Through policy, infrastructural investments, and demand management, government can either nurture or choke off the growth of a cluster . All elements are crucial to a successful cluster however it is often easiest for governments to manage demand, raising taxes or creating preferential treatment policies is faster and easier to do than building an industry or a research institution. In the case of Southern California’s Water industry, providing water to a populous semi-arid urban region establishes sophisticated demand. In meeting these demands, local water technology firms could prosper; however, the organizational structure of the markets might inhibit this advantage. Porter has explicitly argued that environmental conditions—and the legislative controls to fix them—can serve as the impetus that initially spurs innovative industries . It is important to recognize that traditional industrial economic clusters are not intrinsically centers of innovation, static or mature industries that no longer innovate will also often agglomerate doe to the cost saving benefits agglomeration economies. These industrial nodes will still give a region a competitive advantage, but they are often in lower value goods such as industrial products or mature manufactured goods where the opportunity cost of potential economic gains from further innovation is outweighed by the benefits of lower cost inputs—materials and labor.. Under freer trade regimes it tends to be these types of cost saving agglomerations are the most easily outsourced to cheapest global locations .

In rapidly growing technological industries that require constant innovation, economic geographers have documented significant benefits from competition and knowledge spillovers. In fact clustering appears particularly critical to industries that are rapidly evolving . Complex industries those that require industry R&D,ebb and flow table university research and skilled labor as critical inputs . There is a lively academic debate as to what the initial impetus behind innovative clusters formation . Theories such as Porter’s would point to factor endowments for explanations. While others have narrowed this somewhat and looked to individual agents or networks for explanation. For example Feldman and Francis have studied entrepreneurs in the Internet and biotechnology clusters in washington D.C. They argue that individual entrepreneurs are generally the key agents behind innovative agglomerations . Thriving centers of innovation usually have industrial agglomerations as their base, but they also have strong regional institutional assets such as world-class research universities, multiple financing options, or established networks of entrepreneurs . Additionally, these regions have large numbers of highly capitalized firms competing with one another to develop the ‘next big thing.‘ The presence of human capital is particularly important. Ausdrestch and Feldman write that entrepreneurs tend to “originate in locations with strong knowledge assets” and note that these areas also correlate with the highest economic growth. The combination of human capital, research capacity, and inter-firm competition in close proximity strongly promotes innovation. Scholarship has also found a strong correlation with regional R&D expenditures and innovation, with expenditures made by private companies having a larger role then universities . Regions with higher private R&D expenditures tend to have more innovation in larger firms, while regions with higher university expenditures tend to have more innovative small firms .

Zucker and Darby found a strong correlation of start-ups with researchers, but in their case they found that the presence of certain “star scientists,” are the most important element. Regardless of the mechanisms it is clear that Jacobs’ insights into externalities and economic agent diversity seem to be valid. The most popular example of a thriving innovative cluster is modern Silicon Valley, which owes its origin to the presence of a simple cluster of small tech firms loosely centered on Stanford University and eventually growing into the global technology center that it is today . Today the region continues to have a vast diversity of entrepreneurial firms, both large and small. A healthy ecosystem with both universities and large and small firms all investing in R&D seems to yield the strongest innovation systems. Knowledge spillovers have ample opportunities to occur in these systems. In fact these regions are growing even more innovative. For example Sonn & Storper, found that United State’s regional production of patents is growing even more concentrated in certain innovative regions. Michael Storper has argued that regions with strong “relational assets,” or untraded inter dependencies, are the regions where innovation is most likely to occur. Relational assets include local tacit knowledge, face-to-face interchange, social habits and norms, institutions . Storper and Venables have developed the idea of “buzz” in order to try and understand what is going on in these regions. It is clear that something is happening at the regional level and that spillovers are happening, however, the individual mechanisms are unclear. Critics argue that nebulous terms such as ‘relational assets’ are “fuzzy”—in the words of development scholar Ann Markensen . All agree that further scholarship into the individual mechanisms of knowledge transmission is needed . Innovation Systems scholarship attempts to circumvent these difficult to study interactions while seeking to understand the larger context in which innovation happens.

Schumpeter was one of the first innovation scholars to recognize that innovations often clustered around certain industries or time periods . He speculated that these clusters affected business cycles and could generate waves throughout the economy . Seeking to understand how innovations create dynamic interactions between geographical and sectoral clusters and temporal economic waves led scholars to turn to systems theories for explanation. The fact that learning is key to innovation and learning occurs through dynamic relationships and networks only further serves to reinforce the need to seek out dynamic explanations to understand how innovation happens . Systems engineers define a system as “a set of interrelated components working toward a common objective.” They are made up of components, relationships, and attributes . Components are the operating parts of a system, relationships are the linkages between them,flood table and attributes are the properties of each. In mechanical systems components might be the physical parts that make up a machine. In social systems components are generally actors such as firms, individuals, or organizations, but they can also be institutions such as patent laws. To develop theories of systems innovations scholars looked to evolutionary theory for insights into learning and combined these with institutional theories as a basis for systems theories of innovation. Evolutionary theory – with its focus on dynamics and the process of transformation – provides an analytical framework to understand change. Systems approaches emphasize that learning is both an individual and a collective act. This means that learning will occur not only within firms, or individual institutions, but potentially anywhere in the system . Thus an innovation system can be defined as all institutions and economic structures that affect technological change: competing firms, organizations, universities, research centers, government agencies, legal and financial institutions etc. Furthermore each of these will be characterized by “specific learning processes, competencies, beliefs, objectives, organizational structures and behaviors” . It almost goes without saying that the development of an innovation system occurs over decades . There are several different approaches to the study of innovation systems but in general they are defined by either geography, notably National Innovation Systems , Regional Innovation Systems , or by technology, principally the Sectoral Innovation Systems .

Other scholars have refined their approaches through the use of a narrower lens. For example Carlsson and Stankiewicz have pioneered a technological systems approach, a dynamic approach which attempts to follow a technology rather then a sector, or geographical region. Others such as Håkansson have also focused on technologies but linked to their studies on industrial networks. These systems approaches share similar goals but have different boundaries and often employ differing methodologies. Edquist and Johnson , Lundvall and Nelson have all pursued the study of national systems of innovation , but have placed emphasis on different aspects of the systems. For example, Nelson’s fifteen-country analysis identified research and development investment as a critical component of successful NIS . Nelson emphasizes that the economic incentives for innovation have to be present while sources of research and development financing must also exist . Porter’s studies on the competitiveness of industrial agglomerations are also often placed in the NIS literature—although his focus tends to be more on economic performance rather then pure innovation . Porter and Nelson share a focus on market demand as the critical component to shaping innovation investment . In contrast, Edquest and Johnson have often focused their NIS analysis on a nation’s institutional makeup . In their comparative studies of the European industrial regions, most notably a cross comparison of Badden Wurttemburg Germany and Wales, Cooke and Morgan found that Porter’s diamond model of interconnected heterogeneous firms failed to explain why one region succeeded while others failed . Research into identifying the causal factors behind such studies later became the genesis for a more narrow regional systems approach . The RIS approach places a much stronger focus on cultural factors that build trust and social network relationships . This approach closely aligns with the learning regions and relational assets scholarship . It also aligns with the general understanding that urban regions are the critical key nodes in today’s world . An RIS approach recognizes that regions are subservient to the National system which sets research priorities and legal institutions, but believes regions have some sway in those decisions ; the more decentralized a national system is, the more sway powerful regions will have.RIS approaches emphasize five principal concepts: region, innovation, network, learning, and interaction . A region in an RIS is not necessarily politically bounded but is defined by a shared trust and collective order Innovation looks for measurements of innovation, or the successful commercialization of knowledge. Networks seek to identify cooperation-based networks and analyzes knowledge flows, including external knowledge flows. Learning seeks to identify if tacit learning is occurring and if organizations are incorporating that knowledge successfully. Interaction aims to measure if there are opportunities for learning from each other and external groups. A region can be said to become a regional innovation system when it forms a dynamic cluster of firms learning through interaction with one another to innovate. Like Cooke and Morgan’s aforementioned study much of the RIS scholarship has been dedicated to comparisons among ostensibly economically similar regions but seeks to explain differences leading to innovation or economic performance gaps . Some of the mos relevant to this study have looked at why Europe has traditionally lagged behind the United States in innovation. For example Crescenzi et. al, found institutional and cultural barriers that prevent interactions, and thus learning, and are preventing effective market integration. But perhaps most notably Cooke , a key pioneer in the RIS field who has authored numerous comprehensive studies of Europe, identifies Europe’s over-reliance on the state for many of the functions of an innovation system which in the United States are often undertaken by private entities. He believes that incentives for innovative success are better aligned with the profit motive. By studying the functions of innovation systems it is hoped to gain an understanding of how similar results and technological innovation, can come about in vastly different institutional environments. A function can be carried out by a particular set of actors in one innovation system through a uniquely specific form, while the same function might be carried out in a different form by an entirely different actor in a similar system but in a different place or time . Management scholar Carlsson identifies three elements that all systems frameworks should address. First, it is necessary to specify the components of the system and their boundaries. Second, the relationships between the components need to be analyzed. Finally, the characteristics of the components need to be understood to determine the systems performance . The basic components are Malerba’s five building blocks discussed above: actors and networks, knowledge and technologies, and institutions . When it comes to understanding how to analyze these components several comprehensive attempts to identify measurable functions have been made . For example, in a paper titled simply “Functions in Innovation Systems,” Johnson conducted a thorough literature review to derive eight basic functions that all innovation systems share.

The trees were managed and fertilized following current commercial practices, although the amounts of applied fertilizer varied. The soils of the site are alkaline , with red sandy loam from the surface to 90-cm depth, and loam below . The total organic carbon content is very low in the first 30 cm, and below 0.25% in the remainder of the root zone. The climate is characterized as dry, with warm to hot summers and mild winters. The total rainfall during the experimental period from 21 August 2006 to 20 August 2007 was 187 mm , which was slightly below average for the area. Potential evapotranspiration is normally high and equal to 1400 mm per year. Mild frost conditions occur during the winter months. Weather data were collected from an automated weather station located within the research station.The HYDRUS-2D software package was used to simulate the transient two-dimensional movement of water and solutes in the soil. This program numerically solves the Richards’ equation for variably-saturated water flow, and advection–dispersion equations for both heat and solute transport. The model additionally allows specification of root water uptake, which affects the spatial distribution of water, salts and nitrate between irrigation cycles. The solute transport equation considers the advective–dispersive transport in the liquid phase, as well as diffusion in the gaseous phase. The theoretical part of the model is described in detail in the technical manual and in Šimu˚ nek et al. .The water contents measured weekly by EnviroSCAN at different depths at a horizontal distance of 10 cm from the dripper,berry pots and corresponding values simulated by HYDRUS-2D during the entire growing season are illustrated in Fig. 5.

The measured water contents remained similar at 10 and 80 cm cm, fluctuated between 0.1 and 0.2 cm3 cm 3 at 25 and 50 cm, and stayed higher than 0.2 cm3 cm 3 at 110 cm soil depths throughout the growing season, indicating a favourable moisture regime in the crop root zone. However, the simulated water contents were lower than the measured values during the initial period at a depth of 10 cm and during the mid period at a depth of 110 cm. The simulated values matched the measured values more closely at soil depths of 25 and 50 cm, which is the most active root zone for water and nutrient uptake for citrus . However, the profile average water distribution matched well. The MAE between weekly measured and simulated moisture content values across all locations varied from 0.01 to 0.04 cm3 cm 3 , indicating a good agreement between the two sets of values . Slightly higher temporal MAE values during the mid-season agreed well with the variation shown in Fig. 5. Similarly, the MAE values at 10, 25, 50, 80, and 110 cm soil depths at a 10 cm lateral distance from the dripper also revealed that the variation between measured and simulated water contents remained between 0.02 and 0.04 cm3 cm 3 . However, the differences were slightly higher at 10 cm depth as compared to greater depths . Higher variations at the surface depth are to be expected because this part of the soil profile is influenced by soil evaporation, which peaks in day time and is low at night time, while the assumption of a constant atmospheric boundary flux for daily time steps in the model deviated from the actual transient conditions existing at the surface boundary. Other studies also showed a similar magnitude of variations between measured and predicted water contents.Comparison of simulated electrical conductivities of soil solution with weekly measured values at different depths are shown in Fig. 6.

Despite of low irrigation water salinity and low initial soil salinity , the measured ECsw increased in the soil with the onset of irrigation at all depths, except at 150 cm where the increase in salinity occurred only after December 2006. Subsequently, a decreasing trend was observed in ECsw later in the season. The higher amount of irrigation compared to ETC. and an significant amount of precipitation during this period resulted in a reduction in soil solution salinity. On the other hand, the model over-predicted ECsw at a depth of 25 cm from October to December 2006 and under-predicted it at a depth of 100 cm during the same period. However, at a depth of 150 cm, simulated values remained constant till January 2007, indicating a delayed response. The increase in simulated ECsw values was delayed at 100 and 150 cm depths as compared to measured values. Both set of values matched well at a depth of 50 cm and the profile average of ECsw also showed a close match. It is significant to note that irrigation with good quality water in our study led to the development of significant levels of measured ECsw . However, the ECsw values remained below the threshold of salinity tolerance of orange throughout the season . The MAEs between weekly measured and simulated ECsw in the soil ranged from 0.08 to 0.76 dS m 1 , which are acceptable for a complex and highly dynamic soil system, with the exception of a few divergent values obtained between mid October and December . The disagreement in ECsw values during this period was correlated with corresponding fluctuations and low values of water contents, especially at soil depths of 10 and 25 cm and this variability was transferred tothe ECsw values. Differences between measured and simulated ECsw values at 50 cm depth were relatively higher than at other depths . The mean MAE at 25, 100, and 150 cm depths ranged from 0.19 to 0.36 dS m 1, showing a good agreement with the measured values at these depths. The spatial distribution of ECsw in the soil profile at various dates is depicted in Fig. 7. It can be seen that salts remained restricted to roughly the upper 50 cm of the soil profile until December.

