Tag: blueberry container

Given that Huanglongbing is related to ROS-overproduction, ROS-modulating NMs may have significant impact on the disease course. In the nanozyme field, novel ROS-triggering nanozymes are constantly being synthesized. NADPH oxidase, also referred to as RBOH, is a transmembrane enzyme complex that controls the generation of superoxide, which plays an important role in immune signalling pathways. A recent study synthesized a Fe–N-doped graphene nanomaterial that could mimic the activity of NADPH oxidase by efficiently catalysing the conversion of NADPH into NADP+ , subsequently triggering the generation of oxygen radicals. Given these demonstrated ROS-generating properties, FeNGR nanozymes may be applied to cultivate stress-resistant crops. To date, no studies have employed this nanozyme with NADPH oxidase-like activity for stress tolerance enhancement. Thus, the linkage between plant science and nanozyme fields of study could significantly move this field forward. Last, applications of NMs in agriculture need to consider the potential environmental and human health risks. For example, the impacts of NMs on non-target biota needs to be evaluated. The impacts of NMs on soil microbial and fungal communities that are critical to nutrient uptake of plants, as well as carbon and nitrogen cycling, must be evaluated. In addition, the bio-accumulation of NMs, particularly in edible tissues, needs to be investigated to avoid potential transfer in food chains that could negatively impact human or ecosystem health. However, it is clear that sustainable nano-enabled strategies to promote crop species’ tolerance to abiotic and biotic stresses Several studies report the uptake of emerging contaminants from hydroponic solutions, spiked soils and soil irrigated with TWW or amended with bio-solids or animal manure . However,plastic plant containers these studies often report conflicting or contradictory results concerning the rate of uptake and the extent of translocation.

Hydroponic studies often exhibit higher rates of uptake than those observed in spiked or amended soils studies. For example, in a study conducted by Boonsaner and Hawker the maximum concentration of antibiotics in plant tissues was reached within 2 d in spiked water but took 6-8 d when plants were grown in contaminated soils. In hydroponic systems, plant uptake and translocation are largely driven by the contaminants water solubility, log Kowand/or the pH of the hydroponic solution and the potential for ionization, log Dow, . Whereas in soils, soil-specific processes such as soil-pore water partitioning, and transformations in soil, also contribute to contaminant uptake and accumulation in plants. Thus, the uptake rate and translocation of a contaminant in plants can vary widely depending upon soil and environmental conditions. For example, a soil with higher organic matter content can limit plant uptake of organic contaminants, due to stronger contaminant adsorption than a soil with lower organic matter content . Also, shifts in soil pH can result in ionization of ionizable organic contaminants, affecting the rate of plant uptake . Antibiotics constitute one of the most extensively used pharmaceuticals classes for both human and livestock and as such are nearly ubiquitously detected in wastewater effluent, bio-solids and livestock manure . Relatively more studies have been reported on terrestrial plant uptake and translocation of antibiotics than other pharmaceuticals in the agro-environment, including studies conducted in hydroponic growth solutions, greenhouses, and under field conditions .In hydroponic growth solution, the antibiotic sulfamethoxazole was taken up in the roots and translocated to leaves of four vegetable plants, including lettuce , spinach , cucumber , and pepper plants , with the concentration report to be significantly greater in the roots .

