphology was examined. Nodulation under hydroponic conditions. Stem cuttings were allowed to root as described above.

Fluorescent light grates were covered with aluminum foil, and individual square openings of the grate, five to six squares apart, were cut out for placement of plants. The rooting medium was gently removed from the roots of the cuttings by placing them in standing tap water. The crown of each rooted cutting was wrapped in cotton and firmly wedged into an opening of a fluorescent light grate. Rooted cuttings were spaced evenly, with 30 cuttings per grate. Each grate was placed on top of a tank containing 30 liters of complete 1 /4-strength Hoagland’s medium. Tanks were continuously aerated with aquarium pumps. Six independent vector control, 12 independent LEC1AS, and 12 independent LEC2AS plant lines were used in each of six hydroponic tanks. The entire assembly of 30 plants could be removed and replaced relatively undisturbed from the medium. The complete nutrient solution was replaced with 30 liters of ¼-strength Hoagland’s medium lacking nitrogen. Five days after medium replacement, a suspension of Rm1021, prepared as described above, was uniformly mixed into the medium, and the roots were returned to the solution. Rm1021 inocula from mid-lag, early-exponential, late-exponential, early-stationary, or stationary phase were used. The liquid level of the hydroponic tanks was maintained by adding deionized water. The plants grew for an additional 28 to 37 dpi. Stems of nodulated plants were cut at the crown, were dried under vacuum at 45°C for 2 days, and were weighed. The nodulated roots were pooled for each plant type and were stored at –20°C; the nodules were later separated from the roots. Nodules and roots were dried under vacuum for 2 days at 45°C and were weighed. Some nodulated roots were left intact, were allowed to dry at room temperature under ambient conditions for 14 days, and then were weighed. Uninoculated plants were removed from the hydroponic conditions, were dried in the greenhouse for 1 week, and then, the roots and vegetative tissues were separated at the crowns and weighed. With the growing population and limited freshwater resources, there is increased interest in water conservation practices like using recycled wastewater and hydroponic agriculture. The presence of pathogens in the associated environmental compartments exposes a large fraction of the general populace to infection risks. Therefore, a need of the hour is ensuring that our infrastructure meets the safety requirements designed to protect human health.

Proper disposal and treatment of wastes generated at hospitals, industries and residences help meet this goal by reducing the pathogen loads in the environment. However, complete elimination of pathogens is not an option. Therefore, a framework to quantify the threat to human health is desired. The popularly adopted framework is called Quantitative Microbial Risk Assessment or QMRA. With the growing population and limited freshwater resources, there is increased interest in water conservation practices like using recycled wastewater and hydroponic agriculture. The presence of pathogens in the associated environmental compartments exposes a significant fraction of the general populace to infection risks. Therefore, a need of the hour is ensuring that our infrastructure meets the safety requirements designed to protect human health. Proper disposal and treatment of wastes generated at hospitals, industries, and residences help achieve this goal by reducing the pathogen loads in the environment. However, complete elimination of pathogens is not an option. Therefore, a framework to quantify the threat to human health is desired. The popularly adopted framework is called Quantitative Microbial Risk Assessment or QMRA. The main tenets of QMRA are as follows: 1) hazard identification; 2) exposure assessment; 3) dose-response modeling; 4) risk characterization, and 5) risk management. Hazard identification constitutes deciding on the system of interest and listing out the pathogens present/expected in that system. After identifying the hazard, the interaction of people with the system are modeled to quantify exposure to the pathogen. Suppose the system of interest is a particular lake used for recreation, and the hazard identified is E. coli. Exposure assessment would entail enumerating the E. coli finally ingested by the person . These processes have a lot of associated variability and uncertainty. Therefore, quantities are stratified by groups or represented by distributions rather than point estimates. Estimating the risk while accounting for these variabilities and uncertainties is done by Monte Carlo sampling. Dose-response models relate the number of the pathogen to the probability of a person falling ill . They are constructed with data from clinical trials in which a predetermined dose of pathogens is administered to a cohort of subjects and the number falling ill counted. The latter is then divided by the total number of subjects to reflect the probability of a single person falling ill.