The downward movement of salts continued in February and March , because in March the amount of irrigation was higher than ETC. . It is pertinent to note here that the ECsw distribution under the dripper remained lower as compared to the adjoining soil at all times,hydroponic grow system because a continuous water application in this region pushes the salts towards the outer boundary of the wetting front. The drainage flux during and after March transported salts vertically downwards, thereby making the soil directly beneath the dripper relatively salt free by the end of the season. Applying additional water at the end of the season could be a strategy to create a salt free root zone which may encourage vigorous root development, and assist the plant growth in the ensuing season.Comparison of weekly measured and daily simulated nitrate– nitrogen concentrations at different depths in the soil profile is illustrated in Fig. 8. Over-prediction was observed at a depth of 25 cm from October to November 2006, which coincided with similar over-prediction for salinity. Similarly, both measured and simulated values matched well at a depth of 50 cm, while a delayed response in predicted nitrate contents was observed at lower depths. However, a fairly good correspondence was observed between profile averaged NO3 –N contents. The temporal MAE values for NO3 –N ranged from 0.1 to 1.97 mmol L 1 . Similar differences between measured and HYDRUS-2D simulated values were also reported in another study involving simulations of nitrogen under field cropped conditions. Additionally, MAE at a 25 cm depth had a higher value L 1 ) than at greater depths L 1 ). A similar match of nitrate distributions has been reported in other studies as well . The reason for differences in ECsw and NO3 –N values may be partially due to the fact that model reports point values, whereas the Solu SAMPLER draws in solution from a sampling area of a certain volume, the size of which depends on the soil hydraulic properties, the soil water content, and the applied suction within the ceramic cup . Hence the measured parameters considered in modelling may not represent the inherent spatial variability of the soil. In addition, while a homogeneous soil environment is assumed by the model, the field site could be far more heterogeneous and anisotropic. Also, the model simulations considered only a 2D movement of nitrogen and the nitrification process, while more complex nitrate processes were not taken into account. Ramos et al. documented numerous factors influencing the correspondence between measurements and simulations of water contents and solute concentrations in the soil under drip irrigation conditions and these factors are relevant also for the present investigation. These factors, including those mentioned above, may modify the error in the simulated NO3 –N values. The simulated movement of nitrate–nitrogen in the soil under a mandarin tree at various dates is shown in Fig. 9.

Nitrate fertigation increased the nitrogen content in the soil with time, as is evident from an increasing size of the concentration plume below the dripper as the season progressed. This indicates that the plant was not able to take up all nitrogen added through fertigation, and thus nitrogen built up in the soil over time, leading to a maximum concentration values in January . Ultimately, nitrogen started moving downwards after late January, when there was high rainfall and total water additions exceeded ETC. Alva et al. also detected greater variations in NO3 –N concentrations in the 0–15 cm depth horizon, as compared to greater depths in a field experiment involving citrus. The seasonal NO3 –N concentrations in the domain varied from 0.01–7.03 mmol L 1 . Hutton et al. reported higher mobilization of nitrate at a shallower depth under drip irrigation of grapevine, and seasonal root zone nitrate concentrations ranging between 0 and 11.07 mmol L 1 in the Murrumbidgee Irrigation Areas in Australia. As the season continued and plant uptake was reduced, excess water further mobilised nitrate–nitrogen out of the root zone, as is evident from 27/04/07 and beyond . At the end of the crop season, little nitrogen remained in the soil system, and what did remain was well beyond the reach of the plants. This nitrogen is expected to continue leaching downwards over time and become a potential source of nitrate–nitrogen loading to the ground water.High levels of nitrate–nitrogen below the crop root zone are undesirable, as some recharge to groundwater aquifers can occur, in addition to flow into downstream rivers, which are used for drinking water and irrigation. These findings are consistent with other studies , in which high nitrate concentrations in drainage water under drip and furrow fertigated irrigation systems have been reported.The seasonal water balance was computed from cumulative fluxes calculated by HYDRUS-2D. Estimated water balance components above and below the soil surface under a mandarin tree are presented in Table 4. It can be seen that in a highly precise drip irrigation system, a large amount of applied water drained out of the root zone, even though the amount of irrigation applied was based on estimated ETC. This drainage corresponded to 33.5% of applied water, and occurred because highly permeable light textured soils, such as those found in this study, are prone to deep drainage whenever the water application exceeds ETC. The drainage amount in our study falls within the range of recharge fluxes to groundwater reported by Kurtzman et al. under citrus orchards in a semiarid Mediterranean climate. Mandarin root water uptake amounted to 307.3 mm, which constitutes about 49% of applied water. Root water uptake slightly increased when the model was run without considering solute stress , which is not a significant difference. It further substantiates the results obtained for seasonal ECsw in Fig. 6, where salinity remained below threshold over the season. Evaporation accounted for 17.7% of the total water applied through irrigation and rainfall. The modelling study overestimated the sink components of the water balance by 4.79 mm . There were major differences between water input and output from January 2007 onwards . During this period, irrigation and precipitation significantly exceeded tree water uptake , which eventually resulted in deep drainage from March 2007 onwards. Therefore, current irrigation scheduling requires adjustment during this period. This illustrates how simulations were helpful in evaluating the overall water dynamics in soil under the mandarin tree. The nitrogen balance is presented in Table 5.

The powder wash was chosen for use in all the experiments requiring BRF extract.Intriguingly, while comparing different methods for bacterial inoculation on agar plates, it was observed that production of this surfactant increased dramatically when the strain was grown on the porous surface of hydrated filter paper discs placed on agar plates. This was true both when the bacteria were directly applied with a toothpick as a single spot on the paper surface, and somewhat less so when inoculated as a larger patch from an aqueous cell suspension. A variety of additional materials other than cellulose such as cotton and polyester fabrics were tested for their stimulation of apparent surfactant production, and all induced production as long as the material was wettable. The rough surface induction of surfactant production led us to the hypothesis that the surfactant might contribute to the colonization of natural surfaces and thus prompted further investigation. Of the six mutants identified as being completely blocked in biosurfactant production three of the insertions were into the global regulatory genes gacS, ompR, and fleQ, and thus were deemed to be not specifically responsible for surfactant biosynthesis. GacS is a global regulator of secondary metabolites and extracelullar enzymes , while an OmpR homolog has recently been hypothesized to be a membrane stress sensor in P. aeruginosa , and FleQ is the initial regulatory element of flagellar biosynthesis. Of the remaining genes influencing biosurfactant production, neither Psyr_0215 which is predicted to have general base excision repair activity,arandanos planta nor Psyr_4446 which is an osmotically induced outer membrane lipoprotein, are likely candidates for contributing to surfactant synthesis.

On the other hand, a predicted acyltransferase, Psyr_3129, having 48.5% identity to rhlA and 49% identity to phaG in P. aeruginosa PAO1, seemed likely to be involved directly in surfactant biosynthesis. RhlA is responsible for production of 3-alkanoic acids , the precursor to rhamnolipids in P. aeruginosa, and is independently recognized as a biosurfactant that promotes swarming motility. PhaG is involved in polyhydroxyalkanoic acid synthesis, which is a carbon and energy storage molecule. Both enzymes divert hydroxydecanoic acids from fatty acid de novo synthesis, and exhibit similar and sometimes overlapping polymerization functions. Because the transposon insertion was in the promoter region immediately upstream of Psyr_3129, we confirmed that a knockout of this gene also blocked surfactant production by constructing a chromosomal deletion of Psyr_3129 in the ∆syfA background of P. syringae. This double mutant was also incapable of swarming ability. To ensure that disruption of brfA and not genomic changes elsewhere was responsible for abrogating biosurfactant production, we complemented this gene in trans. Expression of brfA under the control of the constitutive npt2 promoter in plasmid p519n-gfp, where gfp was replaced with brfA, proved to be lethal to P. syringae. However, when brfA was inserted into pMF54 , to form plasmid pBRF2 where brfA is driven by an IPTG-inducible trc promoter, this plasmid produced viable transformants. Curiously, when this plasmid is introduced into a ∆syfA/∆brfA double mutant, biosurfactant was produced abundantly without IPTG addition , emphasizing the leaky nature of this plasmid. Addition of IPTG did not result in surfactant production beyond that observed in uninduced cells. Thus, either BrfA synthesizes the surfactant or is essential for its expression. Significantly, rhlA from P. aeruginosa has been shown to be sufficient for HAA production in E. coli , as well as an rhlA homolog in Serratia sp. ATCC 39006 which produces an unidentified biosurfactant. 

We thus tested if our potential rhlA homolog was sufficient to confer biosurfactant production in E. coli. E. coli DH5α harboring plasmid pBRF2 produced a large amount of surfactant. It is important to note that although production of this surfactant in a ∆syfA strain of P. syringae is readily detected with the atomized oil assay, it was not detectable with other assays such as the drop collapse assay or by direct chemical detection. This suggested that either the molecule had properties such as low water solubility that prevented its detection with assays such as water drop collapse, or that it was made in relatively low amounts that are not easily detected by assays with lower sensitivity. However, a ∆syfA strain carrying pBRF2 for constitutive BrfA expression was observed to cause a drop collapse , thus we presume that low rates of production in native strains explain its lack of detection in a ∆syfA strain with a drop collapse assay. Using a modified protocol for HAA extraction , we extracted BRF from plate-grown cultures of ∆syfA. The resulting powder yielded an opaque solution in water, indicative of a surfactant with low water solubility exhibiting aggregate formation. This concentrated surfactant lowered the surface tension of water to 29 dyn/cm when measured in a pendant drop assay, confirming its potent surfactant activity. It remains to be determined what the chemical structure of BRF is, and if it is HAA. An insertion into the transcription factor fleQ, which is involved in the initiation of flagellar assembly results in a total loss of surfactant production. Disruption of flgC, a Class III flagellar assembly gene that is involved in formation of the basal body rod in P. aeruginosa , also resulted in a large reduction in the surfactant halo. The identification of these two mutants led us to hypothesize that assembly of the flagellar base structure is important for production of BRF. Surprisingly, an insertion in fliC, a Class IV structural gene encoding the actual flagellin protein, resulted in enhanced surfactant production.

Furthermore, insertions in fgt1 and fgt2, two genes involved in flagellar glycosylation that have been shown in P. syringae pv. tabaci 6605 to be important for flagellar function , both also result in up-regulation of surfactant production. This suggested that once the flagellar base is assembled and flagellin synthesis is initiated, mutations which hinder flagellar assembly or functionality serve to up-regulate the production of BRF. Curiously, even though an insertion in fgt1 only impaired flagellar swimming motility while an insertion in fgt2 did not appear to confer any flagellar impairment , these mutations both stimulated surfactant production to a similar extent as a loss of flagellin itself. We remain uncertain how these mutations lead to up regulating surfactant production. To further support our hypothesis that expression of BRF is dependent on flagellar assembly itself and not merely coincidentally with expression of certain flagellar genes,square nursery pots we constructed targeted knockouts in additional flagellar genes involved at different stages of flagellar assembly. A directed knockout mutant of fleQ was deficient in surfactant production, confirming our earlier observations of an insertional mutant of this gene. Although the initial screen did not identify any insertions in Class II genes that are important for the initial establishment of the flagellar apparatus, a directed knockout of fliF exhibited a dramatic loss of surfactant production. Furthermore, a knockout of flgD, a Class III flagellar gene in an operon downstream of flgC, resulted in a similar 3-fold reduction in the size of the BRF halo. Disruption of fliA, encoding the sigma factor responsible for initiating transcription of Class IV genes, also conferred a 3-fold reduction in surfactant production. Thus, although FliA is necessary for expression of late stage flagellar genes, it does not appear necessary for production of BRF. Because the establishment of the flagellar base appears important for production of this surfactant, we postulated that perhaps the flagellum is in some way necessary for the export of BRF. In order to test this model, we introduced plasmid pBRF2 conferring constitutive BrfA expression into a ∆syfA/fleQ– double mutant strain of P. syringae. This strain, despite lacking flagella, exhibited unaltered surfactant production , indicating that flagella are not necessary for surfactant export. Thus it appears that the flagellar assembly process most likely influences brfA at the transcriptional level.