In a 55 day hydroponic study, three antibiotics, i.e., tetracycline, cephalexin, and sulfamethoxazole, were found to be taken up and translocated into edible tissues of pakchoi , with concentrations ranging from 6.9 – 11.8, 26.4 – 48.1, and 18.1 – 35.3 µg kg-1 for tetracycline, cephalexin and sulfamethoxazole, respectively . Several studies have also explored plant uptake of antibiotics from spiked soils . For example, Boxall et al., exposed carrot and lettuce plants to soils spiked with 1 mg kg-1 of 7 antibiotics, i.e., sulfadiazine, trimethoprim, tylosin, amoxicillin, enrofloxacin, florfenicol, and oxytetracycline. After 103 d and 152 d cultivation, antibiotics were quantified in both crops. However, the concentrations varied considerably among different antibiotics and between plant species. For example, amoxicillin was detected at < 1 µg kg-1 in lettuce tissues but was 24 µg kg-1 in carrot tissues . Three sulfonamides, i.e., sulfadiazine, sulfamethazine, and sulfamethoxazole, were also reported to be taken up by pakchoi cultivated in spiked-soils, with sulfamethoxazole having the highest concentration among the three antibiotics throughout the 49 d cultivation . To better predict environmentally relevant risks from antibiotic uptake to human consumption, several studies have been carried out on crops grown in soils irrigated with spiked TWW and/or amended with livestock manure . These studies showed that food crops were capable of taking up and accumulating antibiotics from wastewater and/or manure-amended soils; however, the levels were often very low. For example, chlortetracycline was taken up by corn , green onion , and cabbage that were grown in soils amended with antibioticspiked manure . However, the concentrations were low . Sulfamethoxazole and lincomycin were found to accumulate in lettuce tissues at concentrations up to 125 µg kg-1 and 822 µg kg-1 , respectively, after irrigation with antibiotic-spiked synthetic wastewater at 1 mg L-1 , . Similarly, in field studies, crops irrigated with TWW were found to take up antibiotics, including but not limited to, roxithromycin, clindamycin, ciprofloxacin, sulfamerazine, and sulfamethoxazole . However, in nearly every case the concentration of antibiotics in plant tissues was negligibly low. Nonsteroidal anti-inflammatories are the most commonly consumed class of pharmaceuticals in the world .

As such they are ubiquitously found in TWW, bio solids, and surfaces water . They have been reported to accumulate in soils that receive TWW or bio solids . Several studies have explored the potential for uptake and translocation of NSAIDs in plants, including in hydroponic systems, amended soils, and field studies . NSAIDs have a wide range of physicochemical range properties and, as such, have displayed vastly different uptake and translocation rates . For example, in a hydroponic study the NSAID diclofenac was observed to accumulate only in the roots of four vegetables while relatively high levels of acetaminophen were detected in the leaves . Similarly, a study exploring plant uptake of 14C labeled naproxen and diclofenac from hydroponic solutions showed that two vegetables, i.e., lettuce and collard greens , were capable of accumulating both compounds, and both plants accumulated significantly more diclofenac than naproxen . Radish and ryegrass were shown to absorb and accumulate diclofenac from soils spiked with the chemical at an initial concentration of 1 mg kg-1 . However, after 40 d cultivation, the concentration of diclofenac in the plants was very low < 1 µg kg-1 . Greenhouse studies using soils amended with bio solids and field studies using TWW irrigation considered the uptake of NSAIDs under environmentally relevant conditions. For example, Cortés et al. conducted a greenhouse study in which soybeans and wheat were cultivated in bio solids-amended soils for 60 and 110 d. However, none of the four NSAIDs was detected in the plant shoots. On the other hand, in a long-term field study , diclofenac was found relatively high levels in the fruits of tomato plants after prolonged irrigation with TWW, as compared to sulfamethoxazole and trimethoprim . Further, in another field study, naproxen was detected in the edible tissues of various vegetables irrigated with TWW or TWW fortified with the chemical at 250 ng L-1 and grown until maturity . Several NSAIDs have also been considered in the investigation of potential metabolism of pharmaceuticals in plant cell cultures and whole plants . The metabolism of diclofenac was investigated in four different plant systems, including a horseradish hairy root culture , barley , Arabidopsis thaliana cell culture,blueberry container and Arabidopsis thaliana whole plants . However, the formation of diclofenac metabolites differed significantly by plant systems. For instance, while phase I hydroxylation was observed in all the systems, the horseradish hairy root cultures and barley formed a glucopyranoside as the major Phase II metabolite . Arabidopsis thaliana, on the other hand, produced acyl-glutamatyl-diclofenac as the major Phase II metabolite via direct conjugation . Direct conjugation of naproxen and ibuprofen with glutamic acid and glutamine was also observed in Arabidopsis thaliana plants . The metabolism of acetaminophen has also been studied in multiple plant systems, including horseradish hairy root cultures and Indian mustard . In these studies, direct glucuronisation, glucosidation, and sulfation were observed along with the formation of a reactive metabolite N-acetyl-pbenzoquinoneimine . Taken together these studies have highlighted the ability of plants to uptake and transform NSAIDs. Several classes of psychiatric pharmaceuticals have been detected in TWW and bio-solids including antidepressants, mood stabilizers, and antianxiety agents . Of these compounds, carbamazepine has been likely considered in probably the most in the agroenvironment due to its stability during wastewater treatment and in the environment .