This process is repeated for different pathogen doses to generate data for the models. While these clinical trials may use animals, datasets generated from human trials are preferred since they better reflect the human situation. Popular DRMs are the exponential and beta-Poisson models. DRMs for different pathogens may share the same functional form but differ in the numerical values of model parameters as a consequence of the biological differences between the pathogens. Risk characterization involves calculating the risk posed by the hazard by integrating the output of the exposure assessment with the DRM of choice for that pathogen. One then compares these estimates with guidelines established by the U.S. Environmental Protection Agency or the World Health Organization . Based on these comparisons, risk management measures can be investigated in an iterative process by computing the risk posed by the intervention measures. Understanding the risk posed by ARB has been stymied by the absence of DRMs parameterized for ARB. This difficulty arises from the clinical trials used to parameterize current DRMs, which were performed using antibiotic sensitive bacteria . While we have invitro kinetic information relating ARB to ASB, the biophysical/kinetic interpretation of the parameters of the popular exponential and beta-Poisson DRMs is not straightforward. Moreover,hydroponic barley fodder system the dose-response outcome is potentially complicated by the other processes at play, such as horizontal gene transfer and the differential influence of antibiotics on ASB and ARB death rates. The resulting illness may or may not respond to antibiotic treatment if the ARB sub-population persists. These challenges require a mathematical framework capable of handling the underlying processes, which can then be used to perform risk assessments of ARB and determine the best course of action. A point of longstanding debate in QMRA, and broadly the topic of disease progression, is the hypothesis of independent action. It proposes that pathogens act independently of one another, and each has a probability p of initiating infection. The alternative hypothesis is one of cooperation where infection is expected when more than one organism survives to overwhelm the host’s defenses collectively. DRMs assuming independent action have wider acceptance than DRMs which assume cooperativity. However, DRMs with cooperativity consider the cumulative effects of bacteria but not the potential synergistic interactions between bacterial cells or quorum sensing. I believe that incorporating cell-cell interaction in dose-response is an essential step to developing a better understanding of the development of disease and its treatment.Risk estimates for lettuce grown in the hydroponic tank or soil are presented in Fig. 2.4. Across these systems, the FP model predicted the highest risk while the 1F1 model predicted the lowest risk.

For a given risk model, higher risk was predicted in the hydroponic system than in the soil. This is a consequence of the very low detachment rates in soil compared to the attachment rates. Comparison of results from Sc1 and Sc2 of soil grown lettuce indicated lower risks and disease burdens under Sc1 . Comparing with the safety guidelines, the lowest risk predicted in the hydroponic system is higher than the U.S. EPA defined acceptable annual drinking water risk of 10−4 for each risk model. The annual burdens are also above the 10−6 benchmark recommended by the WHO. In the case of soil grown lettuce, neither Sc1 nor Sc2 met the U.S. EPA safety benchmark. Two risk models predicted borderline disease burden according to the WHO benchmark, for soil grown lettuce in Sc1, but under Sc2 the risk still did not meet the safety guideline. I found that neither increasing holding time of the lettuce to two days after harvesting nor using bigger tanks significantly altered the predicted risk . In comparison, the risk estimates of are higher than range of soil grown lettuce outcomes presented here for 2 of 3 models. The SCSA sensitivity indices are presented in Fig. 2.5. For hydroponically grown lettuce, the top 3 factors influencing daily risk are amount of lettuce consumed, time since last irrigation and the term involving consumption and ρshoot. Also, the risk estimates are robust to the fitted parameters despite low identifiability of some model parameters . For soil grown lettuce, kp appears to be the major influential parameter, followed by the input viral concentration in irrigation water and the lettuce harvest time. Scorr is near zero, suggesting lesser influence of correlation in the input parameters. To predict viral transport in plant tissue, it is necessary to couple mathematical assumptions with an understanding of the underlying biogeochemical processes governing virus removal, plant growth, growth conditions and virus-plant interactions. For example, although a simple transport model without AD could predict the viral load in the lettuce at harvest, it failed to capture the initial curvature in the viral load in the growth medium . An alternative to the AD hypothesis that could capture this curvature is the existence of two populations of viruses as used in, one decaying slower than the other. However, I did not adopt this approach as the double exponential model is not time invariant. This means that the time taken to decay from a concentration C1 to C2 is not unique and depends on the history of the events that occurred . Other viral models, such as the ones used in faced the same issues. Incorporating AD made the model time invariant and always provided the same time for decay between two given concentrations. This model fitting experience showcases how mathematics can guide the understanding of biological mechanisms. The hypothesis of two different NoV populations is less plausible than that of viral attachment and detachment to the hydroponic tank. While it appears that incorporating the AD mechanism does not significantly improve the accuracy of viral load predictions in the lettuce shoot at harvest, this is a consequence of force fitting the model to data under the given conditions.