In order to investigate the contribution of flagellar assembly to transcriptional regulation of brfA we linked a gfp reporter gene to the promoter containing region 5’ to brfA in the stable plasmid vector pPROBE-GT to produce reporter plasmid pPbrfA-gfp. We introduced pPbrfA-gfp into the different insertional mutants blocked at different stages of flagellar assembly and observed that, as was indicated by the atomized oil assay, the expression of brfA was higher in a ∆syfA/fliC– mutant compared to that in either a ∆syfA/fleQ– or ∆syfA/flgC– mutant. We also constructed reporter plasmid pPfliC-gfp in which a gfp reporter gene was fused to the promoter-containing region of fliC to provide estimates of the expression of the gene encoding flagellin, a late stage flagellar gene. Similar to what was observed for expression of brfA, the expression of fliC was greatly reduced in both a ∆syfA/fleQ– and ∆syfA/flgC background but was over-expressed relative to that in a ∆syfA background alone in a ∆syfA/fliC mutant. As far as we are aware, flagellar glycosylation has not been documented to have a feedback role in flagellin biosynthesis. Although it is intuitive that a loss of flagellin production might result in constitutive activation of the late-stage flagellar genes through FliA, it is less obvious how flagellar glycosylation mutations might be feeding back to up-regulate flagella production, especially in the case of fgt2 which does not exhibit any impairment of flagellar function. In order to investigate the feedback process, we constructed transcriptional reporters of both flgB, a class II flagellar gene, and fliE, a class III flagellar gene, in addition to the fliC reporter. Reporter plasmids pPflgB-gfp and pPfliE-gfp, respectively, were separately introduced into the original ∆syfA strain as well as a ∆syfA/fgt2– strain, so that the effect of flagellar glycosylation on the expression of the three classes of flagella genes could be observed. We clearly observed that a loss of flagellar glycosylation results in up-regulation only of the late stage flagellin gene fliC and not of fliE or flgB. Loss of glycosylation most likely affects the flagella in such a way as to encourage the export of the anti-sigma factor FlgM, either through increased flagellar breakage or increased export within the flagella, thus releasing FliA from FlgM control. To address the process by which paper surfaces up-regulate production of BRF we addressed the expression of brfA under various growth conditions. The GFP fluorescence of a WT strain carrying pPbrfA-gfp was compared between when grown on filter paper discs on agar plates and when grown directly on agar plates. While GFP fluorescence exhibited by P. syringae harboring plasmid p519n-gfp conferring constitutive GFP expression was similar in these two growth conditions, much higher GFP fluorescence was observed after growth on the porous paper in the strain carrying pPbrfA-gfp. Such apparent paper surface-induced upregulation of brfA was observed in both the WT strain as well as a ∆syfA strain. No such induction of syfA was observed when strains harboring pPsyfA-gfp were grown on paper discs , indicative that syringafactin is not similarly regulated. Because we observed both enhanced production of BRF and elevated expression of brfA in cells grown on hydrated paper discs, as well as a dependence of BRF production on flagella assembly, we hypothesized that genes for flagella for motility would be up-regulated on the paper discs coincidently with those for BRF production. To test this, we compared the GFP fluorescence of cells harboring the fliC reporter plasmid pPfliC-gfp when grown on agar plates and paper discs. As hypothesized, we observed an up-regulation of genes encoding flagellin when the strain is exploring the porous paper surface. In order to examine the necessity of flagella for movement through hydrated paper, we compared the lateral spread of a WT strain and a fleQ– mutant on paper discs. While flagellated strains quickly moved both into and along the length of the paper discs, the non-flagellated strains remained at the site of inoculation and formed colonies only on top of the paper. This requirement of motility for colonization of paper disks appears very similar to that observed for exploration of a porous ceramic surface. To better determine the relative rate of movement of different strains along paper, we increased the distance over which the bacteria were allowed to move.

Solutes tend to concentrate on surfaces, and thus cells might respond to the higher osmolarity or concentration of particular ions at surfaces. Additionally, bacteria that are situated in biofilms on a surface experience lower oxygen and higher cell density conditions, and might interpret these conditions as location cues. Other modes of surface sensing include responses to physical perturbation of the membrane upon adherence, such as the Cpx two-component system in E. coli , or responding to the increased torque that appendages such as flagella might encounter upon their interaction with surfaces. Thus, it appears that bacteria have a variety of mechanisms with which they can sense surfaces. Different conditions might trigger biosurfactant production in different bacteria, depending on the function of the surfactant to a given species and habitat. However, are there limitations to the tasks a given surfactant can be used for? Although biosurfactant production has been noted for decades, the significance of their different chemical structures is only starting to be appreciated. For instance, it has been found that small changes in peptide components of Bacillus surfactants result in large changes of their anti-fungal and antimicrobial properties. However, as of yet there are no good guidelines on what surfactant structures are appropriate for a given type of bacterial function. This is in contrast to synthetic surfactants, where manufacturers have developed many tools for choosing appropriate surfactant formulations from thousands of synthetic surfactants. One goal of this research is to identify biosurfactants with different physical properties, and determine how these properties affect the biological roles they play to the producing organism. A particularly important property that was focused on in this study is the water solubility of biosurfactants, a proxy for their hydrophilic lipophilic balance HLB. HLB values are a scalar factor that reflects the degree to which a surfactant is hydrophilic or lipophilic, with a value of zero reflecting a completely lipophilic molecule,maceta cuadrada 25 x 25 a value of 10 corresponding to a compound with equivalent hydrophobic and hydrophilic groups, and values over 10 descriptive of predominantly hydrophilic molecules. 

This value is of great significance commercially since it is used to determine appropriate functions of surfactants. For example, common surfactants such as SDS and Tween 20 have high HLB values and are therefore best suited for emulsifying a hydrophobic substance into the water phase. On the other hand, surfactants such as Silwet® L-77 with HLB values near 10 are more suited for wetting, or spreading of a water phase over surfaces such as leaves. At the other end of the spectrum, lipophilic surfactants are best at forming inverseemulsions of water into oil. Although biosurfactants were originally proposed to be used by bacteria to solubilize hydrophobic nutrient sources , by the HLB classification alone it is obvious that only a small subset of biosurfactants would be optimal for this purpose. Biosurfactant producers are common in the environment, with around 10% of culturable bacteria in a given environment readily exhibiting this trait. Given their prevalence, the general field of microbiology will benefit from a better understanding of biosurfactant production. Additionally, in order for humans to best utilize biosurfactants, it should be informative to discover their natural functions which, in turn, might reveal novel applications for these molecules. Biosurfactants have been implicated in a large variety of functions beyond hydrocarbon emulsification. In aqueous environments, bacteria might use surfactants to coat themselves and/or surfaces to alter adherence or deherence. On the other hand, terrestrial surfaces often only harbor thin films of water; bacteria in such habitats often experience water stress and suffer from low diffusional nutrient fluxes. In this circumstance, biosurfactants might prevent evaporation or act as osmotic agents, thus maintaining thicker water films, relieving water stress and increasing microbial access to nutrients. Their ability to lower the surface tension of water has been implicated in promoting aerial hyphal growth , while their emulsification properties might enable delivery of antagonistic compounds. Because biosurfactants are amphiphilic, they can insert into membranes, and some surfactants have thus been noted for their potent membrane disrupting and resultant antimicrobial properties. 

Biosurfactants appear essential for biofilm formation in some bacteria , while they appear to prevent biofilm formation in others. Indeed, the anti-adhesive properties of some biosurfactants make them excellent candidates for coating medical devices. Additionally, some biosurfactants are proposed to act as auto inducers to signal cellular differentiation. Obviously all these traits do not apply to a given biosurfactant, but is inclusive of a rather broad spectrum of diverse molecules. Biosurfactant research would greatly benefit from further categorizations of biosurfactants based on their physical properties and demonstration of functions in which they participate.A classic function of biosurfactant activity is its enhancement of bacterial motility across soft agar plates. This motility, termed swarming motility, is an active form of translocation and is generally reliant on flagellar motility and biosurfactant production. Although biosurfactants are necessary for swarming motility in many bacteria, their production provides no benefit to swimming motility, and it is difficult to imagine a natural environment that would support the large local population sizes necessary for swarming motility. Nonetheless, it is widely assumed that biosurfactant production supports bacterial movement in vivo. How exactly might biosurfactants be beneficial to motility, and under what natural conditions do they aid motility? This question is addressed in chapter 6. Biosurfactant production has been noted in many bacterial species, but few bacterial habitats allow for as easy observation and manipulation of surfactant production as do leaves. Thus, the phyllosphere is an excellent setting in which to test the biological roles of biosurfactant production. Epiphytic bacteria not only survive, but readily flourish on leaves despite the high UV exposure, cycles of desiccation and hydration, rapid temperature fluctuations,macetas de plastico 25 litros and low and heterogeneous nutrient availability found on most leaves. It has been shown that growth of surfactant-producing bacteria on a plant can change the wettability of the leaf. It has previously been postulated that such biosurfactant production might be beneficial to the epiphytic life of bacteria and it is widely assumed that the plant environment is especially enriched with biosurfactant producers for this reason. 

It is already known that once inside the leaf, surfactant production by bacteria such as P. syringae is important for the development of disease symptoms, most likely through the induction of plant cell leakage. However, it remains unclear how biosurfactants specifically aid epiphytic growth of bacteria. Continuous water films may not normally form on such waxy surfaces; by decreasing the interfacial tension between the leaf surface and dispersed water droplets, biosurfactants could increase the wetted surface area of the leaf. Such enlarged water films might increase the distribution of locally abundant nutrients that might be separated by waxy regions of the leaf which would not otherwise be wetted by water. During periods of abundant leaf surface water, it is hypothesized that epiphytes will leave cellular aggregates in which they survive and explore the leaf surface, moving between dispersed nutrient-rich sites ; surfactant-mediated enlarged wetted areas might enable increased regions over which such motility could occur. Furthermore, surfactants might have lubricating properties, and increase bacterial motility on leaves by decreasing potential attractive forces that could immobilize bacteria on surfaces. Besides increasing growth through redistribution of nutrients and bacteria, surfactants might also increase nutrient or water availability in those sites already colonized by bacteria through their plasticizing effect on the cuticle. A number of plant-associated organisms have been studied for biosurfactant production, but few have been directly tested for the role of these compounds in planta. When surfactant-deficient mutants have been tested in planta, the focus is usually on the contributions of the biosurfactants to virulence or to the membrane-disruptive, phytotoxic properties of these molecules. A few studies have attempted to include movement in their assessment of biosurfactant roles, but the results are generally mixed; it is difficult to pinpoint the exact cause of a deficiency of colonization of plant surfaces by a mutant. Thus, although it has been speculated that the decreased fitness of biosurfactant mutants is due to their decreased motility and/or access to nutrients, neither of these factors have been directly proven on plants. Although there is a paucity of research on the role of different types of biosurfactants in the phyllosphere, the widespread use of synthetic surfactants in agriculture has provided a large source of information that might be applied to biosurfactants. Surfactants are capable of solubilizing plant epicuticular wax, thus diminishing the barrier of nutrient diffusion from the leaf onto the surface, although solubilization will only occur at concentrations above the critical micelle concentration. Biosurfactant production could potentially reach high enough local concentrations in bacterial aggregates to solubilize and strip away adjacent waxes if the biosurfactant is suited for solubilizing hydrophobic substances into water.

At lower concentrations, surfactants will have different effects on the cuticle depending on their structures. Hydrophilic surfactants, when adsorbed into the cuticle, will increase the hydration of the cuticle and therefore increase the movement of not only water but also water-soluble molecules. Alternatively, although hydrophobic surfactants readily adsorb into the cuticle, they do not increase the hydration but rather the fluidity of cuticular waxes that, in turn, increases the rate of diffusion of hydrophobic compounds across the cuticle. Additionally, movement of water and bacteria into the apoplast is normally prevented by the high surface tension of water, but can occur spontaneously when the surface tension of the liquid is reduced such as in Zebrina purpusii when the surface tension of liquid is less than 30 dyn/cm. Similarly, during plant invasion, pathogens could be employing a surfactant with high surface tension lowering abilities to facilitate water entry into stomata and other openings. Biosurfactants have been implicated in a wide variety of roles, and all of these roles might prove true in specific situations. However, it is important to start defining what types of surfactants are good at achieving a given result. The goal of this dissertation is to examine biosurfactant production in the phyllosphere with an emphasis on the plant-associated Pseudomonas syringae, in which several surfactants that it produces will be characterized and studed for their specific roles in the phyllosphere, based on clues from their genetic regulation. Biosurfactant-producing organisms have classically been identified by their ability to emulsify and utilize hydrocarbons as a nutrient source. It has only been recently appreciated that biosurfactants are produced by bacteria for many reasons other than access to hydrophobic nutrient sources. Among the numerous functions identified, are their use for swarming motility , biofilm structure and maintenance, and delivery of insoluble signals. Biosurfactants have been identified that can either promote biofilms or disperse them on root and abiotic surfaces. Additionally, some biosurfactants have been noted for their membrane-disrupting and thus zoosporicidal or antimicrobial activity. An unexplored arena where biosurfactants may prove particularly important is the colonization of waxy leaf surfaces. In order to survive on leaf surfaces, epiphytes must be able to access limited and spatially heterogeneous nutrient supplies and endure daily fluctuations in moisture availability in forms such as dew and rainfall. Continuous water films may not normally form on such waxy surfaces, and surfactants might thus aid in diffusion of compounds across the plant. If the bacteria have a pathogenic life phase, they must first have a method to enter plant tissue after which they create a favorable apoplastic environment for growth. It is already known that once inside the leaf, bacteria such as P. syringae use surfactants to cause plant cell leakage and disease symptoms. However, some studies have also implicated biosurfactants in the pre-pathogenic stages of plant-associated bacteria. Pseudomonas syringae pv. syringae B728a, a sequenced model organism with a prominent epiphytic lifestyle, produces biosurfactants. A study of the genetic regulation of biosurfactant production should provide insight into its function in this species. The identification of mutants altered in surfactant production would be an important first step in this process. However, an effective method of identifying such mutants needed to be found. Many studies have compared various screening methods to identify biosurfactant producers from limited collections of environmental isolates. Some of the most commonly used methods for analyzing biosurfactant production are drop-collapse, emulsification, and tensiometric evaluation. However, when many strains need to be assessed for surfactant production, the drop-collapse assay has been the method of choice. 