Carbamazepine has been often reported to be taken up by plants in both field and laboratory settings . In hydroponic systems, carbamazepine has been shown to accumulate in both roots and shoots of multiple plant species, including lettuce, spinach, cucumber, and peppers . Cucumber was found to readily translocate carbamazepine when cultivated in hydroponic systems . However, a high rate of translocation was not observed in cabbage plants cultivated in hydroponic systems . In greenhouse studies, carbamazepine was reported to be taken up by cucumbers and ryegrass grown in soils irrigated with TWW and urine . In addition, Shenker et al., reported that uptake into cucumbers was negatively correlated with soil organic matter content. In fields irrigated with TWW, trace levels of carbamazepine was found to accumulate in different parts of various vegetables . Carbamazepine was also reported to transfer to humans after consumption of contaminated vegetables . The metabolism of carbamazepine in plants has also been investigated . In carrot cell cultures five phase I metabolites of carbamazepine were observed to form over 22 d . Further, 10,11-epoxycarbamazepine and 10,11-dihydroxycarbamazepine have been reported in carrots and sweet potatoes grown in fields irrigated with CEC-spiked TWW . Fluoxetine is an antidepressant prescribed for both human and animal consumption , resulting in fluoxetine being commonly detected in environmental samples . In hydroponic cultivations fluoxetine was taken up by cauliflower and accumulated in the stems and leaves . In a greenhouse study exploring plant uptake of fluoxetine from soils irrigated with TWW and amended with bio solids fluoxetine accumulated in the roots , but, it was not translocated to the leaves . In addition, fluoxetine displayed an opposite uptake pattern to that for carbamazepine, and showed a greater accumulation in plants grown in bio-solid-amended soils as opposed to soil irrigated with TWW . Benzodiazepines, are one of the most prescribed classes of pharmaceuticals . Of these, diazepam is among the most commonly detected pharmaceuticals in TWW, with concentration ranging from ng L-1 to low µg L-1 . Benzodiazepines have been shown to be taken up and accumulate in tissues of plants grown in treated hydroponic solutions or soils . In hydroponic solutions, diazepam has been observed to accumulate in both the leaves and roots of lettuce, spinach, cucumber, and pepper with BCF of 10-100 ]. Further, in a greenhouse study exploring the uptake of seven benzodiazepines , both silver beets and radish crops took up and accumulated all seven benzodiazepines from the treated-soil . Oxazepam was found to have the highest accumulation in both plants, with concentrations up to 14.2 µg g-1 in silver beets and 5 µg g-1 in radishes . However, the fate of these pharmaceuticals in the agro-environment is still relatively unexplored, even though their physicochemical properties indicate a high potential for uptake by plants .A multitude of antimicrobials and preservatives are used in health and grooming products, collectively known as personal care products . Personal care products have garnered increased scientific attention due to their presence in surface waters and concerns that some of these antimicrobials and preservatives may be endocrine disruptors . Of these, triclocarban and triclosan have been amongst the best studied compounds in the terrestrial environment due to their ubiquitous occurrence in bio-solids and relative stability in soils after bio-solid application .

The exposure variable as well as covariates were all measured using self-reported survey data and subject to recall bias, which has been well described for exposure and disease studies. We limited recall bias in the survey by anchoring the past in memorable events such as recent rainy and dry seasons as well as holidays. While survey respondents sometimes found it difficult to precisely quantify household land area, the evidence for recall bias in agricultural surveys in sub-Saharan Africa is limited. Additionally, infection outcomes are limited by the sensitivity and specificity of available diagnostic methods: urine filtration for S. haematobium and duplicate Kato-Katz examination of two stool samples for S. mansoni. The detection methods used for S. haematobium are more sensitive compared to those used for S. mansoni , but the low sensitivity of diagnostic techniques used to detect S. mansoni infections—especially low intensity infections—may have contributed to the inconclusive results we observed for this parasite species. Our findings add a new dimension to the notion that the benefits of water resources development for food security are offset by infectious disease. While we cannot speak to the dam’s net impact, we find that schistosomiasis risk may be a result of land use for subsistence livelihoods as well as landscape-level environmental change. Residents of the lower basin of the Senegal River face an unfortunate trade-of where the prevailing economic activity may make them sick.Every bio-process in which cells are the final product or used in the production process requires suitable culture conditions for cell growth and product quality. In the rapidly growing cellular agriculture/cultivated meat industry, where cells are grown for consumption to replace carbon‐intensive and often unethical animal agriculture,plastic plant container cost‐effective media has been identified as the most critical aspect in scale‐up and commercialization .