The application of an appropriate photochemical model could answer this unknown

Although some microorganisms also fix nitrogen, they do not represent significant sources of atmospheric NH3 on Earth. Likewise, the associated detection of N2O and other nitrogen-containing species would provide confidence that the production of NH3 is associated with industrial disruption of a planetary nitrogen cycle. It is worth emphasizing that NH3 or N2O alone would not necessarily be technosignatures, as either of these species could be false positives for life or could arise from nontechnological life . Rather, it is the combination of NH3 and N2O that would indicate disruption of a planetary nitrogen cycle from an ExoFarm, which may also show elevated abundances of NOx gases as well as CH4. The short lifetime of NH3 in an oxic atmosphere implies that a detectable abundance of NH3 would suggest a continuous production source. Although NH3 could be produced abiotically by combining N2 and H2, an atmosphere rich in H2 would be unstable to the O2 abundance required to sustain photosynthesis. The technosignature of an ExoFarm would therefore require the simultaneous detection of both NH3 and N2O in the atmosphere of an exoplanet along with O2, H2O, and CO2.Large-scale agriculture based on Haber–Bosch nitrogen fixation could be detectable through the infrared spectral absorption features of NH3 and N2O as well as CH4. A robust assessment of the detectability of such spectral features in an Earth-like atmosphere would ideally use a three-dimensional coupled climate–chemistry model to calculate the steady-state abundances of each of these nitrogen-containing species a function of biological and technological surface fluxes. But as an initial assessment,hydropopnic barley fodder system we consider a scaling argument to examine the spectral features that could be detectable for present-day and future Earth agriculture.

We define four scenarios for considering agriculture on an Earth-like planet, with the corresponding atmospheric abundances of nitrogen-containing species listed in Table 1. The present-day Earth scenario is based on recent measurements of NH3, N2O, and CH4 abundances . The choice of 10 ppb for NH3 is toward the higher end for Earth today and corresponds to regions of intense agricultural production. The preagricultural Earth scenario serves as a control, where the agricultural and technological contributions of NH3, N2O, and CH4 have been removed. Note that this approach assumes that eliminating the technological contributions to the atmospheric flux of these nitrogen-containing species will reduce the steady-state atmospheric abundance by a similar percentage; this approach is admittedly simplified, but the results can still be instructive for identifying the possibility of detectable spectral features. The third and fourth scenarios project possible abundances of NH3, N2O, and CH4 for futures with 30 and 100 billion people, respectively. Earth holds about 7.9 billion people today, and population projections differ on whether or not Earth’s population will stabilize in the coming century . These two population values were selected because they correspond approximately to the maximum total allowable population using all current arable land and all possible agricultural land . Most published estimates of Earth’s carrying capacity range from about 8 to 100 billion, although some estimates are less than 1 billion while others are more than 1 trillion . Theoretically, an extraterrestrial population with the energy requirements of up to 100 billion calorie consuming humans could sustain Haber–Bosch synthesis over long timescales, as long as sustainable energy sources are used . These scenarios also follow a scaling argument by assuming that the per-person contributions of these three nitrogen-containing species will remain constant as population grows. This again is a simplifying assumption that is intended as an initial approach to understanding the detectability of such scenarios.