As DLK2 binds and weakly hydrolyzes 5DS in vitro, we tested whether the compound would inhibit growth of DLK2 OE hypocotyls. DLK2 OE lines were unresponsive to both 5DS and 5DS, indicating that DLK2 does not transduce 5DS signal.To elucidate the spatio-temporal regulation of DLK2 expression induced by dark and SLs, we generated a transcriptional fusion of a 1023 bp DLK2 promoter fragment with the GUS genecoding region. We assayed for GUS expression in at least seven representative T4 homozygous Arabidopsis Col-0 lines. In young control seedlings grown on 0.5 × MS plates, GUS stain was detected first in the cotyledons which progressively intensified with the onset of the cotyledon expansion and subsequently was detected also in the roots. In seedlings grown on plates supplemented with 10 µM racGR24, a specific and strong GUS signal appeared at the basal end of the hypocotyl. In accordance with the real-time PCR data, dark-grown seedlings displayed intensive GUS accumulation , especially in the hypocotyl. In the aerial parts of adult plants, GUS signal was strong in primary and mature leaves and petals. No GUS activity was detected in mature hypocotyl, petiole vasculature and non-elongating, mature stems , while the axillary buds and the vascular bundles of elongating stem segments adjacent to the cauline leaves displayed intensive GUS staining. Interestingly, DLK2 promoter activity was strong in buds and the vascular cells connecting the stipules with the vasculature of the petiole. In the root system of adult plants, GUS activity was strong in the differentiation zone and the GUS signal gradually faded away toward the primary root tip. 

Notably, lateral root primordia displayed no GUS signal,macetas de 10 litros while DLK2 promoter activity was detected in young lateral root tips. These findings indicate that DLK2 expression pattern is tissue specific and regulated by SLs or dark directly. There is compelling evidence that at least two butenolide signaling pathways exist in vascular plants. The ancient KAI2 pathway has an as yet unknown butenolide ligand , which is neither SL nor karrikin. During the course of evolution, KAI2 underwent a gene duplication event which resulted in the D14 clade. The D14 pathway perceives the canonical SL ligand and diverged from the KAI2 clade both evolutionarily and physiologically. The question then emerges, how does DLK2 relate to these MAX2-dependent signaling pathways? We showed that recombinant DLK2 does not hydrolyze 5DS and is not destabilized in the presence of 5DS , indicating that DLK2 is not an SL receptor nor an SL hydrolase that functions in a negative feedback system to remove excess SL. This is further supported by the sensitivity of dlk2 mutants to 5DS and rac-GR24 and DLK2 OE lines do not show a SL-deficient phenotype. On the other hand, compared to AtD14, DLK2 shows weaker stereospecific binding and hydrolysis toward 5DS , a non-natural SL which, along with karrikins, oddly substitutes for the unknown endogenous KAI2 ligand. It is intriguing to consider that DLK2 might be a receptor or hydrolase for the enigmatic KL. The structure of KL is unknown; therefore, it is hard to draw a parallel between DLK2 and KAI2 ligand-binding mechanisms, and SL binding does not necessarily result in physiological effects. The light hyposensitivity of DLK2 over expressing lines might be the consequence of KL metabolism by excess DLK2 and the elongated hypocotyl phenotype of DLK2 OE lines resembles the htl-3hypocotyl phenotype, however, other htl-3-related traits, such as suppressed cotyledon expansion or broad leaves were not observed in these lines.

Furthermore, dlk2 mutants are sensitive to 5DS and to karrikin treatment , suggesting that DLK2 is not involved in KL signaling, although 5DS and karrikin do not necessarily mimic KL action. We propose that DLK2 neither perceives nor hydrolyzes the natural ligand of D14 and KAI2. A remaining question is whether DLK2 should be regarded as a component of a separate signaling pathway, or is its function merely to regulate other MAX2-dependent pathways through the sequestration of the signaling molecules. The known pathways related to the D14 family diverge at the level of SMXL-family proteins. Intuitively, the weakly characterized members of the SMXL/D53 family, SMXL3, -4 and -5 might be co-opted by DLK2. SMXL4, originally referred to as AtHSPR , plays a role in abiotic stress responses and displays a vascular bundle-specific expression , as does DLK2 in elongating stem segments. It was shown recently that smxl4 smxl5 double mutants are defective in carbohydrate accumulation and phloem transport and SMXL3, -4 and -5 are essential for phloem formation. In SMXL3, -4 and -5, the RGKT motif needed for MAX2-mediated protein degradation of D53/SMXL7 is absent , and SMXL5 is not degraded upon rac-GR24 application , suggesting that these proteins may not be degraded through MAX2. Intriguingly, DLK2 lacks the residues required for the physical interaction with MAX2. A recent publication also suggested that DLK2 homologues presumably do not interact with MAX2. The glycine residue in position 158 is required to form a π-turn structure, which is a prerequisite of proper conformational changes of the D14 lid during SL activation. Other substitutions that reportedly do disrupt D14–MAX2 interactions , and are conserved in KAI2, are not present in DLK2. 

Furthermore, DLK2 is not degraded upon rac-GR24 application suggesting that DLK2 does not interact with MAX2; however, its expression regulation is mostly accomplished through MAX2. It was previously shown that upon binding their proposed ligand, AtD14 and KAI2 underwent substrate-induced protein degradation. AtD14 is degraded in a MAX2-dependent manner through the 26S proteasome system , and KAI2 is degraded independently of MAX2 and 26S proteasomes. The immunoblot analysis showed a slight increase in the amount of DLK2:sGFP protein even in 35Spro:DLK2:sGFP plants,medidas maceta 30 litros suggesting a post transcriptional effect. It cannot be ruled out that other but enolides or the proposed KL might promote DLK2 degradation. A potential future direction of DLK2 research could be the elucidation of the relationship between DLK2 and SMXL3, SMXL4, and SMXL5. We demonstrated that KAI2 is a principal promoter of cotyledon expansion in the D14 family, although interactions can be observed. Over expression of DLK2 in wt, dlk2-2 and dlk2-3 d14-1 kai2-2 backgrounds results in more elongated hypocotyls and expanded cotyledons under low light conditions , suggesting that DLK2 is indeed capable of regulating these physiological responses per se. However, dlk2 mutants do not display the opposite phenotypes, and the phenotype of the OE lines does not correlate with the transcript level , so neomorphic or hypermorphic effects of DLK2 over expression cannot be ruled out. We propose that DLK2 can promote hypocotyl elongation under sub-optimal light conditions, although this effect is modulated by other members of the D14 family. This finding is in conflict with the interpretation of an earlier report , where the authors suggested that the shorter mesocotyls of KAI2– RNAi d14 seedlings compared to those of the d3 mutant in rice is due to suppression by DLK2. However, differences between species might also contribute to this effect, and, as the authors noted, this finding should be interpreted with caution as there was residual KAI2 expression in the RNAi lines. We demonstrated that apart from the well documented SL and karrikin responsiveness, DLK2 expression is also down-regulated by light. Dark adaptation promotes DLK2 expression especially in the hypocotyl, and DLK2 upregulation in dark-kept seedlings is accomplished through MAX2 and KAI2. DLK2 expression is suppressed in the pif Q mutant either in light or dark, indicating that light signaling regulates DLK2 transcription via PIFs. It is also noteworthy that the spatial DLK2 expression pattern is regulated by rac-GR24 , suggesting a dynamic adaptation of DLK2 transcription to hormonal and environmental changes. DLK2 activity is strong in root hair and cortex, implying that DLK2 might be involved in the physiological processes linked to these tissues, such as water and nutrient uptake and edaphic stress responses. DLK2 expression was strong in axillary buds and the adjacent vascular bundles might also suggest that DLK2 plays a role in the regulation of nutrient distribution. In summary, the results herein show that although it is structurally similar to its paralog D14 family proteins, DLK2 only weakly binds or hydrolyzes natural and unnatural SL ligands. DLK2 is widely expressed in seedlings and has a role in the promotion of hypocotyl elongation. These data together with the knowledge accumulated so far on DWARF14 family suggest that DLK2 represents a divergent member of the family.

The fine details of DLK2 regulation, signaling and its role in adult plant life are the subject of future investigations.Pesticides are natural or synthetic chemicals used to control pests. In order to support an expanding population there is a continuous need for pesticides. Worldwide, there are thousands of pests including insects, weeds, fungi, bacteria, viruses, mycoplasma and nematodes that destroy crops, transmit diseases and compete for resources. One of the first written records of pesticide use was from around 1000 B.C. when Homer described the use of sulfur to control pests by farmers. Many natural pesticides and botanicals were used since that initial discovery: arsenic, mercury, lead, nicotine, pyrethrum and rotenone. However, insect resistance and safety issues for these inorganics and botanicals led to the production and use of the first synthetic organic insecticide, dichlorodiphenyltrichloroethane discovered in 1939 by Paul Müller. Currently, there are over 40,000 different pesticide products for retail sales with different formulations and control mechanisms. Since the major discovery of DDT, advances have continued with the synthesis and commercialization of hundreds of pesticides including five major neuroactive insecticide classes all with unique toxicity profiles and target sites: chlorinated hydrocarbons , pyrethroids, carbamates, organophosphates and neonicotinoids. Chlorinated hydrocarbons and pyrethroids are insecticidal through their ability to destabilize voltage-gated sodium ion channels receptor for some chlorinated hydrocarbons. DDT has low acute toxicity to mammals, but is persistent in the environment which ultimately led to it being banned in the US in 1972. Other problems from DDT include its potential carcinogenicity, thinning of bird eggshells and fish death. Pyrethroids, modeled from natural pyrethrin compounds from the Chrysanthemum flower, are relatively non-toxic and are less stable in the environment than DDT. Carbamates and organophosphates both inhibit acetylcholinesterase leading to accumulation of acetylcholine and over stimulation of the nervous system. Carbaryl was at one time the most commonly used carbamate with low mammalian toxicity and broad-spectrum use and selectivity. Organophosphates are related to potent nerve agents. Often highly toxic to mammals, they are metabolized and detoxified readily. Neonicotinoids, the most important class of insecticides, have favorable mammalian and environmental toxicology and now account for approximately 25 percent of the worldwide insecticide market value. In an attempt to understand the mechanism of action of nicotine, Izuru Yamamoto discovered that insecticidal activity depends on ionization or basicity of the nitrogen of nicotine and all nicotine-related compounds. Yamamoto and colleagues realized that although ionization prevents penetration of the CNS of insects which decreases insecticidal activity, these insecticides needed to be ionized to interact with the nAChR. The search began for synthetic insecticides with high insecticidal activity, low mammalian toxicity and the ability to penetrate the insect CNS yet basic enough to interact with the nAChR. Nithiazine, a nitromethylene heterocycle, was the first neonicotinoid prototype developed by Shell Development Company in 1978. It had excellent insecticidal activity, good systemic action in plants and low mammalian toxicity. However, nithiazine was highly photolabile. Shinzo Kagabu and colleagues modified the structure of nithiazine and synthesized a series of compounds with varying ring structures and sub-stituents and screened them for insecticidal activity against the major rice pest, the green rice leaf hopper. This led to the discovery of the first highly active neonicotinoid, imidacloprid , in 1985. IMI has 12 times higher insecticidal activity than nicotine, is more systemic and photostable and therefore was commercialized by Bayer in 1991. Other first-generation chloropyridinyl-containing neonicotinoids include nitenpyram , acetamiprid and thiacloprid commercialized in 1995, 1996 and 2000, respectively. Further derivatization and optimization lead to the discovery of the two second-generation neonicotinoids, thiamethoxam and clothianidin by Novartis and Takeda, respectively. Finally, the only tetrahydrofuranyl-containing neonicotinoid, dinotefuran , was commercialized by Mitsui Chemical Company in 2002.