Optimizing these conditions is difficult due to a large number of media components with nonlinear and interacting effects between cells, medium, matrix material, and reactor environment . Typically, culture media used for processes in cellular agriculture consist of a basal medium of glucose, amino acids, vitamins, and salts supplemented with fetal bovine serum for improved cell survival. FBS is an undefined, animal‐derived serum consisting of proteins, hormones, and other large molecular weight components, and contributes substantially to the cost of media . Even when enriched with additional growth factors or FBS, media is often far from optimal for all cell types and requires adaptation and/or optimization , which is difficult for media mixtures with >30 components, as is common in cell culture. To manage this complexity, design‐of‐experiments methods are often employed in which factors are set to a user‐specified value and outputs are measured . These DOE designs are arranged in such a way that statistically meaningful correlations can be found in fewer experiments than techniques like intuition, “one‐factor‐at‐a‐time” sequences, or random designs. A more advanced form of this is to use sequential, model‐based DOEs such as a radial basis function or Gaussian Process , combined with an optimizer/sampling policy, to automatically select sequences of optimal designs. These approaches are often more efficient than traditional DOE at optimizing systems using fewer experiments and allow for more natural incorporation of process priors , measurement noise , probabilistic output constraints and constraint learning , multi-objective , multi-point , and multi‐information source designs . Even with these methods available, limitations still exist. In previous work, we applied a machine learning approach to optimize complex media design spaces but had limited success due to the difficulty in measuring cell number for multi-passage growth . Therefore, in this study, we utilized a multi‐information source Bayesian model to fuse “cheap” measures of cell biomass with more “expensive” but higher quality measurements to predict long‐term medium performance.

We refer to the simpler and cheap assays as “low‐fidelity” IS, and more complex and expensive assays as “high‐fidelity” IS. While not always predictive of long‐term growth, these lower fidelity assays are at least correlated with cell health and can help in identifying interesting regions of the design space for further study with the high‐fidelity IS. We used this model, with Bayesian optimization tools, to optimize a cell culture medium with 14 components while minimizing the number of experiments, optimally allocating laboratory resources, and building process knowledge to improve our optimization scheme and model. In Section 2 we discuss the computational and experimental components of this BO method. In Section 3 we present the results of the BO method in comparison to a traditional DOE method, followed by Section 4 where we demonstrate the importance of fusing multiple sources of information to obtain relevant process knowledge and/or optimization results.The system under consideration was the proliferation of C2C12 cells. These cells are immortalized muscle cells with similar metabolism and growth characteristics as other adherent cell lines useful in the cellular agriculture industry. Cells were stored in 70% DMEM , 20% FBS , 10% dimethyl sulfoxide freeze medium at −196°C until thawed. Vials were thawed to 25°C and the freezing medium was removed by centrifugation at 1500 g for 5 min. The centrifuged cell pellet was resuspended in 17 ml of DMEM with 10% FBS and placed on 15 cm sterile plastic tissue culture dishes . Cells were incubated in a 37°C and 5% CO2 environment. After 24 h the medium was removed, the culture dish‐washed with Phosphate Buffer Solution , and fresh DMEM with 10% FBS was introduced. After an additional 24 h, cells were harvested using tripLE solution , diluted in PBS, and counted using Countess II with trypan blue exclusion and disposable slides . The process of removing cells from a plate, counting, and re‐plating them with fresh medium is called sub-culturing or passaging.