We consider the detectability of all four of these scenarios using the Planetary Spectrum Generator . PSG is an online radiative transfer tool for calculating synthetic planetary spectra and assessing the limits of detectability for spectral features that can range from ultraviolet to radio wavelengths. The ultraviolet features of NH3, N2O, and CH4 are strongly overlapping and only show weak absorption, but mid-infrared features of all these species could be more pronounced. The mid-infrared spectral features of NH3, N2O, and CH4 calculated with PSG for preagricultural, present-day, and future Earth scenarios are plotted in Figure 1, which shows the relative intensity and transmittance spectra for observations of an Earth-like exoplanet orbiting a Sun-like star. The spectra shown in Figure 1 show the strongest absorption features due to NH3 from 10 to 12 μm, while N2O shows absorption features from 3 to 5 μm, 7 to 9 μm, and 16 to 18 μm. Absorption features due to CH4 overlap some of the N2O features from 3 to 5 μm and 7 to 9 μm. The change in peak transmittance between 10 and 12 μm for NH3 compared to the preagricultural control case is about 50% for the future Earth scenario with 100 billion people and about 25% for the scenario with 30 billion people. For N2O, the change in peak transmittance between 16 and 18 μm compared to the preagricultural control case is about 70% for 100 billion people and 50% for 30 billion people. The change in relative intensity for the 100 billion people scenario is up to about 10% compared to the preagricultural control case between 7 and 9 μm and 10 and 12 μm. Present-day Earth agriculture would exert a weakly detectable signal that might be difficult to discern from the preagricultural control case, but future scenarios with enhanced global agriculture could produce absorption features that are easier to detect. The spectral features of NH3, N2O, and CH4 could be detectable in emitted light or as transmission features for transiting planets. Specifically, the N2O line at 17.0 μm shows a strong dependency with the N2O volume mixing ratio and to a second order the NH3 line at 10.7 μm. For the future 100 billion case, both display strong enough absorption to bdetectable by the Large Interferometer for Exoplanets , Origins and Mid-InfraRed Exo-planet CLimate Explorer infrared mission concepts.

The James Webb Space Telescope Near Infrared Spectrograph could potentially detect CH4 within the 0.6–5.3 μm range for transiting exoplanets . However, the detection of CH4 alone would provide no basis for distinguishing between technological, biological, or photochemical production. The detectability of these spectral features do not necessarily directly correspond to the peak transmittance, and a full accounting of the detectability of each band would need to account for the observing mode and instrument parameters. It is beyond the scope of this present paper to present detectability calculations for specific missions, as any missions capable of searching for mid-infrared technosignatures are in an early design phase, at best. One of the goals of this Letter is to highlight the importance of examining mid-infrared spectral features of exoplanets,livestock fodder system as many potential technosignatures could be most detectable at such wavelengths. Also, it demonstrates the duality of the search for bio-signatures and technosignatures. The search for passive, atmospheric technosignatures does not require the development of a dedicated instrument but can leverage the capability of instruments dedicated to the search for bio-signatures.The calculations presented in this Letter indicate the possibility of detecting a technosignature from planetary-scale agriculture from the combined the spectral features of NH3 and N2O, as well as CH4. The signature of such an ExoFarm could only occur on a planet that already supports photosynthesis, so such a planet will necessarily already show spectral features due to H2O, O2, and CO2. The search for technosignatures from extraterrestrial agriculture would therefore be a goal that supports the search for bio-signatures of Earth-like planets, as the best targets to search for signs of nitrogen cycle disruption would be planets already thought to be good candidates for photosynthetic life. A better constraint on the detectability of the spectral features of an ExoFarm would require the use of an atmospheric photochemistry model. This Letter assumed simple scaling arguments for the abundances of nitrogen containing species, but the steady-state abundance of nitrogen containing atmospheric species will depend on a complex network of chemical reactions and the photochemical impact of the host star’s UV spectrum. In such future work, the increases of NH3 and N2O, and CH4 from agriculture would be parameterized via surface fluxes instead of arbitrary fixed and vertically constant mixing ratios. A network of photochemical reactions would then determine the vertical distribution of those species in the atmosphere. A photochemical model could also capture the processes of wet and dry deposition of NH3, which is the major sink in Earth’s present atmosphere, as well as aerosol formation from NH3 and SO2/N2O that can occur in regions of high agricultural production. Past studies have predicted more favorable build-up of bio-signature gases on oxygen-rich Earth-like planets orbiting later spectral type stars due to orders of magnitude less efficient production of OH, O, and other radicals that attack trace gases like CH4 .