In comparison with the four new fungicides, effectiveness of potassium phosphite in greenhouse studies was high to moderate and was moderate for mefenoxam. In the field study, a significant reduction in disease and soil populations by mefenoxam was only observed after increasing applications to high-label rates. Lower rates were initially used because this fungicide is known to cause phytotoxic effects to young citrus trees as was also observed in preliminary greenhouse studies where a range of rates was evaluated. Thus, the reduced effectiveness of mefenoxam in our study,a treatment that has been used successfully in commercial applications for managing Phytophthora root rot of various tree crops for many years, may have been due to using inadequate rates. Furthermore, trees were inoculated with an isolate of P. nicotianae with an EC50 value for mycelial growth of 0.24 mg/liter that was in the mid-range among 31 isolates from California evaluated previously. Because baseline sensitivities before commercial use of mefenoxam were never established for P. nicotianae from citrus, and the phenylamide class of fungicides has been used since the 1980s in California citriculture, this isolate may be part of a less-sensitive sub-population of the species that cannot be easily managed with mefenoxam applications. Soil populations of untreated control trees in our field and greenhouse studies were often very high considering that >15 propagules/g of soil is considered a threshold level where management is recommended. Still,maceteros fresas disease incidence of feeder roots was mostly low, especially during summer samplings in the field.

We chose ‘Carrizo citrange’ in the field studies because it is commonly used commercially as a rootstock. It is considered of intermediate susceptibility or tolerant to Phytophthora root rot, and this could have accounted for the low disease incidence. In the greenhouse studies, disease incidence may have been increased by pruning feeder roots of seedlings as it was done in studies by others. Root injuries may occur naturally in the field by nematode or root weevil infestations in the soil, and these pests are known to increase the incidence of Phytophthora root rot. Still, although disease incidence was overall low in our studies, fungicide efficacy could be compared and significant differences were observed. The four new Oomycota fungicides are single-site mode of action inhibitors. Their resistance risk currently has not been completely characterized , and resistant field isolates have not yet been detected in Phytophthora species. Resistance, however, has been described for Plasmopara viticola, another Oomycota organism, to mandipropamid. In our previous baseline sensitivity assessments, outliers with higher EC50 values for mycelial growth inhibition of P. syringae by fluopicolide and of P. citrophthora by ethaboxam were identified that were >23-fold less sensitive than the most sensitive isolates of the respective species used in the study, and this was considered to possibly indicate a potential for selecting isolates with reduced sensitivity to these fungicides. Thus, as with any single-site mode of action fungicide, resistance management strategies should be followed from the onset of commercial use. Because two of the new fungicides each have the same registrant in the United States, the commercialization of pre-mixtures will be facilitated. In summary, our study demonstrated that the new Oomycota fungicides ethaboxam, fluopicolide, mandipropamid, and oxathiapiprolin provided highly effective control of Phytophthora root rot of citrus caused by P. nicotianae or P. citrophthora. The efficacy was generally better than for the previously available fungicides mefenoxam and potassium phosphite.

The new compounds promoted the recovery of infected trees andenhanced fruit yield, with fluopicolide and oxathiapiprolin showing the most consistent increases in these measures. Based in part on our studies, fluopicolide recently received a federal and oxathiapiprolin a full registration for use on citrus, whereas registration for ethaboxam and mandipropamid has been requested. Species of Phytophthora cause several diseases on citrus, including root rot, foot rot, brown rot of fruit, and gummosis of tree trunks and larger limbs. Phytophthora root rot is common in orchards in California and other citrus production areas worldwide. The disease can be especially damaging in new citrus plantings where overwatering is conducive for infection, and the limited root system of young trees cannot generate new growth fast enough to replace infected and damaged tissues. This can result in poor tree growth and delayed orchard establishment. In California, the disease is mainly caused by Phytophthora nicotianae Breda de Haan during the warmer months of the year, whereas P. citrophthoraLeonian is active year-round. P. palmivoraE. J. Butler is the major citrus root rot pathogen in Florida. P. cactorumJ. Schröt., P. capsici Leonian, P. cinnamomi Rands, P. drechsleri Tucker, and P. megasperma Drechsler have been occasionally identified in some production areas. Phytophthora root rot is characterized by discoloration and softening of the outer root cortex that becomes water-soaked in appearance and prone to sloughing off, eventually exposing the inner stele. Damage of the root system can lead to tree decline and yield losses from lack of water and nutrient uptake, and if left untreated, to tree death. Phytophthora root rot can be managed by cultural practices such as the use of Phytophthora-tolerant root stocks , irrigation or orchard drainage strategies that avoid overwatering, and fungicide applications. These practices are best used in an integrated approach. Among fungicides,maceta 30l the phenylamides and the phosphonates have been used since the 1980s, and until recently, no alternatives were available.

The limited number of fungicides registered resulted in their over-use, and in subsequent resistance development. Resistance to the phenylamide class of fungicides has been reported in Oomycota pathogens of numerous crops including Phytophthora spp. that are known to be pathogenic to citrus such as P. citricola and P. nicotianae. Phenylamide-resistant populations of P. nicotianae are established in Florida orchards and nurseries. Phosphonate resistance is less common but has been identified in isolates of P. cinnamomi and P. infestans , and more recently in isolates of P. citrophthora, P. syringae, and P. nicotianae from California citrus orchards. With the need for alternative chemical treatments to manage Phytophthora diseases of citrus, new fungicides have recently become available for evaluation. They include the thiazole carboxamide ethaboxam, the benzamide fluopicolide, the carboxylic acid amide mandipropamid, and the piperidinyl thiazole isoxazoline oxathiapiprolin. Each compound has a unique mode of action that is different from those of the previously registered compounds. Among these, oxathiapiprolin was recently registered on citrus for foliar and soil treatments against Phytophthora diseases. This compound was found to be toxic in vitroat very low concentrations against several life stages of the pathogens and was shown to be highly effective in managing root rot and brown rot. Belonging to the Fungicide Resistance Action Committee code 49, its mode of action is the inhibition of an oxysterol binding protein, resulting in the inhibition of multiple cellular processes. Uptake of oxathiapiprolin into citrus plants after soil application is unknown. Previous work has been conducted on annual crops , however, there is currently no information on the mobility and activity of oxathiapiprolin within perennial tree crops. This information may provide a better understanding of its protective and eradicative capabilities in controlling Phytophthora root rot of citrus and have implications on its field use in managing the disease. Therefore, the objectives of this research were to determine if oxathiapiprolin can be detected inside roots and above ground portions of citrus seedlings after soil application as compared to mefenoxam and if concentrations of the fungicides inside the plants can be effective against P. citrophthora. For this, bio-assays and analytical residue analyses were performed at selected time periods after treatment of plants. Sweet orange Osbeck) cv. ‘Madam Vinous’ seedlings in 15 cm x 15 cm x 15 cm pots were grown from seeds in the greenhouse at 24°C to 30°C for 6 to 7 months. At this time, plants were between 25 cm and 30 cm tall. Prior to treatment, plants were moved to an incubator set for a 12-h photoperiod with 34˚C during the light cycle and 26.7˚C during the dark cycle. There were three single-plant replicates for each fungicide treatment and each of the four sample timings. Plants were arranged in a randomized complete block design with all four sampling times in each block. Additionally, three replications of untreated control plants were used.

Solutions of oxathiapiprolin and mefenoxam were prepared in distilled water, and 50 ml was added to each pot, resulting in final applications amounts of 50 mg of oxathiapiprolin and 130 mg of mefenoxam per pot. These amounts are comparable to labeled chemigation rate ranges based on the total basin area for 288 trees/Ha and considering that the treatment area of a potted plant is approximately 1/9 of the basin of a newly planted citrus tree. Solutions were added to each pot without wetting the stem, and distilled water was used for the controls. Each pot was then placed in a plastic bag that was tied around the bottom of the stem to reduce evaporation. Plants were watered once nine days after treatment. Plants were harvested 7, 10, 13, or 16 days after treatment. The root ball was shaken to remove most of the soil, washed using tap water, and allowed to air-dry briefly at ambient temperature. Roots were sampled randomly. The stems were cut 1.5 cm above the soil line to avoid fungicide contamination from the soil application. Another cut was done 10 cm above the first cut, and stem and leaf tissues within this stem segment were separated.One gram of each tissue was placed into glass scintillation vials. The vials were covered with a single layer of cheesecloth and frozen at -80°C for 24 h, lyophilized for 24 h , and then capped and stored at -20°C. A standard procedure was followed for extraction of plant tissues for both fungicides. For this, the lyophilized tissues were transferred to 2-ml impact resistant tubes containing two stainless-steel grinding balls and pulverized for 60 s using the FastPrep-24 set at 6.0 m/s. The contents of each tube were transferred to a 15-ml conical polypropylene plastic tube for a single-phase extraction. For this, 1 ml of sterile ultrapure water was added to each tube and the tube was incubated for 5 min to allow soaking of the sample. An additional 800 µl of sterile ddiH2O, 2.4 ml of acetonitrile, and 20 µl of formic acid were added, and the tubes were placed on an orbital shaker at 300 rpm for 5 min. The tubes were centrifuged at 1,380 g for 10 min. The supernatant was transferred to a 15-ml plastic tube, stored at -20ºC, and used for determining fungicide activity in a bio-assay within 7 days. For analytical residue analyses using HPLC-MS/MS , 500 µl of each tissue extract was transferred into a scintillation glass vial, 2 ml of methanol , and 4.5 ml of 1% formic acid were added, 0.6 ml of the resulting solution was aliquoted into a 2-ml low absorption vial , and vials were stored at -20°C until analyses. The experiment was done twice. Analytical grade oxathiapiprolin and mefenoxam were dissolved in acetonitrile and serially diluted. The samples were analyzed for oxathiapiprolin and mefenoxam using a standard curve method. The concentration of standards used for quantitation were 0.1, 0.5, 1.0, and 10 ng/ml. Each dilution was transferred to a 2-ml low-absorption vial, and aliquots were transferred to auto-sampler vials for analysis that was performed by Environmental Micro Analysis Inc.. The autosampler vials were analyzed using high-pressure liquid chromatography coupled with tandem electrospray mass spectrometer. The chromatographic separation was achieved on a XB-C18 HPLC column. The samples were analyzed with standard concentration levels indicated above. For bio-assays using plant extracts with unknown amounts of fungicides, the dependent variable was the log10-transformed mean inhibition zone; whereas for plant extracts analyzed using HPLC-MS/MS, the dependent variable was the log10-transformed mean amount of fungicide calculated per g of tissue. These data were analyzed using generalized linear mixed models with the GLIMMIX procedure of SAS. For this, root, stem, and leaf extracts or days after treatment were treated as fixed effects, and experiment, replication , and the overall error term were treated as random effects.

Silver uses the Replex replication protocol to address these issues. Driving scale-out distributed software requires more than merely spreading data across clusters and replicating it for fault tolerance; it requires name services to place data and locate it; ownership management, locking and fail over atomicity and isolation of multi-object transactions, in-memory caching, snapshot, checkpoint; and so on. As a result, the software stack of most distributed systems in production today contains a plethora of tools–Cassandra,Redis, ZooKeeper, and others. Each tool comes with its own data-model, proprietary API and query language. In order to make use of any specific tool, a developer needs to cast its own application’s state into the tool’s format, and use the tool’s API or query language in order to extract information about the state and to manipulate it. As an example, consider the life cycle of a typical distributed platform: developers may begin with the need for a distributed database such as Cassandra to store data. As the system grows and scales out, programmers begin to realize they need a way to manage Cassandra itself, so Zoo Keeper is deployed to manage configuration data and provide a mechanism for coordinating clients. Soon, a programmer realizes that funneling everything through ZooKeeper is becoming a bottleneck, so Kafka is bolted on to provide reliable high speed messaging. To further improve performance, Redis is added to implement a distributed cache. Finally, because the programmers still need a way to query data, everything in Kafka is also inserted into Cassandra. Getting different tools to work together and sharing updates across them is a nightmare.

The same information ends up duplicated and translated between multiple tools, resulting in data redundancies,maceta cuadrada plastico inefficiencies, inconsistencies, and difficult maintenance. On boarding new programmers now requires learning multiple tools and picking the correct one for each task.In an on-going joint venture, the NSX team and the VM ware Research Group are contemplating what a Clustered Management PLAT form for driving the control of VM ware’s SDN technology should look like. The design and implementation of Corfu specifically draws motivation from this venture. Figure 6.6 depicts the components of the CMPLAT-Corfu design. The left side of the figure portrays a deployment scenario. Every component in Corfu is built with redundancy and completely automated life-cycle management: Initialization, failure-monitoring, reconfiguration and fail-over. This obviates the operation of CMPLAT as a service with 24/7 availability, driving network control of large, mission critical clusters. The right side portrays the live network model CMPLAT maintains of a real network. Like previous network control planes , examples of items reflected inside CMPLAT are ports, switches, nodes, transport zones, and others. These objects are grouped into maps, e.g., a map of ports, a map of switches. Object and maps may reference one another, e.g., ports and switches belong to zones, and each port resides on some node. CMPLAT exposes an API for admins to manipulate virtual network components, e.g., create a virtual switch containing a certain number of ports, connect ports to virtual machines, and so on.This necessitates back-and-forth translation between the management plane app-servers, which use Java hash-maps to represent the model, and the DBMS. There is a rather complex a data abstraction layer that performs the translation, internally using a SQL-like query-interface for storing and retrieving information from the remote DMBS. In contrast, since Corfu supports arbitrary data-structures, CMPLAT simply uses the most natural data representation, e.g., a hash-map of ports, a linked-list of zones, and so on.