How well the C2C12 cells survive and grow after passaging is indicative of their long‐term potential in a large cellular agriculture process. The design space was comprised of the components and minimum/maximum concentrations listed in Table 1. These components were chosen because they are often used to supplement standard DMEM to improve cell growth; this represents a reasonable test case for the industrial application of these multi‐IS BO methods to the cellular agricultural industry. The composition of standard DMEM , is shown in Table 3, and should not be confused with the base DMEM “supplement” , which contains only amino acids, trace metals, salts, and vitamins and none of the other 14 components. pH and osmolarity are not controlled in this study, so act as latent variables.Production scale cellular agricultural processes will require >10 passages of cell growth so optimizing growth based on single‐passage information is not adequate . However, multi-passage growth assays are difficult/ expensive to measure, and even more difficult to optimize when given many components. We managed this complexity by coupling long‐term cell number measurements with simpler but less valuable rapid growth chemical assays in murine C2C12 cultures as a model system for cellular agricultural applications, capturing a more wholistic model of the process. We combined this with an optimization algorithm that efficiently allocates laboratory resources toward solving argmax D x for desirability function D x , a function that incorporates both cell growth and medium cost. This resulted in a 38% reduction in experimental effort, relative to a comparable DOE method, to find a media 227% more proliferative than the DMEM control at nearly the same cost. As the longer‐term passaging study suggests, our Passage 2 objective function and IS were well‐calibrated to mimicking the complex industrial process of growing large batches of cells over many passages,blueberry container with Passage 4 cell numbers well‐predicted by this objective function. The reasons for the success of the BO are myriad. The BO method iteratively refines a single process model to improve certainty in D x‐optimal regions, whereas the DOE relies on a series of BB designs where the older data sets are ignored because they were outside of the optimal factor space. The BO also used a variety of IS, whereas the DOE only used a single low‐fidelity AlamarBlue metric . Looking at Figure 8c, the AlamarBlue and LIVE tended to cluster around the point y = 1, making it difficult to distinguish between high‐quality and low‐quality media. This may be due to the deviation of linearity of the %AB and F530 metric at high biomass. The BO method also refined its multi‐IS model over the entire feasible design space, allowing it to take advantage of optimal combinations and concentrations of all 14 components over the entire domain, whereas the DOE needed to reduce the design and factor spaces to reduce the number of experiments needed, and may have identified the wrong optimal boundary locations resulting in suboptimal experimental designs. The BO method was also able to leverage information about process uncertainty to improve the model is poorly understood regions of the design space, whereas the steepest accent method used by the DOE chased after improved D x with little regard for overall noise or experimental errors.

This was worsened by the sensitivity of the polynomial model to random inter‐batch fluctuations in %AB, which may have driven the DOE to suboptimal media. Note that the success of our BO method should not be taken as generic superiority over all potential instantiations of DOE or commercial media used for C2C12 growth. While the BO method worked well at solving the experimental optimization problem, the multi‐IS GP accuracy was limited to highly sampled regions of the design space, thus limiting the efficacy of sensitivity analysis. This was a conscious decision made to trade off postfacto analysis for sampling media with high desirability D x . Accuracy was also limited by the low amount of data N available relative to the large dimensionality p, which is inherently the case in complex biological experiments where each batch of q experiments takes >1 week to evaluate. Finally, the hyperparameters θ* used in the multi‐IS squared exponential kernel were deliberately regularized with prior distributions to smooth the posterior of the prediction μ x . Regularization may have diminished the quality of the inter‐IS correlations; the model hyperparameters ignored features where IS differed in favor of a simpler correlative structure to explain the data. This is seen in Figure 8b,c, where the kernel evaluations show nearly equal inter‐IS correlative strength for most IS used. This may have “squished”/ignored features that could have provided additional information, but at the cost of sampling the design space too widely, again a deliberate choice of model skepticism towards outliers. Even with these limitations, the BO method clearly performs well on media optimization systems relevant to cellular agriculture, that is, those with multiple and potentially conflicting information sources with varying levels of difficulty in measuring. The media resulting from the BO algorithm supported significantly more C2C12 cell growth with only a small increase in cost. This algorithm performs better than traditional DOE in this case, especially in incorporating critical data from growth after the multiple passages in an affordable manner. With these results, it should be possible to implement this type of experimental optimization algorithm in other systems of importance to cellular agriculture and cell culture production processes with difficult‐to‐measure output spaces, including for optimization of serum‐free media for cell growth and for differentiation.Water management is becoming more challenging by the effects of climate change, population growth, and severe competition for water by the municipal, agricultural, industrial, and energy sectors. Accordingly, integrated water resources management focuses on water demand and supply management to achieve sustainable development. Water is a scarce resource essential for societal survival and functioning. This makes the application of integrated water resources management essential to cope with scarcity and the challenges posed by climate change and increased water demand to by expanding economies. A conceptual framework combining integrated landscape management and institutional design principles perspectives was applied to analyze cooperation initiatives involving water suppliers and agricultural stakeholders from agricultural wastewater. A national drought risk assessment for agricultural lands taking into account the complex interaction between different risk components was presented. The research showed that crop diversification, crop pattern management, and conjunctive water management can be effective in improving agricultural water.