The photochemical lifetime of N2O and therefore its steady-state mixing ratio will be enhanced by less efficient production of O radicals that destroy it. However, because deposition is the major sink of NH3, it is not clear whether a different stellar environment would alter the atmospheric lifetime of NH3, and if so, to what extent.Examining the four scenarios in this study with such a photochemical model would require additional development work to extend the capabilities of existing models to oxygenrich atmospheres. Past photochemical modeling studies that have included NH3 considered anoxic early Earth scenarios where the focus was determining the plausible greenhouse impact of NH3 to revolve the faint young Sun paradox . More recent studies have considered NH3 bio-signatures in H2-dominated super-Earth atmospheres, which would greatly favor the spectral detectability of the gas relative to high molecular weight O2-rich atmospheres . On H2 planets with surfaces saturated with NH3, deposition is inefficient, and sufficient biological fluxes can overwhelm photochemical sinks and can allow large NH3 mixing ratios to be maintained . These “Cold Haber Worlds” are far different from the O2–N2 atmosphere we consider here, where surfaces saturated in NH3 are implausible and photochemical lifetimes are shorter. Ideally, future calculations would use a three-dimensional model with coupled climate and photochemical processes suitable for an O2–N2 atmosphere to more completely constrain the steady-state abundances, and time variation, in nitrogencontaining species for planets with intensive agriculture. Future investigation should also consider false-positive scenarios for NH3 and N2O as a technosignature. One possibility is that a species engages in global-scale agriculture using manure only; such a planet could conceivably accumulate detectable quantities of NH3 and N2O without the use of the Haber–Bosch process. The distinction between these two scenarios might be difficult to resolve, but both forms of agriculture nevertheless represent a technological innovation. Whether or not similar quantities of NH3 and N2O could accumulate on a planet by animal-like life without active management is a possible area for future work. External factors such as stellar proton events associated with flares could also produce high abundances of nitrogen-containing species in an atmosphere rich in NH3 , so additional false-positive scenarios should be considered for planets in systems with high stellar activity. This Letter is intended to present the idea that the spectral signature of extraterrestrial agriculture would be a compelling technosignature. This does not necessarily imply that extraterrestrial agriculture must exist or be commonplace, but the idea of searching for spectral features of an ExoFarm remains a plausible technosignature based on future projections of Earth today. Such a technosignature could also be long-lived, perhaps on geologic timescales, and would indicate the presence of a technological species that has managed to coexist with technology while avoiding extinction. Long-lived technosignatures are the most likely to be discovered by astronomical means, so scientists engaged in the search for technosignatures should continue to think critically about technological processes that could be managed across geologic timescales. J.H.M. gratefully acknowledges support from the NASA Exobiology program under grant 80NSSC20K0622. E.W.S. acknowledges support from the NASA Interdisciplinary Consortia for Astrobiology Research program. T.J.F and R.K.K. acknowledge support from the GSFC Sellers Exoplanet Environments Collaboration , which is supported by NASA’s Planetary Science Divisions Research Program. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of their employers or NASA.