Persisting updates to the data-structure is done transparently and seamlessly, without developer awareness. An example of a NSX logical switch modeled in Corfu is shown in figure 6.7. Since CMPLAT drives the network of entire data centers, it has stringent availability and consistency guarantees. This makes it a catastrophic experience to build over platforms with weaker guarantees. Additionally, there are radically different requirements from different components, for example, live feeds from the network require high-throughput and cannot go through a slow and heavy database service, whereas admin directives must never be lost, and require strong commit guarantees. But building a management platform out of a hybrid system of components is problem-prone. For example, Onix reports anomalous situations in which a node has been updated in a “nodes base”, but the port states this node references have not been updated in the “ports base”. Corfu has the capacity to sustain millions of updates per second, and app-servers efficiently consume updates by selective filtering. This makes it possible to use Corfu as the single data platform for all the information CMPLAT processes. In this way, all of CMPLAT needs are addressed in one place, providing consistency across updates to any part, while avoiding unnecessary duplication and translation of the same information.The era of cloud-scale computing has resulted in the exponential growth of workloads. To cope with the barrage, system designers chose to trade consistency for scalability by partitioning the system and eliminating features which require communication across partitions. As cloud-scale applications became more sophisticated, programmers realized that those features were necessary for building robust, reliable distributed applications. Many of these features were then retrofitted back on, resulting in decreased performance and sometimes serious bugs in an attempt to achieve consistency across a now heavily partitioned system. This dissertation has explored Corfu, a platform for scalable consistency which answers the question: “If we were to build a distributed system from scratch, taking into consideration both the desire for consistency and the need for scalability, what would it look like?”. At the heart of this dissertation is the Corfu distributed log.

The Corfu log achieves strong consistency by presenting the abstraction of a log – clients may read from anywhere in the log but they may only append to the end of the log. The ordering of updates on the log are decided by a high throughput sequencer, which we show can issue millions of tokens per second. The log is scalable as every update to the log is replicated independently, and every append merely needs to acquire a token before beginning replication. This means that we can scale the log by merely adding additional replicas, and our only limit is the number of tokens the sequencer can issue. We have shown that we can build a sequencer using low-level networking interfaces capable of issuing more than half a million tokens per second. We have also built a prototype FPGA storage unit which can interface directly with SSDs and raw flash,maceta 7 litros which can easily saturate a gigabit network a uses a simplified UDP-based protocol. On top of the Corfu distributed log, we have shown how multiple applications may share the same log. By sharing the same log, updates across multiple applications can ordered with respect to one another, which for the basic building block for advanced operations such as transactions. We presented two designs for virtualizing the log: streaming, which divides the log into streams built using log entries which point to one another, and stream materialization, which virtualizes the log by radically changing how data is replicated in the shared log. Materializing streams greatly improves the performance of random reads, and allows applications to exploit locality by placing virtualized logs on a single replica. Efficiently virtualizing the log turns out to be important for implementing distributed objects in Corfu, a convenient and powerful abstraction for interacting with the Corfu distributed log introduced in Chapter 5. Rather than reading and appending entries to a log, distributed objects enable programmers to interact with in-memory objects which resemble traditional data structures such as maps, trees and linked lists. Under the covers, the Corfu runtime, a library which client applications link to, translates accesses and modifications to in-memory objects into operations on the Corfu distributed log. The Corfu runtime provides rich support for objects. An automated translation process converts plain old Java objects directly into Corfu objects through both runtime and compile-time transformation of code. This allows programmers to quickly adapt existing code to run on top of Corfu. The Corfu runtime also provides strong support for transactions, which enable multiple applications to read and modify objects without relaxing consistency guarantees. We show that with stream materialization, Corfu can support storing large amounts of state while supporting strong consistency and transactions. In Chapter 6, we describe our experience in both writing new applications and adapting existing applications to Corfu. We start by building an adapter for Zookeeper clients to run on top of Corfu, then describe the implementation of Silver, a new distributed file system which leverages the power of the vCorfu stream store.

We then conclude the chapter by describing our efforts to retrofit a large and complex application: a software defined network switch controller, and detail how the strong transaction model and rich object interface greatly reduce the burden on distributed system programmers. Overall, Corfu demonstrates a highly scalable yet strongly consistent system, and shows that such a system greatly simplifies development without sacrificing performance. A slow sand filtration system is a filtration process which contaminated water percolates through a sand medium and through various physical, chemical, and biological processes, the contaminants are removed. The first known slow sand filtration system was made in 1804 by John Gibb in Scotland to produce drinking water. Since then, this technique has been widely used not only for drinking water production , but also for improving the quality of wastewater before being reused or discharged into the environment.Bio-filtration generally encompasses any type of filtration of contaminated water through sand, soil, or other various media that contains biomass to aid degradation and removal. Several types of bio-filtration have been extensively studied in literature: bio-swales, trickling filters, constructed wetlands and natural wetlands, treatment ponds, riparian zones, bank filtration, and slow sand filtration. An effective filter is the result of biological degradation and physical/chemical processes such as adsorption and straining of contaminants on the bio-filter media. Both of these processes can be effective as a result of the slow flow rates and long hydraulic residence times that allow the formation of a biological active layer composed of alga, protozoa, bacterium, fungus, actinomycetes, plankton, diatoms, and rotifer population. This layer, called the schmutzdecke, develops within the top centimeters of the filter as a result of the accumulation of the organic matter, microbes, and other particulates that settle from the fluid. Thus, as leachate water is passed through, pathogens and contaminants are trapped and broken down by these microbes as a food source, aiding to the physical and biological processes required for filtration. Depending on the raw and target effluent water quality, a slow sand filtration system can be used by itself or in series to other additional treatments, like pretreatment to protect sensible processes such as reverse osmosis or membrane filtrations , or as a polishing process to eliminate disinfection by-products after ozonation or chlorination. The benefits of SSF combines a high efficiency system in reducing cloudiness and harmful bacteria and viruses along with an economical edge. SSF uses minimal power input and no chemical requirements, does not require close operator supervision, uses locally available materials and labor, and does not produce unwanted by-products. This cost-effective technique that was once used in big cities like London, now has special application in the treatment of water at smaller scales such as isolated households in rural areas, in developing countries, or in small businesses with high water consumption, like plant nurseries.Some other media used in biofiltration are biochar , compost , woodchips , activated carbon , pressmud , anthracite , agricultural wastes , etc. In a study by Nyberg et al. , various substrates were researched as the best effective SSF medium to remove zoospores of P. nicotianae from nursery production effluent. Substrates included sand, crushed brick, calcined clay, Kaldes medium, and polyethylene beads. They discovered that within 21 days, all substrate treatments removed more zoospores than day 0. Of all the substrate treatments evaluated, the columns with 10 cm of sand removed the most zoospores on day 21. By their research, sand was the most effective medium using physical filtration alone at depths of 40 cm and 60 cm.

While our prototype unit is built with an FPGA, we envision that a production device would be built with a low-cost ASIC and a NAND flash array instead of a SSD, offering a better performance, lower price, and lower power than the platform that we are currently using. Inside the FPGA, we use a variant of the Beehive. Beehive is a many-core architecture implemented in a single FPGA. A single Beehive instance can comprise up to 32 conventional RISC cores connected by a fast token ring. Network interfaces, a memory controller, and other devices, such as disk controllers, are implemented as nodes on the ring.Data is returned from reads via a dedicated pipe lined bus. There are additional data paths to enable DMA between high-speed devices and memory. We configure various Beehive cores to take on specific roles, as shown in Figure 3.10. Whereas the memory controller, Ethernet core, and System core are common to all Beehive designs, we use the following special-purpose cores to construct a SLICE.The Beehive architecture enables us to handle requests in parallel stages while running the FPGA at a low frequency , thus reducing device power. Note that new functionality can be easily added to the SLICE design. Additional cores running specialized hardware can enhance the performance of timing-critical tasks. For example, our current design uses a specialized hardware accelerator to speed up packet processing. At the same time, latency-insensitive operations can be coded in a familiar programming language ,vertical garden hydroponic significantly reducing complexity. Table 3.1 shows the percentage of time the various cores are idle under maximal load and number of assembly instructions per core in the SLICE design.

The Comm core has a slightly different architecture than the rest of the cores , thus we did not measure its idle time. If we need more or differently allocated compute resources, we can use different configurations of cores. In an earlier alternative design, we used two Packet Processing Cores running the same code base: one processed even packets and the other processed odd packets. The earlier design used more FPGA resources than the current design, but both designs can run the Ethernet at wire speed. We could also just as easily add a second Comm, Packet Proc, Read or Write core, should the workload require it. We now present our design for using Cuckoo Hashing to efficiently map an SVA to an SPA. Cuckoo Hashing minimizes collisions in the table and provides better worst-case bounds than other methods, like linear scan. Under Cuckoo Hashing, two mapping functions are applied to each inserted key, and such a key can appear at any of the resultant addresses. If, during insertion, all candidate addresses are occupied, the occupant of the first such address is evicted, and a recursive insert is invoked to place it in a different location. The original insertion is placed in the vacated spot. On average, 1.5 index look-ups are required for successful lookups in such a table. Table lookups for entries not in the table always require two lookups, one for each mapping function. In order to save space in each hash table entry, we store only a fraction of the bits of each SVA. The remainder of the bits can be recovered by using hash functions that are also permutations. Such permutations can be reversed, for example during a lookup, to reconstruct the missing bits so as to determine whether the target matches. The end result of hashing an SVA can then be represented by the mapping function F which is the concatenation F1 and F2, computed as described below.

The lower order bits of F are used to index into the mapping hash table and the remainder of F is stored in the table entry for disambiguation, along with a bit indicating which mapping function was used. This ensures that for any given table entry, we can recover all of F from an entry’s position and contents, and thus we can derive X and Y, and finally the original SVA.We evaluated a software implementation of the Cuckoo Hashing page mapping scheme and compared it with Chain Hashing. To do so, we ran sequences of insertion / lookup pairs using a varying number of keys on hash tables of both types, and then compared the elapsed times. Figure 3.12 shows the difference in performance, about 10X, when using the two page mapping schemes. We used a 64,000 entry table for both tests. These tests employed a dense key-space with relatively few hash collisions. The advantage of Cuckoo Hashing should increase with the likelihood of collisions.The stability of SLICE storage depends on the persistence of its mapping table. Building a persistent mapping table for a Corfu software implementation is problematic. Writing separate metadata for every data write is not plausible. The remaining possibilities either involve batching metadata updates, which risks losing state on power failure, or writing metadata and data in the same chunk,vertical farm tower which reduces the space available for data. Fortunately, when custom hardware is in play, a further option becomes available. Using super-capacitors or batteries, we can ensure that the hardware will always operate long enough to flush the mapping table. Our optimized mapping table takes only a few seconds to flush to flash, so this is an attractive option for metadata persistence. We have specified the hardware needed for this capability, but not yet implemented it. Ultimately, solid-state storage with fine write granularity, such as PCM, would provide the best alternative for storing such metadata and modifying it in real time.Our SLICE prototype uses an existing SSD rather than raw flash. Using an SSD, each SPA referenced in our mapping table is a logical SSD page address.

This was an expedient for prototyping, and it eliminates a raft of potential problems. For instance, we don’t need to worry about out-of-order writes, since these are possible on an SSD but problematic on raw flash. Furthermore, we don’t need to worry about bad block detection and management or error correction. But the most significant problem that using an SSD eliminates is the need to handle garbage collection and wear-leveling. With an SSD, allocating a flash page during a write operation is as simple as popping the head of the free list. Similarly, reclaiming a page requires adding it to the free list and issuing a SATA TRIM command to the drive. Wear-leveling is performed by the SSD.The downside of using an SSD is that it duplicates Flash Translation Layer functionality. Specifically, our mapping table requires a extra address translation in addition to that done by the SSD. Since SSDs are fundamentally log-structured, and since we are in practice writing a log, which is significantly simpler than a random-access disk, one might hope that this would result in a less complex FTL. A further downside is that we lose control over the FTL, which might have been useful to facilitate system-wide garbage collection. For example, if there are many SLICEs in a system, it is possible to use the configuration mechanism in Corfu to direct writes away from some units and allow garbage collection and wear-leveling to operate in the absence of write activity. In addition, if we had access to raw flash, our system would be able to store mapping-table metadata in the spare space associated with each flash page and possibly leverage this, ensuring persistence without special hardware, in the manner of Birrell et al.. Fortunately, it seems likely that writing a log over an SSD will in many cases produce optimal behavior. An application that maintains a compact log works actively to move older, but still relevant data from the oldest to the newest part of the log. Doing this allows such applications to trim entire prefixes of the log. This sort of log management is appropriate for applications that maintain fast changing and small datasets, such as ZooKeeper. With this sort of workload, appends to the log march linearly across the address-spaces of all the SLICEs, and prefix trims at the head of the log proceed at the same pace. This should produce optimal wear and capacity balancing across an entire cluster.

Assuming that our firm ware allocates SSD logical pages in a sequential fashion, the regular use of prefix trim should help avoid fragmentation at the SSD block level which is a major contributor to write amplification. In other applications, for example a Corfu virtual disk, it can be too expensive to move all old data to the head of the log. Because offset trim operates at single page granularity, we can support applications that require data to remains at static log positions.For throughput, we evaluate Corfu on a cluster of 32 Intel X25V drives. Our experiment setup consists of two racks; each rack contains 8 servers and 11 clients. Each machine has a 1 Gbps link. Together, the two drives on a server provide around 40,000 4KB read IOPS; accessed over the network, each server bottlenecks on the Gigabit link and gives us around 30,000 4KB read IOPS. Each server runs two processes, one per SSD, which act as individual flash units in the distributed system. Currently, the top-of-rack switches of the two racks are connected to a central 10 Gbps switch; our experiments do not generate more than 8 Gbps of inter-rack traffic. We run two client processes on each of the client machines, for a total of 44 client processes. In all our experiments, we run Corfu with two-way replication, where appends are mirrored on drives in either rack. Reads go from the client to the replica in the local rack. Accordingly, the total read throughput possible on our hardware is equal to 2 GB/sec or 500K/sec 4KB reads. Append throughput is half that number, since appends are mirrored. Unless otherwise mentioned, our throughput numbers are obtained by running all 44 client processes against the entire cluster of 32 drives. We measure throughput at the clients over a 60-second period during each run. We first summarize the end-to-end latency characteristics of Corfu in Figure 3.13. We show the latency for read, append and filloperations issued by clients for four Corfu configurations. The left-most bar for each operation type shows thelatency of the server-attached flash unit where clients access the flash unit over TCP/IP when data is durably stored on the SSD; this represents the configuration of our 32-drive deployment. To illustrate the impact of flash latencies on this number, we then show , in which the flash unit reads and writes to RAM instead of the SSD. Third, presents the impact of the network stack by replacing TCP with UDP between clients and the flash unit. Lastly, shows end-to-end latency for the FPGA+SSD flash unit, with the clients communicating with the unit over UDP. Against these four configurations we evaluate the latency of three operation types. Reads from the client involve a simple request over the network to the flash unit. Appends involve a token acquisition from the sequencer, and then a chained append over two flash unit replicas. Fills involve an initial read on the head of the chain to check for incomplete appends, and then a chained append to two flash unit replicas. In this context, Figure 3.13 makes a number of important points. First, the latency of the FPGA unit is very low for all three operations, providing sub-millisecond appends and fills while satisfying reads within half a millisecond. This justifies our emphasis on a client-centric design; eliminating the server from the critical path appears to have a large impact on latency. Second, the latency to fill a hole in the log is very low; on the FPGA unit, fills complete within 650 microseconds. Corfu’s ability to fill holes rapidly is key to realizing the benefits of a client-centric design, since hole-inducing client crashes can be very frequent in large-scale systems. In addition, the chained replication scheme that allows fast fills in Corfu does not impact append latency drastically; on the FPGA unit, appends complete within 750 microseconds.

In addition, the average fresh weight and diameter of the fruits from the 869T2-inoculated plants were greater than those of the control plants , although the average fruit lengths were similar. These data demonstrate that the okra fruits became heavier and wider after inoculation with strain 869T2. In summary, inoculation of strain 869T2 into hot pepper and okra plants could cause plants to flower at earlier growth stages.The members of the genus Burkholderia belong to the class β-proteobacteria and have a broad distribution, residing universally in soil, water, and in association with plants, fungi, animals, and humans. Some Burkholderia species are plant pathogens in many vegetables and fruits, while others have been reported as opportunistic pathogens of humans and other animals. However, many other Burkholderia species are beneficial to plants, suppressing plant diseases and promoting plant growth by various processes, including the production of antibiotics, secretion of allelochemicals, induction of pathogen resistance in plants, nitrogen fixation, or enhancing nutrient uptake by host plants. These beneficial Burkholderia species are free-living or endophytic and form mutualistic associations with their host plants. Burkholderia species’ high versatility and adaptability to different ecological niches rely on the high genomic plasticity of their large multichromosome genomes and the production of various bacteria secondary metabolites. In this study, we characterized the endophytic bacterium Burkholderia seminalis strain 869T2 isolated from vetiver grass, outdoor vertical plant stands which was recently described and included in the Burkholderia cepacia complex. We have documented the IAA production, siderophore synthesis, and phosphate solubilization abilities of B. seminalis strain 869T2.

Inoculations of strain 869T2 into tested plants demonstrated the plant growth promotion ability of this bacterium in several plant species from the Brassicaceae, Asteraceae, and Amaranthaceae families. Plant endophytic bacteria can increase the nutrient uptake and biomass accumulation of host plants through the production or regulation of various plant hormones, such as auxin, cytokinin, gibberellins, and ethylene. Indole acetic acid is a naturally occurring auxin produced by several endophytic bacterial species through the L-tryptophan metabolism pathway. Tryptophan can exist in the exudates of plants and is utilized by the bacteria to synthesize auxin, which enhances the growth of host plants. Auxin is the major plant hormone that regulates various aspects of plant growth and development, such as root initiation and development, leaf formation, fruit development, floral initiation and patterning, phototropism, and embryogenesis. Several plant-growth promoting bacteria can synthesize IAA, including Bacillus, Burkholderia, and Pseudomonas species. In this study, Burkholderia seminalis strain 869T2 was able to synthesize approximately 2.0 to 2.2 µg mL−1 IAA in the presence of tryptophan and increased both the above ground and below ground biomass of tested plant tissues. Several previous reports also demonstrated that low levels of IAA stimulated primary root growth. Similar to our observations, the Burkholderia sp. SSG that was isolated from boxwood leaves produced 2.9 to 4.5 µg mL−1 of IAA with tryptophan and had plant growth promotion ability in three boxwood varieties. Additionally, Burkholderia phytofirmans strain PsJN, which was isolated from onion roots, showed higher IAA production, around 12 µg mL−1 , with the addition of tryptophan and improved the growth of potato, tomato, maize, and grapevines. Other Burkholderia seminalis strains can also synthesize IAA and have been reported to increase rice and tomato seedling growth.

These previous studies, along with our observations, suggest that B. seminalis strain 869T2 may be similar to other Burkholderia species and other plant-growth-promoting bacteria that utilize IAA to increase root growth, which may assist host plants in taking up nutrients from the surrounding environment and improve aerial tissue growth. Consistent with this hypothesis, we observed that plant size, height, fresh weight, dry weight, and total leaf areas of several tested plant species all significantly increased after inoculation with B. seminalis strain 869T2. It is known that the IAA can positively affect cell division, enlargement, tissue differentiation, root formation, and the control process of nutrition growth. The IAA can also function as a signal molecule to influence the expression of various genes involved in energy metabolism and other plant hormone synthesis, such as gibberellin and ethylene. Interestingly, we observed earlier flowering in the 869T2-inoculated hot pepper and okra plants, suggesting that acceleration of plant growth rates might occur in these plants. In the future, transcriptome analysis of plant hormone response genes and energy-metabolic-related genes in the 869T2-inoculated plants might help us further decipher the possible mechanism of plant growth promotion ability of strain 869T2. From the results of our study, we observed that B. seminalis strain 869T2 had a better IAA yield at a temperature range of 25 ◦C to 37 ◦C and pH of 6 to 9. Similarly, Burkholderia pyrrocinia strain JK-SH007 reached the maximum production of IAA at 37 ◦C and pH 7.0. Several other plant-growth-promoting bacteria, including Bacillus siamensis, Bacillus megaterium, Bacillus subtilis, and Bacillus cereus, had relatively higher IAA yields at temperatures of 2–135 ◦C and pH 7–8. Three different bacteria isolated from therhizosphere of Stevia rebaudiana also exhibited greater production of IAA at a pH range of 6–9 and a temperature of 35 ◦C to 37 ◦C; these bacteria also increased the root and shoot bio-masses of wheat and mung bean.

Various carbon sources are used as an energy source for IAA production and could enhance recycling of cofactors in bacterial cells. Our results revealed that IAA yields of B. seminalis strain 869T2 were slightly better when glucose and fructose were used in media. Several previous publications also indicated that the ability of plant-growth-promoting bacteria to produce IAA was different, depending on the carbon source used in the media. Results from these studies and our study demonstrated that IAA production by different plant-growth promoting bacteria can be influenced by various factors, such as temperature, pH, carbon sources, culture conditions, and bacterial species. In this study, we utilized the colorimetric method to estimate the IAA amounts of B. seminalis strain 869T2 when grown in various in vitro conditions and media. Because the available tryptophan in the rhizosphere and root exudates of plants might be relatively lower than the tryptophan used in the media, the IAA production of B. seminalis strain 869T2 when grown in inoculated plants shall be determined with more sensitive and accurate methods, such as high-performance liquid chromatography or ultra-performance liquid chromatography systems. Apart from the IAA production ability of B. seminalis strain 869T2, this bacterium exhibited siderophore production and phosphate solubilization activities.Most iron in soils is present in the highly insoluble ferric form,vertical plant rack which is unavailable for plant absorption. Endophytic bacteria can yield iron-chelating agents such as siderophores, which bind ferric iron and help transport it into plant cells via root-mediated degradation of organic chelate, ligand exchange, or other mechanisms. Phosphorus is another essential macro-nutrient for numerous metabolism processes in plants, such as biosynthesis of macromolecules, signal transduction, photosynthesis, and respiration. Most of the phosphorus in soil is insoluble and not available for root uptake to support plant growth. In order to increase the bio-availability of phosphorus for plants, certain endophytic bacteria turn insoluble phosphate into soluble forms via the processes of chelation, ion exchange, acidification, or production of organic acids. Previous studies have also correlated siderophore production and phosphate solubilization abilities with the plant growth promotion traits of other Burkholderia species, such as the Burkholderia sp. SSG isolated from boxwood and the Burkholderia sp. MSSP isolated from root nodules of Mimosa pudica. Burkholderia cenocepacia strain CR318, which was isolated from maize roots, significantly enhanced maize plant growth by solubilizing inorganic tricalcium phosphate. Other studies have revealed that additional Burkholderia species also have the ability to solubilize inorganic phosphate to increase available phosphorous in agricultural soils and improve agricultural production. In summary, both previous studies and our results suggest that the IAA synthesis, siderophore production, and phosphate solubilization abilities of B. seminalis strain 869T2 may collectively contribute to the growth enhancement observed in the several plant species tested here.

We successfully inoculated and reisolated B. seminalis strain 869T2, which was originally isolated from the monocot plant vetiver grass, in several eudicot plant species of the Brassicaceae, Asteraceae, Amaranthaceae, Solanaceae, and Malvaceae families. Strain 869T2 can significantly improve the growth of both the roots and aerial parts of Arabidopsis and several leafy vegetables, including ching chiang pak choi, pak choi, loose-leaf lettuce, romaine lettuce, red leaf lettuce, and Chinese amaranth. These results suggest that the endophytic bacterium strain 869T2 may have a wide host range. A similar observation was reported for Burkholderia phytofirmans strain PsJN, first isolated from onion roots, which enhanced the growth of Arabidopsis, switch-grass, potato, tomato, maize, wheat, and grapevines. We did not observe significant growth improvement in hot pepper or okra plants after inoculation with strain 869T2; however, we did observe early flowering and better fruit development in these tested plants. These results suggest that the plant growth promotion abilities of strain 869T2might be more apparent in crops with a shorter life cycle or that the latter two tested host plant species might not be fully compatible with this bacterium. The plant colonization process and growth promotion abilities of endophytic bacteria seem to be active processes that are regulated by different characteristics of both the host plants and bacteria. In conclusion, our study revealed the potential of Burkholderia seminalis strain 869T2 for use as a bio-inoculant in agriculture to improve plant growth and production. The balance between C3 carbon fixation and photorespiration depends on the relative amounts of CO2 and O2 entering the active site of Rubisco and the specificity of the enzyme for each gas. Atmospheric concentrations of CO2 and O2 are currently 0.04% and 20.94%, respectively, yielding a CO2 :O2 ratio of 0.0019. Gaseous CO2 , however, is much more soluble in water than O2 , and so the CO2 :O2 ratio near the chloroplast, the part of a cell where these reactions occur, is about 0.026 at 25°C. Rubisco has about a 50-fold to 100-fold greater specificity for CO2 than O2. Together, because of the relative concentrations of and specificity for CO2 over O2 , Rubisco catalyzes about two to three cycles of C3 carbon fixation for every cycle of photorespiration under current atmospheres. Conditions that inhibit photorespiration—namely, high CO2, or low O2 atmospheric concentrations—stimulate carbon fixation in the short term by about 35%. Temperature influences the balance between C3 carbon fixation and photo respiration in two ways. First, as temperature rises, the solubility of CO2 in water decreases more than the solubility of O2, resulting in a lower CO2:O2 ratio. Second, the enzymatic properties of Rubisco shift with increasing temperature, stimulating the reaction with O2 to a greater degree than the one with CO2. Warmer temperatures, therefore, favor photo respiration over C3 carbon fixation, and photosynthetic conversion of absorbed light into sugars becomes less efficient. Based on the temperature response of Rubisco carboxylation and oxygenation, C4 plants should be more competitive in regions where the mean monthly air temperature exceeds 22°C. Overall, Rubisco seems a vestige of the high CO2 and low O2 atmospheres under which plants first evolved. To compensate for the shortcomings of Rubisco, some plants employ CO2 pumping mechanisms such as C4 carbon fixation that elevate CO2 concentrations at the active site of the enzyme. The C4 pathway is one of the most convergent evolutionary adaptations in life with at least 66 independent origins. Extensive efforts are underway to emulate Mother Nature and transfer the C4 pathway into rice and other C3 crops. Explanations for the decline in plant protein concentrations at elevated CO2 include: plants under elevated CO2 grow larger, diluting the protein within their tissues ; carbohydrates accumulate within leaves, down-regulating the amount of the most prevalent protein Rubisco ; carbon enrichment of the rhizosphere leads to progressively greater limitations in the soil N available to plants ; and elevated CO2 directly inhibits plant N metabolism, especially the assimilation of NO3 – into proteins in shoots of C3 plants. Recently, several independent meta-analyses conclude that this last explanation is the one most consistent with observations from hundreds of studies. Information about the biochemistry of RuBP oxygenation is limited.

Hemicellulose polymers both rigidly associate with cellulose fibrils and extend into the matrix environment where they exhibit significant molecular motion and can interact with lignin polymers in the secondary plant cell wall.Differences across monocot and eudicot plant species have been observed, such as variable substitution patterns on hemicellulose which can dictate cellulose hemicellulose association morphology for arabinose substitutions.The details of lignin structure are particularly challenging to analyze due to high heterogeneity and mobility, so partial extraction of the polymer is often necessary for assessment.Lignin is a polyphenolic network formed from the oxidative cross linking of the monolignols p-coumaryl alcohol , coniferyl alcohol , and sinapyl alcoholas well as Ferulic Acid.Lignin exists within the plant cell matrix, interfacing with both hemicellulose and cellulose.61 Solution-state NMR in combination with MS, which relies on swelling ball-milled plant cell walls with deuterated solvents, provides detailed information on the types, functionalization, and abundance of lignin linkages present.However, due to the necessity for drying, mechanical treatment, dissolution, or solvent extraction in these techniques, previous work does not report on recalcitrance in the intact secondary plant cell wall.NMR is inherently an atomic resolution technique,vertical farming hydroponic as the observed signals derive from nuclear spin magnetic moments located at precise locations in the molecules under study.

In contrast to solution-state NMR, which requires solubilization of the sample, solid-state NMR methods allow for analysis of intact plant tissues.The cost of implementing solid-state NMR limited early studies of the plant cell walls.Access to cost effective 13C labeling has contributed to the feasibility of understanding plant cell walls with solid state NMR.The requirement of NMR-active13C isotopes was a major hurdle for characterizations of native plant cell wall structure.13C has a low natural abundance and the cost of early efforts at isotope incorporation restricted their use.Relatively low13C enrichment enabled early studies on hardwood.The ability to detect the relative populations of rigid polymers was then applied to samples of pure cellulose and heterogeneous assemblies containing cellulose including paper products, cotton, wood chips, and pulp.While early X-ray diffraction studies demonstrated the crystalline nature of cellulose in plant cell walls,solid-state NMR measurements provided more detail, such as the pattern of hydrogen bond interactions responsible for the macroscopic shape of in situ cellulose fibers.A set of 1D cross polarization measurements was successfully applied to crystalline cellulose in birch and spruce biomass and offered the possibility of detecting exterior and interior cellulose components in macroscopic cellulose fibers.These straightforward 1D experiments were also useful for characterizing amorphous cellulose after ionic liquid processing of crystalline cellulose fibrils.The 2D cross polarized refocused Incredible Natural Abundance Double Quantum Transfer Experiment reports on directly bonded carbon atoms within polymers and has been useful for probing rigid structures, for example, resolving carbons and 5 signals of cellulose in Populus euramericana hardwood samples and characterizing the structure of amorphous cellulose.A breakthrough occurred when a highly efficient method of 13C incorporationwas coupled with multi-dimensional solid-state NMR to investigate the primary plant cell wall structure.This series of studies provided both a compositional and architectural description of the primary plant cell wall.

Hemicellulose-cellulose interactions were found to be much less prevalent in the primary plant cell wall than suggested by earlier models based on solvent extracted hemicellulose and enzymatic hemicellulose digestion studies.Furthermore, it was also revealed that the hemicellulose xyloglucan interacts mainly with the flat surfaces of crystalline cellulose fibers,expanding on the idea of xyloglucan associating, cross linking, and embedding into cellulose fibrils.Semiquantitative distance measurements recorded with the Proton Driven Spin Diffusion experiments substantiated the organization of cellulose, xyloglucan, and pectin in primary cell walls of both monocot and eudicot cell species.These advances in 13C enrichment allowed the use of advanced solid-state NMR approaches shaping the primary plant cell wall architecture and how secondary plant cell wall architecture could be approached with solid-state NMR.The strategy of 13C glucose feeding is not suitable to the study of the secondary plant cell wall because the plants need to be grown to relative maturity and complicated by respiration-dependent glucose synthesis.The development of less expensive growth chambers, utilizing 13C enriched carbon dioxide as the sole carbon source, which support the growth of plants throughout their life cycle, enabled the efficient incorporation of 13C isotopesin to plant tissues.Multidimensional solid-state NMR revealed significant differences in the dominant hemicellulose-cellulose contacts in different plant species.For example, in eudicot Arabidopsis thaliana , 2-fold screw conformations of hemicellulose xylan , dictated by even patterns of substitutions, enable a close association with crystalline cellulose.In contrast, in monocot sorghum, the high degree and irregularity of arabinose substitution patterns on xylan dictate a 3-fold screw conformation,enabling association with amorphous cellulose.Additionally, in softwoods, cellulose fibrils can be tethered by both xylan and mannan hemicellulose, increasing the strength of the plant cell wall.

For the sorghum case, limitations in biochemical techniques prevent the analysis of carbohydrate substitutions on xylan and the solid-state NMR measurements which can show the xylan-cellulose interaction that is otherwise unobtainable using other methods.Carbon dioxide 13C labeling and new applications of advanced solid-state NMR techniques have helped elucidate the structure of lignin in the secondary plant cell wall.Signal enhancement by dynamic nuclear polarization demonstrated that lignin directly bridges hemicellulose polymers and interacts strongly with cellulose fibers in uniformly labeled switch grass, highlighting the role of lignin in supporting the 3D organization of hemicellulose and cellulose.However, effective penetration of the DNP reagent into the plant cell wall for this signal enhancement required 15–20 min of milling,which could perturb native lignin structure.Direct polarization experiments utilizing PDSD performed on 13C enriched poplar stems highlight a potential avenue to probe lignin contacts and spatial proximities through selective excitation and magnetization transfer from lignin to other polymers,which provide support for the putative organization of lignin in poplar,switch grass,and Arabidopsis.Further development of selective excitation and other solid-state NMR methods to probe biomass with minimal sample manipulation have the potential to provide a more complete picture of the secondary plant cell wall structure and how established sample preparation methods influence that structure.Although a wide variety of solid-state NMR methods can be applied to highly 13C enriched plant tissues, two methods provide rapid and straightforward characterization of the polymer organization in the secondary plant cell wall.First,vertical planters for vegetables the INADEQUATE approach provides an avenue for the characterization of the polymers present within a secondary cell wall sample at relatively high resolution and can distinguish at least three populations of amorphous and crystalline cellulose, in addition to three populations of xylan.Second, 13C-13C recoupling methods, such as PDSD and Dipolar Assisted Rotational Resonance , report on the spatial proximity of cellulose, hemicellulose, and lignin.

Polymers free, dynamic, and in the plant cell matrix are captured by the refocused Incredible Nuclear Enhancement by Polarization Transfer experiment.Lower power proton decoupling is used in the rINEPT so polymers only with high intrinsic mobilityare detectable.The rINEPT experiment techniques share commonalities with solution state NMR experiments used to evaluate lignin content in deconstruction efforts and marks an upper limit of dynamic polymers which can be captured with solid-state NMR.These experiments provide a more complete picture of the polymers in the plant cell wall than has ever been obtainable before.In plants, cellulose fibrils have genetically and environmentally determined sizes so continuous fibrils change their direction and length resulting in nonuniform fibril orientations in plant tissues.Amorphous cellulose is important in the plant cell wall because they support cellulose fibril junctions so fibrils can change directions and adapt in tissues.For plant cellulose fibrils , only a fraction of the cellulose polymers have perfect hydrogen bonding patterns and order associated with crystalline cellulose.Crystalline cellulose is predicted to be more digestible in deconstruction by hydrolases for chemicals like HMF.Amorphous cellulose polymers in plant cellulose fibrils are associated with indigestible material and treated as a marker for recalcitrance.However there is still ambiguity regarding if the amorphous cellulose is recalcitrant due to being out of register cellulose within the polymer assembly.Considering enzyme digestion, the current consensus correlates the amorphous cellulose content within fibrils with recalcitrance,which can be correlated with a crystallinity index.Hemicellulose, the 1-O-4 linked linear polysaccharides contributing to the structural strength of the plant cell wall, interacts with both lignin and cellulose.The role of hemicellulose as a tethering component within the plant cell wall was first proposed in the primary plant cell wall structure and coheres with mechanical strength of plants provided by the secondary plant cell wall.Past deconstruction methods targeting hemicellulose resulted in higher recalcitrance.Even with ionic liquid digestion, early NMR studies with pulsed sequences show decreased lignin yields and increase in amorphous cellulose.Structural hemicellulose associating with amorphous cellulose fibril surfaces concerns recalcitrance when more amorphous cellulose surfaces form upon mechanical processing as predicted by milled cellulose fibrils in cotton.Structural hemicellulose also cross links with lignin upon plant maturity which greatly complicates digestion of roughly 60% of the secondary plant cell wall.In fact, hemicellulose-first deconstruction methods were largely abandoned due to high observed recalcitrance and supported the switch for deconstruction techniques to focus on lignin first extraction from the secondary plant cell wall.Finally, lignin is critical to the plant and plant development within all species,and high lignin content is associated with recalcitrance.High ratio of G/S lignin is attributed to greater heterogeneity and branching patterns within lignin networks and thus correlated with recalcitrance.Past correlations of recalcitrance outputs to the order in which polymers are digested have directed many deconstruction techniques to a “lignin first” model.Unfortunately, lignin also plays a vital role in plant water transport, pathogenic protection, and maturity; many mutations aimed at eliminating lignin are lethal to the organism.The complexity and insolubility of plant cell wall samples often requires heavy sample manipulation in deconstruction.However, whether recalcitrance is introduced in sample preparation of plant biomass conversion to bio-products is a complicated issue to address given the major discrepancies between lab and industrial processes.An immediate motivation to adopt more systematic approaches is the energy investments differing between the lab and industrial scale.This can become problematic in cases involving massive solvent extraction techniques and other preprocessing techniques as energy does not always scale from laboratorial to industrial settings.One example is the frequently used mechanical preprocessing at the lab scale which often proves to be too energetically expensive at the industrial scale.So, tracking assumptions and changes in the native plant cell wall structure behind the discrepancies is critical so that lab scale optimizations can benefit industrial applications.Mechanical preprocessing is commonly used to reduce biomass particle size to increase solvent accessibility and polymer solubilization.Lab scale vibratory ball-milling achieves this goal by rapidly vibrating a chamber containing lignocellulosic biomass with grinding balls.Importantly, past studies on the plant cell wall structure used mechanical milling to prepare samples for analysis,so the outcomes have been influenced by non-native interactions and contacts between these polymers.However, milling leading to recalcitrance is frequently reported during lignocellulosic biomass conversion efforts, impeding the efficiency of subsequent processing and separation steps.Common preprocessing sample preparations taken before specific deconstruction methods should be under investigation because of the potential for introducing wide spread recalcitrance.Mechanical preprocessing leading to recalcitrance is reported during lignocellulosic deconstruction pathways at the lab scale, which impedes the efficiency of subsequent steps in biomass processing.Milling induced recalcitrance could be due to the production of reactive lignin species promoting aberrant hemicellulose-lign in crosslinks as the lignin self-associates and condenses, resulting in polymers which may be less accessible for digestion.Additionally, increased amorphous cellulose content and exposed cellulose surfaces produced from milling cellulose fibrils5 could induce reorganization of hemicellulose-cellulose contacts due to their multiple modes of interaction in the native plant cell wall.Although the cost of applying milling to biomass as a technique on an industrial scale makes it energetically impractical to apply, the impact of potential recalcitrance induction during lab scale methods development could still influence efforts in developing deconstruction pathways and estimating their effectiveness.One recent study on milling cellulose fibrils offers potential insight into what happens to cellulose fibrils.Cellulose fibrils are nonuniformly oriented in the plant cell wall which results in irregular signal detection making some spectroscopic techniques challenging on intact material.Cellulose fibrils scatter light nonlinearly because crystalline cellulose belongs to a noncentro symmetric crystal group.Milling pure cellulose in cotton allowed for easier sample orientation which is important in the Ling et al.2019 study contrasting 13 different techniques to study crystallinity, including x-ray scattering techniques, vibrational spectroscopy and 1D CP solid-state NMR.In the study, Field-Emission Scanning Electron Microscopywas used to monitor sample morphology for cotton milled between 15–120 minutes at 30 Hz.